Public Health Computational and Operational Research (PHICOR) Group, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Clin Microbiol Infect. 2013 Nov;19(11):1014-22. doi: 10.1111/1469-0691.12284. Epub 2013 Jun 25.
During the 2009 H1N1 pandemic, decision-makers had access to mathematical and computational models that were not available in previous pandemics in 1918, 1957, and 1968. How did models contribute to policy and action during the 2009 H1N1 pandemic? Modelling encountered six primary challenges: (i) expectations of modelling were not clearly defined; (ii) appropriate real-time data were not readily available; (iii) modelling results were not generated, shared, or disseminated in time; (iv) decision-makers could not always decipher the structure and assumptions of the models; (v) modelling studies varied in intervention representations and reported results; and (vi) modelling studies did not always present the results or outcomes that are useful to decision-makers. However, there were also seven general successes: (i) modelling characterized the role of social distancing measures such as school closure; (ii) modelling helped to guide data collection; (iii) modelling helped to justify the value of the vaccination programme; (iv) modelling helped to prioritize target populations for vaccination; (v) modelling addressed the use of antiviral medications; (vi) modelling helped with health system preparedness planning; and (vii) modellers and decision-makers gained a better understanding of how to work with each other. In many ways, the 2009 pandemic served as practice and a learning opportunity for both modellers and decision-makers. Modellers can continue working with decision-makers and other stakeholders to help overcome these challenges, to be better prepared when the next emergency inevitably arrives.
在 2009 年 H1N1 大流行期间，决策者可以使用在 1918 年、1957 年和 1968 年之前的大流行中不可用的数学和计算模型。模型如何为 2009 年 H1N1 大流行期间的政策和行动做出贡献？建模面临六个主要挑战：（i）对建模的期望没有明确定义；（ii）没有及时提供适当的实时数据；（iii）建模结果没有及时生成、共享或传播；（iv）决策者并不总是能够理解模型的结构和假设；（v）建模研究在干预措施表示和报告结果方面存在差异；（vi）建模研究并不总是向决策者展示有用的结果或结果。但是，也有七个普遍的成功：（i）建模描述了社交距离措施（如学校关闭）的作用；（ii）建模有助于指导数据收集；（iii）建模有助于证明疫苗接种计划的价值；（iv）建模有助于确定疫苗接种的重点人群；（v）建模涉及抗病毒药物的使用；（vi）建模有助于进行卫生系统准备规划；（vii）建模者和决策者更好地了解了如何相互合作。在许多方面，2009 年的大流行既是建模者和决策者的实践机会，也是学习机会。建模者可以继续与决策者和其他利益相关者合作，帮助克服这些挑战，为下一次不可避免的紧急情况做好更好的准备。
