PLoS ONE (Jan 2015)

Weather Variability Associated with Aedes (Stegomyia) aegypti (Dengue Vector) Oviposition Dynamics in Northwestern Argentina.

  • Elizabet L Estallo,
  • Francisco F Ludueña-Almeida,
  • María V Introini,
  • Mario Zaidenberg,
  • Walter R Almirón

DOI
https://doi.org/10.1371/journal.pone.0127820
Journal volume & issue
Vol. 10, no. 5
p. e0127820

Abstract

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This study aims to develop a forecasting model by assessing the weather variability associated with seasonal fluctuation of Aedes aegypti oviposition dynamic at a city level in Orán, in northwestern Argentina. Oviposition dynamics were assessed by weekly monitoring of 90 ovitraps in the urban area during 2005-2007. Correlations were performed between the number of eggs collected weekly and weather variables (rainfall, photoperiod, vapor pressure of water, temperature, and relative humidity) with and without time lags (1 to 6 weeks). A stepwise multiple linear regression analysis was performed with the set of meteorological variables from the first year of study with the variables in the time lags that best correlated with the oviposition. Model validation was conducted using the data from the second year of study (October 2006- 2007). Minimum temperature and rainfall were the most important variables. No eggs were found at temperatures below 10 °C. The most significant time lags were 3 weeks for minimum temperature and rains, 3 weeks for water vapor pressure, and 6 weeks for maximum temperature. Aedes aegypti could be expected in Orán three weeks after rains with adequate min temperatures. The best-fit forecasting model for the combined meteorological variables explained 70 % of the variance (adj. R(2)). The correlation between Ae. aegypti oviposition observed and estimated by the forecasting model resulted in rs = 0.80 (P < 0.05). The forecasting model developed would allow prediction of increases and decreases in the Ae. aegypti oviposition activity based on meteorological data for Orán city and, according to the meteorological variables, vector activity can be predicted three or four weeks in advance.