Journal Article

Faster indicators of chikungunya incidence using Google searches

Mizzi, Giovanni, Bastos, Leonardo Soares, Miller, Sam, Moat, Helen Susannah, Coelho, Flávio Codeço, Preis, Tobias, Gomes, Marcelo Ferreira da Costa, Codeço, Claudia Torres

2022

Overview

Chikungunya, a mosquito-borne disease, is a growing threat in Brazil, where over 640,000 cases have been reported since 2017. However, there are often long delays between diagnoses of chikungunya cases and their entry in the national monitoring system, leaving policymakers without the up-to-date case count statistics they need. In contrast, weekly data on Google searches for chikungunya is available with no delay. Here, we analyse whether Google search data can help improve rapid estimates of chikungunya case counts in Rio de Janeiro, Brazil. We build on a Bayesian approach suitable for data that is subject to long and varied delays, and find that including Google search data reduces both model error and uncertainty. These improvements are largest during epidemics, which are particularly important periods for policymakers. Including Google search data in chikungunya surveillance systems may therefore help policymakers respond to future epidemics more quickly.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Animals / Bayes Theorem / Brazil - epidemiology / Chikungunya fever / Chikungunya Fever - epidemiology / Chikungunya virus / Database searching / Forecasts and trends / Incidence / Internet/Web search services / Medicine and Health Sciences / Methods / Online searching / People and places / Physical Sciences / Search Engine