Agent-based modelling of West Nile virus propagation in southern Manitoba, Canada
Nasrinpour, Hamid Reza
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This research addresses the design and development of a data-driven Agent-Based Modelling (ABM) framework to simulate transmission and spread of West Nile Virus (WNV) among heterogeneous mobile humans, various bird species, and Culex genus mosquitoes over a geographic region at a province-scale. A diverse variety of topics and techniques regarding the data collection phase is presented, as modelling WNV has many disparate attributes. WNV is a mosquito-borne disease influenced by avian species as their amplifying hosts. A significant amount of data, such as home range, flight speed, WNV competence index, etc., regarding over 150 bird species along with their population estimates and locations in Manitoba, Canada are estimated and assembled. The primary contribution of this thesis is the development and validation of a data-driven Cellular Difference Equation (CDiffE) scheme for adoption in WNV-ABMs or other mosquito-borne disease ABMs. The migration patterns of different bird species, nocturnal biting activities of Culex mosquitoes, daily temperature and rainfall, and land cover impact are incorporated into the CDiffE model. The CDiffE model at its core employs difference equations, which are computationally faster than commonly used differential equation models. The proposed CDiffE model is cellular to capture heterogeneity of various geographical areas. The CDiffE has been rigorously verified and validated. While the whole system is designed from an ABM perspective at a cellular level, it exhibits biologically compatible behaviour at the macro-level scale. The proposed CDiffE demonstrates high accuracy in predicting real-world mosquito population trends and geographical distributions, evidenced by the mosquito trap data from Manitoba. The proposed CDiffE model updates on an hourly step to act as an environment for a comprehensive ABM of WNV spread among peripatetic humans. Such a hybrid ABM is successfully built on top of the proposed CDiffE scheme to study the impact of human movements on the prevalence of the virus. The human movement component is modeled on data available from cell phone trajectories as well as census and demographic datasets. Simulation results clearly illustrate the importance of human movement patterns and demonstrate the need for real-world data. Yet human mobility is often disregarded within current WNV modeling efforts.