Forecasting of Cases for Climate Sensitive Mosquito-Borne Diseases Using Online/Social Media Information

• Activity Number: 691
• Type: Topic Contributed
• Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Lilia Leticia Ramirez Ramirez* and Yulia R. Gel and Vyacheslav Lyubchich
• Companies: Centro de Investigacion en Matematicas and The University of Texas at Dallas and University of Maryland Center for Environmental Science
• Keywords: vector epidemic model ; climate sensitive infections ; bio surveillance ; social media ; time series

Abstract

Climate-sensitive viruses threaten not just a single state or a country, but whole macro-regions and continents. In summer 2014 Mexico reported the first confirmed case of mosquito-borne chikungunya virus. Since then, spread of the virus across North and Central America has been attracting a lot of attention from the health care professionals. Since data on new diseases in America as zika and chikungunya are scarce and the virus is transmitted by the same type of mosquito as dengue, we use Google Dengue Trend in Mexico as a proxy for the current estimate of chikungunya epidemiological situation in the neighboring countries. We analyze the Google Dengue Trends in the states of Mexico to unveil their possible common characteristics with available chikungunya data, which abet or hinder the virus spread. We then develop a time series model for predicting chikungunya epidemiological curve (i.e., location and intensity of spike), using Google Dengue Trend as an exogenous covariate.