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原文連結
論文資訊
- 類型：已發表論文
- 日期：2013-11-21
摘要
數學 modeling of 疾病 傳播 has provided quantitative predictions for health policy, facilitating the evaluation of 流行病學ological outcomes and the cost-effectiveness of interventions. However, typical sensitivity analyses of deterministic dynamic infectious 疾病 models focus on model architecture and the relative importance of parameters but neglect parameter uncertainty when reporting model predictions. Consequently, model results that identify point estimates of intervention levels necessary to terminate 傳播 yield limited insight into the probability of success. We apply probabilistic uncertainty analysis to a dynamic model of influenza 傳播 and assess global uncertainty in outcome. We illustrate that when parameter uncertainty is not incorporated into outcome estimates, levels of 疫苗接種 and treatment
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