Dynamic Forecasting of Zika Epidemics Using Google Trends

Yue Teng, Dehua Bi, Guigang Xie, Yuan Jin, Yong Huang, Baihan Lin, Xiaoping An, Dan Feng and Yigang Tong

PLOS ONE, 2017, vol. 12, issue 1, 1-10

Abstract: We developed a dynamic forecasting model for Zika virus (ZIKV), based on real-time online search data from Google Trends (GTs). It was designed to provide Zika virus disease (ZVD) surveillance and detection for Health Departments, and predictive numbers of infection cases, which would allow them sufficient time to implement interventions. In this study, we found a strong correlation between Zika-related GTs and the cumulative numbers of reported cases (confirmed, suspected and total cases; p

Date: 2017
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0165085

DOI: 10.1371/journal.pone.0165085

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