Fefferman Nina H, Naumova Elena N
Department of Public Health and Family Medicine, Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA 02111, USA.
Math Biosci. 2006 Aug;202(2):269-87. doi: 10.1016/j.mbs.2006.03.012. Epub 2006 Apr 24.
We use mathematically rigorous definitions of epidemiological concepts in order to derive a sequential combinatorial model of disease outbreak decomposition. We define the idea of a population specific 'disease signature' and use this in order to decompose and further understand outbreaks as incidents of spatial and temporal spread of disease exposure both in, and across, populations. This allows us to differentiate between different disease spread scenarios with a level of sensitivity that previous models were unable to provide. This perspective leads us to propose a new practical definition for 'outbreak'. In addition, we are able to use this model to understand, estimate, and, in some cases, correct for, the likely instances of reporting error inherent in disease surveillance. We demonstrate our model first with a hypothetical outbreak scenario and then in an analysis of suspected outbreaks of waterborne diseases in Massachusetts (MA) in 1995.
我们使用流行病学概念的数学严格定义，以推导疾病爆发分解的顺序组合模型。我们定义了特定人群“疾病特征”的概念，并以此来分解和进一步理解疾病爆发，将其视为疾病暴露在人群内部和人群之间的时空传播事件。这使我们能够以前所未有的敏感度区分不同的疾病传播情况。这种观点引导我们为“爆发”提出一个新的实用定义。此外，我们能够使用这个模型来理解、估计，并在某些情况下校正疾病监测中固有的报告误差的可能情况。我们首先用一个假设的爆发情景展示我们的模型，然后对1995年马萨诸塞州（MA）的水源性疾病疑似爆发进行分析。
