A machine learning-based algorithm can precisely forecast microclimatic temperature within breeding grounds of Aedes albopictus mosquitoes, showing that the insects can thrive even in winter.
Michael Barnes of Texas A&M University (TAMU) said these mathematical models "can greatly facilitate a quick assessment of mosquito populations and consequently, vector-borne disease transmission."
TAMU researchers installed sensors in mosquito breeding grounds around Houston, and trained the algorithm on information on ambient temperatures from the U.S. National Oceanic and Atmospheric Administration.
The model could predict microclimatic temperatures for diverse ambient temperatures and breeding grounds within 1.5 degrees centigrade, as well as anticipating local temperatures for any ambient temperature.
The researchers fed the values of the microclimatic temperatures to a population dynamic model, enabling it to calculate mosquito populations at different lifecycle stages, and to demonstrate that large numbers could survive the winter in storm drains.
From Texas A&M Today
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