MODELS FOR PREDICTING AEDES AEGYPTI LARVAL INDICES BASED ON SATELLITE IMAGES AND CLIMATIC VARIABLES

ELIZABET L. ESTALLO; MARIO A. LAMFRI; CARLOS M. SCAVUZZO; FRANCISCO F. LUDUEÑA ALMEIDA, MARIO ZAIDENBERG, WALTER R. ALMIRÓN; MARÍA V. INTROINI; MARIO ZAIDENBERG; WALTER R. ALMIRÓN

JOURNAL OF THE AMERICAN MOSQUITO CONTROL ASSOCIATION

Allen Press

Lugar: Lawrence; Año: 2008 vol. 24 p. 368 - 376

8756-971X

Forecasting Models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (Tartagal and Orán cities, northwestern Argentina), based on the Breteau and House indices, and environmental variables considered with and without time lags. Descriptive Models were first developed for each city and each index by multiple linear regressions, followed by a Regional Model including both cities together. Finally, two Forecasting Regional Models were developed and evaluated. Forecasting Regional Model2 for Breteau index and House index fit the data significantly better than Forecasting Regional Model1. Evaluating these models, a higher correlation was observed for Forecasting Regional Model1 than Forecasting Regional Model2 for Breteau index (r = 0.83 and 0.62 for 3 months, r = 0.86 and 0.67 for 45 days, respectively) and House index (r = 0.85 and 0.79 for 3 months, r = 0.79 and 0.74 for 45 days, respectively). Early warning based on these forecasting models can assist health authorities to improve vector control.