Vino Thiripura, Singh Gurmeet R, Davison Belinda, Campbell Patricia T, Lydeamore Michael J, Robinson Andrew, McVernon Jodie, Tong Steven Y C, Geard Nicholas
School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia.
Menzies School of Health Research, Darwin, Northern Territory, Australia.
PeerJ. 2017 Oct 26;5:e3958. doi: 10.7717/peerj.3958. eCollection 2017.
Households are an important location for the transmission of communicable diseases. Social contact between household members is typically more frequent, of greater intensity, and is more likely to involve people of different age groups than contact occurring in the general community. Understanding household structure in different populations is therefore fundamental to explaining patterns of disease transmission in these populations. Indigenous populations in Australia tend to live in larger households than non-Indigenous populations, but limited data are available on the structure of these households, and how they differ between remote and urban communities. We have developed a novel approach to the collection of household structure data, suitable for use in a variety of contexts, which provides a detailed view of age, gender, and room occupancy patterns in remote and urban Australian Indigenous households. Here we report analysis of data collected using this tool, which quantifies the extent of crowding in Indigenous households, particularly in remote areas. We use these data to generate matrices of age-specific contact rates, as used by mathematical models of infectious disease transmission. To demonstrate the impact of household structure, we use a mathematical model to simulate an influenza-like illness in different populations. Our simulations suggest that outbreaks in remote populations are likely to spread more rapidly and to a greater extent than outbreaks in non-Indigenous populations.
家庭是传染病传播的重要场所。家庭成员之间的社会接触通常更为频繁、强度更大,而且与一般社区中的接触相比,更有可能涉及不同年龄组的人群。因此,了解不同人群的家庭结构对于解释这些人群中的疾病传播模式至关重要。澳大利亚的原住民家庭往往比非原住民家庭规模更大,但关于这些家庭结构以及它们在偏远社区和城市社区之间的差异的数据有限。我们开发了一种收集家庭结构数据的新方法,适用于各种情况,该方法提供了澳大利亚偏远和城市原住民家庭中年龄、性别和房间居住模式的详细情况。在此,我们报告使用该工具收集的数据的分析结果,这些数据量化了原住民家庭,特别是偏远地区家庭的拥挤程度。我们利用这些数据生成传染病传播数学模型所使用的特定年龄接触率矩阵。为了证明家庭结构的影响,我们使用一个数学模型来模拟不同人群中的流感样疾病。我们的模拟结果表明,偏远人群中的疫情可能比非原住民人群中的疫情传播得更快、范围更广。