BackgroundIn 2009 and the early part of 2010, the northern hemisphere had to cope with the first waves of the new influenza A (H1N1) pandemic. Despite high-profile vaccination campaigns in many countries, delays in administration of vaccination programs were common, and high vaccination coverage levels were not achieved. This experience suggests the need to explore the epidemiological and economic effectiveness of additional, reactive strategies for combating pandemic influenza.MethodsWe use a stochastic model of pandemic influenza to investigate realistic strategies that can be used in reaction to developing outbreaks. The model is calibrated to documented illness attack rates and basic reproductive number (R0) estimates, and constructed to represent a typical mid-sized North American city.ResultsOur model predicts an average illness attack rate of 34.1% in the absence of intervention, with total costs associated with morbidity and mortality of US$81 million for such a city. Attack rates and economic costs can be reduced to 5.4% and US$37 million, respectively, when low-coverage reactive vaccination and limited antiviral use are combined with practical, minimally disruptive social distancing strategies, including short-term, as-needed closure of individual schools, even when vaccine supply-chain-related delays occur. Results improve with increasing vaccination coverage and higher vaccine efficacy.ConclusionsSuch combination strategies can be substantially more effective than vaccination alone from epidemiological and economic standpoints, and warrant strong consideration by public health authorities when reacting to future outbreaks of pandemic influenza.

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We use a stochastic simulation model of pandemic influenza to investigate realistic intervention strategies that can be used in reaction to developing outbreaks. The model is constructed to represent a typical midsized North American city. Our model predicts average illness attack rates and economic costs for various intervention scenarios, e.g., in the case when low-coverage reactive vaccination and limited antiviral use are combined with minimally disruptive social distancing strategies, including short-term closure of individual schools. We find that such combination strategies can be substantially more effective than vaccination alone from epidemiological and economic standpoints. INTRODUCTIONWith modern advances in science and technology, simulation has been widely used in many research fields. Epidemic simulation models provide useful tools to increase our understanding of the dynamics and patterns of disease propagation, and to study and evaluate the potential impacts of various government policies and intervention strategies for pandemic diseases, including prophylactic use of antivirals and social distancing strategies such as school closure, quarantine, and isolation. These tools are especially timely in light of the recent H1N1 swine flu pandemic. Similar to other simulation studies, epidemic simulations consist of three parts: identification of relevant inputs, model building, and output data analysis. The inputs typically include basic population data, the contact behavior of the individuals in the population, and disease transmission parameters. In the U.S., the population and their behavior are generated based on census bureau and demographic research, respectively, and the transmission parameters are based on epidemiologic research. Regarding model logic, the most-popular approaches are individual-based epidemiological compartment models, for example, 2221 978-1-4244-9865-9/10/$26.00 ©2010 IEEE