Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Proceedings of the 23rd international conference on Supercomputing
Winter Simulation Conference
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Public-health policy makers have many tools to mitigate an epidemic's effects. Most related research focuses on the direct effects on those infected (in terms of health, life, or productivity). Interventions including treatment, prophylaxis, quarantine, and social distancing are well studied in this context. These interventions do not address indirect effects due to the loss of critical services and infrastructures when too many of those responsible for their day-to-day operations fall ill. We examine, both analytically and through simulation, the protection of such essential subpopulations by sequestering them, effectively isolating them into groups during an epidemic. We develop a framework for studying the benefits of sequestering and heuristics for when to sequester. We also prove a key property of sequestering placement which helps partition the subpopulations optimally. Thus we provide a first step toward determining how to allocate resources between the direct protection of a population, and protection of those responsible for critical services.