Abstract

Traditional epidemiological models for managing disease risk face serious hurdles when applied to complex life-cycle parasites that involve several host species. Echinococcus multilocularis (Em) is such a parasite and the aetiological agent of a serious zoonosis, Alveolar Echinococcosis, affecting thousands of people every year worldwide. The parasite is transmitted through predation of infectious intermediate hosts (rodents) by definitive hosts (foxes, coyotes). Definitive hosts are usually territorial with individual home ranges in spatially heterogeneous urban landscapes, where they carry very diverse parasite load, thus creating a highly heterogeneous distribution of the parasite in the urban environment. To incorporate individual differences and spatial heterogeneity into an epidemiological model, we developed Calgary Echinococcus multilocularis Coyote Agent-based model (CEmCA).The CEmCA was developed to understand the processes and mechanisms that produces the heterogeneity in the transmission of Em. The model simulates behaviors of individual coyotes inhabiting the City of Calgary as agents, reproducing behavioral patterns such as their home ranges, where and which prey species they hunt, where they defecate, and how they transmit Em. The agents perform all its behaviors in a simulation landscape that represent an actual Calgary landscape that includes maps of natural habitats and small mammal assemblages.The CEmCA proved to be highly sensitive to unobservable epidemiological parameters, and although not fully matching the observed patterns it provided useful insights into the epidemiological processes of Em. Moreover, our experimental simulations supported the hypothesis that distribution of intermediate hosts and separation of habitats were the main causes of spatial heterogeneity in infection.By integrating individual differences and spatial heterogeneity this study contributed to the understanding of the epidemiology of trophically transmitted parasite with complex life-cycles. Notwithstanding requiring further work, this approach holds many promises for further applications in preventative management of infectious diseases in urban landscapes.

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