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1.
Figure 3

Figure 3. Geographic variation of state-level covariates.. From: Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends.

The covariates most highly associated with GDT accuracy () were average annual dengue cases (A), average annual precipitation (B), mean temperature (C) and maximum temperature (D).

Rebecca Tave Gluskin, et al. PLoS Negl Trop Dis. 2014 Feb;8(2):e2713.

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2.
Figure 2

Figure 2. Observed and model-estimated R2 for GDT and reported dengue cases.. From: Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends.

Darker shading indicates a higher coefficient of determination between GDT and traditional surveillance data from observed data (A) and for predictions from the model using maximum temperature, precipitation and the interaction of those two variables (B).

Rebecca Tave Gluskin, et al. PLoS Negl Trop Dis. 2014 Feb;8(2):e2713.

CitationFull text

3.
Figure 1

Figure 1. Time Series of monthly reported cases and Google Dengue Trends, Mexico.. From: Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends.

2003–2011. The number of cases reported by the Secretariat of Health is shown on the left axis (black) and the GDT index on the right (blue). The correlation coefficient between reported dengue cases and GDT was 0.91 over the 9 years, indicating that GDT captured approximately 83% of the variability in the national surveillance data.

Rebecca Tave Gluskin, et al. PLoS Negl Trop Dis. 2014 Feb;8(2):e2713.

CitationFull text

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