Advances in using Internet searches to track dengue

TL;DR

This paper extends a Google search-based model originally for flu to estimate dengue cases in five countries, demonstrating its potential to enhance real-time dengue surveillance globally.

Contribution

It adapts and validates a search trend-based framework for dengue, improving real-time tracking across multiple countries.

Findings

Model accurately estimates dengue activity in five regions.

Search trends correlate strongly with reported dengue cases.

Framework can be used for timely public health responses.

Abstract

Dengue is a mosquito-borne disease that threatens more than half of the world's population. Despite being endemic to over 100 countries, government-led efforts and mechanisms to timely identify and track the emergence of new infections are still lacking in many affected areas. Multiple methodologies that leverage the use of Internet-based data sources have been proposed as a way to complement dengue surveillance efforts. Among these, the trends in dengue-related Google searches have been shown to correlate with dengue activity. We extend a methodological framework, initially proposed and validated for flu surveillance, to produce near real-time estimates of dengue cases in five countries/regions: Mexico, Brazil, Thailand, Singapore and Taiwan. Our result shows that our modeling framework can be used to improve the tracking of dengue activity in multiple locations around the world.