Model-based predictions of mosquito species distribution need to be improved in many parts of the country, researchers at the University of Colorado Boulder found.
Researchers assessed and combined previously developed computational models to generate new predictions of where Aedes aegypti and Aedes albopictus mosquitoes could be found in every county in the contiguous United States. The species transmit chikungunya, dengue, yellow fever, and Zika viruses.
The models were then compared to estimates from real-world mosquito collection data. Researchers discovered that despite the relatively high availability of mosquito data, existing models have gaps that were not previously been identified.
Researchers also discovered that high uncertainty in models in regions likely to be borderline habitats for the species and other models appeared to be biased.
The findings mean improved models and additional data are needed to understand the range of mosquito species and the risk of disease transmission.
“By comparing analytical models and data, we identified key gaps in mosquito surveillance data and models,” Michael Johansson, the study’s senior author, said. “Understanding those limitations helps us to be better prepared for infectious disease threats today and to focus on key needs to be even better prepared tomorrow.”
The researchers are in the process of organizing an ongoing collaborative project to collect more mosquito data and analyze new models.