MODIS environmental data to assess Chikungunya, Dengue and Zika diseases through Aedes (Stegomia) aegypti oviposition activity estimation

Abstract

Aedes aegypti is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a main threat for our region. Taking into account this situation, several efforts have been done to use remote sensing to support public health decision making. Moderate resolution imaging spectroradiometer (MODIS) sensor provides moderate-resolution remote sensing products; therefore, we explore the application of MODIS products to vector-borne disease problems in Argentina. We develop temporal forecasting models of Ae. aegypti oviposition, and we include its validation and its application to the 2016 Dengue outbreak. Temporal series (10/2005 to 09/2007) from MODIS products of normalized difference vegetation index and diurnal land surface temperature were built. Two linear regression models were developed: model 1 which uses environmental variables with time lag and model 2 uses environmental variables without time lags. Model 2 was the best model (AIC = 112) with high correlation (r = 0.88, p < 0.05) between observed and predicted data. We can suggest that MODIS products could be a good tool for estimating both Ae. aegypti oviposition activity and risks for Ae. aegypti-borne diseases. That statement is also supported by model results for 2016 when a dengue outbreak that started unusually earlier this season. If such activity could be forecast by a model based on remote sensing data, then a potential outbreak could be predicted.