Kucharski Adam J, Kwok Kin O, Wei Vivian W I, Cowling Benjamin J, Read Jonathan M, Lessler Justin, Cummings Derek A, Riley Steven
Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
PLoS Pathog. 2014 Jun 26;10(6):e1004206. doi: 10.1371/journal.ppat.1004206. eCollection 2014 Jun.
Variability in the risk of transmission for respiratory pathogens can result from several factors, including the intrinsic properties of the pathogen, the immune state of the host and the host's behaviour. It has been proposed that self-reported social mixing patterns can explain the behavioural component of this variability, with simulated intervention studies based on these data used routinely to inform public health policy. However, in the absence of robust studies with biological endpoints for individuals, it is unclear how age and social behaviour contribute to infection risk. To examine how the structure and nature of social contacts influenced infection risk over the course of a single epidemic, we designed a flexible disease modelling framework: the population was divided into a series of increasingly detailed age and social contact classes, with the transmissibility of each age-contact class determined by the average contacts of that class. Fitting the models to serologically confirmed infection data from the 2009 Hong Kong influenza A/H1N1p pandemic, we found that an individual's risk of infection was influenced strongly by the average reported social mixing behaviour of their age group, rather than by their personal reported contacts. We also identified the resolution of social mixing that shaped transmission: epidemic dynamics were driven by intense contacts between children, a post-childhood drop in risky contacts and a subsequent rise in contacts for individuals aged 35-50. Our results demonstrate that self-reported social contact surveys can account for age-associated heterogeneity in the transmission of a respiratory pathogen in humans, and show robustly how these individual-level behaviours manifest themselves through assortative age groups. Our results suggest it is possible to profile the social structure of different populations and to use these aggregated data to predict their inherent transmission potential.
呼吸道病原体传播风险的变异性可能由多种因素导致，包括病原体的内在特性、宿主的免疫状态和宿主行为。有人提出，自我报告的社会交往模式可以解释这种变异性的行为成分，基于这些数据的模拟干预研究经常被用于为公共卫生政策提供信息。然而，在缺乏针对个体生物学终点的有力研究的情况下，尚不清楚年龄和社会行为如何影响感染风险。为了研究社会接触的结构和性质如何在单一疫情过程中影响感染风险，我们设计了一个灵活的疾病建模框架：将人群划分为一系列日益详细的年龄和社会接触类别，每个年龄 - 接触类别的传播性由该类别的平均接触情况决定。将模型与2009年香港甲型H1N1p流感大流行的血清学确诊感染数据进行拟合，我们发现个体的感染风险强烈受其年龄组报告的平均社会交往行为影响，而非其个人报告的接触情况。我们还确定了影响传播的社会交往分辨率：疫情动态由儿童之间的密切接触、儿童期后高风险接触的下降以及35 - 50岁个体接触的随后上升所驱动。我们的结果表明，自我报告的社会接触调查可以解释人类呼吸道病原体传播中与年龄相关的异质性，并有力地展示了这些个体层面的行为如何通过不同年龄组表现出来。我们的结果表明，有可能描绘不同人群的社会结构，并利用这些汇总数据预测其内在传播潜力。
