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Background: Approximately 40 countries in Central and South America have experienced local vector-born transmission of Zika virus, resulting in nearly 300,000 total reported cases of Zika virus disease to date. Of the cases that have sought care thus far in the region, more than 70,000 have been reported out of Colombia.

Objective: In this paper, we use nontraditional digital disease surveillance data via HealthMap and Google Trends to develop near real-time estimates for the basic (R 0) and observed (R obs) reproductive numbers associated with Zika virus disease in Colombia. We then validate our results against traditional health care-based disease surveillance data.

Methods: Cumulative reported case counts of Zika virus disease in Colombia were acquired via the HealthMap digital disease surveillance system. Linear smoothing was conducted to adjust the shape of the HealthMap cumulative case curve using Google search data. Traditional surveillance data on Zika virus disease were obtained from weekly Instituto Nacional de Salud (INS) epidemiological bulletin publications. The Incidence Decay and Exponential Adjustment (IDEA) model was used to estimate R 0 and R obs for both data sources.

Results: Using the digital (smoothed HealthMap) data, we estimated a mean R 0 of 2.56 (range 1.42-3.83) and a mean R obs of 1.80 (range 1.42-2.30). The traditional (INS) data yielded a mean R 0 of 4.82 (range 2.34-8.32) and a mean R obs of 2.34 (range 1.60-3.31).

Conclusions: Although modeling using the traditional (INS) data yielded higher R 0 estimates than the digital (smoothed HealthMap) data, modeled ranges for R obs were …