Mathematical modeling can perform a deci-sive task in understanding, controlling, and preventingthe transmission of infectious diseases by forecastingtheir spread, estimating the effectiveness of interventionmeasures, and updating public health policies. A math-ematical epidemic model is a vital tool that can mockup the spread of infections under different scenariosand environments, allowing researchers to test and refinetheir understanding of the fundamental mechanisms. Thispaper attempts to review some existing mathematicalcompartmental epidemic models and explore the impact ofmeteorological factors such as air temperature, humidity,and wind speed on epidemiology. The goal is to identifyand categorize key components, research trends, majorfindings, and gaps within the models. Additionally, thepaper discusses some strategies to address these gapsand proposes a compartmental augmentation of the SEIRmodel incorporating meteorological factors for furtherwork
Subedi et al. (2025) studied this question.