Simulating school closure policies for cost effective pandemic decision making
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Background: Around the globe, school closures were used sporadically to mitigate the 2009 H1N1 influenza pandemic. However, such closures can detrimentally impact economic and social life. Methods: Here, we couple a decision analytic approach with a mathematical model of influenza transmission to estimate the impact of school closures in terms of epidemiological and cost effectiveness. Our method assumes that the transmissibility and the severity of the disease are uncertain, and evaluates several closure and reopening strategies that cover a range of thresholds in school-aged prevalence (SAP) and closure durations. Results: Assuming a willingness to pay per quality adjusted life-year (QALY) threshold equal to the US per capita GDP ($46,000), we found that the cost effectiveness of these strategies is highly dependent on the severity and on a willingness to pay per QALY. For severe pandemics, the preferred strategy couples the earliest closure trigger (0.5% SAP) with the longest duration closure (24 weeks) considered. For milder pandemics, the preferred strategies also involve the earliest closure trigger, but are shorter duration (12 weeks for low transmission rates and variable length for high transmission rates). Conclusions: These findings highlight the importance of obtaining early estimates of pandemic severity and provide guidance to public health decision-makers for effectively tailoring school closures strategies in response to a newly emergent influenza pandemic.
Ozgur M. Araz is with the College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA -- Paul Damien is with the Information, Risk, and Operations Management Department, McCombs School of Business, The University of Texas, Austin, TX, 78712, USA -- David A. Paltiel and Alison Galvani are witht the School of Medicine, Yale University, CT, New Haven, 06510, USA -- Sean Burke, Bryce van de Geijn and Lauren Ancel Meyers are with the Section of Integrative Biology, The University of Texas at Austin, Austin, TX, 78712, USA -- Alison Galvani is with the Epidemiology and Public Health, New Haven, CT, 06510, USA -- Lauren Ancel Meyers is with the Santa Fe Institute, Santa Fe, NM, USA