Back

Temporal models using environmental variables to predict Aedes aegypti oviposition activity in a temperate region of Argentina.

Benitez, E. M.; Estallo, E. L.; Grech, M.; Frias-Cespedes, M.; Almiron, W. R.; Luduena-Almeida, F. F.

2019-10-23 ecology
10.1101/816421 bioRxiv
Show abstract

Environmental variables are some of the factors that more impact on Aedes aegypti, vector of Dengue, Chikungunya and Zika viruses. In this study, the Ae. aegypti oviposition activity was related to satellite and meteorological variables, in Cordoba City (Argentina). Eggs were collected using ovitraps placed throughout the city from 2009 to 2012, replaced them weekly. Generalized Linear Mixed Models were developed with negative binomial distributions of errors, modeling average number of eggs collected weekly as a function of satellite and meteorological variables with time lags. The best model included a vegetation index, vapor pressure of water, precipitation and photoperiod, lagged between 3 and 4 weeks. By each increment unit in vegetation index, vapor pressure (hPa) and light hour, the average number of eggs increases by 72%, 20% and 29%, respectively, in the following 3 or 4 weeks. In addition, the average number of eggs decreases a 50% in the following month by each millimeter of rain. The results evince the relevant importance of the vegetation, maybe due to the shade that provide to the containers as breeding habitat of this species and the shelter for adults. On the other hand, the negative effect of precipitation could be a consequence of abundant rainfalls that fulfill containers avoiding females to lay eggs in there. Although no significant effect of the photoperiod on the vector abundance has been detected in the north of the country, in Cordoba City an important effect is observed when it is presented together with other variables, producing different effects of these variables in different regions. Lastly, it is necessary to emphasize the importance of the minimum temperature in temperate zones, since it would be a limiting factor that prevents the Ae. aegypti oviposition activity.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.