Early COVID-19 Pandemic Preparedness: Informing Public Health Interventions and Hospital Capacity Planning Through Participatory Hybrid Simulation Modeling

Yuan Tian (), Jenny Basran, Wade McDonald and Nathaniel D. Osgood
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Yuan Tian: Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada
Jenny Basran: Saskatchewan Health Authority, Saskatoon, SK S7K 0M7, Canada
Wade McDonald: Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada
Nathaniel D. Osgood: Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada

IJERPH, 2024, vol. 22, issue 1, 1-23

Abstract: We engaged with health sector stakeholders and public health professionals within the health system through a participatory modeling approach to support policy-making in the early COVID-19 pandemic in Saskatchewan, Canada. The objective was to use simulation modeling to guide the implementation of public health measures and short-term hospital capacity planning to mitigate the disease burden from March to June 2020. We developed a hybrid simulation model combining System Dynamics (SD), discrete-event simulation (DES), and agent-based modeling (ABM). SD models the population-level transmission of COVID-19, ABM simulates individual-level disease progression and contact tracing intervention, and DES captures COVID-19-related hospital patient flow. We examined the impact of mixed mitigation strategies—physical distancing, testing, conventional and digital contact tracing—on COVID-19 transmission and hospital capacity for a worst-case scenario. Modeling results showed that enhanced contact tracing with mass testing in the early pandemic could significantly reduce transmission, mortality, and the peak census of hospital beds and intensive care beds. Using a participatory modeling approach, we not only directly informed policy-making on contact tracing interventions and hospital surge capacity planning for COVID-19 but also helped validate the effectiveness of the interventions adopted by the provincial government. We conclude with a discussion on lessons learned and the novelty of our hybrid approach.

Keywords: COVID-19; pandemic preparedness; hybrid simulation; participatory modeling; contact tracing; hospital capacity planning; agent-based modeling; discrete-event simulation; system dynamics (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
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