Simulating school closure policies for cost effective pandemic decision making

Authors

Ozgur M. Araz, University of Nebraska - LincolnFollow
Paul Damien, The University of Texas, Austin
David A. Paltiel, Yale University
Sean Burke, The University of Texas at Austin
Bryce van de Geijn, The University of Texas at Austin
Alison Galvani, Yale University
Lauren Ancel Meyers, The University of Texas at Austin

Date of this Version

2012

Document Type

Article

Citation

doi:10.1186/1471-2458-12-449

Cite this article as: Araz et al.: Simulating school closure policies for cost effective pandemic decision making. BMC Public Health 2012 12:449.

Comments

© 2012 Araz et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License

Abstract

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.