Assessing key model parameters for economic evaluation of pandemic influenza interventions: the data source matters

评估大流行性流感干预措施经济评价的关键模型参数:数据来源至关重要。

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Abstract

BACKGROUND: In our previous systematic review of economic evaluations of pandemic influenza interventions, five model parameters, namely probability of pandemic, duration of pandemic, severity, attack rate, and intervention efficacy, were not only consistently used in all studies but also considered important by authors. OBJECTIVES: Because these parameters originated from sources of varying quality ranging from experimental studies to expert opinion, this study aims to analyze the variation in values used according to sources of information across studies. METHODS: An analysis of estimated values of key parameters for economic modeling was performed against their different data sources, following the standard hierarchy of evidence. RESULTS: A lack of good-quality evidence to estimate pandemic duration, pandemic probability, and mortality reduction from antiviral treatment results in a large variation of values used in economic evaluations. Although there are variations in quality of evidence used for attack rate, basic reproduction number, and reduction in hospitalizations from antiviral treatment, the estimated values do not vary significantly. The use of higher-quality evidence results in better precision of estimated values compared to lower-quality sources. CONCLUSION: Hierarchies of evidence are a necessary tool to identify appropriate model parameters to populate economic evaluations and should be included in methodological guidelines. Knowledge gaps in some key parameters should be addressed, because if good-quality evidence is available, future economic evaluations will be more reliable. Some gaps may not be fulfilled by research but consensus among experts to ensure consistency in the use of these assumptions.

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