[SS05] Data and model driven - study on infectious diseases modelling

[SS05-01] Integrating dynamic models and neural networks to discover the mechanism of meteorological factors on Aedes population

*Xia Wang¹ (1. Shaanxi Normal University (China))

Keywords:

Aedes mosquitoes,dynamic model,environmental factors

Aedes albopictus is known for transmitting a variety of mosquito-borne diseases and poses a major threat to public health and safety. Due to complex interactions between biological mechanisms and environmental factors, modeling Aedes albopictus population dynamics requires an integrated approach. In this study, we built a model coupling differential equations with neural networks to simulate the dynamics of mosquito populations, and explored the relationship between oviposition rate, temperature, and precipitation through neural networks. By integrating the traditional dynamic model with machine learning, our model can adhere to specific biological mechanisms while extracting patterns from data, thus enhancing its interpretability in biology. Our approach provides both accurate modeling and an avenue for uncovering potential unknown biological mechanisms.