Infectious disease epidemiology under meteorological factors: A review of mathematical models and an extended SEIR framework

Source abstract

Mathematical modeling can perform a decisive task in understanding, controlling, and preventing the transmission of infectious diseases by forecasting their spread, estimating the effectiveness of intervention measures, and updating public health policies. A mathematical epidemic model is a vital tool that can mock up the spread of infections under different scenarios and environments, allowing researchers to test and refine their understanding of the fundamental mechanisms. This paper attempts to review some existing mathematical compartmental epidemic models and explore the impact of meteorological factors such as air temperature, humidity, and wind speed on epidemiology. The goal is to identify and categorize key components, research trends, major findings, and gaps within the models. Additionally, the paper discusses some strategies to address these gaps and proposes a compartmental augmentation of the SEIR model incorporating meteorological factors for further work.