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

人类接触动力学的高分辨率半参数贝叶斯建模。

• 批准号: 2602755
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2602755
• 关键词: resolution; semi; parametric; Bayesian; modelling

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.

该项目属于EPSRC数学科学研究领域。项目摘要：艾滋病毒等传染病是通过人类密切性接触传播的。为了了解疾病传播并描述封闭人群中动态的人类性行为，统计模型对于推断高分辨率的接触模式（按性别划分的1岁年龄组）至关重要。在接触矩阵中编码的接触模式，量化了目标年龄-性别群体中一个人在一年中与特定年龄-性别人群的性伴侣数量。在艾滋病毒的背景下，接触模式是根据东非乌干达纵向开放Rakai社区队列研究（RCCS）中前所未有的性接触数据推断出来的，在那里存在报告偏差和调查局限性。现有文献显示了妇女报告不足问题的证据，这就引入了性别报告偏见。然而，造成妇女报告不足问题的潜在因素仍不清楚。我们利用联系人的对称属性，并依赖于男性报告的联系人数据来捕获未报告的女性联系人。此外，我们分析了妇女的职业，以探索妇女中报告不足问题的分布。调查的另一个问题是，参与者没有详细报告所涉及的伴侣，这就引入了不可靠的联系。为此，我们与Rakai健康科学计划合作，开发了一种半参数贝叶斯模型，该模型可以估计高分辨率接触模式，并在统一框架中调整低报接触和无信息接触的潜在影响。在该框架中，接触模式通过随机函数描述，并在计算上有效地逼近希尔伯特空间高斯过程先验。我们重点调查了维多利亚湖周围内陆和渔区的40个调查社区，分别于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，在艾滋病毒高流行率的渔业社区，妇女在其社区内的性接触报告严重不足，而在低流行率的内陆社区则较少。渔业社区的低报调整后性接触强度几乎是内陆社区的两倍，而且他们的年龄结构差别很大。随着时间的推移，我们发现内陆和渔业社区的性接触模式分别没有显著变化。我们的研究结果表明，从2011年到2020年，乌干达Rakai的性接触行为没有实质性的变化，这可以解释同一时期艾滋病毒发病率的显著变化。此外，我们还调查了女性的某些职业（如性工作），这些职业与未被报告的接触密切相关。在将我们的模型应用于RCCS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片。这项工作有望帮助理解东非的性接触行为，更现实的传染病模型参数化，以及更深入地理解hiv相关疾病是如何在人群中传播的。