VEMS Vector-borne epidemic models and simulator

One objective of this project is to create an interactive software that can simulate the dynamics of mosquito populations under various control methods. The software allows the user to input the relevant data regarding the mosquitoes life cycle, such as development periods, and to define the interaction of different vector populations. It also accepts information about the environment, for instance the number of breeding sites and their spatial distribution. After defining the mosquito and its environment, the user will be able to run simulations evaluating the efficacy of various mosquito management methods and assess their effectiveness. Since the mosquito lifecycle parameters are temperature dependent, the simulation uses temperature data which can either be provided by the user or accessed from a database used by the software. In addition to assessing the control measures, the software can be used to simulate the diffusion of mosquitoes, and transmission of disease to human or other hosts. To this end, the user can define the transmission model and diffusion mechanisms, add other layers of data such as host population distribution and simulate the system. To make the software user friendly, we add predefined transmission models, mosquitoes and diffusion mechanisms in addition to database including human population density and temperature for different locations. This enables the user to simulate the system with minimal inputs.

Another objective of this research is to develop accurate network-based transmission models. Such models not only improve vector-borne disease transmission models but also advance the modeling of direct virus transmission among individuals such as with monkey pox, vesicular stomatitis virus, or some routes of pig-to-pig Japanese encephalitis virus transmission. Traditionally, virus transmission models have been analyzed using ordinary differential equations that assume homogeneous mixing of populations. However, in real-world scenarios, the interactions among different components of the transmission system are heterogeneous. While, there are mean field network models that consider heterogeneity in transmission components, due to the stochastic nature of transmissions, such models cannot accurately describe real-world transmission. Often, simplifying transmission models can result in overestimating the course of an epidemic when compared to the exact simulation of the process. In fact, we have witnessed such overestimations in the case of COVID spread. As individuals decrease the number of contacts, the viable paths for virus transmission change, leading to discrepancies between the outputs of transmission models that do not account for the sparse nature of contact networks.

Duration July 1, 2023- June 30, 2024

Investigator

Faculty

Aram Vajdi (PI)

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Data

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