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ISDS 2012 Conference Abstracts

Using Google Dengue Trends to Estimate Climate
Effects in Mexico
Rebecca T. Gluskin*1, Mauricio Santillana2 and John S. Brownstein1, 3

1Boston Children’s Hospital, Boston, MA, USA; 2Harvard School of Engineering and Applied Sciences, Cambridge, MA, USA;
3Department of Pediatrics, Harvard Medical School, Boston, MA, USA

Objective
To evaluate the association between Dengue Fever (DF) and cli-

mate in Mexico with real-time data from Google Dengue Trends
(GDT) and climate data from NASA Earth observing systems.

Introduction
The incidence of dengue fever (DF) has increased 30 fold between

1960 and 2010 [1]. The literature suggests that temperature plays a
major role in the life cycle of the mosquito vector and in turn, the
timing of DF outbreaks [2]. We use real-time data from GDT and
real-time temperature estimates from NASA Earth observing systems
to examine the relationship between dengue and climate in 17 Mex-
ican states from 2003-2011. For the majority of states, we predict that
a warming climate will increase the number of days the minimum
temperature is within the risk range for dengue.

Methods
The GDT estimates are derived from internet search queries and

use similar methods as those developed for Google Flu Trends [3]. To
validate GDT data, we ran a correlation between GDT and dengue
data from the Mexican Secretariat of Health (2003-2010). To analyze
the relationship between GDT and varying lags of temperature, we
constructed a time series meta-analysis. The mean, max and min of
temperature were tested at lags 0 -12 weeks using data from the Mod-
ern Era Retrospective-Analysis for Research and Applications. Fi-
nally, we built a binomial model to identify the minimum 5° C
temperature range associated with a 50% or higher Dengue activity
threshold as predicted by GDT.

Results
The time series plot of GDT data and the Mexican Secretariat of

Health data (2003- 2010) (Figure 1) produced a correlation coeffi-
cient of 0.87. The time series meta-analysis results for 17 states
showed an increase in minimum temperature at lag week 8 had the
greatest odds of dengue incidence, 1.12 Odds Ratio (1.09-1.16, 95%
Confidence Interval). The comparison of dengue activity above 50%
in each state to the minimum temperature at lag week 8 showed 14/17
states had an association with warmest 5 degrees of the minimum
temperature range. The state of Sonora was the only state to show an
association between dengue and the coldest 5 degrees of the mini-
mum temperature range.

Conclusions
Overall, the incidence data from the Mexican Secretariat of Health

showed a close correlation with the GDT data. The meta-analysis in-
dicates that an increase in the minimum temperature at lag week 8 is
associated with an increased dengue risk. This is consistent with the
Colon-Gonzales et al. Mexico study which also found a strong asso-
ciation with the 8 week lag of increasing minimum temperature [4].
The results from this binomial regression show, for the majority of
states, the warmest 5 degree range for the minimum temperature had

the greatest association with dengue activity 8 weeks later. Inevitably,
several other factors contribute to dengue risk which we are unable
to include in this model [5]. IPCC climate change predictions sug-
gest a 4° C increase in Mexico. Under such scenario, we predict an
increase in the number of days the minimum temperature falls within
the range associated with DF risk.

Figure 1. Time Series Correlation: Google Dengue Trends vs. Secretariat of
Health, Mexico 2003-2010

Keywords
Time Series; Mexico; Google Dengue Trends; Climate Change;
Meta-analysis

Acknowledgments

Funded by the NIH Grant # 1R01LM010812-01 and the Applied Public
Health Informatics Fellowship Program administered by CSTE and
funded by the Centers for Disease Control and Prevention (CDC) Coop-
erative Agreement 3U38HM000414-04W1.

References

1.(WHO), W.H.O., Dengue. 2010.
2.Yang, H.M., et al., Assessing the effects of temperature on the popula-

tion of Aedes aegypti, the vector of dengue. Epidemiol Infect, 2009.
137(8): p. 1188-202.

3.Chan, E.H., et al., Using web search query data to monitor dengue epi-
demics: a new model for neglected tropical disease surveillance. PLoS
Negl Trop Dis, 2011. 5(5): p. e1206.

4.Colon-Gonzalez, F.J., I.R. Lake, and G. Bentham, Climate variability
and dengue fever in warm and humid Mexico. Am J Trop Med Hyg,
2011. 84(5): p. 757-63.

5.Thai, K.T. and K.L. Anders, The role of climate variability and change
in the transmission dynamics and geographic distribution of dengue.
Exp Biol Med (Maywood), 2011. 236(8): p. 944-54.

*Rebecca T. Gluskin
E-mail: rgluskin@health.nyc.gov

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e94, 2013