King Aaron A, Ionides Edward L, Pascual Mercedes, Bouma Menno J
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109, USA.
Nature. 2008 Aug 14;454(7206):877-80. doi: 10.1038/nature07084.
In many infectious diseases, an unknown fraction of infections produce symptoms mild enough to go unrecorded, a fact that can seriously compromise the interpretation of epidemiological records. This is true for cholera, a pandemic bacterial disease, where estimates of the ratio of asymptomatic to symptomatic infections have ranged from 3 to 100 (refs 1-5). In the absence of direct evidence, understanding of fundamental aspects of cholera transmission, immunology and control has been based on assumptions about this ratio and about the immunological consequences of inapparent infections. Here we show that a model incorporating high asymptomatic ratio and rapidly waning immunity, with infection both from human and environmental sources, explains 50 yr of mortality data from 26 districts of Bengal, the pathogen's endemic home. We find that the asymptomatic ratio in cholera is far higher than had been previously supposed and that the immunity derived from mild infections wanes much more rapidly than earlier analyses have indicated. We find, too, that the environmental reservoir (free-living pathogen) is directly responsible for relatively few infections but that it may be critical to the disease's endemicity. Our results demonstrate that inapparent infections can hold the key to interpreting the patterns of disease outbreaks. New statistical methods, which allow rigorous maximum likelihood inference based on dynamical models incorporating multiple sources and outcomes of infection, seasonality, process noise, hidden variables and measurement error, make it possible to test more precise hypotheses and obtain unexpected results. Our experience suggests that the confrontation of time-series data with mechanistic models is likely to revise our understanding of the ecology of many infectious diseases.
在许多传染病中，有一部分感染产生的症状非常轻微，以至于未被记录下来，这一事实可能会严重影响对流行病学记录的解读。霍乱这种大流行性细菌性疾病就是如此，据估计，无症状感染与有症状感染的比例在3到100之间（参考文献1 - 5）。在缺乏直接证据的情况下，对霍乱传播、免疫学和防控等基本方面的理解一直基于对这一比例以及隐性感染免疫后果的假设。在此，我们表明，一个纳入高无症状感染比例和快速衰减免疫力、同时考虑人类和环境感染源的模型，能够解释来自霍乱病原体的地方性发源地——孟加拉26个地区长达50年的死亡率数据。我们发现，霍乱的无症状感染比例远高于此前的推测，而且轻度感染所产生的免疫力衰减速度比早期分析所表明的要快得多。我们还发现，环境宿主（自由生活的病原体）直接导致的感染相对较少，但它可能对疾病的地方性流行至关重要。我们的结果表明，隐性感染可能是解读疾病爆发模式的关键。新的统计方法基于包含多种感染源和感染结果、季节性、过程噪声、隐藏变量及测量误差的动态模型，实现了严格的最大似然推断，从而能够检验更精确的假设并获得意想不到的结果。我们的经验表明，将时间序列数据与机制模型相结合，可能会改变我们对许多传染病生态学的理解。
