Artículos de revistas
Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
Fecha
2008-09Registro en:
Estallo, Elizabet Lilia; Lamfri, Mario; Scavuzzo, Carlos Marcelo; Ludueña Almeida, Francisco; Introini, María V.; et al.; Models for predicting aedes aegypti larval indices based on satellite images and climatic variables; American Mosquito Control Association; Journal of the American Mosquito Control Association; 24; 3; 9-2008; 368-376
8756-971X
CONICET Digital
CONICET
Autor
Estallo, Elizabet Lilia
Lamfri, Mario
Scavuzzo, Carlos Marcelo
Ludueña Almeida, Francisco
Introini, María V.
Zaidenberg, Mario
Almiron, Walter Ricardo
Resumen
Forecasting models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (cities of Tartagal and Orn, 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 (FRM) were developed and evaluated. FRM2 for the Breteau index and House index fit the data significantly better than FRM1. An evaluation of these models showed a higher correlation FRM1 than for FRM2 for the Breteau index (R 0.83 and 0.62 for 3 months; R 0.86 and 0.67 for 45 days) and the House index (R 0.85 and 0.79 for 3 months; R 0.79 and 0.74 for 45 days). Early warning based on these forecasting models can assist health authorities to improve vector control. © 2008 by The American Mosquito Control Association, Inc.