High-resolution semi-parametric Bayesian modelling of human contact dynamics.

该项目属于EPSRC数学科学研究领域。项目摘要：传染性疾病，如艾滋病毒，通过密切的人类性行为传播。为了了解疾病的传播和描述封闭人群中动态的人类性行为，统计模型对于以高分辨率推断接触模式(按性别划分的1岁年龄段)至关重要。接触模式编码在联系矩阵中，量化了目标年龄-性别群体中一人在一年中与特定年龄-性别人口发生的性伴侣数量。在艾滋病毒方面，接触模式是根据在东非乌干达进行的纵向开放式Rakai社区队列研究(RCCS)中前所未有的性接触数据推断的，那里存在报告偏见和调查限制。现有文献显示了妇女报告不足问题的证据，这导致了按性别进行报告的偏见。然而，可能导致报告不足的妇女问题的潜在因素仍然不清楚。我们利用联系人的对称性，并依赖于男性报告的联系人数据来捕获女性报告不足的联系人。此外，我们还分析了妇女的职业，以探讨报告不足问题在妇女中的分布情况。调查的另一个问题是，参与者报告的有关伴侣的细节不多，这导致了信息不多的联系人。为此，我们与Rakai健康科学计划合作，开发了一个半参数贝叶斯模型，该模型估计了高分辨率的联系模式，在一个统一的框架中调整了报告不足和信息不足的联系的潜在影响。在该框架中，接触模式用随机函数来描述，并用希尔伯特空间高斯过程先验进行高效的计算逼近。我们重点调查了内陆和维多利亚湖周围渔区的40个调查社区，并分别在2011年8月至2013年8月和2018年6月至2020年11月进行了两轮调查。我们发现，在艾滋病毒感染率较高的渔业社区，妇女在其社区内的性接触行为严重漏报，而在感染率较低的内陆社区，这种情况较少。渔业社区未报告的调整后的性接触强度几乎是内陆社区的两倍，其年龄结构差别很大。随着时间的推移，我们发现内陆和渔业社区的性接触模式没有显著变化。我们的研究结果表明，从2011年到2020年，乌干达拉凯的性接触行为没有发生实质性变化，这可以解释同一时期艾滋病毒发病率的显著变化。此外，我们还调查了某些与漏报的接触密切相关的女性职业(例如性工作)。在将我们的模型应用到农村信用社的接触调查中，我们提供了按性别划分的性接触模式的详细图景。这项工作有望帮助理解东非的性接触行为，更切合实际的传染病模型参数，以及更深入地理解艾滋病毒相关疾病是如何通过人群传播的。

This project falls within the EPSRC mathematical sciences research area.Project summaries: Infectious diseases, such as HIV, are transmitted through close human sexual contacts. To understand the disease spread and characterise dynamic human sexual behaviours within a closed population, statistical models are essential to infer contact patterns at high resolution (1-year age bands by gender). The contact patterns, encoded in contact matrices, quantify the number of sexual partners in a year with a specific age-gender population by one person in a target age-gender group. In the context of HIV, the contact patterns are inferred based on unprecedented sexual contact data from the longitudinal open Rakai Community Cohort Study (RCCS) in Uganda, East Africa, where the reporting bias and survey limitations exist. Existing literature shows evidence of the under-reporting issue of women, which introduces the reporting bias by gender. However, the potential factors that would cause the under-reporting issue of women are still unclear. We leverage the symmetric property of contacts and rely on the male-reported contact data to capture the under-reported contacts of women. Additionally, we analyse the occupations of women in order to explore the distribution of the under-reporting issue among women. Another issue of the survey is that participants reported without much detail on the partner involved, which introduced uninformative contacts. To this end, collaborating with the Rakai Health Sciences Program, we develop a semi-parametric Bayesian model which estimates high-resolution contact patterns that adjusts for the potential effects of under-reporting contacts and uninformative contacts in a unified framework. In the framework, contact patterns are described through random functions, and computationally efficiently approximated with Hilbert Space Gaussian processes priors. We focus on 40 surveyed communities in inland and fishing areas around Lake Victoria, and on two survey rounds from August 2011 to August 2013 and from June 2018 to November 2020, respectively. We uncover substantial under-reporting of sexual contacts by women within their communities in the high-HIV-prevalence fishing communities, and less so in the lower-prevalence inland communities. The under-reporting adjusted sexual contact intensities in fishing communities are nearly two-fold higher than in inland communities, and their age structure differs considerably. Over time, we find no significant changes in sexual contact patterns in inland and fishing communities respectively. Our findings indicate that there were no substantial changes in sexual contact behaviour from 2011 to 2020 in Rakai, Uganda that could causally explain the marked changes in HIV incidence during the same time period. Additionally, we investigate certain occupations (such as sex work) of women that significantly correlate to under-reported contacts. In applying our model to the RCCS contact survey, we provide a detailed picture of the sexual contact patterns by gender. This work promises to aid the understanding of sexual contact behaviour in East Africa, more realistic parameterisations of infectious disease models, and a deeper understanding of how HIV-related diseases are propagated through populations.