Advancing Mathematical Models of Mosquito-Borne Diseases

Dear Colleagues,

Mosquito-borne diseases are a significant global health burden. The incidence and global distribution of some mosquito-borne diseases have increased substantially in the past two decades, driven by urbanization, increased global travel, and changes in climate, among other factors. Mathematical models have proven to be a useful tool for studying the epidemiology of infectious diseases as they provide a framework to describe the complex interactions and characterize feedback between groups in dynamic systems. There is an increasing need for improved models to better understand the complex transmission processes that drive disease spread and better inform and optimize disease mitigation efforts.

Mosquito-borne disease dynamics are often complicated by interactions between environmental factors, meteorological changes, population dynamic processes, anthropogenic interactions, and more across multiple temporal and spatial scales. Mathematical models that consider these factors can help us to better understand the mosquito population dynamics and what drives mosquito-borne disease spread. Furthermore, mathematical models provide quantitative and qualitative assessments for potential control measures. Many mosquito-borne diseases lack pharmaceutical interventions, so most mosquito-borne disease control relies on controlling the vector population and preventing the vector population from interacting with hosts. Traditional control via source reduction and application of insecticides has not been sufficient to eliminate some mosquito-borne diseases, and substantial progress has been made in developing novel control measures, such as releasing genetically or biologically modified mosquitoes into wild populations to reduce wild populations or replace them with mosquitoes incapable of transmitting diseases.

This Special Issue is dedicated to examining mathematical models of mosquito-borne diseases and control measures.  We hope to feature models that integrate ecological and epidemiological dynamics across different scales to understand the mechanisms underlying disease spread and mitigation.

Dr. Michael A. Robert
Dr. Zhuolin Qu
Dr. Nick W. Ruktanonchai
Guest Editors

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