Center for Statistics and Quantitative Infectious Diseases/Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
PLoS Comput Biol. 2010 Jan 29;6(1):e1000656. doi: 10.1371/journal.pcbi.1000656.
Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development.
传染病的数学和计算机模型有助于我们了解传染病的传播方式以及控制或减轻传染病所需的措施。为了帮助我们为未来的季节性流感或大流行做好准备，我们开发了一种新的流感在大人群中传播的随机模型。该模型中的个体具有现实的社会接触网络，并且传播和感染是基于对流感自然史的当前知识状态。该模型已经过校准，以便结果与 1957/1958 年亚洲 A(H2N2)和 2009 年大流行 A(H1N1)流感病毒一致。我们展示了如何使用该模型来研究美国流感疫情的动态，并模拟使用药物干预和社会隔离措施来减轻或延迟疫情的方法。计算机模拟模型在为公共政策提供信息和评估大流行准备计划方面发挥着至关重要的作用。我们已经公开了该模型的源代码，以鼓励其使用和进一步开发。
