Simulation modeling of zoonotic diseases between swine and human populations for informing policy decisions

摘要

Approximately 60% of human pathogens and emerging infectious diseases are zoonotic. Simulation models are increasingly being used to investigate the spread of diseases, evaluate intervention strategies and guide the decisions of policy makers. In this thesis a systematic review of modeling methods and approaches used for zoonotic influenza in animals and humans was conducted, and knowledge gaps were identified. Furthermore, the disease spread and intervention parameters used in these studies were summarized for ready reference in future work.Building on this review work, the research presented in this thesis evaluated the effects of transmissibility of the pandemic H1N1 2009 (pH1N1) virus at the swine- human interface and the control strategies against its spread in swine and human populations as a case study for zoonotic disease modeling. The feasibility of North American Animal Disease Spread Model (NAADSM) for modeling directly transmitted zoonoses was also assessed. Population data based on swine herds and households (categorized as rural households with or without swine workers, and urban households without swine workers) of a county in Ontario, Canada was used. The swine workers served as a bridging population for the spread of the virus between swine herds and households. Scenarios based on the combinations of the transmissibility of the virus (low (L), medium (M), and high (H)) from swine-to-human and human-to-swine (LL, ML, HL, MM, HM, LL), and targeted vaccination of swine worker households (0% to 60%) were evaluated. The results showed that lowering the influenza transmissibility atthe interface to low level and providing higher vaccine coverage (60%) had significant beneficial effects on all outcome measures. However, these measures had little or negligible impact on the total number of rural and urban households infected. A set of models evaluating the combination of control strategies indicated that a moderate speed of the detection (within 5 to 10 days of the first infection), combined with the quarantine of detected units alone, contained the outbreak within the swine population in most simulations. However, a zone-based quarantine strategy was more effective when the detection was delayed until around three weeks after initial infection. Ring vaccination had no added beneficial effect. This work suggested that NAADSM can be used for modeling the directly transmitted zoonotic diseases under similar simplifying assumptions adopted in these studies. However, this needs to be evaluated further with more accurate parameters and influenza outbreak data.To fill in some of the gaps identified in the review study, network analyses of swine shipments among farms, and between farms and abattoirs were conducted. This provided network metrics and parameters necessary for disease modeling and risk-based disease management in swine in Ontario for the first time. Finally, agent-based network models assessing the spread and control of pH1N1 in swine established the importance of explicitly incorporating appropriate contact network structures into such models to increase their validity. It also demonstrated the benefits of targeted control strategies against highly connected farms. In conclusion, the modeling tools developed in this thesis can assist decision makers in preparedness and response of outbreaks of infectious diseases as more information become available for the parameterization of models.