Inequality, infections and chronic disease in England: the interaction of risk factors and the dynamics of transmission

英国的不平等、感染和慢性病：危险因素和传播动态的相互作用

• 批准号: MR/X033260/1
• 负责人: Rosalind Eggo
• 金额: $ 267.28万
• 依托单位: London School of Hygiene & Tropical Medicine
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FX033260%2F1
• 关键词: Inequality; infections; chronic; disease; England

In England, there are differences between people in how likely they are to catch infections. There are also differences in how ill people get when they are infected. The same groups of people are more likely to get infected and more likely to get very unwell. Those groups are people of ethnic minority backgrounds, and those groups who experience socioeconomic deprivation. There are lots of reasons why some groups are more likely to catch infections, for example because they have more social contacts because of their job, or their behaviour, or they may have different types of contact, for example if they work in a hospital or have to go there frequently for treatment. Other factors include the size of households that people live in, or the different ages of people they live with. This is important because a lot of infectious disease transmission happens in households. The reasons why people are more likely to get very unwell if they are infected are mostly because of their age and if they have an existing health condition, for example, heart disease. Some of these conditions are more common amongst people who live with socioeconomic deprivation, and amongst ethnic minority groups. Differences in health between groups of people are called health disparities, and there are lots of reasons why these differences exist, and how difficult they are to solve. What this study aims to do is understand better the health disparities and the role that infectious diseases play in creating and sustaining them. Ultimately the aim is to develop better interventions to try to decrease the health disparities that people who live with socioeconomic deprivation or ethnic minority groups experience. I will study these problems by analysing electronic health records data for over 20 million people in England. The health records are held securely on an analysis platform called OpenSAFELY, and individual patient health data is never at risk of being exposed. To add to the health records, I will use a smartphone app called Airmid to ask people about how many social contacts they have in a day and the age and occupation of their contacts. I will also use the app to ask people about how many infections they get, how severe they are, and whether they go to the GP or hospital for that infection. Collecting these data will help understand the differences seen between groups. During the project, I will analyse how infections are distributed among different groups in the population and what factors are associated with having more infections. I will look at how infections are associated with different causes of death, and if those associations are different for ethnic minority groups or those experiencing deprivation. Later in the project I will use computer models to try to understand if there are interventions that could decrease the health disparities, such as vaccination or better treatment. The project will have patient advisors involved to share their experiences and participate in the research.

在英格兰，人们感染病毒的可能性存在差异。人们被感染后病情的严重程度也存在差异。同一群人更有可能被感染，也更有可能变得非常不适。这些群体是有少数民族背景的人，以及那些经历社会经济剥夺的群体。 某些群体更容易感染的原因有很多，例如，因为他们的工作或行为而有更多的社会接触，或者他们可能有不同类型的接触，例如，如果他们在医院工作或必须经常去那里治疗。其他因素包括人们居住的家庭规模，或居住在一起的人的不同年龄。这很重要，因为许多传染病传播发生在家庭中。人们被感染后更有可能变得非常不适的原因主要是因为他们的年龄以及他们是否患有心脏病等现有健康状况。其中一些情况在社会经济贫困的人和少数民族群体中更为常见。 不同人群之间的健康差异被称为健康差异，这些差异存在的原因有很多，解决起来也很困难。这项研究的目的是更好地了解健康差异以及传染病在造成和维持健康差异方面所发挥的作用。最终目标是制定更好的干预措施，试图减少社会经济贫困的人们或少数族裔群体所经历的健康差距。 我将通过分析英格兰超过 2000 万人的电子健康记录数据来研究这些问题。健康记录安全地保存在名为 OpenSAFELY 的分析平台上，患者个人健康数据永远不会面临暴露的风险。为了添加健康记录，我将使用一款名为 Airmid 的智能手机应用程序来询问人们每天有多少社交联系人以及联系人的年龄和职业。我还将使用该应用程序询问人们感染的数量、感染的严重程度以及是否因感染而去看全科医生或医院。收集这些数据将有助于了解群体之间的差异。在该项目期间，我将分析感染在人口中不同群体之间的分布情况以及哪些因素与更多感染相关。我将研究感染与不同死因之间的关系，以及这些关联对于少数族裔群体或经历贫困的人是否有所不同。在该项目的后期，我将使用计算机模型来尝试了解是否有可以减少健康差异的干预措施，例如疫苗接种或更好的治疗。该项目将邀请患者顾问分享他们的经验并参与研究。