Effectiveness of normalized difference water index in modelling Aedes aegypti house index

Abstract

The application of remotely sensed data to public health has increased in Argentinain the past few years, especially to study vector-borne viral diseases such as dengue.The normalized difference vegetation index (NDVI) has been widely used for 15remote sensing of vegetation as well as the brightness temperature for many years.Another environmental variable obtained from satellites is the normalized differencewater index (NDWI) for remote sensing of the status of the vegetationliquid water from space. The aim of the present article was to test the effectivenessof NDWI together with other satellite and meteorological data to develop two 20forecasting models, namely, the SATMET (satellite and meteorological variables)model and the SAT (satellite environmental variables) model. The models weredeveloped and validated by dividing the data file into two sets: the data betweenJanuary 2001 and April 2004 were used to construct the models and the databetween May 2004 andMay 2005 were used to validate them. The regression anal- 25ysis for the SATMET and SAT models showed an adjusted R2 of 0.82 and 0.79,respectively. To validate the models, a correlation between the estimates and theobservations was obtained for both the SATMET model (r = 0.57) and the SATmodel (r = 0.64). Both models showed the same rootmean square error (RMSE) of0.04 and, therefore, the same forecasting power. For this reason, these models may 30have applications as decision support tools in assisting public health authorities inthe control of Aedes aegypti and risk management planning programmes.