Victims of Crime Survey, 2017/18
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Victims of Crime Survey
2017/18

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Victims of Crime Survey: 2017/18
This statistical release presents a selection of key findings from the Victims of Crime Survey (VOCS)
2017/18, which was conducted by Statistics South Africa (Stats SA) from April 2017 to March 2018.

Published by Statistics South Africa, Private Bag X44, Pretoria 0001
© Statistics South Africa, 2018
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Victims of Crime Survey, 2017/18

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Table of Contents
1. EXECUTIVE SUMMARY ......................................................................................................................8
2. INTRODUCTION ................................................................................................................................10
3. METHODOLOGY ...............................................................................................................................13
4. GENERAL OVERVIEW OF CRIME ...................................................................................................15
4.1 Five-year trends .....................................................................................................................15
4.2 Crime levels in 2017/18 ..........................................................................................................18
5. HOUSEHOLD EXPERIENCE OF CRIME ..........................................................................................21
5.1 Theft of motor vehicle .............................................................................................................21
5.2 Housebreaking/burglary .........................................................................................................24
5.3 Home robbery.........................................................................................................................30
5.4 Theft of poultry, livestock and other animals ..........................................................................32
5.5 Theft of crops planted by household ......................................................................................36
5.6 Murder ....................................................................................................................................37
5.7 Theft out of motor vehicle .......................................................................................................39
5.8 Deliberate damage, burning or destruction of residential dwellings ......................................42
5.9 Motor vehicle vandalism or deliberate damaging of motor vehicles ......................................44
5.10 Theft of bicycle .....................................................................................................................45
5.11 Sexual offence and assault ..................................................................................................46
5.12 Comparison of household crimes experienced ....................................................................47
6. INDIVIDUAL EXPERIENCE OF CRIME ............................................................................................48
6.1 Theft of personal property ......................................................................................................48
6.2 Hijacking of motor vehicles ....................................................................................................50
6.3 Robbery outside home ...........................................................................................................53
6.4 Sexual offence........................................................................................................................56
6.5 Assault ....................................................................................................................................58
6.6 Consumer fraud......................................................................................................................61
6.7 Corruption ...............................................................................................................................62
6.8 Comparison of individual crimes experienced .......................................................................64
7. INDIVIDUAL AND COMMUNITY RESPONSE TO CRIME................................................................65
7.1 Victim support and other interventions ...................................................................................65
7.2 Protection measures taken by victims....................................................................................68
7.3 Community interaction ...........................................................................................................69
8. ATTITUDES AND PERCEPTIONS OF CRIME .................................................................................71
8.1 Perceptions on crime trends ..................................................................................................71
8.2 Feelings of safety ...................................................................................................................77

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8.3 Beliefs about reasons for committing crime ...........................................................................79
8.4 Attitudes towards police .........................................................................................................81
8.5 Attitudes towards courts .........................................................................................................88
8.6 Attitudes towards correctional services ..................................................................................92
9. TECHNICAL NOTES ..........................................................................................................................96
9.1 Survey requirements and design ...........................................................................................96
9.2 Questionnaire design .............................................................................................................96
9.3 Sample design........................................................................................................................97
9.4 Data collection ........................................................................................................................99
9.5 Editing and imputation ..........................................................................................................100
9.6 Construction of household sample weights .........................................................................100
9.7 Individual sample weights ....................................................................................................101
9.8 Estimation .............................................................................................................................101
9.9 Reliability of the survey estimates ........................................................................................102
9.10 Comparability with previous surveys ..................................................................................102
9.11 Sampling and the interpretation of the data .......................................................................102
9.12 Limitations of crime victimisation surveys ..........................................................................102
9.13 Differences between victim surveys and police-reported data ..........................................103
10. DEFINITION OF TERMS................................................................................................................104
11. GLOSSARY OF ABBREVIATIONS/ACRONYMS ..........................................................................106
ANNEXURE A: SAPS AND VOCS CRIME TYPES .............................................................................107
ANNEXURE B: SAPS AND VOCS DEFINITIONS OF CRIME ............................................................108

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List of Tables
TABLE 1: REFERENCE PERIODS FOR DATA COLLECTION ....................................................................................................... 10
TABLE 2: QUALITY CLASSIFICATION OF ESTIMATES............................................................................................................. 14
TABLE 3: NUMBER OF INCIDENCES OF HOUSEHOLD AND INDIVIDUAL CRIME BY PROVINCE, 2013/14–2017/18 .......................... 15
TABLE 4: PERCENTAGE OF HOUSEHOLDS AND INDIVIDUALS AFFECTED BY CRIME BY PROVINCE, 2013/14–2017/18 ..................... 16
TABLE 5: PERCENTAGE OF HOUSEHOLDS AND INDIVIDUALS WHO EXPERIENCED CRIME ACCORDING TO GENDER AND POPULATION
GROUP, 2017/18 ............................................................................................................................................ 18
TABLE 6: NUMBER OF INCIDENCES, NUMBER OF HOUSEHOLDS AFFECTED AND DISTRIBUTION OF HOUSEHOLD CRIME EXPERIENCED,
2017/18 ....................................................................................................................................................... 18
TABLE 7: NUMBER OF INCIDENCES, NUMBER OF INDIVIDUALS AFFECTED AND DISTRIBUTION OF INDIVIDUAL CRIME EXPERIENCED,
2017/18 ....................................................................................................................................................... 20
TABLE 8: DISTRIBUTION OF VEHICLE OWNERSHIP BY GENDER AND POPULATION GROUP OF HOUSEHOLD HEAD, 2017/18 ............... 21
TABLE 9: TRENDS IN MOTOR VEHICLE THEFT ESTIMATED FROM VOCS, 2013/14–2017/18 ................................................... 22
TABLE 10: THEFT OF MOTOR VEHICLES AND MOTOR CYCLES REPORTED TO THE POLICE, 2013/14–2017/18 .............................. 23
TABLE 11: PERCENTAGE OF THEFT OF MOTOR VEHICLES REPORTED TO THE POLICE BY GENDER AND POPULATION GROUP OF THE
HOUSEHOLD HEAD AND INSURANCE STATUS, 2016/17–2017/18 ............................................................................ 24
TABLE 12: TRENDS IN HOUSEBREAKING/BURGLARY, 2013/14–2017/18 ............................................................................ 24
TABLE 13: HOUSEBREAKING OR BURGLARY REPORTED TO THE POLICE, 2013/14–2017/18 .................................................... 25
TABLE 14: PERCENTAGE OF HOUSEBREAKING OR BURGLARY REPORTED TO THE POLICE BY GENDER AND POPULATION GROUP OF THE
HOUSEHOLD HEAD, PROVINCE AND GEOGRAPHICAL AREA, 2016/17–2017/18 ........................................................... 26
TABLE 15: DISTRIBUTION OF HOUSEBREAKING/BURGLARY BY GENDER AND POPULATION GROUP OF THE HOUSEHOLD HEAD, PROVINCE
AND GEOGRAPHICAL AREA, 2017/18 ................................................................................................................... 27
TABLE 16: PERCENTAGE OF HOUSEHOLD GOODS STOLEN DURING HOUSEBREAKING/BURGLARY BY TYPE, 2017/18 ....................... 28
TABLE 17: REASONS FOR NOT REPORTING HOUSEBREAKING TO THE POLICE, 2017/18 ............................................................ 28
TABLE 18: SATISFACTION WITH THE POLICE BY GENDER, POPULATION GROUP OF THE HOUSEHOLD HEAD, GEOGRAPHICAL AREA AND
PROVINCE, 2017/18 ........................................................................................................................................ 29
TABLE 19: TRENDS IN HOME ROBBERY, 2013/14–2017/18 ............................................................................................ 30
TABLE 20: ROBBERY AT RESIDENTIAL PREMISES REPORTED TO THE POLICE BY PROVINCE, 2013/14–2017/18 ............................ 30
TABLE 21: PERCENTAGE OF HOME ROBBERIES REPORTED TO THE POLICE BY GENDER AND POPULATION GROUP OF THE HOUSEHOLD
HEAD, GEOGRAPHICAL AREA AND PROVINCE, 2016/17–2017/18 ............................................................................ 31
TABLE 22: HOME ROBBERIES EXPERIENCED BY GENDER AND POPULATION GROUP OF THE HOUSEHOLD HEAD, GEOGRAPHICAL AREA AND
PROVINCE, 2017/18 ........................................................................................................................................ 32
TABLE 23: TRENDS IN THEFT OF LIVESTOCK, POULTRY AND OTHER ANIMALS, 2013/14–2017/18 ............................................ 33
TABLE 24: STOCK THEFT REPORTED TO THE POLICE BY PROVINCE, 2013/14–2017/18 .......................................................... 33
TABLE 25: PERCENTAGE OF THEFT OF LIVESTOCK, POULTRY AND OTHER ANIMALS REPORTED TO THE POLICE BY GENDER AND
POPULATION GROUP OF THE HOUSEHOLD HEAD AND GEOGRAPHICAL AREA, 2016/17–2017/18 .................................... 34
TABLE 26: DISTRIBUTION OF THEFT OF POULTRY/LIVESTOCK BY GENDER OF THE HOUSEHOLD HEAD, GEOGRAPHICAL AREA AND
PROVINCE, 2017/18 ........................................................................................................................................ 35
TABLE 27: NUMBER OF ANIMALS STOLEN AND PERCENTAGE OF HOUSEHOLDS THAT SUFFERED LOSS, 2017/18 ............................ 36
TABLE 28: TRENDS IN THEFT OF CROPS PLANTED BY THE HOUSEHOLD, 2013/14–2017/18 .................................................... 36
TABLE 29: TRENDS IN MURDER, 2013/14–2017/18 ...................................................................................................... 37
TABLE 30: MURDER AND CULPABLE HOMICIDE REPORTED TO THE POLICE, 2013/14–2017/18 ............................................... 38
TABLE 31: MURDER REPORTED TO THE POLICE BY GENDER OF THE HOUSEHOLD HEAD AND GEOGRAPHICAL AREA, 2016/17–2017/18
..................................................................................................................................................................... 39
TABLE 32: TRENDS IN THEFT OUT OF MOTOR VEHICLE, 2013/14–2017/18......................................................................... 39
TABLE 33: THEFT OUT OF OR FROM MOTOR VEHICLE REPORTED TO THE POLICE BY PROVINCE, 2013/14–2017/18 ..................... 40
TABLE 34: PERCENTAGE OF THEFT OUT OF MOTOR VEHICLE REPORTED TO THE POLICE BY GENDER AND POPULATION GROUP OF THE
HOUSEHOLD HEAD AND GEOGRAPHICAL AREA, 2016/17–2017/18 .......................................................................... 41
TABLE 35: NUMBER AND PERCENTAGE OF HOUSEHOLDS THAT EXPERIENCED THEFT OUT OF MOTOR VEHICLE BY GENDER AND
POPULATION GROUP OF THE HOUSEHOLD HEAD, GEOGRAPHICAL AREA AND PROVINCE, 2017/18 .................................... 41
TABLE 36: TRENDS IN DELIBERATE DAMAGE, BURNING OR DESTRUCTION OF DWELLINGS, 2017/18 ........................................... 42
TABLE 37: MALICIOUS DAMAGE TO PROPERTY AND ARSON REPORTED TO THE POLICE BY PROVINCE, 2013/14–2017/18 ............. 42
TABLE 38: PERCENTAGE OF DELIBERATE DAMAGING, BURNING OR DESTRUCTION OF DWELLINGS REPORTED TO THE POLICE BY GENDER
OF THE HOUSEHOLD HEAD AND GEOGRAPHICAL AREA, 2016/17–2017/18 ................................................................ 43

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TABLE 39: NUMBER AND PERCENTAGE OF HOUSEHOLDS THAT EXPERIENCED DELIBERATE DAMAGE, BURNING OR DESTRUCTION OF
DWELLINGS BY GENDER OF THE HOUSEHOLD HEAD AND GEOGRAPHICAL AREA, 2017/18 ................................................ 44
TABLE 40: TRENDS IN MOTOR VEHICLE VANDALISM, 2013/14–2017/18............................................................................ 44
TABLE 41: PERCENTAGE OF HOUSEHOLDS THAT REPORTED MOTOR VEHICLE VANDALISM TO THE POLICE BY GENDER OF THE HOUSEHOLD
HEAD, 2016/17–2017/18 ............................................................................................................................... 44
TABLE 42: NUMBER AND PERCENTAGE OF HOUSEHOLDS THAT EXPERIENCED MOTOR VEHICLE VANDALISM BY GENDER AND POPULATION
GROUP OF THE HOUSEHOLD HEAD, 2017/18 ......................................................................................................... 45
TABLE 43: TRENDS IN THEFT OF BICYCLE, 2013/14–2017/18 .......................................................................................... 45
TABLE 44: DISTRIBUTION OF THEFT OF BICYCLE BY GENDER OF THE HOUSEHOLD HEAD, 2017/18 .............................................. 45
TABLE 45: PERCENTAGE OF HOUSEHOLDS THAT REPORTED BICYCLE THEFT TO THE POLICE BY GENDER OF THE HOUSEHOLD HEAD,
2016/17–2017/18 ........................................................................................................................................ 46
TABLE 46: HOUSEHOLD SEXUAL OFFENCE AND ASSAULT BY GENDER OF THE HOUSEHOLD HEAD, 2017/18 .................................. 46
TABLE 47: HOUSEHOLD EXPERIENCES OF SEXUAL OFFENCE AND ASSAULT BY GENDER OF VICTIM, 2017/18 ................................. 47
TABLE 48: TRENDS IN THEFT OF PERSONAL PROPERTY, 2013/14–2017/18 ......................................................................... 48
TABLE 49: PERCENTAGE OF VICTIMS WHO REPORTED THEFT OF PERSONAL PROPERTY TO THE POLICE BY GENDER, POPULATION GROUP
AND GEOGRAPHICAL AREA, 2016/17–2017/18 ................................................................................................... 48
TABLE 50: DISTRIBUTION OF THEFT OF PERSONAL PROPERTY BY GENDER, POPULATION GROUP, GEOGRAPHICAL AREA AND PROVINCE,
2017/18 ....................................................................................................................................................... 49
TABLE 51: NUMBER AND PERCENTAGE OF VICTIMS WHO KNEW THE PERPETRATOR AND VICTIMS WHO WERE SATISFIED WITH POLICE
RESPONSE, 2017/18 ........................................................................................................................................ 49
TABLE 52: PLACE WHERE THEFT OF PERSONAL PROPERTY OCCURRED, 2017/18 .................................................................... 50
TABLE 53: NUMBER AND PERCENTAGE OF VICTIMS WHO LOST VARIOUS ITEMS THROUGH THEFT OF PERSONAL PROPERTY, 2017/18 50
TABLE 54: TRENDS IN MOTOR VEHICLE HIJACKING, 2013/14–2017/18 ............................................................................. 51
TABLE 55: CARJACKING AND TRUCK HIJACKING REPORTED TO THE POLICE BY PROVINCE, 2013/14–2017/18 ............................. 51
TABLE 56: MOTOR VEHICLE HIJACKING REPORTED TO THE POLICE BY GENDER AND GEOGRAPHICAL AREA, 2016/17–2017/18 ...... 52
TABLE 57: TRENDS IN ROBBERY, 2013/14–2017/18...................................................................................................... 53
TABLE 58: COMMON ROBBERY AND ROBBERY WITH AGGRAVATING CIRCUMSTANCES REPORTED TO THE POLICE BY PROVINCE,
2013/14–2017/18 ........................................................................................................................................ 53
TABLE 59: PERCENTAGE OF ROBBERIES REPORTED TO THE POLICE BY GENDER, POPULATION GROUP, GEOGRAPHICAL AREA AND
PROVINCE, 2016/17–2017/18 ......................................................................................................................... 54
TABLE 60: DISTRIBUTION OF ROBBERY BY GENDER, GEOGRAPHICAL AREA AND PROVINCE, 2017/18 .......................................... 55
TABLE 61: PERCENTAGE OF INDIVIDUALS ROBBED USING A SPECIFIED TYPE OF WEAPON, 2017/18 ............................................ 55
TABLE 62: PERCENTAGES FOR DIFFERENT ROBBERY SCENARIOS, 2017/18 ............................................................................ 56
TABLE 63: TRENDS IN SEXUAL OFFENCES, 2013/14–2017/18 .......................................................................................... 56
TABLE 64: SEXUAL OFFENCES REPORTED TO THE POLICE BY PROVINCE, 2013/14–2017/18 .................................................... 57
TABLE 65: PERCENTAGE OF SEXUAL OFFENCES REPORTED TO THE POLICE BY GENDER, 2016/17–2017/18 ................................ 57
TABLE 66: DISTRIBUTION OF SEXUAL OFFENCES BY GENDER, 2017/18 ................................................................................. 58
TABLE 67: TRENDS IN ASSAULT, 2013/14–2017/18 ...................................................................................................... 58
TABLE 68: COMMON ASSAULT AND ASSAULT WITH INTENT TO INFLICT GRIEVOUS BODILY HARM REPORTED TO THE POLICE BY PROVINCE,
2013/14–2017/18 ........................................................................................................................................ 58
TABLE 69: PERCENTAGE OF ASSAULTS REPORTED TO THE POLICE BY GENDER AND GEOGRAPHICAL AREA, 2016/17–2017/18........ 59
TABLE 70: NUMBER AND PERCENTAGE OF INDIVIDUALS WHO EXPERIENCED ASSAULT BY GENDER, GEOGRAPHICAL AREA AND PROVINCE,
2017/18 ....................................................................................................................................................... 60
TABLE 71: DISTRIBUTION OF PLACE WHERE ASSAULT OCCURRED, 2017/18 .......................................................................... 61
TABLE 72: TRENDS IN CONSUMER FRAUD, 2013/14–2017/18......................................................................................... 61
TABLE 73: PERCENTAGE OF CONSUMER FRAUD VICTIMS WHO REPORTED TO THE POLICE, 2016/17–2017/18 ........................... 61
TABLE 74: DISTRIBUTION OF CONSUMER FRAUD BY GENDER, 2017/18................................................................................ 61
TABLE 75: FIVE-YEAR TRENDS IN INDIVIDUAL EXPERIENCES OF CORRUPTION, 2013/14–2017/18 ............................................ 62
TABLE 76: NUMBER OF INCIDENCES OF CORRUPTION AND PERCENTAGE OF INDIVIDUALS WHO EXPERIENCED CORRUPTION, 2017/1862
TABLE 77: INDIVIDUAL EXPERIENCES WITH BRIBES, 2017/18 ............................................................................................. 63
TABLE 78: PERCEPTIONS OF SOUTH AFRICAN HOUSEHOLDS ON CORRUPTION, 2017/18 ......................................................... 64
TABLE 79: NUMBER AND PERCENTAGE OF HOUSEHOLDS WHO KNEW WHERE TO TAKE A VICTIM OF CRIME TO ACCESS MEDICAL SERVICES
BY TYPE OF INSTITUTION AND PROVINCE, 2017/18 ................................................................................................. 67
TABLE 80: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO TOOK MEASURES TO PROTECT THEMSELVES FROM CRIME BY PROVINCE,
2017/18 ....................................................................................................................................................... 68
TABLE 81: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' KNOWLEDGE OF THEIR NEIGHBOURS' NAME BY THEIR TRUST IN NEIGHBOURS,
2017/18 ....................................................................................................................................................... 69

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TABLE 82: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' KNOWLEDGE OF THEIR NEIGHBOURS' NAME BY WHETHER THEY WOULD LET
THEM WATCH THEIR CHILDREN, 2017/18 ............................................................................................................. 69
TABLE 83: CRIMES PERCEIVED BY HOUSEHOLDS TO BE THE MOST COMMON AND FEARED IN SOUTH AFRICA, 2017/18 .................. 76
TABLE 84: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO WERE PREVENTED FROM ENGAGING IN DAILY ACTIVITIES AS A RESULT OF
CRIME IN THEIR AREA, 2017/18.......................................................................................................................... 78
TABLE 85: CONTENTS OF THE VOCS 2017/18 QUESTIONNAIRE ......................................................................................... 97
TABLE 86: COMPARISON BETWEEN THE 2007 (OLD) MASTER SAMPLE AND THE NEW MASTER SAMPLE (DESIGNED IN 2013) .......... 98

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List of Figures
FIGURE 1: Percentage CHANGE OF HOUSEHOLD AND INDIVIDUAL CRIME LEVELS BY PROVINCE, 2016/17–2017/18 .................. 17
FIGURE 2: PERCENTAGE OF HOUSEHOLDS AND INDIVIDUALS THAT WERE VICTIMS OF CRIME, 2013/14–2017/18 ....................... 17
FIGURE 3: COMPARISON OF DISTRIBUTION OF HOUSEHOLD CRIME, 2016/17–2017/18 ........................................................ 19
FIGURE 4: COMPARISON OF DISTRIBUTION OF INDIVIDUAL CRIME, 2016/17–2017/18 ......................................................... 20
FIGURE 5: PERCENTAGE DISTRIBUTION OF HOUSEHOLD VEHICLE OWNERSHIP BY POPULATION GROUP OF THE HOUSEHOLD HEAD,
2016/17–2017/18 ........................................................................................................................................ 22
FIGURE 6: TRENDS IN THEFT OF MOTOR VEHICLES AND REPORTING OF MOTOR VEHICLE THEFT TO THE POLICE, 2013/14–2017/18 23
FIGURE 7: TRENDS IN HOUSEBREAKING/BURGLARY AND REPORTING TO THE POLICE, 2013/14–2017/18 .................................. 25
FIGURE 8: HOME ROBBERY AND REPORTING OF ROBBERY AT RESIDENTIAL PLACES TO THE POLICE, 2013/14–2017/18 ................ 31
FIGURE 9: THEFT OF LIVESTOCK AND REPORTING OF STOCK AND CROP THEFT TO THE POLICE, 2013/14–2017/18....................... 34
FIGURE 10: PERCENTAGE OF HOUSEHOLDS THAT EXPERIENCED THEFT OF LIVESTOCK, POULTRY OR OTHER ANIMALS BY GEOGRAPHICAL
AREA, 2017/18............................................................................................................................................... 35
FIGURE 11: MURDER AND REPORTING OF MURDER AND CULPABLE HOMICIDE TO THE POLICE, 2013/14–2017/18 ..................... 38
FIGURE 12: THEFT OUT OF MOTOR VEHICLE REPORTED TO THE POLICE, 2013/14–2017/18 ................................................... 40
FIGURE 13: DELIBERATE DAMAGING, BURNING OR DESTRUCTION OF DWELLINGS AND REPORTING TO THE POLICE, 2013/14–2017/18
..................................................................................................................................................................... 43
FIGURE 14: NUMBER OF HIJACKING INCIDENCES AND CASES REPORTED TO THE POLICE, 2013/14–2016/17 .............................. 52
FIGURE 15: NUMBER OF ROBBERY INCIDENCES AND ROBBERIES REPORTED TO THE POLICE, 2013/14–2017/18 ......................... 54
FIGURE 16: NUMBER OF SEXUAL OFFENCE INCIDENCES AND SEXUAL OFFENCES REPORTED TO THE POLICE, 2013/14–2017/18 ..... 57
FIGURE 17: VOCS ESTIMATED ASSAULT INCIDENCES AND REPORTING OF SAPS COMMON ASSAULT AND ASSAULT WITH INTENT TO
INFLICT GRIEVOUS BODILY HARM TO THE POLICE, 2013/14–2017/18 ....................................................................... 59
FIGURE 18: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO KNEW WHERE TO TAKE A VICTIM OF CRIME TO ACCESS SELECTED
SERVICES, 2012–2017/18 ............................................................................................................................... 65
FIGURE 19: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO KNEW WHERE TO TAKE A VICTIM OF CRIME TO ACCESS SELECTED
SERVICES BY PROVINCE, 2017/18 ....................................................................................................................... 66
FIGURE 20: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO TOOK MEASURES TO PROTECT THEMSELVES FROM CRIME, 2017/18 68
FIGURE 21: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' KNOWLEDGE OF THEIR NEIGHBOURS' NAME BY ACTIVITIES IN WHICH THEY
PARTAKE, 2017/18 .......................................................................................................................................... 70
FIGURE 22: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF VIOLENT CRIME LEVELS IN THEIR AREAS OF RESIDENCE OVER
THREE-YEAR INTERVAL PRIOR TO THE SURVEY, 2012–2017/18 ................................................................................ 71
FIGURE 23: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF VIOLENT CRIME LEVELS IN THEIR AREAS OF RESIDENCE IN
THE PAST THREE YEARS, 2017/18 ....................................................................................................................... 72
FIGURE 24: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF PROPERTY CRIME LEVELS IN THEIR AREAS OF RESIDENCE
OVER THREE-YEAR INTERVAL PRIOR TO THE SURVEY, 2012–2017/18 ........................................................................ 73
FIGURE 25: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF PROPERTY CRIME LEVELS IN THEIR AREAS OF RESIDENCE IN
THE PAST THREE YEARS, 2017/18 ....................................................................................................................... 74
FIGURE 26: CRIMES PERCEIVED BY HOUSEHOLDS TO BE MOST COMMON IN SOUTH AFRICA, 2012–2017/18 ............................. 75
FIGURE 27: COMPARISON OF FEELINGS OF SAFETY WHEN WALKING ALONE IN THEIR AREAS OF RESIDENCE DURING THE DAY AND WHEN
IT IS DARK, 2017/18 ........................................................................................................................................ 77
FIGURE 28: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO FELT SAFE WALKING ALONE IN THEIR AREAS OF RESIDENCE DURING THE
DAY AND WHEN IT IS DARK, 2012–2017/18 ......................................................................................................... 78
FIGURE 29: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTION OF THE MOST LIKELY PERPETRATORS OF PROPERTY CRIME,
2012–2017/18 ............................................................................................................................................. 79
FIGURE 30: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF WHY PERPETRATORS COMMIT CRIME, 2017/18 .......... 80
FIGURE 31: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF THE AVERAGE TIME IT TAKES TO REACH THE NEAREST POLICE
STATION USING THEIR USUAL MODE OF TRANSPORT, 2012–2017/18 ........................................................................ 81
FIGURE 32: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF THE AVERAGE LENGTH OF TIME IT TAKES TO REACH THE
NEAREST POLICE STATION USING THEIR USUAL MODE OF TRANSPORT BY PROVINCE, 2017/18 ......................................... 82
FIGURE 33: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS OF THE AVERAGE LENGTH OF TIME IT TAKES THE POLICE TO
RESPOND TO AN EMERGENCY CALL BY PROVINCE, 2017/18 ...................................................................................... 83
FIGURE 34: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO SAW THE POLICE, IN UNIFORM AND ON DUTY, IN THEIR AREA OF
RESIDENCE, 2012–2017/18 ............................................................................................................................. 84
FIGURE 35: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO SAW THE POLICE, IN UNIFORM AND ON DUTY, IN THEIR AREA OF
RESIDENCE BY PROVINCE, 2017/18 ..................................................................................................................... 85

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FIGURE 36: PERCENTAGE OF HOUSEHOLDS SATISFIED WITH POLICE SERVICES IN THEIR AREA, 2013/14 – 2017/18...................... 86
FIGURE 37: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WHO WERE SATISFIED WITH POLICE IN THEIR AREA BY PROVINCE, 2016/17–
2017/18 ....................................................................................................................................................... 87
FIGURE 38: DISTRIBUTION OF HOUSEHOLDS' REASONS FOR BEING SATISFIED WITH THE WAY THE POLICE DEAL WITH CRIME, 2017/18
..................................................................................................................................................................... 87
FIGURE 39: DISTRIBUTION OF HOUSEHOLDS' REASONS FOR BEING DISSATISFIED WITH THE WAY THE POLICE DEAL WITH CRIME,
2016/17–2017/18 ........................................................................................................................................ 88
FIGURE 40: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' SATISFACTION WITH POLICE SERVICES IN THEIR AREA AND THE WAY IN WHICH
COURTS GENERALLY DEAL WITH PERPETRATORS OF CRIME, 2013/14 – 2017/18 ......................................................... 89
FIGURE 41: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' SATISFACTION WITH THE WAY IN WHICH COURTS GENERALLY DEAL WITH
PERPETRATORS OF CRIME BY PROVINCE, 2016/17–2017/18 .................................................................................. 90
FIGURE 42: PERCENTAGE DISTRIBUTION OF REASONS FOR HOUSEHOLDS BEING SATISFIED WITH THE WAY IN WHICH COURTS GENERALLY
DEAL WITH PERPETRATORS OF CRIME BY PROVINCE, 2017/18 ................................................................................... 90
FIGURE 43: PERCENTAGE DISTRIBUTION OF REASONS FOR HOUSEHOLDS BEING DISSATISFIED WITH THE WAY IN WHICH COURTS
GENERALLY DEAL WITH PERPETRATORS OF CRIME BY PROVINCE, 2017/18 ................................................................... 91
FIGURE 44: PERCENTAGE OF HOUSEHOLDS WHO THOUGHT THAT SENTENCING OF VIOLENT CRIME WAS LONG ENOUGH TO DISCOURAGE
PEOPLE FROM COMMITTING THESE CRIMES, 2017/18 ............................................................................................. 92
FIGURE 45: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS' PERCEPTIONS ABOUT SERVICES PROVIDED BY CORRECTIONAL SERVICES,
2017/18 ....................................................................................................................................................... 93
FIGURE 46: PERCENTAGE OF HOUSEHOLDS THAT ARE SATISFIED WITH SERVICES PROVIDED BY CORRECTIONAL SERVICES, 2016/17–
2017/18 ....................................................................................................................................................... 93
FIGURE 47: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WILLING TO WELCOME A FORMER PRISONER BACK IN THEIR COMMUNITY,
2017/18 ....................................................................................................................................................... 94
FIGURE 48: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WILLING TO PROVIDE EMPLOYMENT OR MARRY TO A FORMER PRISONER BY
GENDER GROUP, 2017/18 ................................................................................................................................ 94
FIGURE 49: PERCENTAGE DISTRIBUTION OF HOUSEHOLDS WILLING TO PROVIDE EMPLOYMENT OR MARRY A FORMER PRISONER BY
POPULATION GROUP, 2017/18 .......................................................................................................................... 95
FIGURE 50: DISTRIBUTION OF PRIMARY SAMPLING UNITS BY PROVINCE, 2007 (OLD) MASTER SAMPLE AND THE NEW MASTER SAMPLE
(DESIGNED IN 2013) ......................................................................................................................................... 99

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1. EXECUTIVE SUMMARY
Aggregate crime levels increased in 2017/18 compared to 2016/17. It is estimated that over 1,5 million
incidences of household crime occurred in South Africa in 2017/18, which constitutes an increase of 5%
compared to the previous year. Incidences of crime on individuals are estimated to be over 1,6 million,
which is an increase of 5% from the previous year. Aggregate household crime levels increased in Free
State, KwaZulu-Natal, North West, Gauteng and Mpumalanga. Individual crime levels increased in Free
State, North West and Gauteng. North West experienced a drastic increase of 80% in the individual
crime level. More provinces experienced an increase in household and individual crime levels if
comparisons were done using proportions instead of absolute numbers.
Housebreaking or burglary continued to be the dominant type of crime in 2017/18, accounting for 54%
of all household crimes surveyed in the Victims of Crime Survey (VOCS). An estimated 832 122
incidences of housebreaking occurred, which is a 7% increase compared to the previous year. An
estimated 156 089 incidences of home robbery occurred, constituting an increase of 3% from last year.
It is estimated that 16 809 incidences of murder occurred in 2017/18, which is an increase of about 4%
from the previous year. The definition of murder in VOCS includes culpable homicide because it is
practically impossible to separate the two types of killing in a household survey. This is one of the
reasons that the VOCS estimates differ from the figures released by the South African Police Service
(SAPS). Another reason for the VOCS murder estimates being different from those of the SAPS is that
some murders recorded by the SAPS are not known at household level; for example, murders of
immigrants that have no relatives in South Africa.
In the case of individual crimes, theft of personal property was the most dominant, accounting for about
41% of individual crimes. It is estimated that 693 219 incidences of theft of personal property occurred
in 2017/18, which is a decrease of 2% from the previous year. Robbery away from home decreased by
5%, sexual offence decreased by 61%, and assault increased by 12% from the previous year. Sexual
offence has a narrower definition in VOCS compared to the SAPS definition, which includes offences
such as bestiality and sexual acts with a corpse. On the other hand, assault is defined more broadly in
the VOCS compared to the SAPS and combines SAPS common assault and assault with intent to cause
grievous bodily harm. Disagreement between VOCS and SAPS statistics should not be a matter of
concern at this stage, as the two organisations do not use the same definitions of crime types. Moreover,
not all crime experienced by individuals is reported to the police. Despite the challenge of non-aligned
definitions, in many cases, VOCS and SAPS trends agree for similar types of crime.
Perceptions of South Africans on crime in 2017/18 were more sceptical compared to the previous year.
About 42% thought property crime increased during the past three years. This is an increase of 6,9%
from the previous year. Those who thought violent crime increased during the past three years were
46%, which is an increase of 4,5% over the previous year. Western Cape was the most sceptical about
crime trends, as 84% of Western Cape residents thought that crime in South African increased or stayed
the same. Mpumalanga was the least sceptical among the nine provinces, where 65% thought that crime
increased or stayed the same during the past three years. Crimes that are feared most are those that
are most common.

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An estimated 79% of South Africans felt safe walking alone in their neighbourhoods during the day,
which is a decrease of 6,7% from last year. About 32% of South Africans felt safe walking alone in their
neighbourhoods at night, constituting an increase of 8% from last year.
Police visibility declined between 2017/17 and 2017/18. It is estimated that the proportion of South
Africans who never saw a police officer in uniform during the past twelve months increased by 6%.
Police visibility was least in the Eastern Cape, where the percentage of people who never saw a police
officer in uniform during the past twelve months is estimated to be 38%. The percentage of South
Africans who were satisfied with police response in 2017/18 was 54%, which is a decrease of 5,5% from
the previous year. The most common (34,4%) reason for dissatisfaction with the police was that "they
don't respond in time". The most common reason for dissatisfaction in 2016/17 was "they don't recover
goods". South Africans who were satisfied with the courts dropped by 8,5% from last year to 41%.
Gender and population group are important factors that impact the level of confidence on the capacity
of correctional services to rehabilitate prisoners. On the question of whether the respondent would be
willing to offer employment to a former prisoner, the estimates for a "Yes" response were: Males (51%)
and females (45%); Black Africans (52%), coloureds (38%), Indians/Asians (31%) and whites (35%).
On the question of whether the respondent would be willing to marry a former prisoner, the estimates
for a "Yes" response were: Males (25%) and females (19%); Black Africans (25%), coloureds (13%),
Indians/Asians (9%) and whites (12%).

Risenga Maluleke
Statistician-General

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2. INTRODUCTION
Crime prevention and ultimate elimination is one of the top priority goals of the National Development
Plan (NDP). Crime affects all people irrespective of their background, and it is a topic that attracts a lot
of media attention. Analysis will show that some groupings are affected by certain types of crime more
than others. Crime statistics are essential in order to understand the temporal and spatial dynamics of
crime. Such understanding is vital for planning targeted interventions and assessing progress made
towards achieving a crime free nation where
"people living in South Africa feel safe at home, at school and at work, and they enjoy a community life
free of fear. Women walk freely in the streets and children play safely outside".
There are two major sources of crime statistics in South Africa, namely the South African Police Service
(SAPS) and Statistics South Africa (Stats SA). The other smaller sources such as the Institute for
Security Studies (ISS) and the Medical Research Council (MRC) are by no means insignificant, as they
provide statistics for types of crime not adequately covered by the major players, such as domestic
violence. While the methodologies used by the SAPS and Stats SA are very different, the two institutions
produce crime statistics that complement each other. The SAPS produces administrative data of crime
reported to police stations by victims, the public and crime reported as a result of police activity. Stats
SA produces crime statistics estimated from household surveys. The crime types reported by the SAPS
and VOCS are listed in Annexure A, where an attempt was made to juxtapose SAPS and VOCS crimes
where similar definitions apply. Crimes reported to the SAPS do not always have the same definitions
as crime statistics produced from VOCS. In addition, not all crimes reported by the SAPS are reported
by VOCS and vice versa. Working in close collaboration with Stats SA, the SAPS has undertaken to
align its Classification of Crime for Statistical Purposes (CCSP) to the International Classification of
Crime for Statistical Purposes (ICCS).
Stats SA started conducting the annual collection of the VOCS as from 2011. Data collections for VOCS
2011 and VOCS 2012 were conducted from January to March of that year and referred to incidents of
crime experienced during the previous year (i.e. from January to December). Since 2013, Stats SA has
changed the data collection methodology to continuous data collection. Data are collected from April of
the current year to March of the following year, and the reference period is for the 12 months preceding
the interview date. The following table shows the reference periods for each data collection period.
Table 1: Reference periods for data collection
Year

Data collection

Reference period

2011

January 2011 – March 2011

January 2010 – December 2010

2012

January 2012 – March 2012

January 2011 – December 2011

2013/14

April 2013 – March 2014

April 2012 – February 2014

2014/15

April 2014 – March 2015

April 2013 – February 2015

2015/16

April 2015 – March 2016

April 2014 – February 2016

2016/17

April 2016 – March 2017

April 2015 – February 2017

2017/18

April 2017 – March 2018

April 2016 – February 2018

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The survey series is a countrywide household-based survey and has three main objectives:
•

Provide information about the dynamics of crime from the perspective of households and the victims
of crime.

•

Explore public perceptions of the activities of the police, prosecutors, courts and correctional
services in the prevention of crime and victimisation.

•

Provide complementary data on the level of crime within South Africa (SA) in addition to the
statistics published annually by the South African Police Service (SAPS).

VOCS focuses on people's perceptions and experiences of crime, as well as their views regarding their
access to, and effectiveness of the police service and the criminal justice system. Households are also
asked about community responses to crime. The survey profiled different aspects that are inherent in
the different types of crime, such as the location and timing of the different crimes, the use of weapons
and the nature and extent of the violence that takes place. The VOCS 2017/18 is comparable to the
previous versions in cases where the questions remained largely unchanged.
While the VOCS cannot replace police statistics, it can be a rich source of information that will assist in
the planning of crime prevention and provide a more holistic picture of crime in South Africa. The data
can be used for the development of policies and strategies, as well as for crime prevention and public
education programmes. This report ventures into exploring the possibility of integrating the VOCS and
SAPS crime statistics by tabulating estimates from VOCS and statistics released by SAPS for every
category of crime that is common to both sources. The biggest challenge in this project is the difference
of definitions of crime categories used by VOCS and SAPS. For example, "murder" for VOCS includes
both the intentional and unintentional killing of a human being, while for SAPS "murder" only refers to
the intentional killing of a human being. For SAPS, "sexual offence" includes bestiality while in VOCS it
is limited to sexual violations against human beings.
Like other household surveys conducted by Stats SA, VOCS is designed to produce accurate estimates
at national and provincial levels. The accuracy of estimates at lower levels or small areas cannot be
guaranteed. Small areas include specific demographic or social groupings of interest such as children
under 15 or sex workers. VOCS data cannot produce sexual offence statistics for children under 15 or
murders of sex workers. Statistics for small areas require specialised methodologies that are not readily
available in Stats SA. Some of the institutions that use these methodologies for small areas are the
South Africa Medical Research Council, the Human Sciences Research Council (HSRC) and
universities.
This report is organised as follows: In Chapter 3 a brief account of the methodology used by the VOCS
will be given. This will include the methodology used to calculate the errors of the estimates and the
classification of the quality of the estimates. A general overview of the crime situation in 2017/18 and
the trends leading to it are presented in Chapter 4. The crime trends are presented for overall household
and individual crimes, and are disaggregated by province, gender and population group. Estimates of
totals and percentages for specific types of crimes covered by VOCS will be confined only for the
2017/18 survey period.
Chapter 5 will focus on the details of specific household types of crime covered by VOCS. Some types
of crime may have more details than others, depending on the quantity of information gathered for each
crime type. For example, housebreaking or burglary will have most details because it is a crime that
affects most households. Details may include disaggregation by province, gender and population group;
reporting to the police behaviour; reasons for not reporting to the police; and levels of satisfaction with
police service. For the number of cases reported to the police we shall only present statistics from SAPS;

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however, we shall present estimates of proportions of households that reported crime to the police.
Simultaneous presentation of crime statistics from the two major sources is expected to provide a better
understanding of the crime situation and trends in the country.
Chapter 6 focuses on the same content as the previous chapter, but for individual crimes. The chapter
reports on various types of crime experienced by individuals aged 16 or above. Child interviews require
specialised techniques and settings that were not planned for the VOCS. Therefore, the survey does
not report on crime against children. This makes it difficult to compare VOCS individual crimes with
crime statistics (crimes against a person) reported by SAPS, as the latter does not have an age
restriction.
Statistics on how communities respond to crime are presented and discussed in Chapter 7, while
Chapter 8 deals with perceptions of household heads and individuals on issues of crime, safety and
satisfaction with the criminal justice system in South Africa. Statistics from these chapters feed into
impact indicators of the National Development Plan (NDP) on crime and safety.

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3. METHODOLOGY
The VOCS 2016 uses the master sample sampling frame which has been developed as a generalpurpose household survey frame that can be used by all other Stats SA household-based surveys
having design requirements that are reasonably compatible with the VOCS. The VOCS 2015/16
collection was drawn from the 2013 master sample. This master sample is based on information
collected during Census 2011. In preparation for Census 2011, the country was divided into 103 576
enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were
used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the
master sample, since they covered the entire country and had other information that is crucial for
stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the master sample
with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the
current master sample (3 324) reflect an 8,0% increase in the size of the master sample compared to
the previous (2008) master sample (which had 3 080 PSUs). The larger master sample of PSUs was
selected to improve the precision (smaller coefficients of variation, known as CVs) of the VOCS
estimates.
The master sample is designed to be representative at provincial level and within provinces at
metro/non-metro levels. The sample is also distributed by geographical type. The three geographical
areas are metro, rural and urban. This implies, for example, that within a province, the sample is
representative of the different geographical areas that may exist within that metro.
The sample of the VOCS is based on a stratified, two-stage design with probability proportional to size
(PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling
in the second stage.

Indicators of crime level
Statistics that are used mostly in this report are the totals, proportions and percentages, as has been
the case for a number of years. This year, two more statistics will be introduced in order to enrich the
presentation of the crime situation in the country. The new statistics introduced in this report are the
repeat victimisation index (RVI) and the multiple victimisation index (MVI) defined as:

 Estimated total number of incidents of a specific type of crime committed 
RVI = 
 × 100
Estimated total number of victimised households or individuals


n

= 100 ×

∑ f w1
i =1
n

fi

i i

∑w 1
i =1

where

i

i i

is the number of times household/individual i experienced a specific type of crime,

sampling weight of household/individual i and
specific type of crime and 0 otherwise.

Victims of Crime Survey, 2017/18

1i

wi

is the

equals to 1 if household/individual i experienced the

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 Estimated total number of crimes of different types committed 
MVI = 
 × 100
 Estimated total number of victimised households/individuals 
n

= 100 ×

∑c w 1
i =1
n

i

∑w 1
i =1

where

ci

i i

i i

is the number of different types of crimes experienced by household/individual i during the

reference period.
The repeat victimisation index is thus a weighted average number of repeated victimisation through a
specific type of crime per 100 households/individuals. Similarly, the multiple victimisation index is the
weighted average of the number of different types of crime experienced by 100 households/individuals.
The bigger the value of any of these indices, the worse the crime situation is. The minimum value of
each index is 100.

Quality flag
In this report, every estimate will be assigned a quality level based on the coefficient of variation (CV)
of the estimate. Coefficient of variation is a measure of the relative size of error defined as

 Standard error 
100 × 

 Estimate value 
The South African Statistical Quality Assurance Framework (SASQAF) prescribes four quality levels
based on a number of criteria, including the coefficient of variation. Each quality level will be labelled by
colour (flag) as defined in the table below.
Table 2: Quality classification of estimates
Coefficient of variation range

Level

Interpretation

0 – 16,5

Quality statistics (reliable estimates)

16,6 – 33,4

Acceptable estimate (use with caution)

33,5 – 100,0

Poor estimate (not fit for use)

The survey package of the R software was used to calculate the estimates and the CVs. The package
is specifically designed for analysis of data from complex surveys. Every computation using the survey
package requires specification of three key design parameters, namely the strata, clusters (PSUs) and
final weights.
Estimates with CVs highlighted in orange must not be used as they are of poor quality. These poor
quality estimates are left in the table just for completeness. The poor estimates are also highlighted in
grey as a further indication that they should not be used.

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4. GENERAL OVERVIEW OF CRIME
This chapter provides an overview of various crime types from the period 2013/14 and 2017/18. The
Victims of Crime Survey (VOCS) focuses on eleven types of household crimes and seven types of
crimes against individuals. Crimes against households are discussed in more detail in Chapter 5, and
those against individuals are discussed in Chapter 6. The household crimes measured in VOCS are
theft of motor vehicle, housebreaking or burglary, home robbery, theft of livestock/poultry and other
animals, theft of crops planted by households, murder, trafficking in persons, theft out of motor vehicles,
deliberate damaging/burning/ destruction of dwellings, motor vehicle vandalism/deliberate damage of
motor vehicles, and theft of bicycles. The individual crime section focuses on crime experienced by a
randomly selected person in the household aged 16 years and older. Individual crimes involve crimes
that are violent and non-violent in nature, such as theft of personal property, hijacking of motor vehicle,
robbery, sexual offence, assault, consumer fraud and corruption.

4.1 Five-year trends
The section aims to give a general overview for each of the nine provinces. Each figure below represents
the estimate of the total number of incidences of household (or individual) crime that occurred in the
specific year in the particular province.
Table 3: Number of incidences of household and individual crime by province, 2013/14–2017/18
Household crime

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

345 600

300 164

307 572

217 428

213 697

Eastern Cape

376 178

315 564

190 397

196 187

183 007

Northern Cape

74 918

86 826

28 534

48 009

39 287

Free State

52 231

57 300

80 291

77 061

85 467

KwaZulu-Natal

157 579

156 134

239 091

282 805

304 626

North West

133 905

138 831

113 425

72 496

103 276

Gauteng

445 768

402 500

498 474

377 834

401 139

Mpumalanga

252 783

248 081

138 609

102 802

128 953

Limpopo

275 909

171 871

103 341

93 658

86 250

2 114 871

1 877 271

1 699 734

1 468 279

1 545 701

Western Cape

420 193

377 725

366 138

346 048

261 758

Eastern Cape

219 256

226 347

247 602

262 161

233 166

Northern Cape

50 949

59 455

43 489

40 113

34 710

Free State

137 340

110 452

76 943

81 916

124 333

KwaZulu-Natal

219 485

306 090

226 997

184 980

162 943

North West

142 612

127 208

105 765

90 982

164 383

Gauteng

544 484

558 552

432 340

375 643

486 270

Mpumalanga

162 356

123 688

142 868

116 591

112 276

Limpopo

138 180

74 904

111 903

104 206

102 786

2 034 854

1 964 421

1 754 044

1 602 640

1 682 624

SOUTH AFRICA
Individual crime

SOUTH AFRICA

Proportions and percentages usually provide a better understanding than absolute numbers.

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Table 4: Percentage of households and individuals affected by crime by province,
2013/14–2017/18
Household crime

2013/14

2014/15

2015/16

2016/17

2017/18

Qty

Western Cape

13,4

13,9

11,1

9,0

8,7

Eastern Cape

12,3

12,4

10,2

9,0

8,6

Northern Cape

10,7

10,0

7,5

8,2

8,4

6,8

6,9

7,2

5,7

7,3

10,5

9,1

7,5

7,8

8,5

North West

9,9

7,2

7,2

6,3

6,4

Gauteng

9,7

10,2

9,1

6,5

6,8

11,5

9,7

9,0

6,5

8,9

6,5

6,6

5,0

5,4

4,8

SOUTH AFRICA

10,2

9,9

8,5

7,2

7,5

MVI

109

107

109

106

124

Western Cape

7,6

7,0

6,5

5,4

4,6

Eastern Cape

4,8

4,3

5,2

5,1

4,2

Northern Cape

5,3

5,9

4,3

2,9

3,9

Free State

5,0

4,8

3,3

3,5

5,0

KwaZulu-Natal

3,2

3,1

2,3

2,3

1,8

North West

4,9

4,5

3,6

3,1

5,0

Gauteng

4,5

5,0

3,9

3,1

4,2

Mpumalanga

5,2

3,5

4,3

4,1

3,4

Limpopo

3,0

2,0

2,0

2,3

2,6

SOUTH AFRICA

4,7

4,4

3,9

3,5

3,7

MVI

104

105

105

105

119

Free State
KwaZulu-Natal

Mpumalanga
Limpopo

Individual crime

It is important to note that the statistics provided in Table 3 and Table 4 do not include crimes that are
not covered by the VOCS, such as business robbery, cash in transit robbery, drug trafficking or illegal
possession of firearms or ammunition, just to mention a few. The multiple victimisation index (MVI) tries
to capture the multiplicity of crimes experienced by households or individuals in a particular year.

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Figure 1 below gives a summary of the changes of the levels of crime between 2016/17 and 2017/18
for household and individual crimes.
Figure 1: Percentage change of household and individual crime levels by province,

2016/17–2017/18
100,0
80,0

Percentage

60,0
40,0
20,0
0,0
-20,0
-40,0
Househohold
Individual

Western
Cape
-1,7

Eastern
Cape
-6,7

Northern
Cape
-18,2

-24,4

-11,1

-13,5

10,9

KwaZuluNatal
7,7

51,8

-11,9

Free State

Gauteng

Mpumalanga

42,5

6,2

25,4

-7,9

SOUTH
AFRICA
5,3

80,7

29,5

-3,7

-1,4

5,0

North West

Limpopo

Figure 1 shows that between 2016/17 and 2017/18, five provinces have experienced an increase in
household crime, while three have experienced an increase in individual crime. North West had the
highest increase of both household (43%) and individual crime (81%), followed by Free State and
Gauteng for individual crime.
Figure 2: Percentage
2013/14–2017/18

of

households

and

individuals that

were victims of

crime,

12
10

Percentage

8
6
4
2
0
Household crimes

2013/14
10,2

2014/15
9,9

2015/16
8,5

2016/17
7,2

2017/18
7,5

Individual crimes

4,7

4,4

3,9

3,5

3,7

Figure 2 shows that household and individual crime followed similar trends between 2013/14 and
2017/18, where both declined between 2013/14 and 2016/17, and both escalated between 2016/17 and
2017/18.

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Table 5: Percentage of households and individuals who experienced crime according to gender
and population group, 2017/18
Percentage of
households

CV%

Percentage of
individuals

CV%

Male

7,8

4

4,3

6

Female

7,1

4

3,1

7

7,2

3

3,7

5

Coloured

7,4

10

3,9

14

Indian/Asian

11,7

16

1,9

39

White

8,5

10

3,8

15

SOUTH AFRICA

7,5

3

3,7

4

Gender

Population group
Black African

Male-headed households and individual males aged 16 year and older experienced significantly more
crime in 2018/17 compared to female-headed households and females aged 16 years and older.
Indian/Asian households (11,7%) were more likely to experience household crime compared to other
population groups, while coloured individuals aged 16 and above (3,9%) were more likely to experience
individual crime than other population groups.

4.2 Crime levels in 2017/18
In this section we look at statistics related to specific types of crime covered in VOCS. Estimates are
provided for 2017/18. Changes between 2016/17 and 2017/18 are also discussed.
Table 6: Number of incidences, number of households affected and distribution of household
crime experienced, 2017/18

Type of household crime
Theft of motor vehicle

Number of crime
incidences
experienced by
households

CV%

Number of
households that
experienced crime
(%)

Percentage of
total
household
crimes
experienced

CV%

56 526

15

54 092 (0,33)

4

14

Housebreaking or burglary

832 122

5

705 569 (4,25)

54

4

Home robbery
Theft of livestock, poultry and other
anima

156 089

9

133 549 (0,80)

10

9

159 421

10

127 826 (0,77)

10

8

Theft of crops planted by the household

11 493

38

8 252 (0,05)

1

33

Murder

16 809

31

12 585 (0,08)

1

25

130 350

11

112 063 (2,35)

8

9

50 426

19

38 143 (0,23)

3

14

40 155

16

40 155 (0,24)

3

16

29 264

20

29 264 (0,18)

2

20

63 045

13

54 556 (0,33)

4

13

1 545 701

4

1 244 152 (7,5)

100

Theft out of motor vehicle
Deliberate damaging, burning,
destruction of buildings
Motor vehicle vandalism/deliberate
damage of motor vehicle
Theft of bicycle
Other crimes
SOUTH AFRICA

Table 6 shows that housebreaking or burglary constituted 54% of all household crimes surveyed by
VOCS. According to SAPS 2017/18 statistics, burglary also had the highest figure among the
community-reported serious crimes. The least experienced crimes were murder and theft of crops,
where 1% of households experienced these crimes.

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Figure 3: Comparison of distribution of household crime, 2016/17–2017/18
2016/17

2%

2017/18

2%

3%

4% 3%

4% 4%

3%

3%
1%
1%

2%

10%

1%
1%

8%

10%

11%

53%
10%

54%
10%

Housebreaking or burglary
Home robbery
Theft of livestock, poultry and other animals
Theft of crops planted by the household
Murder
Theft out of motor vehicle
Deliberate damaging, burning, destruction of buildings
Motor vehicle vandalism/deliberate damage of motor vehicle
Theft of bicycle
Other crimes
Theft of motor vehicle

Figure 3 shows that housebreaking or burglary continues to be the dominant household crime,
accounting for about 54% of all household crimes in 2017/18.

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Table 7: Number of incidences, number of individuals affected and distribution of individual
crime experienced, 2017/18

Type of individual crime

Number of crime
incidences
experienced by
individuals

Theft of personal property

693 219

6

663 477 (1,72)

41,2

6

Hijacking of motor vehicle

34 880

27

34 880 (0,09)

2,1

27

280 526

12

258 910 (0,67)

16,7

11

28 596

35

22 694 (0,06)

1,7

33

Assault

355 739

13

277 397 (0,72)

21,1

10

Consumer fraud

137 274

29

89 065 (0,23)

8,2

18

Corruption

134 442

18

116 014 (0,30)

8,0

16

17 949

44

9 956 (0,03)

1,1

39

1 682 624

6

1 417 731 (4,0)

100

Robbery
Sexual offence

Other crimes
SOUTH AFRICA

Number of
individuals who
experienced crime
%

CV%

Percentage of total
individual crimes
experienced

CV%

In 2017/18, over 1,6 million individuals aged 16 years and above were victims of crime, of which 74%
experienced theft of personal property, robbery or assault.
Figure 4: Comparison of distribution of individual crime, 2016/17–2017/18
2016/17

2017/18
1%

2%
3%

6%

8%
8%

20%

41%

44%
21%

5%
18%

2%
2%

17%

2%

Theft of personal property
Hijacking of motor vehicle
Robbery
Sexual offence
Assault
Consumer fraud
Corruption
Other crimes

Figure 4 shows that the theft of personal property, assault and robbery were the most common crimes
against individual adults 16 years and older in 2017/18.

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5. HOUSEHOLD EXPERIENCE OF CRIME
In this chapter, household crime statistics are presented according to the type of crime. The Victims of
Crime Survey (VOCS) focuses on thirteen types of household crime and seven types of crimes against
individuals. Crimes against individuals will be discussed in the next chapter. The household crimes
measured in VOCS are theft of motor vehicle, housebreaking or burglary, home robbery, theft of
livestock/poultry and other animals, theft of crops planted by households, murder, trafficking in persons,
theft out of motor vehicles, deliberate damaging/burning/destruction of dwellings, motor vehicle
vandalism/deliberate damage of motor vehicles, theft of bicycles, sexual offence, and assault. For
definitions of these crimes, refer to Annexure B. No estimates for trafficking in persons will be presented,
as the number of households that experienced this type of crime is too small.
Every section will have a graph showing a five-year trend for the particular type of crime covered in that
section. Disaggregated statistics will be presented only when the majority of the estimates are of
acceptable quality.

5.1 Theft of motor vehicle
Estimates of the total number and percentages of households affected by motor vehicle theft in 2017/18
are presented according to the gender and population group of the household head.
Information on the household ownership of motor vehicles for various groups of people in South Africa
may provide useful information when analysing the profiles of victims of theft of motor vehicles later in
the section.
Table 8: Distribution of vehicle ownership by gender and population group of household head,
2017/18
Number of
vehicles

CV%

Percentage of households

CV%

Male

3 623 088

2

37,2

1

Female

1 392 177

4

20,3

3

2 704 131

3

20,2

2

Coloured

467 622

6

38,9

4

Indian/Asian

314 963

8

82,0

3

White

1 528 550

4

91,6

1

SOUTH AFRICA

5 015 266

2

30,2

1

Indicator
Gender of the household head

Population group of the household head
Black African

Household ownership of motor vehicles according to the population group of the household head is
highlighted in the bar chart below:

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Figure 5: Percentage distribution of household vehicle ownership by population group of the
household head, 2016/17–2017/18
100

94,2

90

81,3

80

91,6

82

Percentage

70
60
50

41,8

40
30
20

19,8

38,9

20,2

10
0

Black African

Coloured
2016/17

Indian/Asian

White

2017/18

Figure 5 shows that two out of ten black African households owned a motor vehicle, in working condition,
while more than nine in ten of white households owned a motor vehicle in a working condition. The
distribution of motor vehicle ownership is the same as that of 2016/17.
It is useful to examine the trend in motor vehicle theft over a number of years. As indicated in the
introduction, two trends are presented: one is the estimate of the number of households that experienced
motor vehicle theft in the past twelve months, and the other is the number of vehicles and motorcycles
reported as stolen to the police (SAPS). Stolen vehicles reported to SAPS include commercial vehicles
while VOCS estimates only reflect stolen motor vehicles owned by households.
Table 9: Trends in motor vehicle theft estimated from VOCS, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

57 415 (15)

67 104 (12)

57 783 (14)

47 586 (15)

56 526 (15)

53 172 (15)

62 819 (12)

57 783 (14)

45 593 (14)

54 092 (14)

***

***

1,26 (14)

0,95 (14)

0,33 (14)

108 (5)

107 (3)

100 (0)

104 (4)

104 (4)

*Vehicle ownership was not asked in this period

Table 9 shows that between 2016/17 and 2017/18 theft of motor vehicles increased from 47 586 to
56 526 incidences. This was an increase of 19%.

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SAPS statistics combines theft of motor vehicles with theft of motor cycles, unlike VOCS, which reports
only on the former. The number of motor vehicles and motor cycles reported as stolen to the police
(SAPS) are presented in Table 10. The VOCS estimates cannot be disaggregated by province like the
SAPS data because of the small number of incidences recorded during the survey.
Table 10: Theft of motor vehicles and motor cycles reported to the police, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

9 460

8 918

8 378

7 381

7 104

Eastern Cape

3 376

3 276

2 678

2 739

2 443

321

327

246

219

233

Free State

2 022

1 743

1 745

1 588

1 596

KwaZulu-Natal

8 674

8 404

8 673

8 413

8 240

North West

2 039

1 984

2 070

2 068

2 112

27 436

27 147

26 646

27 674

25 705

2 340

2 303

2 222

2 208

2 206

Northern Cape

Gauteng
Mpumalanga
Limpopo
SOUTH AFRICA

977

988

1 151

1 017

1 024

56 645

55 090

53 809

53 307

50 663

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

It is unfortunate that SAPS data do not separate motor vehicle and motor cycle theft. This makes it
difficult to compare the two series.
Figure 6: Trends in theft of motor vehicles and reporting of motor vehicle theft to the police,
2013/14–2017/18

Number of incidences / cases

70 000
65 000
60 000
55 000
50 000
45 000
40 000
35 000
30 000

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

57 415

67 104

57 783

47 586

56 526

SAPS

56 645

55 090

53 809

53 307

50 663

Between 2014/15 and 2016/17, both series show declining trends, although VOCS declined more rapidly
than SAPS. VOCS shows a sharp increase in theft of motor vehicles between 2016/17 and 2017/18. It
must be remembered that the SAPS statistics include motor cycles and non-private vehicles, while
VOCS counts only motor vehicles owned by households.

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Table 11: Percentage of theft of motor vehicles reported to the police by gender and population
group of the household head and insurance status, 2016/17–2017/18
Percentage in
2016/17

CV%

Percentage in
2017/18

CV%

Male

81

7

77

10

Female

100

0

81

10

81

9

74

10

Coloured

87

11

100

0

Indian/Asian

100

0

85

18

White

94

7

79

17

Insured

100

0

95

5

Not insured

91

7

81

9

SOUTH AFRICA

86

5

78

7

Indicator
Gender of the household head

Population group of the household head
Black African

Insurance

Table 11 shows a significant decline in the percentage of motor vehicle thefts that are reported to the
police (from 86% to 78%). Among the stolen motor vehicles that were insured, however, 95% of the
thefts were reported to the police in 2017/18. Among the non-insured, 91% and 81% were reported to
the police in 2016/17 and 2017/18, respectively. Population group seems to be a factor associated with
the reporting of motor vehicle thefts, where black Africans had the lowest reporting rates in both years
and coloureds had the highest reporting rate in 2017/18. Among black African households who had cars
stolen, only 32% had car insurance while 70% of white households had car insurance. 37% of maleheaded households had car insurance, while 50% of female-headed households had car insurance.

5.2 Housebreaking/burglary
Housebreaking or burglary accounts for 54% of all household crimes covered by VOCS and for about
14% of community reported serious crimes released by SAPS in 2017/18. In both cases it is the
dominant type of crime. In this section, five-year series of VOCS housebreaking estimates are presented
together with burglary at residential premises released by SAPS. The purpose is to visualise the trends
in order to determine the commonalities of the data sources with respect to burglary.
Table 12: Trends in housebreaking/burglary, 2013/14–2017/18

Statistic

2013/14

2014/15

2015/16

Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)

940 954 (5)

874 606 (4)

714 089 (4)

Repeat victimisation index (CV%)

2016/17

2017/18

844 982 (4)

776 933 (4)

832 122 (5)

767 917 (4)

727 130 (4)

647 340 (4)

705 569 (4)

4,86 (4)

5,07 (4)

4,66 (4)

4,04 (4)

4,25 (4)

132 (4)

114 (2)

116 (2)

120 (2)

118 (2)

Table 12 shows a steady decline in housebreaking incidences between 2013/14 and 2016/17, but
then an increase to 832 122 incidences in 2017/18.

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Table 13: Housebreaking or burglary reported to the police, 2013/14–2017/18

Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

50 503

47 783

47 569

46 043

42 662

Eastern Cape

24 643

24 329

23 901

24 385

23 758

Northern Cape

6 013

6 204

6 469

6 518

6 228

Free State

16 314

15 618

15 323

14 635

13 463

KwaZulu-Natal

43 969

43 274

42 429

41 013

38 545

North West

15 388

15 687

15 568

15 908

15 267

Gauteng

67 988

66 172

64 968

63 661

56 255

Mpumalanga

18 489

18 183

18 162

18 507

17 565

Limpopo

16 477

16 466

16 217

15 984

14 351

259 784

253 716

250 606

246 654

228 094

SOUTH AFRICA

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

At national level, the VOCS estimates are more than three times those of the SAPS. This is to be
expected, because not all burglaries are reported to the police.
Figure 7: Trends in housebreaking/burglary and reporting to the police, 2013/14–2017/18

Number of burglaries /cases

1 000 000
900 000
800 000
700 000
600 000
500 000
400 000
300 000
200 000
100 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

940 954

874 606

844 982

776 933

832 122

SAPS

259 784

253 716

250 606

246 654

228 094

Figure 7 shows that both VOCS estimates and SAPS reported cases declined between 2013/14 and
2016/17, although the rate of decline for SAPS was much slower than for VOCS. SAPS figures
continued to decline in 2017/18 while the VOCS estimate of the number of housebreaking incidences
increased. This is unexpected, as the estimated rate of reporting housebreaking to the police remained
the same, as shown in Table 14 below.

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Table 14: Percentage of housebreaking or burglary reported to the police by gender and
population group of the household head, province and geographical area, 2016/17–2017/18
Percentage in
2016/17

CV%

Percentage in
2017/18

CV%

Male

54

4

50

5

Female

46

6

53

5

Black African

46

4

46

4

Coloured

63

11

64

10

Indian/Asian

71

14

76

12

White

86

5

80

6

Metro

***

***

54

5

Rural

***

***

32

29

Urban

***

***

50

5

Western Cape

64

9

58

11

Eastern Cape

40

13

40

12

Northern Cape

78

8

39

18

Free State

72

11

72

8

KwaZulu-Natal

47

9

46

9

North West

56

13

52

15

Gauteng

49

7

53

7

Mpumalanga

42

18

52

12

Limpopo

43

14

54

12

SOUTH AFRICA

51

4

51

4

Indicator
Gender of the household head

Population group of the household head

Geographical area

Province

Nationally, the proportion of households that reported housebreaking or burglary to the police remained
the same as in 2016/17 at 51%. The provincial reporting rates remained essentially the same except for
the Northern Cape, where the number of households that reported housebreaking to the police dropped
sharply from 78% to 39%. The rates for reporting to the police were significantly higher in the metro and
urban areas compared to the rural areas. This may be due to better accessibility of police stations in
metro and urban areas when compared to rural areas.

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Table 15: Distribution of housebreaking/burglary by gender and population group of the
household head, province and geographical area, 2017/18

Number of incidences of
housebreaking/burglary
experienced by households

CV%

Percentage of households that
experienced at least one
housebreaking/burglary

CV%

Male

504 732

6

4,4

5

Female

327 390

7

4,1

6

Black African

683 178

5

4,3

4

Coloured

58 029

14

4,3

13

Indian/Asian

30 010

27

5,9

24

White

60 904

16

3,4

16

Western Cape

97 918

13

4,5

12

Eastern Cape

97 573

16

4,4

11

Northern Cape

23 678

23

5,2

17

Free State

35 912

19

3,6

18

KwaZulu-Natal

188 383

11

5,4

8

North West

55 687

20

3,3

16

Gauteng

209 511

8

3,8

8

Mpumalanga

74 781

14

5,3

12

Limpopo

48 679

15

2,9

15

Metro

369 522

8

4,2

6

Rural

34 641

19

3,0

18

Urban

427 959

6

4,5

5

SOUTH AFRICA

832 122

5

4,25

4

Indicator
Gender of the household head

Population group*

Province

Geographical area

*of the household head

It is estimated that 832 122 incidences of housebreaking or burglary took place in 2017/18, affecting
4,25% of households in South Africa. This is an increase of 7% from 2016/17. Northern Cape, KwaZuluNatal and Mpumalanga had the highest proportion of households affected by housebreaking, while
Limpopo had the lowest proportion of households affected by housebreaking. The Indian/Asian
population group had the highest proportion of housebreakings and the white population group had the
lowest. The difference between male- and female-headed households was marginal, but a greater
proportion of male-headed than female-headed households experienced housebreakings.

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Table 16: Percentage of household goods stolen during housebreaking/burglary by type, 2017/18
Item stolen

Percentage

CV%

Handbag/wallet

8,3

12

Money

20,4

8

Electronic equipment (e.g. laptop)

21,0

8

Travelling bag

6,9

15

Food stuff

22,2

7

Personal effects (e.g. watches)

17,6

8

Cell phones

23,6

7

Clothes

31,6

5

***

***

Radio

16,4

9

Bicycle

1,9

25

Other

31,1

5

TV

Clothes was the most common (31,6%) item stolen during housebreaking in 2017/18, followed by cell
phones and food. Bicycles were the least likely items to be stolen during housebreaking. It is estimated
that 1,9% of households lost bicycles during burglary.
Table 17 gives a summary of reasons for not reporting housebreaking to the police.
Table 17: Reasons for not reporting housebreaking to the police, 2017/18

Reason for not reporting housebreaking/burglary to the police

Percentage

CV%

Solved it myself/perpetrator known to me

4,7

22

Inappropriate for police/police not necessary

11,6

14

Reported to other authorities instead

3,2

28

My family resolved it

6,3

23

No insurance

2,1

37

Police could do nothing/lack of proof

52,8

5

Fear/dislike of the police/no involvement wanted with police

2,1

36

Did not dare (fear of reprisal)

1,1

46

Other reasons

14,4

13

Do not know

1,0

50

"Police could do nothing" accounted for 52,8% of the reasons given by household representatives for
not reporting housebreaking to the police. This reason for not reporting housebreaking to the police has
been the dominant reason for the past five years.

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Victim satisfaction with police handling of crime reported to them is an important indicator of progress in
the war against crime. Satisfaction with the police may encourage communities to work with the police
in the fight against crime. Table 18 provides a summary of the levels of satisfaction among different
groups.
Table 18: Satisfaction with the police by gender, population group of the household head,
geographical area and province, 2017/18
Indicator

Percentage

CV%

Gender of the household head
Male

33

9

Female

33

12

Population group of the household head
Black African

30

9

Coloured

30

24

Indian/Asian

38

34

White

53

17

Metro

33

12

Rural

22

59

Urban

33

10

Western Cape

38

18

Eastern Cape

42

19

Northern Cape

52

21

Free State

43

19

KwaZulu-Natal

29

19

North West

25

40

Gauteng

28

19

Mpumalanga

37

20

Limpopo

26

29

SOUTH AFRICA

33

8

Geographical area

Province

Over 33% of households that reported housebreaking were satisfied with the police response. There
was no difference in the percentage of satisfied households between those headed by males and those
headed by females. Whites were the population group that was most satisfied (53%) with the police
response compared to other groups. Households in Northern Cape, Free State and Eastern Cape were
the most satisfied with the police response when compared to other provinces.

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5.3 Home robbery
Home robbery is a type of robbery that happens at residential premises when there is contact between
perpetrators and one or more household members. Typically, the victims are subdued by force when
the crime is committed. This makes home robbery a more violent crime than housebreaking, where
there is, per definition, no contact between perpetrators and victims when the crime is committed. The
term "Robbery at residential premises" is the expression used by SAPS that has the same meaning as
home robbery.
Nationally it is estimated that 156 089 home robberies were committed in 2017/18. This is an increase
of 3% from last year's estimate.
Table 19 presents the time series of the total number of home robberies, total number of households
affected by home robberies, proportion of households that experienced at least one home robbery in
the last year, and the multiple victimisation index.
Table 19: Trends in home robbery, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

268 639 (7)

208 401 (8)

187 830 (7)

151 279 (9)

156 089 (9)

234,045 (7)

182 692 (7)

171 739 (7)

128 206 (8)

133 549 (8)

1,59 (7)

1,21 (7)

1,10 (7)

0,80 (8)

0,80 (9)

115 (3)

114 (4)

109 (2)

118 (4)

115 (4)

Due to sample limitations, VOCS cannot produce accurate provincial estimates of home robbery for all
provinces. The SAPS provincial breakdown of home robbery or robbery at residential premises is
summarised in Table 20.
Table 20: Robbery at residential premises reported to the police by province, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

Western Cape

1 878

2 158

2 574

2 560

2 787

Eastern Cape

1 924

1 811

2 054

2 171

2 184

Northern Cape

110

123

106

142

159

Free State

753

718

773

875

864

KwaZulu-Natal

4 099

3 958

4 082

4 255

4 174

North West

1 004

1 110

1 065

1 290

1 145

Gauteng

7 438

8 174

7 896

8 731

8 333

Mpumalanga

1 118

1 112

1 080

1 138

1 125

960

1 117

1 190

1 181

1 490

19 284

20 281

20 820

22 343

22 261

Limpopo
SOUTH AFRICA

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

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Number of incidences / cases

Figure 8: Home robbery and reporting of robbery at residential places to the police,
2013/14–2017/18
300 000
250 000
200 000
150 000
100 000
50 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

268 639

208 401

187 830

151 279

156 089

SAPS

19 284

20 281

20 820

22 343

22 261

The home robbery trends for VOCS and SAPS data moved in different directions between 2013/14 and
2016/17. It is quite possible for incidences of home robbery to decline, and for the rate of reporting the
crime to the police to increase, possibly as more people gain better access to police stations.
Table 21: Percentage of home robberies reported to the police by gender and population group
of the household head, geographical area and province, 2016/17–2017/18
Indicator

Percentage in
2016/17

CV%

Percentage in
2017/18

CV%

Gender of the household head
Male

59

4

62

8

Female

43

15

55

12

Black African

47

10

58

8

Coloured

54

21

70

20

Indian/Asian

***

***

36

51

White

73

14

71

16

Metro

***

***

59

10

Rural

***

***

39

62

Urban

***

***

59

9

Western Cape

75

12

71

15

Eastern Cape

40

29

47

22

Northern Cape

59

48

79

17

Free State

***

***

75

18

KwaZulu-Natal

64

14

64

15

North West

40

43

59

35

Gauteng

51

14

55

15

Mpumalanga

42

27

73

17

Limpopo

31

40

33

41

SOUTH AFRICA

53

8

59

7

Population group of the household head

Geographical area

Province

Victims of Crime Survey, 2017/18

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As remarked earlier, accurate provincial estimates of home robbery reporting rates could be calculated
for seven provinces, while estimates from the other two provinces are not usable. Mpumalanga,
Northern Cape, Free State and Western Cape had the highest (over 70%) percentage of robbed
households that reported to the police. In the case of Mpumalanga, the jump in the reporting rate from
42% in 2016/17 to 73% in 2017/18 is quite drastic and needs further investigation.
Table 22: Home robberies experienced by gender and population group of the household head,
geographical area and province, 2017/18
Number of incidences of
home robberies experienced
by households

CV%

Percentage of households
that experienced at least one
home robbery

CV%

Male

83 944

13

0,72

12

Female
Population group of the
household head

72 145

13

0,93

13

Black African

117 961

11

0,76

10

Coloured

11 939

34

0,69

33

Indian/Asian

11 492

42

2,33

44

White

14 697

26

0,85

26

Metro

76 640

14

0,92

13

Rural

4 816

54

0,31

51

Urban

74 633

14

0,76

12

Western Cape

16 792

25

0,85

24

Eastern Cape

19 223

23

0,94

22

Northern Cape

5 617

42

0,96

33

Free State

8 281

35

0,76

33

KwaZulu-Natal

26 673

24

0,83

23

North West

6 187

41

0,45

41

Gauteng

45 679

18

0,84

17

Mpumalanga

12 475

31

0,82

29

Limpopo

15 162

39

0,68

27

SOUTH AFRICA

156 089

9

0,80

9

Indicator
Gender of the household head

Geographical area

Province

It is estimated that nearly 1% of South African households were victims of home robbery in 2017/18.
While housebreaking seems to target male-headed households more than female-headed households,
it is the other way around for home robbery. The difference between victimisation rates between different
population groups with respect to home robbery appears to be significant.

5.4 Theft of poultry, livestock and other animals
In the case of theft of livestock, poultry and other animals, it is reasonable to include a disaggregation
of statistics according to geographical areas, as animals are kept mostly in rural areas. The geographical
classification used here has three categories, namely metro, urban and rural. Metro areas are Cape
Town, Johannesburg, Ekurhuleni, eThekwini, Nelson Mandela Bay, Tshwane, Mangaung and Buffalo
City.

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Table 23 presents estimates of the number of incidences of theft of livestock, poultry and other animals,
the number of households affected, percentage of households affected and multiple victimisation index
for the period 2013/14 to 2017/18. An estimated total of 159 421 incidences of theft of livestock, poultry
and other animals were experienced by South Africans in 2017/18, which is a decrease of 1% from
2016/17. Almost 1% of South African households were affected by this crime.
Table 23: Trends in theft of livestock, poultry and other animals, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

253 373 (8)

164 710 (8)

148 785 (8)

161 063 (10)

159 421 (10)

190 135 (6)

138 397 (7)

124 913 (8)

115 953 (8)

127 826 (10)

1,30 (6)

0,92 (7)

0,80 (8)

0,73 (8)

0,77 (10)

133 (4)

119 (4)

119 (4)

139 (7)

114 (4)

The SAPS crime type that is closest to the VOCS theft of livestock, poultry and other animals is stock
theft. Stock theft, however, includes theft of agricultural produce. A fair comparison can be done when
theft of livestock, poultry and other animals is combined with theft of crops planted by households.
Table 24: Stock theft reported to the police by province, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

Western Cape

789

831

861

885

953

Eastern Cape

5 808

6 087

5 809

6 023

6 217

Northern Cape

1 211

1 331

1 332

1 356

1 558

Free State

4 051

3 527

3 466

3 677

4 032

KwaZulu-Natal

5 754

5 956

5 731

5 959

6 322

North West

2 388

2 574

2 605

3 192

3 447

784

801

818

987

998

Mpumalanga

2 182

2 192

2 337

2 867

3 135

Limpopo

1 567

1 666

1 756

1 956

2 187

SOUTH AFRICA

24 534

24 965

24 715

26 902

28 849

Gauteng

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

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Stock theft as referred to in Figure 9, is based on the expanded SAPS definition of stock theft, which
combines animals and agricultural produce statistics. Thus, the VOCS data in Figure 9 combine theft of
livestock, poultry and other animals and theft of crops planted by households to make it comparable to
SAPS figures.
Figure 9: Theft of livestock and reporting of stock and crop theft to the police, 2013/14–2017/18

Number of incidences / cases

350 000
300 000
250 000
200 000
150 000
100 000
50 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

301 350

181 553

187 940

176 066

159 421

SAPS

24 534

24 965

24 715

26 902

28 849

Theft of stock and crops reported to the police has in general been increasing between 2013/14 and
2017/18, while the VOCS reported a decrease in the incidence of theft of livestock, poultry and other
animals for the same period.
Table 25: Percentage of theft of livestock, poultry and other animals reported to the police by
gender and population group of the household head and geographical area, 2016/17–2017/18
Percentage in
2016/17

CV%

Percentage in
2017/18

CV%

Male

35

15

34

14

Female

19

23

23

20

Black African

25

15

28

12

Coloured

26

66

***

***

Indian/Asian

***

***

***

***

White

61

32

65

27

Metro

***

***

***

***

Rural

***

***

38

31

Urban

***

***

30

12

SOUTH AFRICA

26

13

29

12

Gender of the household head

Population group of the household head

Geographical area

In both 2016/17 and 2017/18, female-headed households tended to report theft of livestock, poultry and
other animals less than male-headed households. In general, the reporting rate of this crime is very low
compared to the reporting rates of other crimes.

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Table 26: Distribution of theft of poultry/livestock by gender of the household head, geographical
area and province, 2017/18
Indicator

Number of incidences

CV%

Percentage of households

CV%

Male

90 125

13

0,73

10

Female

69 297

15

0,83

12

6 327

32

0,09

32

Rural

14 984

27

1,27

24

Urban

138 110

11

1,32

9

Western Cape

4 120

70

0,11

58

Eastern Cape

36 007

13

2,00

13

Northern Cape

2 639

41

0,66

40

Free State

12 478

28

1,19

27

KwaZulu-Natal

47 610

24

1,18

17

North West

15 586

28

1,08

28

Gauteng

8 003

58

0,06

52

Mpumalanga

22 459

29

1,45

20

Limpopo

10 519

27

0,63

27

SOUTH AFRICA

159 421

10

0,77

8

Gender of the head of household

Geographical area
Metro

Province

Theft of livestock, poultry and other animals was experienced significantly more in the rural and urban
areas than in the metro areas.
Figure 10: Percentage of households that experienced theft of livestock, poultry or other animals
by geographical area, 2017/18
0,0140

1,27%

1,32%

Proportion of households

0,0120
0,0100
0,0080
0,0060
0,0040
0,0020
0,0000

0,09%
Metro

Rural

Urban

The non-metro areas dominate in the percentage of households that experienced theft of livestock,
poultry and other animals. This is to be expected, as farming is not a main economic activity in
metropolitan areas.

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Table 27 below presents the number of animals/poultry stolen during theft of livestock, poultry and other
animals as well as the proportion of households that suffered loss from theft.
Table 27: Number of animals stolen and percentage of households that suffered loss, 2017/18
Number of animals
stolen

CV%

Percentage of households that
suffered loss

CV%

177 310

33

23,8

13

***

100

***

Pigs

10 467

43

3,7

35

Sheep

269 226

35

19,0

17

Goats

170 316

22

30,6

12

Poultry (chicken, ducks, etc.)

213 560

27

26,5

12

Dogs (excl. pets)

1 507

71

1,5

60

Horses, donkeys, mules

8 392

50

2,1

45

Other

16 469

98

***

***

SOUTH AFRICA

927 699

17

0,7

8

Type of animal
Cattle
Rabbits

An estimated total of 927 699 animals and poultry were stolen in South Africa in 2017/18, of which 23,8%
were cattle, 30,6% were goats and 26,5% were poultry. Only the estimates on the number of cattle,
goats, poultry and the total are of acceptable quality; the other estimates should not be used. About
9,8% of households that lost livestock knew who stole their livestock. There is sufficient statistical
evidence (at 5% level of significance) of association between knowing the perpetrator of theft of
livestock, poultry and other animals, and reporting of theft to the police.

5.5 Theft of crops planted by household
Only thirty-seven households out of 21 190 surveyed reported that they experienced theft of crops during
the past twelve months, and none of them were located in rural areas. The population estimate of the
total number of incidences of theft of crops for 2017/18 is 11 493. This is a decrease of 21% since
2015/16. We cannot use the 2016/17 figure because of the poor quality of the estimate.
Table 28: Trends in theft of crops planted by the household, 2013/14–2017/18
Statistic
Number of incidences (CV%)
Number of households that experienced at least
one incident (CV%)
Proportion of households that experienced at least
one incident (CV%)
Repeat victimisation index for crop theft (CV%)

Victims of Crime Survey, 2017/18

2013/14

2014/15

2015/16

2016/17

2017/18

47 977 (23)

16 843 (22)

39 155 (26)

15 003 (65)

11 493 (38)

28 005 (17)

14 870 (23)

25 552 (17)

6 031 (32)

8 252 (38)

0,0019 (17)

0,001 (23)

0,0016 (17)

0,00042 (32)

0,05 (33)

171 (16)

113 (7)

153 (20)

249 (57)

111 (7)

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5.6 Murder
Murder is another crime that had a very low count among households interviewed. Only 30 out of a
total 21 190 households reported that they were victims of murder during the past year. Therefore, the
lowest level of disaggregation possible is by geographical area, as given in Table 31.
An estimated 16 809 people were murdered in South Africa in 2017/18. The term "murder" in VOCS
includes what SAPS refers to as "culpable homicide or unintentional killing of a human being". The
SAPS crime statistics release put the total number of murders in 2017/18 as 20 336. The difference with
the VOCS estimate is due to a number of factors; the main one being the inclusion of culpable homicide
in the definition of murder in VOCS. Another reason for the difference is that the SAPS murder count
includes murders identified by the police which households may not be aware of, such as, for example,
murders of immigrants or temporary visitors that have no connection with any household in the sample
frame.
Stats SA understands the importance of distinguishing murder and culpable homicide, but it is not
feasible to collect such information from household surveys where respondents may not understand the
difference between the two. It may also be a challenge at police stations for an officer to determine
whether the case being reported is murder or homicide.
Table 29: Trends in murder, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

26 529 (24)

18 012 (21)

14 930 (24)

16 201 (24)

16 809 (31)

21 693 (20)

18,012 (21)

14 930 (24)

16 201 (24)

12 585 (31)

0,15 (20)

0,12 (21)

0,10 (24)

0,10 (24)

0,08 (25)

122 (15)

100 (0)

100 (0)

100 (0)

111 (7)

The number of households that experienced murder in 2017/18 was 12 585 or 0,08% of all households
in South Africa. The repeat victimisation index being over 100 means that some households experienced
more than one murder during the reference period.

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Table 30: Murder and culpable homicide reported to the police, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

3 902

4 170

4 349

4 404

4 827

Eastern Cape

4 723

4 715

5208

5 100

5 243

Northern Cape

734

759

704

677

665

Free State

1 708

1 679

1 791

1 728

1 825

KwaZulu-Natal

5 854

6 043

6 333

6 449

6 823

North West

1 706

1 709

1 802

1 852

1 837

Gauteng

5 828

6 055

6 383

6 657

6 753

Mpumalanga

1 977

1 954

2 096

2 221

2 113

Limpopo

1 848

1 854

2 163

2 088

2 273

SOUTH AFRICA

28 280

28 938

30 829

31 176

32 359

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

The VOCS and SAPS murder series comparison in Figure 11 below must be viewed with the
background given at the beginning of the section in mind. The two series present related, but not same
type, of measurements.
Figure 11: Murder and reporting of murder and culpable homicide to the police,
2013/14–2017/18

Number of murders / cases

35 000
30 000
25 000
20 000
15 000
10 000
5 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

26 529

18 012

14 930

16 201

16 809

SAPS

28 280

28 938

30 829

31 176

32 359

Figure 11 shows that both VOCS and SAPS statistics show increasing trends in murder in South Africa
between 2015/16 and 2017/18. The fact that SAPS murder figures are higher than the VOCS estimated
number of incidences suggests that there are many murders that are unknown to households.

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Table 31: Murder reported to the police by gender of the household head and geographical area,
2016/17–2017/18

Indicator

Percentage in 2016/17

CV%

Percentage in 2017/18

CV%

Male

72

22

89

11

Female

63

27

88

13

Metro

***

***

90

10

Rural

***

***

***

***

Urban

***

***

82

20

SOUTH AFRICA

66

19

89

9

Gender of the household head

Geographical area

It is estimated that 89% of the murders in 2017/18 were reported to the police.

5.7 Theft out of motor vehicle
Theft out of a motor vehicle occurs when a person gains access to the interior of a motor vehicle, by
force or otherwise, when the owner is not present and takes valuable items. It is estimated that a total
of 130 350 incidences of theft out of motor vehicle occurred in 2017/18. This is a decrease of 7% from
the previous year. A total of 112 063 households were victims of this crime, representing 2,35% of all
households in South Africa that own motor vehicles.
Table 32: Trends in theft out of motor vehicle, 2013/14–2017/18

Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

208 978 (10)

196 236 (8)

192 736 (10)

139 432 (10)

130 350 (11)

163 242 (8)

173 978 (8)

151 485 (8)

121 764 (9)

112 063 (11)

1,12 (8)

1,16 (8)

3,284 (8)

2,54 (9)

2,35 (9)

128 (6)

113 (2)

127 (6)

115 (6)

107 (3)

Note: Coefficients of variation (CVs) in brackets

The SAPS crime category that has almost the same definition as "theft out of motor vehicle" is "theft
out of or from motor vehicle". The main difference between the two definitions is that in the SAPS
definition, it is not a requirement that the owner of the vehicle be absent. For example, a smash-andgrab incident would be recorded by SAPS as theft out of or from motor vehicle, while VOCS would not
record it as theft out of motor vehicle. Table 33 below gives the number of incidences of theft out of or
from motor vehicle reported to the police during the past five years, disaggregated by province.

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Table 33: Theft out of or from motor vehicle reported to the police by province,
2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

Western Cape

42 549

42 221

41 458

37 910

35 532

Eastern Cape

11 771

12 034

11 225

12 195

11 649

Northern Cape

2 968

2 898

2 962

2 911

2 609

Free State

5 661

5 399

4 878

4 822

4 599

KwaZulu-Natal

18 614

18 148

17 896

16 854

16 344

North West

5 981

6 349

5 913

6 293

5 866

Gauteng

42 528

44 809

42 111

45 266

41 298

Mpumalanga

7 675

7 999

7 372

6 926

6 830

Limpopo

5 466

5 501

5 571

4 995

4 447

143 213*

145 358

139 386

138 172

129 174

SOUTH AFRICA

2016/17

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php (*143 801?)

Figure 12: Theft out of motor vehicle reported to the police, 2013/14–2017/18

Number of incidences / cases

220 000
200 000
180 000
160 000
140 000
120 000
100 000

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

208 978

196 236

192 736

139 432

130 350

SAPS

143 801

145 358

139 386

138 172

129 174

Both VOCS and SAPS statistics show decreasing trends for the period 2013/14–2017/18.

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Table 34: Percentage of theft out of motor vehicle reported to the police by gender and
population group of the household head and geographical area, 2016/17–2017/18
Percentage in
2016/17

Indicator

CV%

Percentage in
2017/18

CV%

Gender of the household head
Male

52,3

9

42

11

Female

52,5

18

48

20

Black African

43,2

14

39

14

Coloured

34,1

25

46

22

Indian/Asian

62,0

26

35

44

White

72,0

10

54

17

Metro

***

***

43

12

Rural

***

***

73

22

Urban

***

***

41

19

SOUTH AFRICA

27

15

43

10

Population group of the household head

Geographical area

Reporting of theft out of motor vehicle to police increased from 27% in 2016/17 to over 43% in 2017/18.
With less than half of theft out motor vehicles reported to the police one would have expected the number
of incidences to be more than twice the figure released by SAPS. Rural areas have the highest reporting
rates (73%) compared to urban and metro areas. A comparison among the four population groups
shows that white people have the highest rate of reporting theft out of motor vehicle, and a greater
percentage of female-headed households than male-headed households reported this crime.
Table 35: Number and percentage of households that experienced theft out of motor vehicle by
gender and population group of the household head, geographical area and province, 2017/18
Indicator

Number of incidences

CV%

Percentage of households

CV%

Male

104 392

13

0,92

10

Female
Population group of the
household head

25 958

21

0,33

20

Black African

72 094

16

0,46

11

Coloured

15 658

25

1,18

24

Indian/Asian

8 287

35

2,04

35

White

34 311

21

1,70

19

Metro

93 014

14

1,06

11

Rural

3 203

60

0,27

64

Urban

34 133

16

0,38

15

SOUTH AFRICA

130 350

11

0,67

9

Gender of the household head

Geographical area

Table 35 shows that theft out of motor vehicle affected 2,35% of South African households in 2017/18.
The proportion of affected households in the metropolitan areas was more than twice the proportion
affected in urban areas. The proportion of Indian/Asian households that experienced theft out of motor
vehicles was higher than all other population groups, while black Africans were least affected. More

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male-headed households than female-headed households experienced theft out of vehicles. This is
most likely because car ownership was more prevalent among male-headed households, as shown in
Table 6.

5.8 Deliberate damage, burning or destruction of residential dwellings
This crime includes all deliberate actions that cause damage to or destruction of residential dwellings.
SAPS crime categories that are closely related to deliberate damage, burning or destruction of dwellings
are malicious damage to property and arson. In this definition, the word property means residential
premises.
In 2017/18, it is estimated that 50 426 incidences of deliberate damaging, burning or destruction of
residential dwellings occurred, which is a 7% increase from the previous year.
Table 36: Trends in deliberate damage, burning or destruction of dwellings, 2017/18
Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

58 452 (17)

60 624 (14)

40 892 (15)

46 915 (14)

50 426 (19)

44 660 (13)

53 576 (14)

38 626 (15)

41 895 (14)

38 143 (19)

0,31 (13)

0,36 (14)

0,25 (15)

0,26 (14)

0,23 (14)

131 (9)

113 (4)

106 (4)

112 (4)

120 (9)

Table 37: Malicious damage to property and arson reported to the police by province,
2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

27 107

30 071

29 974

29 997

28 001

Eastern Cape

13 735

13 184

12 498

12 810

11 422

Northern Cape

3 250

3 381

3 256

3 103

2 927

Free State

8 424

7 942

7 816

6 838

6 068

15 850

15 459

15 534

14 709

12 958

6 201

6 231

6 076

6 064

5 821

35 757

35 847

35 312

34 023

31 961

Mpumalanga

5 972

6 130

6 113

5 834

5 519

Limpopo

7 145

7 544

8 225

7 352

6 815

123 441

125 789

124 804

120 730

111 492

KwaZulu-Natal
North West
Gauteng

SOUTH AFRICA

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

Not many interviewed households indicated that they experienced this type of crime. Only one
Indian/Asian household indicated that they experienced deliberate damage, burning or destruction of
property. This puts a limit to the level of disaggregation of the statistics.

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Figure 13: Deliberate damaging, burning or destruction of dwellings and reporting to the police,
2013/14–2017/18

Number of incidences / Cases

140 000
120 000
100 000
80 000
60 000
40 000
20 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

58 452

60 624

40 892

46 915

50 426

SAPS

123 441

125 789

124 804

120 730

111 492

The malicious damage to property and arson cases reported to SAPS steadily declined from 2014/15,
while deliberate damage, burning or destruction of residential dwellings increased since 2015/16. This
is most likely due to the decline of the proportion of households that report this crime to the police. Table
38 below shows that reporting increased from 56% in 2016/17 to 62% in 2017/18. A possible reason for
the VOCS estimates being smaller than SAPS figures could be that SAPS statistics include nonresidential properties, while VOCS estimates are confined to residential properties.
Table 38: Percentage of deliberate damaging, burning or destruction of dwellings reported to the
police by gender of the household head and geographical area, 2016/17–2017/18
Indicator

Percentage in 2016/17

CV%

Percentage in 2017/18

CV%

Male

49

19

60

16

Female

67

15

64

16

Metro

***

***

54

23

Rural

***

***

***

***

Urban

***

***

63

14

SOUTH AFRICA

56

12

62

11

Gender of the household head

Geographical area

In 2017/18, the reporting of deliberate damaging, burning or destruction of property was more common
in urban areas than in metros. Female-headed households were more likely than male-headed
households to report the crime to the police.

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Table 39: Number and percentage of households that experienced deliberate damage, burning
or destruction of dwellings by gender of the household head and geographical area, 2017/18
Indicator

Number of incidences

CV%

Percentage of households

CV%

Male

29 199

25

0,23

19

Female

21 227

28

0,23

22

21 567

32

0,20

25

Rural

2 176

58

0,21

58

Urban

26 683

24

0,26

18

SOUTH AFRICA

50 426

19

0,23

14

Gender of the household head

Geographical area
Metro

An estimated total of 50 426 households experienced deliberate damaging, burning or destruction of
dwellings, representing 0,23% of all households in South Africa. There was no difference between maleheaded and female-headed households as far as the proportion of households that experienced this
type of crime was concerned.

5.9 Motor vehicle vandalism or deliberate damaging of motor vehicles
This crime is only about vandalism of vehicles under the care of or belonging to households. It does not
include vandalism of public vehicles. SAPS does not report on motor vehicle vandalism.
Table 40: Trends in motor vehicle vandalism, 2013/14–2017/18

Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

54 633 (12)

74 824 (15)

67 715 (19)

31 907 (20)

40 155 (16)

54 633 (12)

64 705 (14)

50 424 (15)

29 450 (19)

40 155 (16)

0,37 (12)

0,43 (14)

0,18 (15)

0,18 (19)

0,24 (16)

100 (0)

116 (7)

134 (10)

108 (8)

100 (0)

The challenge of insufficient data for disaggregated statistics also applies in this case. Even estimation
by gender of the household head compromises the quality of the statistics.
Table 41: Percentage of households that reported motor vehicle vandalism to the police by
gender of the household head, 2016/17–2017/18
Percentage in
2016/17

CV%

Percentage in
2017/18

CV%

Male

60

19

48

19

Female

19

69

59

30

SOUTH AFRICA

45

21

50

16

Gender of the household head

Female-headed households were more likely than male-headed households to report motor vehicle
vandalism to the police.

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Table 42: Number and percentage of households that experienced motor vehicle vandalism by
gender and population group of the household head, 2017/18
Indicator

Number of incidences

CV%

Percentage of households

CV%

Male

30 562

18

0,31

18

Female
Population group of the
household head

9 593

37

0,14

37

Metro

31 178

19

0,42

19

Gender of the household head

Rural

***

***

***

Urban

8 108

30

0,10

30

SOUTH AFRICA

40 155

16

0,24

16

The percentage of households that experienced motor vehicle vandalism in the metro areas was more
than four times the percentage of households in the urban areas.

5.10 Theft of bicycle
While motor vehicles are the common mode of transport in urban areas, some rural areas depend on
modest modes of transport such as bicycles. In South Africa urban areas, bicycles are also used for
recreational purposes. In 2017/18, a total of 29 264 households were victims of bicycle theft,
representing 0,18% of all households in South Africa.
Table 43: Trends in theft of bicycle, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of households that experienced at
least one incident (CV%)
Percentage of households that experienced
at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

54 119 (13)

60 375 (16)

37 227 (17)

21 051 (19)

29 264 (20)

52 720 (13)

54 847 (16)

36 319 (17)

21 051 (19)

29 264 (20)

0,36 (13)

0,37 (16)

0,23 (17)

0,13 (19)

0,18 (20)

103 (2)

110 (4)

103 (2)

100 (0)

100 (0)

Table 44: Distribution of theft of bicycle by gender of the household head, 2017/18
Gender of the household head

Number

CV%

Percentage

CV%

Male

17 820

26

0,18

26

Female

11 444

32

0,17

32

SOUTH AFRICA

29 264

20

0,18

20

Results in Table 44 above shows that the difference between male and female-headed households that
reported the theft of a bicycle is not significant.

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Table 45: Percentage of households that reported bicycle theft to the police by gender of the
household head, 2016/17–2017/18
Gender of the household head

Percentage in
2016/17

CV%

Percentage in
2017/18

CV%

37

26

30

29

SOUTH AFRICA

The percentage of households that experienced theft of bicycle decreased from 37% in 2016/17 to
30% in 2017/18.

5.11 Sexual offence and assault
This section deals with sexual offences and assault incidents reported by household heads. Estimates
provided here may not be the same as those arising from individual interviews reported in Section 6.4.
Since household heads may not be aware of all crime experiences of members of their households, it
is expected that the numbers provided here will be smaller than those provided in Section 6.4.
VOCS uses a narrower definition of sexual offence, which is limited to intentional sexual violation of
individuals through grabbing, touching or rape. The SAPS definition of sexual offence is broader and
includes bestiality and sexual acts with a corpse. Therefore, statistics provided by these two
organisations do not measure the same thing. VOCS is compelled to adopt a narrower definition of
sexual offence because of the limitations of the survey methodology.
SAPS has three categories of assault, namely common assault, assault with intent to inflict grievous
bodily harm, and sexual assault. The VOCS definition of assault combines the first two, i.e. common
assault and assault with intent to inflict grievous bodily harm.
In 2017/18, an estimated 28 986 (or 0,17%) of all households had a member who was a victim of sexual
offence, and 136 607 (or 0,82%) of all households had a member who was a victim of assault.
Table 46: Household sexual offence and assault by gender of the household head, 2017/18

Sexual offence
Gender of the
household head

Assault

Number of
households

CV%

Percent of
households

CV%

Number of
households

CV%

Percent of
households

CV%

Male

9 870

28

0,10

28

72 528

11

0,74

11

Female

19 116

21

0,28

21

64 079

12

0,93

12

SOUTH AFRICA

28 986

17

0,17

17

136 607

9

0,82

9

In 2017/18, female-headed households experienced significantly greater proportions of sexual offence
and assault incidences than did male-headed households.

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Table 47: Household experiences of sexual offence and assault by gender of victim, 2017/18
Number of persons who
experienced sexual offence

CV%

Number of persons who
experienced assault

CV%

Male

3 570

56

104 399

18

Female

32 881

23

67 872

16

SOUTH AFRICA

36 451

21

172 270

13

Gender of the victim

Sexual offence is a crime that mostly affects women and girls. It is estimated that the number people
who experienced sexual offence in 2017/18 was 36 451. More males than females experienced
assault in 2017/18, as the estimates in Table 49 show.

5.12 Comparison of household crimes experienced
Theft of motor vehicles, housebreaking, home robbery, theft out of motor vehicle, motor vehicle
vandalism and theft of bicycles are the household crimes that have mostly been decreasing during the
past five years. All crime categories except livestock theft and theft out of motor vehicles increased
during the period 2016/17–2017/18.

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6. INDIVIDUAL EXPERIENCE OF CRIME
This section provides statistics on crime perpetrated against individuals. VOCS randomly selects
individuals from sampled households aged sixteen years and older, and asks if they have been victims
of crime in the twelve months preceding the survey. Individual crimes are typically crimes that mostly
affect individuals rather than entire households. The crimes covered in this section are theft of personal
property, motor vehicle hijacking, robbery, assault, and consumer fraud.

6.1 Theft of personal property
Personal property includes all items of a personal nature such as clothes, jewellery, watches and cell
phones. An estimated 693 219 incidences of theft of personal property occurred in 2017/18, affecting
663 477 individuals. There was a decline of 2% from the previous year in terms of the number of
incidences, but an increase of 3,6% in terms of the number of individuals affected.
Table 48: Trends in theft of personal property, 2013/14–2017/18

Statistic

2013/14

Number of incidences (CV%)
Number of individuals that experienced
at least one incident (CV%)
Percentage of individuals that
experienced at least one incident (CV%)

2014/15

2015/16

2017/18

2017/18

1 012 537 (8)

921 773 (9)

842 478 (8)

708 357 (7)

693 219 (6)

880 028 (7)

786 895 (6)

750 553 (6)

640 179 (6)

663 477 (6)

2,47 (6)

2,14 (6)

2,03 (6)

1,68 (6)

1,72 (6)

115 (3)

117 (6)

112 (5)

111 (7)

102 (1)

Repeat victimisation index (CV%)

Table 49: Percentage of victims who reported theft of personal property to the police by gender,
population group and geographical area, 2016/17–2017/18
Percentage of persons 16 years
and above in 2016/17

CV%

Percentage of persons 16 years
and above in 2017/18

CV%

Male

36

12

26

14

Female

27

15

22

17

Black African

28

10

19

14

Coloured

23

38

52

23

Indian/Asian

61

28

55

55

White

64

19

42

21

Gender

Population group

Geographical area
Metro

***

27

14

Rural

***

8

71

Urban

***

21

17

SOUTH AFRICA

32

24

11

9

Data for both 2016/17 and 2017/18 show that males were more likely to report theft of personal property
to the police than females were. The black African population group recorded the least percentage of
victims reporting theft of personal property to the police.

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Table 50: Distribution of theft of personal property by gender, population group, geographical
area and province, 2017/18
Gender

Number of incidences

CV%

Percentage

CV%

Male

371 131

9

1,94

9

Female

322 088

10

1,51

9

Black African

561 986

7

1,79

7

Coloured

41 972

23

1,18

23

Indian/Asian

10 420

57

0,91

59

White

78 842

22

1,91

22

Metro

378 532

9

2,25

9

Rural

19 069

32

0,87

32

Urban

295 618

10

1,38

9

Western Cape

73 905

19

1,51

19

Eastern Cape

64 868

19

1,44

19

Northern Cape

17 993

29

1,95

30

Free State

41 022

24

2,03

24

KwaZulu-Natal

73 750

20

1,01

21

North West

52 517

28

1,59

24

Gauteng

272 656

11

2,61

10

Mpumalanga

41 335

22

1,35

21

Limpopo

55 172

22

1,44

22

SOUTH AFRICA

693 219

6

1,72

6

Population group

Geographical area

Province

Table 50 shows significant gender differences among victims of theft of personal property. Males were
more likely to be victims of theft of personal property than females. People from the coloured population
group had the lowest percentage of individuals who experienced theft of personal property.
Table 50 also shows that the prevalence of theft of personal property was highest amongst those
residing in Gauteng (2,61%) and lowest among people who reside in KwaZulu-Natal (1,01%). In terms
of the number of individuals who experienced theft of personal property, Gauteng recorded the highest
figures at 272 656.
Table 51: Number and percentage of victims who knew the perpetrator and victims who were
satisfied with police response, 2017/18
Number of victims

CV%

Percentage of victims

CV%

Know who stole their personal property

637 765

6

96,1

1

Satisfied with police response – Male

37 674

26

40,7

21

Satisfied with police response – Female

24 365

28

36,4

25

Satisfied with police response – TOTAL

62 039

19

38,9

15

The majority (96,1%) of the victims of theft of personal property knew the perpetrator. The percentage
of males (35,4%) who were satisfied with police response was significantly greater than that of females
(28,5%).

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Table 52: Place where theft of personal property occurred, 2017/18

CV%

Percentage of victims
of theft of personal
property

CV%

33

3,4

33

316 419

9

47,7

7

19 643

29

3,0

28

In a field/park

12 371

45

1,9

44

In some other outdoor area

15 483

44

2,3

44

In someone else's home

26 481

30

4,0

30

In the street outside offices/shops

50 330

20

7,6

30

In a shop/place of business

65 313

20

9,8

20

At a public transport station/taxi rank or shop

34 459

26

5,2

19

While travelling in public transport

11 518

41

1,7

25

At some other indoor area

7 040

61

1,1

40

Other social gathering

4 186

67

8,9

60

Other

58 972

21

9,2

20

Number victims of theft
of personal property

In the workplace

22 831

In the street in a residential area
At an entertainment area/bar/tavern

Stolen items

Most thefts of personal property (47,7%) occurred in the streets in residential areas.
Table 53: Number and percentage of victims who lost various items through theft of personal
property, 2017/18
Number of incidences

CV%

Percentage of persons 16 year
or older

CV%

Money/purse/wallet

300 072

9

45,2

7

Bankbooks/cards

90 102

16

13,6

15

Cell phone

458 700

8

69,1

4

Travel document

7 767

58

1,2

57

Travelling bag

15 664

41

2,4

40

Personal effects (e.g. jewellery)

37 456

25

5,6

24

Portable radio/MP3 player

7 469

69

1,1

68

Clothing

43 097

22

6,5

22

Portable computer

12 311

54

1,9

53

Other

53 132

25

8,0

24

Stolen items

Cell phones dominated the list of items lost through theft of personal property, affecting 69,1% of the
victims. This was followed by theft of money, purse or wallet affecting, 45,2% of the victims.

6.2 Hijacking of motor vehicles
Hijacking of motor vehicles is a type of crime committed against an individual while driving their own
vehicles or vehicles belonging to another person or institution. The question of ownership was not
relevant when respondents were asked whether they had experienced incidents of hijacking during the

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past twelve months. The type of vehicle the victim was driving or riding in as a passenger is also not
relevant. SAPS reports separate statistics for carjacking and truck hijacking.
It is estimated that in 2017/18, there were 34 880 incidences of hijacking of motor vehicles, representing
0,09% of persons aged 16 or above.
Table 54: Trends in motor vehicle hijacking, 2013/14–2017/18

Statistic
Number of incidents (CV%)
Number of individuals that experienced at least
one incident (CV%)
Percentage of individuals that experienced at
least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

26 098 (43)

53 427 (24)

27 414 (32)

30 644 (30)

34 880 (27)

26 098 (43)

53 427 (24)

27 414 (32)

30 644 (30)

34 880 (27)

0,07 (43)

0,15 (24)

0,07 (32)

0,08 (30)

0,09 (27)

100 (0)

100 (0)

100 (0)

100 (0)

100 (0)

Table 54 above shows an increase of 14% in the number of hijackings compared to 2016/17. SAPS
statistics in Table 55 below show a decline in the number of SAPS reported cases of hijackings.
Table 55: Carjacking and truck hijacking reported to the police by province, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

996

1 592

2 078

2 259

2 182

Eastern Cape

804

803

1 010

1 037

999

Northern Cape

28

15

49

29

37

326

359

323

275

235

2 308

2 253

2 564

3 110

2 698

288

323

412

438

425

6 603

7 671

8 062

9 278

8 269

Mpumalanga

556

664

823

988

896

Limpopo

262

372

465

486

584

12 171

14 052

15 786

17 900

16 325

Free State
KwaZulu-Natal
North West
Gauteng

SOUTH AFRICA

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

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Table 56: Motor vehicle hijacking reported to the police by gender and geographical area,
2016/17–2017/18
Percentage of persons 16 years
and above in 2016/17

Indicator

CV%

Percentage of persons 16 years
and above in 2017/18

CV%

Gender
Male

78

74

19

Female

100

67

26

Geographical area
Metro

***

***

66

20

Rural

***

***

100

0

Urban

***

***

83

21

SOUTH AFRICA

88

13

70

16

The percentage of victims of hijackings that reported this crime to the police dropped from 88% in
2016/17 to 70% in 2017/18.
Figure 14: Number of hijacking incidences and cases reported to the police, 2013/14–2016/17

Number of hijackings / cases

60 000
50 000
40 000
30 000
20 000
10 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

26 098

53 427

27 414

30 644

34 880

SAPS

12 171

14 052

15 786

17 900

16 325

The VOCS and SAPS statistics on hijacking trended in different directions between 2016/17 and
2017/18.

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6.3 Robbery outside home
This is robbery committed against individuals outside their homes. It could happen in the street, at the
workplace, in a shopping mall or other places outside a person's home.
Table 57: Trends in robbery, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of individuals that experienced
at least one incident (CV%)
Percentage of individuals that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2017/18

2017/18

373 148 (18)

348 349 (12)

283 544 (10)

294 874 (13)

280 526 (12)

303 205 (10)

297 683 (10)

267 613 (10)

269 610 (13)

258 910 (12)

0,85 (10)

0,81 (10)

0,72 (10)

0,71 (13)

0,67 (11)

123 (12)

117 (6)

106 (2)

109 (3)

108 (4)

In 2017/18, it is estimated that 280 526 incidences of robbery outside the home occurred, affecting
258 910 individuals aged 16 or above. This is a decrease of 5% over the previous year. The percentage
of victims decreased by 4%.
The SAPS equivalent of robbery outside the home is a combination of two crime categories, namely
common robbery and robbery with aggravating circumstances. SAPS statistics in Table 58 below are a
sum of these two categories.
Table 58: Common robbery and robbery with aggravating circumstances reported to the police
by province, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

32 591

36 536

36 217

36 606

36 332

Eastern Cape

17 431

16 998

16 467

17 395

16 945

Northern Cape

2 679

2 708

2 735

3 011

2 924

Free State

7 984

7 760

7 082

7 339

7 227

29 354

28 738

28 585

29 632

28 139

KwaZulu-Natal
North West

7 750

8 396

8 698

9 606

9 649

58 085

64 741

67 843

71 160

68 690

Mpumalanga

8 229

8 590

8 742

9 652

9 298

Limpopo

8 365

9 505

10 268

9 973

9 887

172 468

183 972

186 637

194 374

189 094

Gauteng

SOUTH AFRICA

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

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Figure 15: Number of robbery incidences and robberies reported to the police, 2013/14–2017/18
400 000

Number of incidences / Cases

350 000
300 000
250 000
200 000
150 000
100 000
50 000
0
VOCS

2013/14
373 148

2014/15
348 349

2015/16
283 544

2016/17
294 874

2017/18
280 526

SAPS

172 468

183 972

186 637

194 374

189 094

Figure 15 shows that during the past three years, the VOCS and SAPS statistics have had almost similar
trends.
Table 59: Percentage of robberies reported to the police by gender, population group,
geographical area and province, 2016/17–2017/18
Percentage of persons 16 years
and above in 2016/17

CV%

Percentage of persons 16 years
and above in 2017/18

CV%

Male

35

15

40

16

Female

30

24

29

26

Black African

31

17

32

17

Coloured

31

26

41

46

Indian/Asian

***

***

***

***

White

37

63

70

26

Metro

***

***

32

20

Rural

***

***

43

54

Urban

***

***

41

20

Western Cape

34

22

26

34

Eastern Cape

30

40

31

32

Northern Cape

76

22

***

***

Free State

42

38

46

29

KwaZulu-Natal

35

50

54

40

North West

7

104

22

61

Gauteng

39

24

44

32

Mpumalanga

33

37

55

33

Limpopo

22

57

79

26

SOUTH AFRICA

33

13

36

14

Indicator
Gender

Population group

Geographical area

Province

Some estimates in Table 59 above are not usable due to unacceptably high CVs. The percentage of
victims who reported robbery to the police increased from 33% in 2016/17 to 36% in 2017/18.

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Table 60: Distribution of robbery by gender, geographical area and province, 2017/18
Number of individual
victims 16 years of age
and above

CV%

Victims as percentage
of people 16 years of
age and above

CV%

Male

191 694

16

0,92

14

Female

88 832

17

0,44

17

Metro

160 873

17

0,87

15

Rural

6 868

45

0,34

45

Urban

112 785

17

0,55

17

Western Cape

83 647

28

1,54

23

Eastern Cape

71 376

23

1,53

23

Northern Cape

1 315

76

0,15

77

Free State

33 067

28

1,65

28

KwaZulu-Natal

17 571

43

0,22

43

North West

18 375

39

0,63

38

Gauteng

33 913

29

0,31

27

Mpumalanga

18 022

38

0,61

38

Limpopo

3 239

62

0,08

62

297 885

12

0,67

11

Indicator
Gender

Geographical area

Province

SOUTH AFRICA

An estimated 280 526 incidences of robbery away from home occurred in 2017/18. Results in Table 60
also show that males were more affected by this crime than females. A comparison among the four
population groups is not possible because only the estimate for the black African population is a quality
statistic (reasonably low coefficient of variation). Among acceptable quality statistics, robbery
prevalence was lowest in Gauteng (0,31%) and highest in Free State (1,65%). Nationally, 0,67% of
adults 16 years and older were victims of robbery away from home in 2017/18.
Table 61: Percentage of individuals robbed using a specified type of weapon, 2017/18
Type of weapon used

Percentage of individuals

CV%

Knife

70,9

8

Stick/club

2,6

55

Metal/bar

2,4

52

Axe/panga

1,9

54

Gun

34,0

17

Other

0,4

100

SOUTH AFRICA

73,3

6

A weapon was used in about 73,3% of all robberies. The most common types of weapons used in
robberies were knives, followed by guns.

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Table 62: Percentages for different robbery scenarios, 2017/18
Robbery scenario

Percentage of victims

CV%

Individuals robbed in the street in residential area

65,4

8

Individuals robbed while alone

62,6

9

Individuals who resist robbery

31,5

16

Individuals who sustain injury during robbery

25,8

17

Over 65% of the robberies occurred in a street in residential areas. The majority of the victims (62,6%)
were alone during robbery, while 31,5% of the victims resisted robbery and 25,8% sustained injury.
Statistical evidence (at 0,5% level of significance) from VOCS data shows that there is an association
between resisting robbery and sustaining injury during robbery.

6.4 Sexual offence
VOCS uses a narrower definition of sexual offence limited to intentional sexual violation of individuals
through grabbing, touching or rape. The SAPS definition of sexual offence is broader and includes
bestiality, a sexual act with a corpse and other unlawful sexual acts. Therefore, statistics provided by
these two organisations do not measure the same thing. Given the sensitive nature of this crime and
the context of household-based interviews, sexual offences are thought to be underreported in the
VOCS, and it is likely that most of those individuals who have already reported sexual offences to the
police will proceed to also report it to the survey officer collecting data.
Table 63: Trends in sexual offences, 2013/14–2017/18

Statistic

2013/14

2014/15

2015/16

2016/17

2017/18

Number of incidents (CV%)

62 074 (27)

44 464 (25)

29 473 (27)

73 842 (21)

28 596 (35)

Number of individuals that experienced
at least one incident (CV%)

41,925 (20)

43 696 (26)

29 473 (27)

70 813 (21)

22 694 (33)

Percentage of individuals that
experienced at least one incident (CV%)

0,12 (20)

0,12 (26)

0,08 (27)

0,19 (21)

0,06 (33)

Repeat victimisation index (CV%)

148 (20)

102 (2)

100 (0)

104 (4)

109 (9)

While VOCS estimates cannot be disaggregated by province, SAPS has provincial counts, as shown
in Table 64 below.

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Table 64: Sexual offences reported to the police by province, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

7 760

7 369

7 130

7 115

7 075

Eastern Cape

9 616

9 224

8 797

8 050

8 094

Northern Cape

1 731

1 578

1 719

1 587

1 538

Free State

4 584

4 094

3 928

3 488

3 284

KwaZulu-Natal

9 889

9 079

8 947

8 484

8 759

North West

4 616

4 585

4 164

4 326

4 182

10 264

9 902

9 510

9 566

10 116

3 797

3 474

3 331

3 216

3 198

Gauteng
Mpumalanga
Limpopo
SOUTH AFRICA

4 423

4 312

4 369

3 828

3 862

56 680

53 617

51 895

49 660

50 108

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

Figure 16: Number of sexual offence incidences and sexual offences reported to the police,
2013/14–2017/18

Number of incidences / Cases

80 000
70 000
60 000
50 000
40 000
30 000
20 000
10 000
0

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

62 074

44 464

29 473

73 842

28 596

SAPS

56 680

53 617

51 895

49 660

50 108

Cases of sexual offence reported to the South African Police Service (SAPS) steadily declined between
2013/14 and 2016/17, and marginally increased in 2017/18.
Table 65: Percentage of sexual offences reported to the police by gender, 2016/17–2017/18
Percentage of persons 16 years
and above in 2016/17

CV%

Percentage of persons 16 years
and above in 2017/18

CV%

Male

8

98

***

***

Female

30

35

73

19

SOUTH AFRICA

23

34

73

19

Gender

An estimated 73% of the victims of sexual offence reported the crime to the police in 2017/18.

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Table 66: Distribution of sexual offences by gender, 2017/18
Gender

Number

CV%

Male

Percentage

CV%

***

***

***

***

Female

28 596

35

0,11

33

SOUTH AFRICA

28 596

35

0,06

33

Table 66 shows that an estimated 28 596 individuals, mostly women, experienced a sexual offence in
2017/18.

6.5 Assault
Assault is defined as an attack, physical beating or threat of attack without taking anything from the
victim. This includes domestic violence. The VOCS definition of assault includes what the SAPS terms
common assault and assault with intent to inflict grievous bodily harm.
Table 67: Trends in assault, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of individuals that experienced
at least one incident (CV%)
Percentage of individuals that
experienced at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

431 043 (10)

431 914 (11)

331 913 (12)

318 077 (12)

355 739 (13)

345 030 (9)

344 554 (9)

272 712 (9)

271 970 (11)

277 397 (13)

0,96 (9)

0,94 (9)

0,74 (9)

0,71 (11)

0,72 (10)

125 (5)

125 (6)

122 (7)

117 (7)

117 (5)

It is estimated that 277 397 individuals aged 16 and above were victims of assault in 2017/18 who
experienced 355 739 incidences. The number of incidences increased by 12% from the previous year.
Table 68: Common assault and assault with intent to inflict grievous bodily harm reported to the
police by province, 2013/14–2017/18
Number of reported cases
Province

2013/14

2014/15

2015/16

2016/17

2017/18

Western Cape

37 183

65 350

66 843

64 285

62 162

Eastern Cape

40 691

37 279

36 293

34 341

34 304

Northern Cape

13 493

13 616

13 487

12 613

12 098

Free State

31 529

28 701

28 310

25 270

23 543

KwaZulu-Natal

55 289

53 212

52 368

49 109

49 535

North West

20 214

20 264

20 556

19 752

20 959

Gauteng

85 341

84 748

87 045

81 767

83 139

Mpumalanga

18 179

18 288

19 008

18 608

18 331

Limpopo

21 689

22 584

23 981

21 321

19524

348 414

344 042

347 891

327 066

323 595

SOUTH AFRICA

Source: SAPS Crime Statistics, https://www.saps.gov.za/services/crimestats.php

SAPS figures in Table 68 were obtained by adding together common assault and assault with intention
to inflict grievous bodily harm.

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Figure 17: VOCS estimated assault incidences and reporting of SAPS common assault and
assault with intent to inflict grievous bodily harm to the police, 2013/14–2017/18

Number of incidences / Cases

450 000
430 000
410 000
390 000
370 000
350 000
330 000
310 000
290 000
270 000
250 000

2013/14

2014/15

2015/16

2016/17

2017/18

VOCS

431 043

431 914

331 913

318 077

355 739

SAPS

348 414

344 042

347 891

327 066

323 595

VOCS and SAPS statistics did not differ too much between 2015/16 and 2017/18.
Table 69: Percentage of assaults reported to the police by gender and geographical area,
2016/17–2017/18
Percentage of victims in
2016/17

CV%

Percentage of victims
in 2017/18

CV%

Male

34

19

40

16

Female

62

12

59

13

Metro

***

***

48

18

Rural

***

***

54

39

Urban

***

***

46

13

SOUTH AFRICA

48

11

47

10

Indicator
Gender

Geographical area

A significant difference is noticeable between males and females in the percentage of victims who
reported assault to the police. Figures for both 2016/17 and 2017/18 show that females were more likely
to report assault to the police than males were.

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Table 70: Number and percentage of individuals who experienced assault by gender,
geographical area and province, 2017/18

CV%

Victims as
percentage of people
16 years of age and
above

CV%

184 384

13

0,96

13

148 626

17

0,50

15

Metro

138 249

26

0,53

17

Rural

20 625

44

0,68

41

Urban

196 865

13

0,88

12

Western Cape

88 589

25

1,26

22

Eastern Cape

84 402

38

1,11

21

Northern Cape

13 332

26

1,57

26

Free State

15 118

32

0,68

32

KwaZulu-Natal

15 997

41

0,22

41

North West

46 308

27

1,68

27

Gauteng

35 058

28

0,35

28

Mpumalanga

25 544

42

0,69

42

Limpopo

31 392

29

0,71

30

SOUTH AFRICA

355 739

13

0,72

10

Number of individual
victims 16 years of age
and above

Male
Female

Gender

Geographical area

Province

The difference in the victimisation rates between males and females was very significant. North West
had the highest (1,68%) percentage of adults, aged 16 and above, who were victims of assault during
2017/18.

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Table 71: Distribution of place where assault occurred, 2017/18
Place where assault occurs

Percentage

CV%

At home

30,4

15

In the street in a residential area

25,0

17

In the street outside offices/shops

19,1

19

At an entertainment area/bar/tavern

12,6

28

Other

12,9

Over 87% of all assaults occur at home, in residential area streets, in streets around offices and
shops, and at entertainment areas such as bars and taverns. All other areas accounts for less than
13% of the assaults.

6.6 Consumer fraud
Adults aged 16 and above were also asked whether they were victims of consumer fraud during the
past twelve months. Consumer fraud happens when someone provides services or goods and cheats
on quality or quantity. It is estimated that 137 274 incidences of consumer fraud occurred in South Africa
in 2017/18, affecting 89 065 (0,23%) adults aged 16 or above. This is approximately 60% increase from
the previous year.
Table 72: Trends in consumer fraud, 2013/14–2017/18
Statistic

2013/14

Number of incidents (CV%)
Number of individuals that experienced
at least one incident (CV%)
Percentage of individuals that
experienced at least one incident (CV%)

86 012 (18

90 249 (18)

160 076 (25)

85 848 (22)

137 274 (29)

86 012 (18)

87 664 (18)

108 799 (15)

80 089 (21)

89 065 (29)

0,24 (18)

0,24 (18)

0,30 (15)

0,21 (21)

0,23 (18)

100 (0)

103 (3)

147 (20)

107 (6)

144 (21)

Repeat victimisation index (CV%)

2014/15

2015/16

2016/17

2017/18

Table 73: Percentage of consumer fraud victims who reported to the police, 2016/17–2017/18
Percentage of victims in
2016/17

CV%

Percentage of victims in
2017/18

CV%

32

29

28

29

SOUTH AFRICA

The proportion of households that reported consumer fraud to the police dropped from 32% in 2016/17
to 28% in 2017/18.
Table 74: Distribution of consumer fraud by gender, 2017/18
Number of incidences

CV%

Percentage of people
aged 16 and above

CV%

Male

44 700

33

0,18

30

Female

92 574

40

0,28

22

SOUTH AFRICA

137 274

29

0,23

18

Gender

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The proportion of women aged 16 and above who experienced consumer fraud in 2017/18 was
significantly higher than that of men.

6.7 Corruption
Corruption can be broadly defined as abuse of power entrusted to a public or corporate sector official
for private gain. Apart from a few general questions on perceptions of corruption, VOCS is mainly
concerned with corruption in the public sector. Statistics concerning household perceptions on
corruption and individual experience on payment of bribes to public officials are reported in this section.
In 2017/18 an estimated total of 134 442 incidences of corruption were experienced by 116 014 South
African residents aged 16 and above, representing 0,3% of adults in this age category.
Table 75: Five-year trends in individual experiences of corruption, 2013/14–2017/18
Statistic
Number of incidents (CV%)
Number of individuals that experienced at
least one incident (CV%)
Percentage of individuals that experienced
at least one incident (CV%)
Repeat victimisation index (CV%)

2013/14

2014/15

2015/16

2016/17

2017/18

60 480 (20)

63 437 (21)

45 487 (27)

37 778 (31)

134 442 (18)

60 480 (20)

53 458 (20)

40 019 (27)

32 814 (31)

116 014 (16)

0,17 (20)

0,15 (20)

0,11 (27)

0.09 (31)

0,30 (16)

100 (0)

119 (9)

114 (9)

115 (9)

116 (9)

Individual experience of corruption declined steadily between 2014/15 and 2016/17 and then sharply
increased in 2017/18.
Table 76 below disaggregates the 2017/18 corruption statistics by gender and geographical area.
There are insufficient data on corruption for provincial and lower-level disaggregation.
Table 76: Number of incidences of corruption and percentage of individuals who experienced
corruption, 2017/18
Number of incidences of
corruption experienced by
individuals 16 years of
age and above

CV%

Victims as
percentage of people
16 years of age and
above

CV%

Male
Female

64 714

24

0,30

22

69 728

27

0,30

24

Metro

84 769

24

0,45

21

Rural

14 165

68

0,34

58

Urban

35 508

27

0,17

27

SOUTH AFRICA

134 442

18

0,30

16

Gender

Geographical area

Table 76 shows that there is no difference in the level of corruption experienced by men and that
experienced by women. Metro areas experienced significantly more corruption than urban areas.
Insufficient data prevented an accurate estimation of the level of corruption experienced by people in
the rural areas.
Bribe is a specific form of corruption where a public official demands payment for services that should
be free, or where a person offers a public official payment for a favour or special treatment.

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Table 77: Individual experiences with bribes, 2017/18

CV%

Percentage of adults
aged 16 years and
above

CV%

109 588

17

95

16

75 516

20

69

11

Money

108 306

17

93

4

Favour

***

***

***

***

Present

***

***

***

Number of adults aged
16 years and above

Asked
Paid

People who were asked and/or paid bribe
among those who experienced corruption

Form of bribe requested

Government service
Policing

12 912

48

12

45

Traffic

66 691

22

61

13

Other

***

***

***

Reason for paying a bribe
To avoid payment of fine

48 532

23

59

15

***

***

***

***

***

***

***

***

99 095

17

91

6

Pointless, nobody would care

20 604

33

19

29

Benefited from the bribe

27 766

28

25

25

Common practice

27 766

28

25

25

***

***

***

***

Other
Whether crime was reported to authorities
Reported to the police or other authorities
Did not report to any authority
Reason for not reporting bribe to authorities

Other

It is estimated that in 2017/18, 0,31% of adults aged 16 and above were asked to pay a bribe by
government officials in return for service. In contrast, 10% of household heads had personally been
asked by a public official to pay a bribe or paid a bribe during the past twelve months. An estimated 69%
of the individuals aged 16 and older who were asked for a bribe paid the bribe. Money constituted about
93% of all the bribes that South Africans were asked to pay and most of it (59%) was paid to avoid
paying traffic fines. The majority (91%) of people who were asked for a bribe did not report the matter
to the police or any other authority. The most popular reasons for not reporting bribes were "It is
pointless, nobody would care", "I benefited from the bribe" and "Bribe is a common practice".
Perceptions about corruption also provide a useful indication of the progress made in the fight against
the scourge. The following summaries are based on questions on what respondents (household heads)
thought were the reasons for corruption and whether they perceived corruption as having increased,
decreased or stayed the same during the last twelve months.

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Table 78: Perceptions of South African households on corruption, 2017/18
Perception

Percentage of households

CV%

Real need such as hunger

29,8

2

Greed

85,3

0

Get rich quickly

79,8

1

Other

2,0

9

Increased

78,9

0

Decreased

9,3

4

Stayed the same

11,4

4

People engage in corruption because of …

In the past three years the level of corruption has …

Eighty per cent or more of the households in South Africa believe that people engage in corruption
because of greed or the desire to get rich quickly. The majority (78,9%) thought that the level of
corruption has increased during the last three years.

6.8 Comparison of individual crimes experienced
Theft of personal property and sexual offences are the only individual crimes that saw a decline between
2016/17 and 2017/18 according to VOCS data. SAPS statistics show a decline in hijacking, robbery and
assault (common assault and assault with intent to inflict grievous bodily harm). As mentioned earlier,
the disagreement between VOCS and SAPS statistics should not be a matter of concern at this stage,
as the two organisations do not use the same definitions of crime types. Moreover, not all crime
experienced by individuals is reported to the police.

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7. INDIVIDUAL AND COMMUNITY RESPONSE TO CRIME
The previous chapters provided facts about the crime situation in the country. In this chapter, statistics
on how individuals and communities responded to crime will be presented and discussed. The chapter
focuses on three key areas: (1) The extent of community awareness of support services for victims of
crime; (2) Measures taken by households to protect themselves against crime; and (3) The extent of
community cohesion. In general, every response category of questions relevant to this section enjoys a
large number of responses, resulting in very small standard errors (and CVs). The CVs will therefore be
reported only in cases where some estimates are doubtful.

7.1 Victim support and other interventions
Figure 18 is a graphical representation of households' knowledge of victim support services/institutions
in their area of residence, from 2012 to 2017/18.
Figure 18: Percentage distribution of households who knew where to take a victim of crime to
access selected services, 2012–2017/18
100,0
90,0
80,0
70,0

Percentage

60,0
50,0
40,0
30,0
20,0
10,0
0,0

2012

2013/14

2014/15

2015/16

2016/17

2017/18

Medical services

92,2

93,0

96,3

96,9

95,1

94,2

Counselling services

53,8

57,3

63,0

65,9

68,2

63,1

Shelter/place of safety

15,8

12,7

12,5

11,1

8,9

8,1

The chart shows that the majority of households knew where to take victims of crime to access medical
services, as compared to counselling services and places of shelter. There is a clear increasing trend
in the percentage of households who knew where to take victims for counselling services between 2012

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and 2016/17, then a decline in 2017/18. Also evident is the downward trend among households who
knew the location of shelters or places of safety where they could take victims of domestic violence.
A provincial distribution of the percentage of households who knew where to take a victim of crime to
access selected services is depicted in Figure 19.
Figure 19: Percentage distribution of households who knew where to take a victim of crime to
access selected services by province, 2017/18
100,0
90,0
80,0
70,0

Percentage

60,0
50,0
40,0
30,0
20,0
10,0
0,0

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Medical services

95,9

97,3

95,3

95,3

96,5

94,0

90,9

96,2

92,8

94,2

Counselling services

58,0

66,2

56,6

64,0

67,5

64,3

61,6

62,4

62,9

63,1

Shelter/place of safety

16,4

4,5

5,9

13,8

5,5

3,1

8,8

9,5

4,2

8,1

The same pattern is repeated in all nine provinces: knowledge about medical services for victims of
crime ranked highest (over 94%), followed by counselling services (over 63%), while knowledge about
the location of shelters or places of safety for victims of crime ranked lowest (8,1%). Residents of
KwaZulu-Natal (67,5%) and Eastern Cape (66,2%) were the most knowledgeable of the location of
counselling services for victims. Nationally, a much lower percentage of households in the country
responded that they knew of a shelter or place of safety where they could take a victim of crime (8,1%);
residents of Western Cape (16,4%) and Free State (13,8%) had the highest awareness of the locations
of shelters or places of safety.

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Table 79: Number and percentage of households who knew where to take a victim of crime to
access medical services by type of institution and province, 2017/18
Province
Institution
Police

Hospital or trauma unit

Local clinic

Private doctor

NGO/volunteer group

Victim empowerment

Religious/traditional
group

Courts

Other

Statistics

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Number '000

498

319

89

364

960

281

1 093

318

188

4 111

Per cent

27,4

18,8

26,9

40,8

35,2

24,3

24,8

27,3

12,9

26,2

1 563

1 416

277

777

2 029

778

3600

822

1 009

12 270

85,9

83,2

83,4

87,1

74,5

67,4

81,6

70,4

69,3

78,4

1 054

1 285

205

690

2 427

1 039

3519

985

1 391

12 596

Per cent

58,0

75,5

61,6

77,5

89,1

90,0

79,7

84,4

95,5

80,4

Number '000

577

794

123

349

967

372

1933

332

559

6 006

Per cent

31,7

46,6

36,9

39,1

35,5

32,2

43,8

28,5

38,4

38,4

Number '000

17

39

8

46

93

15

146

29

106

499

Per cent

2,4

2,3

2,4

5,2

3,4

1,3

3,3

2,5

7,2

3,2

Number '000

22

21

6

23

65

8

63

18

79

305

Per cent

1,7

1,2

1,7

2,6

2,4

0,7

1,4

1,6

5,4

1,9

Number '000

30

138

8

44

119

8

232

26

149

832

Per cent

2,6

8,1

2,6

4,9

4,4

7,4

5,3

2,2

10,2

5,3

4

116

2

36

187

2

198

23

54

625

Per cent

0,5

6,8

0,5

4,0

6,9

0,5

4,5

1,9

3,7

4,0

Number '000

16

1

8

55

7

8

11

41

1

142

Per cent

2,3

0,1

2,3

6,2

0,3

0,2

0,2

3,5

0,0

0,9

Number '000
Per cent
Number '000

Number '000

Table 79 presents the number and percentage of households who knew where to take a victim of crime
to access medical services by type of institution and province. Approximately eight in every ten
households responded that they would take victims to a hospital or trauma unit, or a local clinic.

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7.2 Protection measures taken by victims
Figure 20 shows the distribution of households who took measures to protect themselves from crime in
2017/18.
Figure 20: Percentage distribution of households who took measures to protect themselves from
crime, 2017/18
60,0

52,4

Percentage

50,0
40,0
30,0

23,1

20,0

10,9

10,0
0,0

3,8

3,5

2,2

Protected home Protected vehicle Private security Carried weapons Self-help group

Other

Most households in the country took physical protection measures for their homes (52,4%), followed by
protecting their vehicles (23,1%) and using private security (10,9%).
Table 80: Percentage distribution of households who took measures to protect themselves from
crime by province, 2017/18
Province
Protective measure
Protected home
Protected vehicle
Carried weapons
Private security
Self-help groups
Other
•

Statistics

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Number '000

1 265

764

143

487

1 196

503

3 194

616

542

8 709

Per cent

66,,7

43,,7

41,,1

52,1

42,3

40,9

65,8

50,7

34,5

52,4

Number '000

689

256

58

136

477

203

1 612

214

191

3 838

Per cent

36,4

14,7

16,8

14,5

16,9

16,6

33,2

17,7

12,2

23,1

76

31

21

37

92

50

243

49

28

626

Number '000
Per cent

4,0

1,8

6,0

3,9

3,3

4,1

5,0

4,0

1,8

3,8

Number '000

345

105

21

59

229

61

869

67

53

1 809

Per cent

18,2

6,0

6,1

6,3

8,1

5,0

17,9

5,5

3,4

10,9

Number '000

43

84

6

11

59

17

270

33

55

577

Per cent

2,3

4,8

1,6

1,2

2,1

1,4

5,6

2,7

3,5

3,5

Number '000

51

92

19

27

58

5

70

37

11

371

Per cent

2,7

5,2

5,6

2,9

2,1

0,4

1,4

3,1

0,7

2,2

More than one response category could be marked and percentages therefore do not necessarily add up to 100%

Table 80 shows the provincial distribution of households who took measures to protect themselves from
crime. Households in the Western Cape (66,7%) and Gauteng (65,8%) were the more likely to have
taken measures to protect their homes compared to the other provinces. The table shows that in general,
a higher percentage of households in Gauteng and Western Cape, compared to other provinces, took
protective measures.

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7.3 Community interaction
This section measures the level of interaction among community members. This measure is used as a
proxy for the level of community cohesion. The survey asked household heads, answering on behalf of
their households, if they knew the name of their next-door neighbour. About 5,4% of households
indicated that they did not know the name of their next-door neighbour. The percentage of households
that did not know their neighbour's name by geographical area were as follows: metro (7,5%), rural
(5,3%) and urban (3,6%).
Table 81: Percentage distribution of households' knowledge of their neighbours' name by their
trust in neighbours, 2017/18
Trust your neighbour to watch your house
Knowledge of neighbour's name

Do not trust neighbour

Do not know neighbour's name
Know neighbour's name
Total

Trust neighbour

Total

85,6

14,4

100

9,6

90,4

100

13,5

86,5

100

Table 81 above shows that among households that knew the name of their neighbour, the majority
(90,4%) did trust them. The table also suggests that there is a high level of mistrust if the neighbours do
not know each other's names. Among households that did not know their neighbour's name, 85,6% did
not trust their neighbours, while 14,4% did trust their neighbours.
Table 82: Percentage distribution of households' knowledge of their neighbours' name by
whether they would let them watch their children, 2017/18

Knowledge of neighbour's
name

Trust your neighbour to look after your children
Would not let neighbour look after
Would let neighbour look after
your children
your children

Total

Do not know neighbour's name

86,9

13,1

100

Know neighbour's name

17,7

82,3

100

Total

21,3

78,7

100

The general trends observed in Table 81 are also observed in Table 82. Among households that knew
the name of their neighbour, the majority (82,3%) would let them take care of their children. Those
households that did not know their neighbour's name (86,9%) also did not trust their neighbours enough
to let them take care of their children.

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The respondents were also asked if their households participated in any community-based activities.
Figure 21 below depicts the percentage distribution of these community-based initiatives.
Figure 21: Percentage distribution of households' knowledge of their neighbours' name by
activities in which they partake, 2017/18
60,0
50,0

Percentage

40,0
30,0
20,0
10,0
0,0

Sports group

Community
crime
prevention
forum

Other groups

17,7

7,8

2,7

0,6

35,6

5,7

3,4

0,6

34,7

5,8

3,3

0,6

Religious group

Stokvel/savings
group/burial
society

Do not know neighbour

39,0

Know neighbour

51,4

Total

50,7

The findings summarised in Figure 21 suggest that households who know their neighbours are more
likely to belong to religious groups and stokvels/savings groups than those who do not. Knowing the
neighbour's name does not seem to be significantly associated with belonging to other social groups.

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8. ATTITUDES AND PERCEPTIONS OF CRIME
8.1 Perceptions on crime trends
This section addresses the extent to which people in South Africa feel safe as outlined in the Medium
Term Strategic Framework (MTSF) for the period 2014–2019. Households were asked about their
perceptions of how the levels of violent crime have changed in the three years prior to the survey.
Households' perceptions about change in violent crime levels between 2012 and 2017/18 are depicted
in Figure 22 below.
Figure 22: Percentage distribution of households' perceptions of violent crime levels in their
areas of residence over three-year interval prior to the survey, 2012–2017/18

Between 2012 and 2015, there is a clear downward trend in the numbers of those who believe that
crime had decreased over the preceding three years. In 2017/18, the proportion of households who
were of the view that violent crime in their area had increased in the last three years was higher than in
the preceding two years, after a decline between 2015/16 and 2016/17. Thus, emerging positive public
perceptions about the violent crime situation observed between 2015/16 and 2016/17 has reversed
again. The percentage of households who feel that violent crime has decreased was lowest in 2017/18,
and less than a quarter of households felt that violent crime has decreased.

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Figure 23 depicts the provincial distribution of households' perceptions of the levels of violent crime in
their areas of residence in 2017/18.
Figure 23: Percentage distribution of households' perceptions of violent crime levels in their
areas of residence in the past three years, 2017/18
100%
90%
80%
70%

Percentage

60%
50%
40%
30%
20%
10%
0%

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Decreased

12,6

21,7

23,6

27,1

28,8

17,4

26,5

31,7

26,4

24,5

Stayed the same

32,3

31,1

22,1

23,0

29,1

30,7

28,1

29,3

24,5

28,6

Increased

51,7

44,2

43,1

47,3

38,6

47,5

37,7

35,4

46,1

42,1

According to Figure 23, Western Cape (51,7%) had the highest proportion of households who said that
crime increased, followed by North West (47,5%), Free State (47,3%) and Limpopo (46,1%). The
proportions of households that thought crime had decreased were highest in Mpumalanga (31,7%) and
KwaZulu-Natal (28,8%).

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Households' perceptions about property crime levels between 2011 and 2017/18 are shown in Figure
24 below.
Figure 24: Percentage distribution of households' perceptions of property crime levels in their
areas of residence over three-year interval prior to the survey, 2012–2017/18
50,0

45,0

40,0

Percentage

35,0

30,0

25,0

20,0

15,0

2012

2013/2014

2014/2015

2015/2016

2016/2017

2017/2018

Increased

34,7

44,1

46,7

45,6

44,2

46,2

Decreased

37,0

30,3

27,6

26,6

25,5

22,3

Stayed the same

28,3

25,7

25,7

28,2

30,2

26,6

Trends in the perceptions of the changes in property crime, especially with regard to perceptions about
the increase of crime, are similar to those of violent crime, with improved trends for 2015/16 and 2016/17,
only to deteriorate again in 2017/18. Less than a quarter of households feel that crime decreased over
the preceding three years. This number if lower than any of those for the previous years in the time
series.

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Figure 25: Percentage distribution of households' perceptions of property crime levels in their
areas of residence in the past three years, 2017/18
100%
90%
80%
70%

Percentage

60%
50%
40%
30%
20%
10%
0%

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Decreased

10,9

20,8

19,2

27,5

24,4

15,6

24,7

25,2

26,8

22,3

Stayed the same

29,0

30,3

26,6

23,0

28,0

30,2

25,2

23,6

22,9

26,6

Increased

56,6

46,1

40,3

46,6

44,1

50,2

42,2

47,5

47,2

46,2

Figure 25 shows the provincial distribution of households' perceptions of the levels of property crime in
their areas of residence for the period 2011–2017/18. In South Africa as a whole, 46,2% of households
indicated that property crime increased, while 22,3% of the households felt that it has decreased.
Western Cape (56,6%) had the highest proportion of households who said that property crime increased,
followed by Mpumalanga (47,5%) and Limpopo (47,2%).

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Figure 26: Crimes perceived by households to be most common in South Africa, 2012–2017/18
80
70
60

Percentage

50
40
30
20
10
0

2012

2013/2014

2014/2015

2015/2016

2016/2017

2017/2018

Housebreaking/burglary

58,7

61,3

66

58,8

61,7

70,0

Home robbery

41,4

39,3

42,6

41,5

42,5

35,9

Street robbery

45,5

43

43,5

38,5

36,4

43,9

Pick-pocketing or bag-snatching

32,2

24,4

26,5

17,9

19,8

21,1

Assault

23,1

20,3

20,8

19,4

18,9

20,8

Business robbery

17,9

16,4

19,6

17,9

17

18,4

Murder

16,9

17,4

17,4

15,9

15,9

18,6

A time series analysis of crime types perceived to be the most common by households in their area of
residence between 2012 and 2017/18 is shown in Figure 26. The majority of households perceived
housebreaking/burglary as the most common crime type, followed by street and home robbery. The
percentage of households that thought that housebreaking was the most common crime increased
steadily from 58,7% in 2012 to 70,0% in 2017/18.

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Table 83: Crimes perceived by households to be the most common and feared in South Africa,
2017/18
Crime perceived to be most common
Crime type
Housebreaking or burglary

Number

Per cent

Crime feared most
Number

Per cent

1 1640

70,0

10 106

60,8

Home robbery

6 268

37,7

7 846

47,2

Robbery outside home

7 677

46,2

7 700

46,3

Murder

3 301

19,9

6 726

40,5

Sexual assault

2 499

15,0

4 711

28,3

Pick-pocketing or bag-snatching

3 953

23,8

3 892

23,4

Assault

3 645

21,9

3 872

23,3

Drug trafficking

3 179

19,1

2 813

16,9

Car theft or any type of vehicle

2 032

12,2

2 685

16,2

Business robbery

3 416

20,6

2 622

15,8

Vehicle hijacking

2 148

12,9

2 146

12,9

Trafficking in persons

732

4,4

2 038

12,3

Child abuse

946

5,7

1 917

11,5

Livestock/poultry theft

1 990

12,0

1 821

11,0

Mob justice/vigilante group

1 188

7,1

1 658

10,0

Political violence

1 016

6,1

1 502

9,0

Hate crime

715

4,3

1 448

8,7

Identity document theft

238

1,4

1 309

7,9

Deliberate damage to dwelling

474

2,9

1 226

7,4

White-collar crime

301

1,8

1 120

6,7

Bicycle theft

700

4,2

1 083

6,5

Crop theft

457

2,7

936

5,6

Other crimes

626

3,8

462

2,8

Table 83 shows crimes that were perceived to be the most common and those that were feared most
by household representatives. Although it is widely accepted that murder and sexual assault are more
serious crimes than housebreaking, housebreaking is feared more than murder and sexual assault. A
total of 60,8% of households in South Africa fear housebreaking/burglary the most, followed by home
robbery (47,2%) and robbery outside the home (46,3%).

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8.2 Feelings of safety
Figure 27: Comparison of feelings of safety when walking alone in their areas of residence during
the day and when it is dark, 2017/18
60,0
50,0

Percentage

40,0
30,0
20,0
10,0
0,0

Very safe

Fairly safe

A bit unsafe

Very unsafe

During the day

50,3

28,9

11,7

8,5

When is dark

13,5

18,3

19,7

47,7

Figure 27 shows the percentage distribution of households' feelings of safety when walking alone in
their areas of residence during the day and when it is dark. About 79% of households felt safe in their
area during the day (50,3% felt very safe and 28,9% fairly safe). This is a significant decline from
2016/17, when 84,8% felt safe or fairly safe. Feelings of safety at night have been significantly less. In
2017/18, 67,4% felt a bit unsafe or very unsafe (19,7% felt a bit unsafe and 47,7% felt very unsafe).

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Figure 28: Percentage distribution of households who felt safe walking alone in their areas of
residence during the day and when it is dark, 2012–2017/18
100,0
90,0
80,0
Percentage

70,0
60,0
50,0
40,0
30,0
20,0
10,0
0,0

2012

2013/2014

2014/2015

2015/2016

2016/2017

2017/2018

Safe during day

85,4

86,8

85,4

83,7

84,8

79,1

Safe when it is dark

35,9

34,8

31

30,7

29,4

31,8

The percentages of households who felt safe walking alone in their areas of residence during the day
and when it is dark for the period 2012 to 2017/18 are shown in Figure 28. The graph shows that during
the last five years, people in South Africa consistently felt a lot safer walking in their neighbourhoods
during the day than when it is dark. There is also evidence of a steadily declining trend for walking alone
during the day and a slight increase from 2016/17 in the percentage who feel safe walking alone at
night.
Table 84: Percentage distribution of households who were prevented from engaging in daily
activities as a result of crime in their area, 2017/18
Households prevented from engaging in daily activities
Activity

Number in thousands

Per cent

Going to open spaces

5 369

32,3

Allowing children to play

2 838

17,1

Walk town

2 378

14,3

Dressing in any way

1 881

11,3

Walk to shops

2 313

13,9

Public transport

2 318

13,9

Allowing children to walk to school

1 914

11,5

Starting a home business

1 538

9,3

Expressing sexual orientation

1 661

10,0

Keeping livestock

959

5,8

Walking to fetch water/wood

714

4,3

Table 84 summarises the distribution of households who were prevented from engaging in daily
activities. The VOCS 2017/18 data show that, due to the fear of crime, the majority of households were
prevented from going to open spaces (32,3%), allowing children to play in their area (17,1%) and walking
to town (14,3%). About 12% of households that have children did not allow their children to walk to
school due to the fear of crime.

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Figure 29: Percentage distribution of households' perception of the most likely perpetrators of
property crime, 2012–2017/18
100,0
90,0
80,0
70,0

Percentage

60,0
50,0
40,0
30,0
20,0
10,0
0,0

2012

2013/2014 2014/2015 2015/2016 2016/2017 2017/2018

People from outside South Africa

6,5

6,0

6,0

5,5

5,9

5,4

People from other areas in South
Africa

32,0

31,5

31,3

30,5

29,6

30,1

People from this area

61,4

62,5

62,7

64,1

64,5

64,5

Figure 29 depicts the distribution of perceptions about who were the likely perpetrators of property and
violent crime, respectively. From 2012 to 2017/18, the general perception was that perpetrators of
property crime are people from around the neighbourhood. In 2017/18, the majority of households (65%)
thought that perpetrators of property crime are people from their area. The same results were obtained
for the question about violent crimes.

8.3 Beliefs about reasons for committing crime
In the VOCS 2017/18 questionnaire, respondents were asked what they thought could be the motive for
perpetrators committing crime. This question was asked differently in 2017/18 as compared to the
previous years. Users are advised to use caution when comparing these responses across the series.

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Figure 30: Percentage distribution of households' perceptions of why perpetrators commit
crime, 2017/18
60,0

50,0

47,8

Percentage

40,0

30,0

25,3
18,4

20,0
8,1

10,0

0,0

Drugs related need

Real need

Greed

Other reasons

In 2017/18, the majority of households in South Africa thought that the need for drugs (47,8%) was the
main reason perpetrators committed crime. More than a quarter (25,3%) felt that they did so because
of a real need. About 8% of households were of the view that the perpetrators of crime commit crime
because they are greedy. A further 18,4% of households attributed the reasons for committing crimes
to other motives, which include jealousy, hatred, ritual killings and a lack of parental influence over
children.

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8.4 Attitudes towards police
A descriptive analysis of the average length of time it takes households to reach their nearest police
station and for the police to respond to emergency calls, police visibility, as well as household levels of
satisfaction with police services, by selected demographic variables, produced the following results.
Figure 31: Percentage distribution of households' perceptions of the average time it takes to
reach the nearest police station using their usual mode of transport, 2012–2017/18
100,0
90,0
80,0
70,0

Percentage

60,0
50,0
40,0
30,0
20,0
10,0
0,0

2012

2013/14

2014/15

2015/16

2016/17

2017/18

More than 2 hrs

1,5

1,3

1,0

1,1

1,2

1,2

Less than 2 hrs (but more than 1 hr)

6,3

6,1

6,3

5,9

4,3

4,3

Less than 1 hr (but more than 30 min)

25,9

27,6

25,1

28,5

28,2

27,3

Less than 30 min

66,4

64,9

67,7

64,6

66,3

65,7

Figure 31 shows households' perceptions of the average length of time it would take to reach their
nearest police station when using their usual mode of transport between 2011 and 2017/18. Responses
were very similar over time. In 2017/18, slightly less than two-thirds of households in South Africa took
less than half an hour to reach their nearest police station. For the same period, about 27% of
households thought it took between thirty minutes and an hour on average to reach a police station.

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Figure 32: Percentage distribution of households' perceptions of the average length of time it
takes to reach the nearest police station using their usual mode of transport by province, 2017/18
100%
90%
80%
70%

Percentage

60%
50%
40%
30%
20%
10%
0%

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

More than 2 hrs

0,3

0,9

1,6

1,5

2,8

2,1

0,4

1,2

1,4

1,2

Less than 2 hrs (but more than 1 hr)

0,8

6,4

4,9

6,7

6,5

7,8

1,6

3,8

6,2

4,3

Less than 1 hr (but more than 30 min)

10,6

31,8

27,3

32,0

33,5

33,4

20,2

30,3

42,9

27,3

Less than 30 min

87,5

59,2

64,6

59,2

55,5

54,5

75,9

63,2

48,3

65,7

Figure 32 shows the provincial distribution of the average length of time it takes to reach the nearest
police station. The figure indicates that the police stations that are relatively accessible to the public are
situated in Western Cape (87,5%), followed by Gauteng (75,9%) and Northern Cape (64,6%), where
households were able to reach a police station in less than 30 minutes.

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Figure 33: Percentage distribution of households' perceptions of the average length of time it
takes the police to respond to an emergency call by province, 2017/18
100%
90%
80%
70%

Percentage

60%
50%
40%
30%
20%
10%
0%

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Never arrived

11,6

5,1

17,3

13,4

14,0

16,5

10,8

12,4

10,0

11,5

More than 2 hrs

13,5

11,0

35,0

23,2

34,1

40,6

14,1

43,3

16,1

21,1

Less than 2 hrs (but more than 1 hrs)

12,5

17,5

11,0

10,1

14,1

9,0

12,9

8,3

9,7

12,5

Less than 1 hr (but more than 30 min) 22,0

39,0

15,8

28,7

18,7

15,6

26,6

14,5

31,2

24,8

Less than 30 min

23,1

20,1

23,0

12,3

14,6

29,1

17,1

27,9

25,6

37,8

Figure 33 depicts the average length of time it takes the police to respond to an emergency call. Figure
33 showed that most police stations in Western Cape and Gauteng were less than thirty minutes away
from most households, and Figure 33 confirms that Western Cape had one of the fastest police response
times with 59,8% indicating a response time of less than an hour. However, the province with the highest
percentage of responses within an hour was Eastern Cape (62,1%). Limpopo also had good response
times with 59,1% reporting response times of less than an hour. It is also important to note that "Never
arrived" is most problematic in Northern Cape (17,3%), North West (16,5%) and KwaZulu-Natal (14,0%).

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Figure 34: Percentage distribution of households who saw the police, in uniform and on duty, in
their area of residence, 2012–2017/18
45,0
40,0
35,0

Percentage

30,0
25,0
20,0
15,0
10,0
5,0
0,0

2012

2013/2014

2014/2015

2015/2016

2016/2017

2017/2018

At least once a day

38,8

37,0

35,0

33,1

33,8

32,5

At least once a week

27,1

26,8

26,0

27,2

27,9

27,4

At least once a month

11,9

13,4

13,3

13,1

16,4

15,8

Never

14,6

15,7

17,8

19,4

21,8

23,1

Figure 34 represents a time series of police visibility from 2012 to 2017/18. The proportion of households
who saw police in uniform in their neighbourhoods at least once a day declined over the reference
period. The decline was accompanied by slight increases in seeing them at least once a week or month
and an increase from 14,6% to 23,1% between 2012 and 2017/18 among households who say that they
never see the police in their area.

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Figure 35: Percentage distribution of households who saw the police, in uniform and on duty, in
their area of residence by province, 2017/18
100%
90%
80%
70%

Percentage

60%
50%
40%
30%
20%
10%
0%

WC

EC

NC

FS

KZN

NW

GP

MP

LP

RSA

Never

17,6

37,5

11,3

19,4

29,1

26,4

15,0

26,5

27,6

23,1

At least once a month

12,9

15,3

13,7

14,5

22,4

20,5

10,2

18,1

21,0

15,8

At least once a week

23,8

21,8

24,0

26,0

29,5

28,8

29,4

30,4

26,7

27,4

At least once a day

45,5

24,9

49,4

39,5

17,7

22,8

44,0

23,9

22,7

32,5

A provincial distribution of households who saw police, in uniform and on duty, in their area of residence
is depicted in Figure 35. While data show that police stations are more accessible in Western Cape and
Gauteng, Figure 35 shows that a larger proportion of households who saw police on duty, in their area
of residence at least once a day were in Northern Cape (49,4%) and Western Cape (45,5%).

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Figure 36: Percentage of households satisfied with police services in their area, 2013/14 –
2017/18
60

59,4
58,8

Percentage of households satisfied

59
58

57,3

56,9

57
56
55

54,2

54
53
52
51

2013/14

2014/15

2015/16

2016/17

2017/18

Figure 36 represents the proportions of households who are satisfied with the police in their area of
residence. The figure shows that South African households' level of satisfaction with the police has
been declining since 2013/14, with only a slight increase in 2015/16.

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Figure 37: Percentage distribution of households who were satisfied with police in their area by
province, 2016/17–2017/18
70
60
50
Percentage

40
30
20
10
0
2016/17

Western
Cape
58

Eastern
Cape
59

Northern
Cape
60

2017/18

58

56

52

64

KwaZuluNatal
51

64

50

Free State

North West

Gauteng

Mpumalanga

Limpopo

50

57

57

65

SOUTH
AFRICA
57

47

53

56

58

54

The percentage of households satisfied with the police services in their area dropped in every province
except the Western Cape and Free State.
Figure 38 and Figure 39 summarise households' reasons for being satisfied/dissatisfied with the way in
which the police deal with crime. It is worth noting that questions on police satisfaction in the VOCS
2017/18 were asked differently from the previous years. Readers are advised to exercise caution when
comparing VOCS 2017/18 and data from preceding years. The category "Other" comprises a collation
of reasons such as "They are disability sensitive/tolerant" and "They are gender sensitive/tolerant".
Figure 38: Distribution of households' reasons for being satisfied with the way the police deal
with crime, 2017/18
40,0
35,0

35,3

Percentage

30,0

26,1

25,0
20,0

15,6

15,0

10,8

10,0

8,3

5,0
0,0

The police are They come to the They always
committed
scene of the crime respond on time

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They arrest
criminals

They are
trustworthy

0,7

1,6

They recover
stolen property

Other

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More than a third of households (35,3%) who were satisfied with the police, were satisfied because they
are committed and a further 26,1% are happy because they came to the scene of the crime. The reasons
why households are dissatisfied are summarised in Figure 39 below.
Figure 39: Distribution of households' reasons for being dissatisfied with the way the police deal
with crime, 2016/17–2017/18

They never recover goods

58,8

3,2
15,2

They don't repond on time
6,1

They don't come to the area

4,9

They are corrupt

10,5

3,5

They don't have enough resources
They release suspects early

2,9

They cooperate with thiefs/criminals

2,7

They are harsh to victims

0,9
2,3
1

Other

14,8
10,5

4,1

They are lazy

34,4

7,2
6,9
6,5

2,7

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

Percentage
2016/17

2017/18

Among households who were dissatisfied with the way in which the police deal with crime in their area,
the majority (59%) felt that the police never recover their goods. The category "Other" comprises
reasons such as "They are disability insensitive/intolerant" and "They are gender insensitive/intolerant".

8.5 Attitudes towards courts
Households were also asked in the VOCS about their satisfaction with the way in which courts generally
deal with perpetrators, reasons for being satisfied, reasons for being dissatisfied, and their feelings about
the appropriateness of sentences imposed on perpetrators of violent crime.

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Figure 40: Percentage distribution of households' satisfaction with police services in their area
and the way in which courts generally deal with perpetrators of crime, 2013/14 – 2017/18
70

Percentage of households satisfied

65
60

63,9
59,4

58,8

56,9
54

55

57,3
54,2

52,3

50
44,9

45

41,1

40
35
30

2013/14

2014/15

2015/16
Police

2016/17

2017/18

Courts

Figure 40 shows that satisfaction with courts, as perceived by South African households, has been
declining more rapidly than satisfaction with the police during the period 2013/14 - 2017/18.

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Figure 41: Percentage distribution of households' satisfaction with the way in which courts
generally deal with perpetrators of crime by province, 2016/17–2017/18
80
70
60

Percentage

50
40
30
20
10
0
2016/17

Western
Cape
24

Eastern
Cape
43

Northern
Cape
48

2017/18

21

38

41

48

KwaZuluNatal
45

44

40

Free State

North West

Gauteng

Mpumalanga

Limpopo

44

43

51

68

SOUTH
AFRICA
45

44

40

44

64

41

The percentage of households satisfied with the way in which courts generally deal with perpetrators
of crime dropped in every province except the North West.
Figure 42: Percentage distribution of reasons for households being satisfied with the way in
which courts generally deal with perpetrators of crime by province, 2017/18
100,0
90,0
80,0
70,0

Percentage

60,0
50,0
40,0
30,0
20,0
10,0
0,0
They pass sentences appropriate to the crime

WC
48,2

EC
51,6

NC
59,4

FS
49,1

KZN
56,3

NW
48,7

GP
41,4

MP
59,9

LP
59,5

RSA
50,3

They have a high rate of conviction

42,0

28,5

29,6

34,7

21,1

21,6

36,3

12,3

21,3

27,7

They are not corrupt

8,0

20,0

10,6

14,0

24,0

29,2

21,2

28,6

19,2

20,7

Other

0,4

0,0

0,2

2,2

0,1

0,7

0,2

0,0

0,0

0,3

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Figure 42 summarises the reasons why households are satisfied with the way in which courts generally
deal with the perpetrators of crime. The majority (50,3%) of those who were satisfied with the courts,
thought that the courts passed sentences that were appropriate to the crimes committed, while 27,7%
stated that courts had a high rate of conviction and 20,7% were of the opinion that courts were not
corrupt. Mpumalanga (59,9%) had the highest percentage of households who were satisfied with the
passing of appropriate sentences. Mpumalanga was followed by Limpopo (59,5%) and Northern Cape
(59,4%).
Figure 43: Percentage distribution of reasons for households being dissatisfied with the way in
which courts generally deal with perpetrators of crime by province, 2017/18
100,0
90,0
80,0
70,0
Percentage

60,0
50,0
40,0
30,0
20,0
10,0
0,0
Courts are too lenient

WC
50,7

EC
46,2

NC
63,7

FS
63,5

KZN
31,9

NW
56,2

GP
43,4

MP
46,7

LP
54,5

RSA
45,6

Matters drag for too long/postponements

13,5

12,4

They release perpetrators unconditionally

16,0

21,0

17,2

8,5

8,8

10,7

17,7

7,8

16,0

14,7

15,2

14,3

21,0

21,8

13,9

25,2

14,9

They do not have enough convictions

6,5

9,6

2,7

17,1

6,7

9,1

2,4

6,1

4,6

4,5

Courts are corrupt

3,3

5,5

6,4

3,2

1,5

9,9

4,6

8,7

2,3

5,2

Some people get preferential treatment

7,3

6,3

4,1

3,7

4,0

4,0

5,4

8,2

4,6

2,0

5,7

No proper notice of hearing is served
Other

1,6

1,8

0,7

3,3

6,3

1,0

3,7

1,9

5,7

3,3

1,8

0,1

0,2

2,3

0,7

1,3

0,5

0,3

0,0

0,7

Figure 43 depicts the percentage distribution of reasons for being dissatisfied with the way courts
generally deal with perpetrators of crime by province. Households were asked to give reasons why they
were not satisfied with the performance of courts. The majority (45,6%) of the households indicated that
the courts were too lenient on criminals when passing judgement. This was followed by households who
felt that perpetrators are released unconditionally (17,1%) and that matters dragged for too long
(14,3,1%). A high percentage of households who indicated that courts were too lenient on criminals was
observed in Northern Cape (63,7%) and Free State (63,5%).

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Figure 44: Percentage of households who thought that sentencing of violent crime was long
enough to discourage people from committing these crimes, 2017/18
70,0
61,2

60,0

Percentage

50,0
40,0

34,4

36,3

40,9

40,2

40,1

FS

KZN

NW

36,5

38,8

38,2

30,0
20,0

21,3

10,0
0,0

WC

EC

NC

GP

MP

LP

RSA

According to Figure 44, Limpopo had the greatest proportion of households (61,2%) who thought that
the sentence for violent crimes is long enough to discourage people from committing crimes, followed
by Free State (40,9%), KwaZulu-Natal (40,2%), North West (40,1%) and Mpumalanga (38,8%). Western
Cape (21,3%) had a significantly lower percentage of households who thought that the sentence for
violent crimes was long enough to discourage people from committing crimes when compared to other
provinces.

8.6 Attitudes towards correctional services
This section presents findings on households' perceptions of the services provided by correctional
services, households' willingness to welcome a former prisoner back in their community and their
willingness to provide employment to a former prisoner.

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Figure 45: Percentage distribution of households' perceptions about services provided by
correctional services, 2017/18
70,0

65,8

64,3
59,3

60,0

55,7

53,7

Percentage

50,0
40,0

35,1

30,0
20,9

20,5

It is easy to
escape from
prison

Prisons violate
prosoners' rights

20,0
10,0
0,0

Prisons safely Prisons provide
Prisons
Prisners get Prisons are just Former prisoners
lock away those
comfort for
rehabilitates parole too easily colleges for
will not easily
who have been
prisoners
those who have
crooks
commit crimes
setenced
been setenced
again

Figure 45 depicts the percentage distribution of the perceptions about services provided by correctional
services. Households in South Africa were asked whether or not they agree with certain statements
about the services that are provided by correctional services. The majority (65,8%) of households in the
country were of the opinion that prisons safely lock away those who have been sentenced, while 20,5%
agreed with the statement that prisons violate prisoners' rights. About two-thirds (64,3%) of households
indicated that prisons provide comfort to prisoners. More than half of households (59,3%) indicated that
prisons rehabilitate those who have been sentenced, and 55,7% were of the opinion that prisoners get
parole too easily.
Figure 46: Percentage of households that are satisfied with services provided by correctional
services, 2016/17–2017/18
80
70

Percentage

60
50
40
30
20
10
0
2016/17

Western
Cape
31

Eastern
Cape
52

Northern
Cape
62

2017/18

30

43

51

59

KwaZuluNatal
52

62

48

Free State

North West

Gauteng

Mpumalanga

Limpopo

55

57

71

59

SOUTH
AFRICA
54

52

50

63

63

50

Only Free State and Limpopo showed an increase in the percentage of households satisfied with
correctional services.

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Figure 47: Percentage distribution of households willing to welcome a former prisoner back in
their community, 2017/18

Welcome former prisoners into your church/Mosque

79,6

Welcome former prisoners back into your community

74,3

Welcome former prisoners as a next door neighbour

65,8

Welcome former prisoner into your home for a meal

54,8

Provide employment to former prisoner

48,5

Start a business with a former prisoner

32,1

Share an apartment with a former prisoner

31,4

Marry a former prisoner

22,2
0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

Percentage

According to Figure 47, as many as 74,3% of households in South Africa were willing to welcome a
former prisoner back in their community, and 79,6% would welcome them back into their mosque or
church.
More than two-thirds of households (65,8%) would welcome former prisoners as a next-door neighbour,
while less than half of households in South Africa (48,5%) indicated that they were willing to provide
employment to a former prisoner.
Figure 48: Percentage distribution of households willing to provide employment or marry to a
former prisoner by gender group, 2017/18
60
51

Percentage who say Yes

50

45

40
30

25
19

20
10
0

Male
Provide employment

Female
Marry a former prisoner

Figure 48 shows that males are more likely to offer employment and/or to marry former prisoners than
females.

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Figure 49: Percentage distribution of households willing to provide employment or marry a
former prisoner by population group, 2017/18
60
51,6
50
38,3

Percentage

40
30

24,6

20

13,1

10
0

35,5

30,9

Black/African

Coloured
Employ a former prisoner

9,1

Indian/Asian

12,4

White

Marry a former prisoner

According to Figure 49, black African households are more likely than any other population groups to
be willing to employ and/or marry a former prisoner.

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9. TECHNICAL NOTES
9.1 Survey requirements and design
The questionnaire design, testing of the questionnaire, sampling techniques, data collection, computer
programming, data capture, and weighting constituted the research methodology used in this survey,
as discussed below.

9.2 Questionnaire design
Stats SA has committed itself to the highest international standards of data collection. In this regard,
without compromising South African values and concepts, the VOCS 2017/18 strives to bring the
questionnaire content to international standards, so that comparative analyses with other countries can
be undertaken. The VOCS 2017/18 questionnaire was developed based on the questions used in the
International Crime Victim Survey (ICVS), previous VOCSs (both conducted by ISS and Stats SA) with
modifications in some instances. The Stats SA questionnaire design standard for household surveys
was also used as a normative reference. In order to minimise fieldworker and capturing errors, the
questionnaire was largely pre-coded. Some minor changes and additions were made to the
questionnaire for VOCS 2017/18.
Sections 10 to 20 of the questionnaire represent household crimes for which a proxy respondent
(preferably household head or acting household head) answered on behalf of the household. All
analyses done in this report that included demographic variables were done using the demographic
characteristics of the household head or proxy.
Sections 21 to 28 of this questionnaire required that an individual be selected using the birthday section
method to respond to questions classified as individual crimes. This methodology selects an individual
who is 16 years or older, whose birthday was first to follow the survey date.
Table 85 summarises the details of the questions included in the VOCS questionnaire. The questions
are covered in 28 sections, each focusing on a particular aspect.

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Table 85: Contents of the VOCS 2017/18 questionnaire

Section
Cover
page
Flap

Number of
questions

Details of each section
Household information, response details, field staff information, result codes, etc.

10

Demographic information (name, sex, age, population group, etc.)

Section 1

10

Section 2

13

Household-specific characteristics (education, economic activities and household income
sources)
General thinking/beliefs on crime

Section 3

6

Individual and community response to crime

Section 4

7

Victim support and other interventions

Section 5

4

Citizen interaction or community cohesion

Section 6

16

Perception of the police service

Section 7a

9

Perception of the courts

Section 7b

11

Perception of trafficking in persons

Section 8

4

Perception of correctional services

Section 9

4

Corruption experienced by the household

Section 10

4

Experience of household crime (screening table)

Section 11

21

Theft of car experienced by a household member(s) in the past 12 months

Section 12

23

Housebreaking or burglary when no one was at home in the past 12 months

Section 13

28

Section 14

20

Home robbery (including robbery often around or inside the household's dwelling)
experienced by a household member(s) in the past 12 months
Theft of livestock, poultry and other animals in the past 12 months

Section 15

19

Theft of crops planted by the household in the past 12 months

Section 16

23

Murder experienced by a household member(s) in the past 12 months

Section 17

21

Theft out of the motor vehicle experienced by a household member(s) in the past 12 months

Section 18

20

Section 19

20

Section 20

17

Deliberate damaging/burning or destruction of dwelling experienced by a household
member(s) in the past 12 months
Motor vehicle vandalism or deliberate damage of a motor vehicle experienced by a
household member(s) in the past 12 months
Theft of bicycle experienced in the past 12 months

Section 21

7

Section 22

19

Experience of individual crimes (screening table) in the past 5 years and in the past 12
months
Theft of personal property experienced in the past 12 months

Section 23

30

Hijacking of motor vehicle (including attempted hijacking) experienced in the past 12 months

Section 24

27

Section 25

28

Robbery (including street robberies and other non-residential robberies, excluding car or
truck hijackings, and home robberies) experienced in the past 12 months
Sexual offences (including rape) experienced in the past 12 months

Section 26

27

Assault experienced in the past 12 months

Section 27

18

Consumer fraud experienced by the individual in the past 12 months

Section 28

7

Section 29

3

Corruption (when someone is in a position of authority fails to do something he/she is
required to do and solicits a bribe)
Survey officer to answer questions

9.3 Sample design
The VOCS 2017/18 uses the master sample frame that has been developed as a general-purpose
household survey frame that can be used by all other Stats SA household-based surveys having design
requirements that are reasonably compatible with the VOCS. The VOCS 2016/17 collection was based
on the 2013 master sample. This master sample is based on information collected during the 2011
Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576

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enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were
used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the
master sample, since they covered the entire country and had other information that is crucial for
stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the master sample
with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the
current master sample (3 324) reflect an 8,0% increase in the size of the master sample compared to
the previous (2008) master sample, which had 3 080 PSUs. The larger master sample of PSUs was
selected to improve the precision (smaller coefficients of variation, known as CVs) of the VOCS
estimates.
The master sample is designed to be representative at provincial level and within provinces at
metro/non-metro levels. Within the metros, the sample is further distributed by geographical area. The
three geographical areas are metro, rural and urban. This implies that within a metropolitan area, for
example, the sample is representative of the different geographical areas that may exist within that
metro.
The sample for the VOCS is based on a stratified two-stage design with probability proportional to size
(PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling
in the second stage.
Table 86: Comparison between the 2007 (old) master sample and the new master sample
(designed in 2013)
2007 master sample
(VOCS 2008–2014)
Two-stage stratified design

2013 master sample
(VOCS 2015/16 onwards)
Two-stage stratified design

Number of primary
sampling units (PSUs)
Number of dwelling
units (DUs)
Stratification

3 080 PSUs

3 324 PSUs

Approximately 30 000 DUs

Approximately 33 000 DUs

No stratification by geotype within
metros/non-metros

Stratification by geotype within
metros/non-metros

Geotypes

4 geotypes, namely urban formal,
urban informal, tribal areas, and
rural formal

3 geotypes, namely urban, traditional, and
farms

Sample

Sample representative at national,
provincial and metro levels, but
estimates only produced to
provincial level

Sample representative at national,
provincial and metro levels
Weights produced to publish estimates at
metro level

Design

There are a number of aspects in which the two master samples differ. The number of geotypes was
reduced from 4 to 3 while the new master sample allows for the publication of estimates at metro level.
Primary stratification occurred at provincial and metro/non-metro levels, for mining, and geographical
area, while the secondary strata were created within the primary strata based on the demographic and
socioeconomic characteristics of the population.

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Figure 50: Distribution of primary sampling units by province, 2007 (old) master sample and the
new master sample (designed in 2013)

2007

2013

544
872
464
536
384
348
364
440
324
300
288
244
268
244
264
192
180
148

GP
KZN
WC
EC
LP
MP
NW
FS
NC
0

Change
328
72
-36
76
-24
-44
-24
-72
-32

200

400

600

800

1000

Given the change in the provincial distribution of the South African population between 2001 and 2011,
the master sample was adjusted accordingly. There was also an 8% increase in the sample size of the
master sample of PSUs to improve the precision of the VOCS estimates. In particular, the sample sizes
increased most notably in Gauteng, Eastern Cape and KwaZulu-Natal.

9.4 Data collection
Stats SA conducted the fifth annual Victims of Crime Survey in close collaboration with other role players
in the safety and security cluster from April 2016 to March 2017. Since 2013, the Victims of Crime
Survey, the Domestic Tourism Survey (DTS) and the General Household Survey (VOCS) have adopted
the continuous data collection (CDC) methodology. The Victims of Crime Survey conducts data
collection from April to March. In the long run, this methodology will enable data collection to coincide
with the financial year and the reporting cycle of administrative data related to crime.
Data collection took place from April 2016 to March 2017 with a moving reference period of 12 months.
This is different from the 2011 and 2012 collections, which were done from January to March and had
a fixed reference period from January to December of the previous year. The sample has been
distributed evenly over the whole collection period in the form of quarterly allocations. This will provide
a guarantee against possible seasonal effects in the survey estimates. It will, in future, provide an
opportunity for the production of rolling estimates relating to any desired time period. It has been noted
that the change of data collection methodology may cause concerns over the survey estimates,
particularly upon comparisons of years before and after the change. Victimisation questions referred to
the twelve calendar months ending with the month before the interview.
Statistics South Africa is committed to meeting the highest ethical standards in its data collection
processes. In addition to being bound to the Statistics Act, the Victims of Crime Survey, due to its
sensitive nature, required additional measures to ensure that the integrity and well-being of the
households are protected.

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9.5 Editing and imputation
All questionnaires were scanned, and the data were sent to the post-capture process for editing and
imputation. At each stage of checking, data were edited to ensure consistency. Data editing is concerned
with the identification and, if possible, the correction of erroneous or highly suspect survey data. Data
were checked for valid range, internal logic and consistency.
The focus of the editing process was on clearing up skip violations and ensuring that each variable only
contains valid values. Very few limits to valid values were set and data were largely released as it was
received from the field.
When dealing with internal inconsistencies, logical imputation was used, i.e. information from other
questions was compared with the inconsistent information. If other evidence was found to back up either
of the two inconsistent viewpoints, the inconsistency was resolved accordingly. If the internal
consistency remained, the question subsequent to the filter question was dealt with by either setting it
to missing and imputing its value or printing a message of edit failure for further investigation, decisionmaking and manual editing. Hot-deck imputation was used to impute for missing age.

9.6 Construction of household sample weights
The household sample weights for VOCS 2011 to 2017/18 were constructed in such a manner that the
responses from the respondent households could be properly expanded to represent the household
population. The sample weights therefore are a product of several factors, including the original selection
probabilities (design weights), adjustments for PSUs that were subsampled or segmented, excluded
population from the sampling frame, non-response, weight trimming and benchmarking to known
household estimates.
The base weights for the household weighting process are the same as those for the person weighting
process. The adjustments applied to the base weights to obtain the adjusted base weights for household
weighting. In the final step of constructing the household sample weights, the adjusted base weights
were calibrated such that the aggregate totals match with the independently derived (by Stats SA
Demography Division) household estimates by the household head's age, population group and gender
at national and provincial levels. The calibrated weights are constructed with a lower bound on the
calibrated weights of 50 within the StatMx software from Statistics Canada.
The household estimates used in the calibration of the adjusted base weights for VOCS 2011 to 2017/18
were the Mid-November 2010, Mid-November 2011, Mid-May 2013 and Mid-May 2015 population
estimates, respectively, based on the 2016 mid-year population model. The household estimates were
used in benchmarking to two sets of control totals:
•

National level totals that were defined by the cross-classification of age, population group and
gender of the household head. Age represents four age groups, namely 0–34, 35–49, 50–64 and
65+. Population group represents four groups, namely black African, coloured, Indian/Asian and
white. Gender represents two groups, namely male and female. The cross-classification resulted
in 32 calibration cells at national level.

•

Provincial level totals were defined within the provinces by age of household head. The country
has nine provinces; Age represents the four age groups (0–34, 35–49, 50–64 and 65+). The crossclassification of the areas with age resulted in 36 calibration cells.

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9.7 Individual sample weights
The final survey weights were constructed by calibrating the non-response-adjusted design weights to
the known population estimates as control totals using the Integrated Household Weighting method.
The VOCS 2017/18 sample was calibrated using the population estimates of Mid-May 2016 (based on
the 2016 series). The final weights were benchmarked to the known population estimates of 5-year age
groups by population group and by gender at national level, and broad age groups at provincial level.
The 5-year age groups are: 0–4, 5–9, 10–14, 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49,
50–54, 55–59, 60–64, 65–69,70–74, and 75 and older. The provincial-level age groups are 0–14,
15–34, 35–64; and 65 years and older. The calibrated weights are constructed such that all persons in
a household would have the same final weight.
The VOCS 2017/18 had an extra level of selection where one person, 16 years or older, was selected
per household to complete sections 21 to 28 of the questionnaire. The individual weights were
benchmarked to an estimated national population of age 16 and older in mid-May 2016. Records for
which the age, population group or gender had item non-response could not be weighted and were
therefore excluded from the dataset. No additional imputation was done to retain these records.

9.8 Estimation
The final survey weights were used to obtain the estimates for various domains of interest at household
level, for example, victimisation level in South Africa, households' perceptions of crime levels in the
country, etc. The following is the R code used to obtain estimates of totals, proportions and ratios:
Table 1
svyby(~HoCrime, by=~prov, des1,vartype="cvpct", svytotal)
svyby(~HoCrime, by=~prov, denominator=~one, des1,vartype="cvpct", svyratio)
y <- svytotal(~HoCrime, des1, vartype="cvpct")
cv(y)
y <- svyratio(~HoCrime, denominator=~one, des1,vartype="cvpct")
cv(y)
Table 2
svyby(~HoCrimeN, by=~gender, des1,vartype="cvpct",svytotal)
svyby(~HoCrime, by=~gender, denominator=~one, des1,vartype="cvpct",svyratio)
svyby(~HoCrimeN, by=~gender, des1,vartype="cvpct",svytotal)
svyby(~HoCrime, by=~gender, denominator=~one, des1,vartype="cvpct",svyratio)
svyby(~HoCrimeN, by=~race, des1,vartype="cvpct",svytotal)
svyby(~HoCrime, by=~race, denominator=~one, des1,vartype="cvpct",svyratio)
Table 7
y <- svytotal(~CarTheftN, subset(des1,K_MOTORIS==1), vartype="cvpct")
cv(y)
y <- svyratio(~CarTheftN, denominator=~CarTheft, subset(des1,K_MOTORIS==1),,vartype="cvpct")
cv(y)
With minor changes, the above code was used to obtain results other than those in tables mentioned
above.

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9.9 Reliability of the survey estimates
The survey estimates for questions related to perceptions of crime and the criminal justice system are
reliable and provide good estimates at provincial level and even at lower levels in some cases. However,
statistics related to specific types of crime should be used with caution. Crimes that are relatively rare –
such as murder – resulted in very few cases from the sample, resulting in large standard errors. In the
past, guidelines given to determine the quality of estimates were based on rule of thumb. In this report,
for every estimate a coefficient of variation was calculated and presented together with the estimate.
The quality of every estimate is based on the interval range within which the CV falls. The methodology
chapter at the beginning of this report describes the four quality intervals.

9.10 Comparability with previous surveys
The VOCS 2017/18 is comparable to the previous VOC surveys in that several questions have remained
unchanged over time. Where comparisons were possible, it was indicated in the report. The current
survey can provide more accurate estimates at provincial level. Caution should be exercised when
running cross-tabulation of different crimes by province and other variables. For several crimes, the
reported experienced cases were too few to allow for extensive analysis. This is due to the survey being
the first in the series of continuous data collection methodology that was applied.

9.11 Sampling and the interpretation of the data
Caution must be exercised when interpreting the results of the VOCS at low levels of disaggregation.
The sample and reporting are based on the provincial boundaries as defined in 2011. These new
boundaries resulted in minor changes to the boundaries of some provinces, especially Gauteng, North
West, Mpumalanga, Limpopo and Eastern and Western Cape. In previous reports, the sample was
based on the provincial boundaries as defined in 2006, and there will therefore be slight comparative
differences in terms of provincial boundary definitions.

9.12 Limitations of crime victimisation surveys
Victimisation surveys are likely to produce higher crime estimates than police-recorded administrative
data. This is because many crimes are not reported to the police. Victim surveys deal with incidents that
not necessarily match the legal definition of crime. Although data from crime victim surveys are likely to
elicit better disclosure of criminal incidents than data from police records, they can also be subject to
undercounting, as some victims may be reluctant to disclose information, particularly for incidents of a
sensitive nature, such as sexual offences.
The accuracy of statistics is influenced by the ability of people to recall past victimisations. The longer
the elapsed time period, the less likely it is that an incident will be recalled accurately. Surveys are also
subject to sampling and non-sampling errors. The survey is also limited by not involving a monthly cycle
of fieldwork, and the sample of each month being a random subset of the annual sample. Currently, the
survey sample is randomly distributed per quarter.

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9.13 Differences between victim surveys and police-reported data
The most basic difference between the two types of crime measurement is the method of data collection.
Police-reported statistics obtain data from police administrative records. In contrast, victim surveys
collect both household and personal information about their victimisation experiences, through face-toface interviews. The survey covers victims' experiences of crime at microdata level, including the impact
of crime on victims.
Police-reported statistics normally collate information on all incidents reported to a variety of police
stations. Victim surveys ask a sample of the population about their experiences and, if well designed,
this sample should be representative of the population as a whole. Although police statistics and victim
surveys normally cover comparable geographic areas, if appropriately nationally representative, victim
surveys may exclude some categories of victims, such as very young children or persons residing in
institutions such as a prisons, hospitals, care centres or military barracks. The reference period for the
police-recorded statistics is April 2016 to March 2017, whereas the reference period of the VOCS
2017/18 estimates is April 2016 to February 2017.

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10. DEFINITION OF TERMS
Acting household head – any member of the household acting on behalf of the head of the household.
Arson – unlawful and intentional damaging of an immovable structure which is suitable for human
occupation or the storing of goods and which belongs to another, by setting fire to it with the intention to
prejudice the owner.
Assault – direct or indirect application of force to the body of another person.
Note: Includes domestic violence.
College for crooks – a place where people learn how to become crooks/criminals or how to become
even better crooks/criminals.
Consumer fraud – deceptive practices that result in financial losses for consumers during seemingly
legitimate business transactions. Also includes cases where someone provides misleading information
and tricks a person into buying something or signing documents.
Court – an official public forum established by lawful authority to adjudicate disputes and dispense civil,
labour, administrative and criminal justice under law.
Hijacking of motor vehicle – unlawful and intentional forceful removal and appropriation of a motor
vehicle from the occupant(s).
Household – a group of persons who live together and provide themselves jointly with food and/or other
essentials for living, or a single person who lives alone.
Note: The persons basically occupy a common dwelling unit (or part of it) for at least four nights in a
week on average during the past four weeks prior to the survey interview, sharing resources as a unit.
Other explanatory phrases can be 'eating from the same pot' and 'cook and eat together'.
Household head – the main decision-maker, or the person who owns or rents the dwelling, or the
person who is the main breadwinner.
Housebreaking/burglary – unlawful and intentional breaking into a building or similar structure, used
for human habitation, and entering or penetrating it with part of the body or with an instrument, with the
intention to control something on the premises, intending to commit a crime on the premises, where
there is no contact between the victim(s) and the perpetrator(s).
Home robbery – unlawful and intentional forceful removal and appropriation of tangible property from
residential premises of another person while there is contact between the victim(s) and perpetrator(s).
Imputation – a procedure for entering a value for a specific data item where the response is missing or
unusable.
Individual crime – crime affecting a single person rather than an entire household.
Deliberate damage of dwellings – unlawful and intentional damaging of dwellings
Motor vehicle vandalism – unlawful and intentional to a vehicle or parts of a vehicle
Murder – unlawful and intentional killing of another human being.
Multiple households – occurs when two or more households live in the same dwelling unit.
Note: If there are two or more households in the selected dwelling unit and they do not share resources,
all households are to be interviewed. The whole dwelling unit has been given one chance of selection
and all households located there were interviewed using separate questionnaires.

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Panga – a large cutting knife with a broad blade.
Parole – early release of a prisoner who is then subject to continued monitoring as well as compliance
with certain terms and conditions for a specified period.
Perpetrator – person(s) who committed the crime.
Personal property – asset(s) belonging to an individual rather than a group of persons.
Physical force – bodily power, strength, energy or might.
Note: In the context of this survey, physical force includes actions where the human body is used to
compel/force someone to do something or to hurt or kill someone. It can include actions such as pushing,
pressing, shoving, hitting, kicking, throttling, etc.
Police station – building or converted shipping container from which the police force operates and
police officers do their duties.
Prison – a building in which a person is legally held as a punishment for crime he/she has committed
or while awaiting trial.
Property crime – unlawful appropriation of property belonging to other(s).
Prosecutor/state advocate – legal specialist (lawyer/advocate) whose job it is to make a case on behalf
of the State against someone accused of criminal behaviour.
Robbery involving force – unlawfully obtaining property with use of force or threat of force against a
person with intent to permanently or temporarily to withhold it form a person.
Sexual offences (including sexual assault, rape and domestic sexual abuse) – refers to grabbing,
touching someone's private parts or sexually assaulting or raping someone.
Note: In terms of the Sexual Offences Act (Act No. 32 of 2007), section 5, (1) A person ('A') who
unlawfully and intentionally sexually violates a complainant ('B'), without the consent of B, is guilty of the
offence of sexual assault. (2) A person ('A') who unlawfully and intentionally inspires the belief in a
complainant ('B') that B will be sexually violated is guilty of the offence of sexual assault.
Stick/club – a long bar or stick made of wood, plastic or other material and used as a weapon.
Theft – unlawful taking or obtaining of property with the intent to permanently deprive it from a person
or organisation without consent and without the use of force, threat of force or violence, coercion or
deception.
Theft of motor vehicles (excluding hijacking) – unlawful taking or obtaining of vehicles with an
engine, including cars, buses, lorries, construction and agricultural vehicles (excluding motorcycles) with
the intent to permanently deprive it from a person or organization without consent and without the use
of force, threat of force or violence, coercion or deception.
Threat – an intentional behaviour that causes fear of injury or harm.
Vandalism – deliberate damage to property belonging to someone else.
Violent crime – crime where a person was threatened, injured, or killed.
Weapon – an instrument used to cause harm or death to human beings or other living creatures.
Note: Includes knives, guns, pangas and knobkerries, metal or wooden bars/rods, broken glass, rocks,
bricks, etc.

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11. GLOSSARY OF ABBREVIATIONS/ACRONYMS
CDC
CJS
CV
DCS
DoJ & CD
DPME
DSD
DTS
DU
EA
EC
FS
GCIS
GHS
GP
HSRC
ICVS
ISS
JCPS
KZN
LP
MP
MRC
MS
MTSF
MVI
NC
NDP
NHTS
NPC
NW
PPS
PSU
RVI
SA
SAPS
SASQAF
Stats SA
VOCS
WC

Continuous data collection
Criminal Justice System
Coefficient of Variation
Department of Correctional Services
Department of Justice and Constitutional Development
Department of Monitoring and Evaluation
Department of Social Development
Domestic Tourism Survey
Dwelling unit
Enumeration area
Eastern Cape
Free State
Government Communication and Information System
General Household Survey
Gauteng
Human Sciences Research Council
International Crime Victims Survey
Institute for Security Studies
Justice and Crime Prevention and Security
KwaZulu-Natal
Limpopo
Mpumalanga
Medical Research Council
Master sample
Medium Term Strategic Framework
Multiple victimisation index
Northern Cape
National Development Plan
National Household Travel Survey
National Planning Commission
North West
Probability proportional to size
Primary sampling unit
Repeat victimisation index
South Africa
South African Police Service
South African Statistical Quality Assurance Framework
Statistics South Africa
Victims of Crime Survey
Western Cape

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ANNEXURE A: SAPS AND VOCS CRIME TYPES
SAPS crime category

Type of crime – SAPS

Type of crime – VOCS

1. Crime against a person

Murder

Murder

Attempted murder
Sexual offences

Sexual offences

Assault with intent to inflict grievous
bodily harm
Common assault

Assault (excludes sexual assault)

Common robbery
Robbery with aggravating circumstances

2. Sexual offences

Robbery (excludes home robbery and
car/truck hijackings)

Rape
Sexual assault
Attempted sexual offences
Contact sexual offences

3. Trio crimes

Carjacking

Hijacking of motor vehicle

Truck hijacking
Robbery of cash-in-transit
Bank robbery
Robbery at residential premises

Home robbery

Robbery at non-residential premises

4. Property related crime

Burglary at residential premises

House breaking

Theft of motor vehicle & motorcycle

Theft of motor vehicle

Theft out of or from motor vehicle

Theft out of motor vehicle

Stock theft

Theft of livestock/poultry and other animals
Theft of personal property

5. Other property related
crimes

Arson

Deliberate damage/burning/destruction of
dwellings

Malicious damage of residential
premises
Theft of bicycle
Theft of crops

6. Crime detected as a result
of police action

Drug related crime
Driving under the influence of alcohol or
drugs
Sexual offences detected as a result of
police action

7. Other crimes

All theft not mentioned elsewhere

Corruption

Commercial crimes

Consumer fraud

Illegal possession of firearms or
ammunition

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ANNEXURE B: SAPS AND VOCS DEFINITIONS OF CRIME
SAPS
Murder
Murder consists in the unlawful and intentional killing of
another human being.
Sexual offences
Rape, compelled rate, sexual assault, compelled sexual
assault, compelled self-sexual assault, incest, bestiality,
sexual act with corpse, acts of consensual sexual
penetration with certain children (statutory rape), acts of
consensual sexual violation with certain children (statutory
sexual assault).

Assault with intent to inflict grievous bodily harm
Assault with the intent to cause grievous bodily harm is
the unlawful and intentional direct or indirect application of
force to the body of another person with the intention of
causing grievous bodily harm to that person.
Common assault
Assault is the unlawful and intentional —
(a) direct or indirect application of force to the body of
another person, or
(b) threat of application of immediate personal violence to
another, in circumstances in which the threatened person
is prevailed upon to believe that the person who is
threatening him has the intention and power to carry out
his threat.
Common robbery
Robbery is the unlawful and intentional forceful removal
and appropriation of movable tangible property belonging
to another.
Robbery with aggravating circumstances
Robbery with aggravating circumstances is the unlawful
and intentional forceful removal and appropriation in
aggravating circumstances of movable tangible property
belonging to another.
Hijacking
Robbery of a motor vehicle is the unlawful and intentional
forceful removal and appropriation of a motor vehicle
(excluding a truck) belonging to another.
Truck hijacking
Robbery of a truck is the unlawful and intentional forceful
removal and appropriation of a truck (excluding a light
delivery vehicle) belonging to another.
Robbery of cash-in-transit
Cash-in-transit robbery is the unlawful and intentional
forceful removal and appropriation of money or containers
for the conveyance of money, belonging to another while
such money or containers for the conveyance of money
are being transported by a security company on behalf of
the owner thereof.
Robbery at residential premises
House robbery is the unlawful and intentional forceful
removal and appropriation of property from the residential
premises of another person.

Victims of Crime Survey, 2017/18

VOCS
Murder
Unlawful and intentional killing of another human being.
Sexual offences
Refers to grabbing, touching someone's private parts or
sexually assaulting or raping someone. Note: In terms of the
Sexual Offences Act No 32 of 2007 section 5, (1) A person ('A')
who unlawfully and intentionally sexually violates a complainant
('B'), without the consent of B, is guilty of the offence of sexual
assault. (2) A person ('A') who unlawfully and intentionally
inspires the belief in a complainant ('B') that B will be sexually
violated is guilty of the offence of sexual assault.
Assault (excludes sexual assault)
Unlawful and intentional damaging of an immovable structure
which is suitable for human occupation or the storing of goods
and which belongs to another, by setting fire to it with the
intention to prejudice the owner

Robbery (excludes home robbery and car/truck hijackings)
Unlawfully obtaining property with use of force or threat of force
against a person with intent to permanently or temporarily to
withhold it form a person.
Hijacking of motor vehicle
Unlawful and intentional forceful removal and appropriation of a
motor vehicle from the occupant(s).

Home robbery
Unlawful and intentional forceful removal and appropriation of
tangible property from residential premises of another person
while there is contact between the victim(s) and perpetrator(s).

 STATISTICS SOUTH AFRICA

SAPS
Robbery at non-residential premises
Business robbery is the unlawful and intentional forceful
removal and appropriation of property from the business
of another person.
Burglary at residential premises
Housebreaking (residential premises) is committed by a
person who unlawfully and intentionally breaks into a
building or similar structure, used for human habitation,
and enters or penetrates it with part of his or her body or
with an instrument with which he or she intends to control
something on the premises, with the intention to commit a
crime on the premises.
Theft of motor vehicle & motorcycle
Theft of a motor vehicle consists of the stealing of a motor
vehicle belonging to another person.

Theft out of or from motor vehicle
Theft out of a motor vehicle consists of the unlawful and
intentional removal of articles in or on the vehicle from the
vehicle, with the intention of permanently depriving the
owner thereof of control over such articles taken from the
vehicle.
Stock theft
Stock theft consists of the stealing of stock or produce
belonging to another person

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VOCS

House breaking
Unlawful and intentional breaking into a building or similar
structure, used for human habitation, and entering or
penetrating it with part of the body or with an instrument, with
the intention to control something on the premises, intending to
commit a crime on the premises, where there is no contact
between the victim(s) and the perpetrator(s).
Theft of motor vehicle
Unlawful taking or obtaining of vehicles with an engine,
including cars, buses, lorries, construction and agricultural
vehicles (excluding motorcycles) with the intent to permanently
deprive it from a person or organisation without consent and
without the use of force, threat of force or violence, coercion or
deception
Theft out of motor vehicle
Theft out of a motor vehicle occurs when a person gains
access to the interior of a motor vehicle, by force or otherwise,
when the owner is not present and takes valuable items.

Theft of livestock/poultry and other animals

Theft
Stealing of property belonging to someone else while they are
not aware.
Theft of personal property
See theft.
Arson
Arson is the unlawful and intentional setting of fire to
immovable property belonging to another or to one's own
immovable insured property, in order to claim the value of
the property from the insurer.
Malicious damage of residential premises
Malicious injury to property consists in the unlawful and
intentional damaging of property belonging to another or
one's own insured property, with the intention to claim the
value of the property from the insurer.

All theft not mentioned elsewhere
Commercial crimes

Victims of Crime Survey, 2017/18

Deliberate damage/burning/destruction of dwellings
Unlawful and intentional damaging of dwellings.

Theft of bicycle
See theft.
Theft of crops
See theft.
Corruption
Consumer fraud
Deceptive practices that result in financial losses for consumers
during seemingly legitimate business transactions. Also
includes cases where someone provides misleading
information and tricks a person into buying something or
signing documents.