Abstract
Pandemic and seasonal infectious diseases such as influenza may have serious negative health and economic consequences. Certain non-pharmaceutical intervention strategies – including school closures – can be implemented rapidly as a first line of defense against spread. Such interventions attempt to reduce the effective number of contacts between individuals within a community; yet the efficacy of closing schools to reduce disease transmission is unclear, and closures certainly result in significant economic impacts for caregivers who must stay at home to care for their children. Using individual-based computer simulation models to trace contacts among schoolchildren within a stereotypical school setting, we show how alternative school-based disease interventions have great potential to be as effective as traditional school closures without the corresponding loss of workforce and economic impacts.
Highlights
Pandemic diseases, such as the 2009 H1N1 influenza pandemic, threaten global health and economics if their spread is unchecked [1,2,3,4,5]
Another complicating factor is that previous models have indicated that the timing of school closings is critical to the disruption of disease dynamics within a community and have typically recommended specific closure durations (e.g., 1–2 weeks) [8,9,10,11,16,20], but implementation of school closures according to the specified timing and duration guidelines is greatly hampered by a community’s ability to detect disease prevalence and sustain economic losses
We show how other alternative school-based disease interventions have great potential to be as effective as traditional school closures, but without the corresponding loss of workforce and undesirable economic impacts
Summary
Pandemic diseases, such as the 2009 H1N1 influenza pandemic, threaten global health and economics if their spread is unchecked [1,2,3,4,5]. Our primary interest in these simulations was to observe the possible reduction in contact counts, we performed a post hoc analysis to examine the influence of the proposed interventions on disease transmission.
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