Simulation modeling for pandemic decision making: A case study with bi-criteria analysis on school closures

Pandemic influenza continues to be a national and international public health concern, and has received significant attention worldwide with the A/H1N1 influenza outbreak in 2009. Many countries, including the United States, have developed preparedness plans for an influenza pandemic. Preparedness plans are falling under renewed scrutiny as decision-makers apply new findings and seek key leverage points for more effective preparedness and response. School closure has been recommended by the World Health Organization as one of the best ways to protect children and other susceptible individuals at the early stages of the pandemic. However, school closure is a difficult mitigation policy to implement from both strategic and operational points of view. Challenges include impacts on alternative education delivery services, such as student meals and after-school oversight, as well as direct and indirect economic outfalls. To help public health decision makers address these issues, we developed an epidemiological simulation tool for pandemic influenza which enables users to make decisions during a simulated pandemic. We then designed a school closure tabletop exercise using our simulation model as a decision-support tool for evaluating the effectiveness of school closure as a community mitigation strategy for pandemic influenza. We conducted two exercises in February 2009 for the Arizona Department of Health and Human Services including high-ranking health and education administrators from across the state. The purpose of these exercises was to test the state's pandemic preparedness plans with respect to school closure timing and impact. The exercises required participants to make (hypothetical) strategic and operational decisions to mitigate the impacts of pandemic influenza at the state and local levels. Our simulation and decision analysis tool was used to assess the impact of key decisions in the exercises. This paper presents the technical details involved in the design and evaluation of this pandemic decision-support tool. Based on the decisions made in the exercises, we present a bi-criteria decision analysis framework to evaluate analytical results obtained from the simulation model. Our analyses show that sequential school closure and re-opening strategy with a specific decision rule gives the best compromised solution in terms of minimizing the total number of infections and providing minimal educational discontinuity.