Climate Change Indicators in the United States: Lyme Disease
www.epa.gov/climatechange/indicators - Updated May 2014

Lyme Disease
This indicator tracks the rate of reported Lyme disease cases across the United States.

Background
Lyme disease is a bacterial illness that can cause fever, fatigue, joint pain, and skin rash, as well as more
serious joint and nervous system complications. Lyme disease is the most common vector-borne disease
(that is, a disease transmitted by mosquitoes, ticks, or fleas) in the United States. In recent years,
approximately 20,000–30,000 confirmed cases of Lyme disease per year have been reported to the
Centers for Disease Control and Prevention. 1 However, the actual number of illnesses is likely greater
than what is reported to health officials. 2 Lyme disease is transmitted through the bite of certain species
of infected ticks (referred to commonly as deer ticks) that carry the bacteria that cause Lyme disease.
These ticks live not only on deer, but also on rodents, birds, and other host animals. Deer do not harbor
the bacteria that cause Lyme disease, but certain other hosts such as white-footed mice do, and ticks
pick up the bacteria by feeding on these infected hosts.
Climate is just one of many important factors that influence the transmission, distribution, and incidence
of Lyme disease. However, studies provide evidence that climate change has contributed to the
expanded range of ticks, 3 increasing the potential risk of Lyme disease, such as in areas of Canada where
the ticks were previously unable to survive. The life cycle and prevalence of deer ticks are strongly
influenced by temperature. 4 For example, deer ticks are mostly active when temperatures are above
45˚F, and they thrive in areas with at least 85 percent humidity. Thus, warming temperatures associated
with climate change could increase the range of suitable tick habitat, and are therefore one of multiple
factors driving the observed spread of Lyme disease. 5 Because tick activity depends on temperatures
being above a certain minimum, shorter winters could also extend the period when ticks are active each
year, increasing the time that humans could be exposed to Lyme disease. Unlike some other vectorborne diseases, tick-borne disease patterns are generally less influenced by short-term changes in
weather (weeks to months) than by longer-term climate change.
Other factors that affect the number of Lyme disease cases include changes in the populations of host
species (particularly deer), which affect tick population size. The percentage of ticks that are infected
depends on the prevalence and infection rates of white-footed mice and certain other hosts. Host
species populations and habitats can be affected by climate change and other ecosystem disturbances.
Human exposure to infected ticks is also influenced by multiple factors, including changes in the
proximity of human populations to ticks and other hosts, increased awareness of Lyme disease, and
modified behaviors, such as spending less time outdoors, taking precautions against being bitten, and
checking more carefully for ticks.

About the Indicator
This indicator looks at the incidence of Lyme disease, which reflects the rate of new cases contracted in
a given geographic area and time period. Incidence is typically calculated as the number of cases per
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 Climate Change Indicators in the United States: Lyme Disease
www.epa.gov/climatechange/indicators - Updated May 2014

100,000 people per year. Annual Lyme disease totals and rates for each state were provided by the
Centers for Disease Control and Prevention. The original data were collected by state and local health
departments, which track confirmed cases of Lyme disease that are diagnosed by health care providers
and report these cases to the National Notifiable Diseases Surveillance System. Nationwide reporting of
Lyme disease began in 1991.
Figure 1 shows the national incidence of Lyme disease since 1991, and Figure 2 shows trends in
incidence over time in 14 states that collectively account for about 95 percent of the nation’s reported
cases. To provide a simple illustration of changes over time, example maps show the distribution of
reported cases in the years 1996 and 2012.

Key Points
•

The incidence of Lyme disease in the United States has approximately doubled since 1991, from
3.74 reported cases per 100,000 people to 7.01 reported cases per 100,000 people in 2012 (see
Figure 1).

•

Among the states where Lyme disease is most common, New Hampshire and Delaware have
experienced the largest increases in reported case rates since 1991, followed by Maine,
Vermont, and Massachusetts. On average, these five states now report 50 to 90 more cases per
100,000 people than they did in 1991 (see Figure 2).

•

Driven by multiple factors, the number and distribution of reported cases of Lyme disease
appear to be increasing over time (see example maps).

2

 Climate Change Indicators in the United States: Lyme Disease
www.epa.gov/climatechange/indicators - Updated May 2014

This figure shows the annual incidence of Lyme disease, which is calculated as the number of new cases
per 100,000 people. The graph is based on cases that local and state health departments report to CDC’s
national disease tracking system.
Data source: CDC, 2014 6

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 Climate Change Indicators in the United States: Lyme Disease
www.epa.gov/climatechange/indicators - Updated May 2014

This map shows how reported Lyme disease incidence has changed by state since 1991, based on the
number of new cases per 100,000 people. The total change has been estimated from the average annual
rate of change in each state. This map is limited to the 14 states where Lyme disease is most common,
where annual rates are consistently above 10 cases per 100,000. Connecticut, New York, and Rhode
Island had too much year-to-year variation in reporting practices to allow trend calculation.
Data source: CDC, 2014 7

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 Climate Change Indicators in the United States: Lyme Disease
www.epa.gov/climatechange/indicators - Updated May 2014

These maps show the distribution of reported cases of Lyme disease in 1996 and 2012. Each dot
represents an individual case placed according to the patient’s county of residence, which may be
different than the county of exposure. The year 1996 was chosen as a reasonable starting point for
comparison with recent years. These maps focus on the parts of the United States where Lyme disease is
most common.
Data source: CDC, 2014 8

Indicator Notes
For consistency, this indicator only includes data for confirmed cases of Lyme disease that are reported
to CDC, not cases that are considered “probable.” Changes in diagnosing practices and awareness of the
disease over time can affect trends. Cases are reported based on the patient’s county of residence,
which is not necessarily the place where they were infected. Risk of infection is focused in certain
regions of the country, and confirmed reports from low-incidence states are often the result of travel to
an area of higher incidence. Evidence suggests that expanding ranges of ticks in certain northern states
may be more related to a warming climate than expanding ranges in southern states. 9,10 However,
because of the many factors affecting tick populations and reporting of Lyme disease, this indicator does
not provide sufficient information to determine what proportion of the observed changes in Lyme
disease incidence is directly driven by climate change. Further study is critical to improving the
usefulness of this indicator and informing decisions affecting public health. For information on
prevention, symptoms, and treatment of Lyme disease, see: www.cdc.gov/lyme.

Data Sources
All three figures are based on publicly available Lyme disease data compiled by the Centers for Disease
Control and Prevention at: www.cdc.gov/lyme/stats/index.html. Incidence was calculated using midyear population estimates from the U.S. Census Bureau. 11

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 Climate Change Indicators in the United States: Lyme Disease
www.epa.gov/climatechange/indicators - Updated May 2014

1

CDC (Centers for Disease Control and Prevention). 2014. Lyme disease data and statistics.
www.cdc.gov/lyme/stats/index.html. Accessed January 2014.

2

CDC (Centers for Disease Control and Prevention). 2013. CDC provides estimate of Americans diagnosed with
Lyme disease each year. www.cdc.gov/media/releases/2013/p0819-lyme-disease.html.

3

Leighton, P.A., J.K. Koffi, Y. Pelcat, L.R. Lindsay, and N.H. Ogden. 2012. Predicting the speed of tick invasion: An
empirical model of range expansion for the Lyme disease vector Ixodes scapularis in Canada. J. Appl. Ecol. 49(2):
457-464.

4

Leighton, P.A., J.K. Koffi, Y. Pelcat, L.R. Lindsay, and N.H. Ogden. 2012. Predicting the speed of tick invasion: An
empirical model of range expansion for the Lyme disease vector Ixodes scapularis in Canada. J. Appl. Ecol. 49(2):
457-464.

5

Süss, J., C. Klaus, F.-H. Gerstengarbe, and P.C. Werner. 2008. What makes ticks tick? Climate change, ticks, and
tick-borne diseases. J. Travel Med. 15(1):39-45.

6

CDC (Centers for Disease Control and Prevention). 2014. Lyme disease data and statistics.
www.cdc.gov/lyme/stats/index.html. Accessed January 2014.

7

CDC (Centers for Disease Control and Prevention). 2014. Lyme disease data and statistics.
www.cdc.gov/lyme/stats/index.html. Accessed January 2014.

8

CDC (Centers for Disease Control and Prevention). 2014. Lyme disease data and statistics.
www.cdc.gov/lyme/stats/index.html. Accessed January 2014.

9

Diuk-Wasser, M.A., A.G. Hoen, P. Cislo, R. Brinkerhoff, S.A. Hamer, M. Rowland, R. Cortinas, G. Vourc'h, F.
Melton, G.J. Hickling, J.I. Tsao, J. Bunikis, A.G. Barbour, U. Kitron, J. Piesman, and D. Fish. 2012. Human risk of
infection with Borrelia burgdorferi, the Lyme disease agent, in eastern United States. Am. J. Trop. Med. Hyg.
86(2):320–327.

10

Stromdahl, E.Y., and G.J. Hickling. 2012. Beyond Lyme: Aetiology of tick-borne human diseases with emphasis on
the south-eastern United States. Zoonoses Public Hlth. 59(Supplement 2):48–64.

11

U.S. Census Bureau. 2013. Population estimates: Intercensal estimates. Accessed December 5, 2013.
www.census.gov/popest/data/intercensal/index.html.

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