Meyers Lauren Ancel, Pourbohloul Babak, Newman M E J, Skowronski Danuta M, Brunham Robert C
Section of Integrative Biology and Institute for Cellular and Molecular Biology, University of Texas at Austin, 1 University Station C0930, Austin, TX 78712, USA.
J Theor Biol. 2005 Jan 7;232(1):71-81. doi: 10.1016/j.jtbi.2004.07.026.
Many infectious diseases spread through populations via the networks formed by physical contacts among individuals. The patterns of these contacts tend to be highly heterogeneous. Traditional "compartmental" modeling in epidemiology, however, assumes that population groups are fully mixed, that is, every individual has an equal chance of spreading the disease to every other. Applications of compartmental models to Severe Acute Respiratory Syndrome (SARS) resulted in estimates of the fundamental quantity called the basic reproductive number R0--the number of new cases of SARS resulting from a single initial case--above one, implying that, without public health intervention, most outbreaks should spark large-scale epidemics. Here we compare these predictions to the early epidemiology of SARS. We apply the methods of contact network epidemiology to illustrate that for a single value of R0, any two outbreaks, even in the same setting, may have very different epidemiological outcomes. We offer quantitative insight into the heterogeneity of SARS outbreaks worldwide, and illustrate the utility of this approach for assessing public health strategies.
许多传染病通过个体之间身体接触形成的网络在人群中传播。这些接触模式往往高度异质。然而,流行病学中传统的“ compartments”建模假设人群群体完全混合,也就是说,每个个体都有平等的机会将疾病传播给其他任何个体。将 compartments 模型应用于严重急性呼吸综合征(SARS)得出了一个称为基本繁殖数R0的基本量的估计值,即由单个初始病例导致的SARS新病例数,该值高于1,这意味着在没有公共卫生干预的情况下,大多数疫情应该引发大规模流行。在这里,我们将这些预测与SARS的早期流行病学进行比较。我们应用接触网络流行病学方法来说明,对于R0的单个值,任何两次疫情,即使在相同环境下,也可能有非常不同的流行病学结果。我们对全球SARS疫情的异质性提供了定量见解,并说明了这种方法在评估公共卫生策略方面的效用。