Modelling social clustering of susceptibles and its impact on measles elimination
Modelling social clustering of susceptibles and its impact on measles elimination
批准号:
1923699
负责人:
金额:
$0.0万
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
背景尽管麻疹疫苗接种非常广泛,但很少有国家能够实现消除麻疹病毒,即在确定的地理区域内阻断地方性传播。疫苗的效力很高(两剂预防麻疹的效力约为97%;一剂约为90%),麻疹负担在引进后已大大减轻。然而,频繁的疫情继续影响着世界各地的人口。联合王国是发达国家在控制麻疹方面遇到困难的一个代表性例子。在过去十年中,监测系统在英格兰和威尔士每年观察到数百例病例。在过去36个月阻断了地方性传播后,英国于2017年消除了麻疹。尽管如此,社区中对疫苗的不信任日益增加,这可能导致未来几年的地方性传播。需要更好地了解最近的疫情和目前的监测状况,以便提出新的方法来维持消除工作。因此,这类工作的目标应该是:1 .描述和了解最近的疫情,以便2 .评价目前疫苗接种程序的弱点,3 .提出将保持消灭并最终使消灭这一疾病成为可实现目标的准则。该项目将评估常规疫苗接种的弱点、常规疫苗无法覆盖的个人概况以及目前的高危传播方式。目标和方法在高水平疫苗接种下控制麻疹的一个特殊挑战是易感人群聚集,即缺乏免疫力的人优先彼此进行社会接触,或者因为他们有共同的价值观或信仰,或者因为他们属于公共卫生服务不足的同一个社区。我们可以确定三种不同的方法来分析通过与英格兰公共卫生部(PHE)的接触获得的患者级数据集:1 /描述以前的疫情;2 /调查社会网络和易感人群聚集的重要性;3 /由于社会行为的变化而改变了病毒的传播。为了进行这种分析,我们将运用数学、统计学和计算方面的定量技能来分析患者级数据集。这项工作旨在重建一个概率传播网络,以在个体层面上深入了解病毒的传播。PHE常规收集的基因序列数据将用于提高概率传播树的准确性,并指出两个病例之间的接近性(相同的索引病例,它们之间的直接传播……)。我们将使用先进的系统发育工具生成概率传播树,并跟踪共同特征,以描述能够催化病毒传播的个体。最后,利用有关社会混合模式、人口统计和社会行为变化的数据,我们的目标是量化导致社区中儿童疾病传播动态变化的过程。这将导致对疫苗接种运动的影响进行卫生经济学分析,以确定不同干预措施的成本效益。所有这些分析将为了解最近麻疹在英国的传播以及该病毒在该国传播的潜在未来风险提供重要见解。我们期望拟议的研究能够提出改进疫苗接种战略的建议,以消除和减轻疫情风险。在更广泛的范围内,由于英国是西欧国家在完全根除麻疹病毒方面面临的复杂情况的一个很好的例子,这项研究还将深入了解应如何使用控制措施来降低麻疹风险
英文摘要
BackgroundDespite the very widespread use of measles vaccination, few countries have been able to achieve elimination of the measles virus, which refers to the interruption of endemic transmission in a defined geographical area. Vaccine efficacy is high (two doses is roughly 97% effective at preventing measles; one dose is about 90% effective) and the burden of measles has been substantially reduced after its introduction. Nevertheless, frequent outbreaks continue to affect populations around the world.The United Kingdom is a representative example of the difficulties experienced by developed countries to control measles. In the last ten years, surveillance systems observed hundreds of annual cases in England and Wales. After the interruption of endemic transmission for the last 36 months, the United Kingdom achieved elimination of measles in 2017. Nonetheless, increasing mistrust in vaccine is observed in the community, which may lead to endemic transmission in the years to come. A better understanding of recent outbreaks and the current state of surveillance is required to propose new methods to maintain elimination. The objectives of such work should therefore be:i/ Describe and understand recent outbreaks, in order to ii/ evaluate the weaknesses of the current vaccination routine and iii/ propose guidelines which will maintain elimination and, ultimately, make eradication of the disease an achievable objective. This project will assess what are the weaknesses of the vaccination routine, the profiles of the individuals this routine are unable to reach, and the current high-risk modes of transmission.Aims and MethodsA particular challenge for control of measles at high levels of vaccination is clustering of susceptibles, whereby those lacking immunity are preferentially in social contact with each other, either because they share a set of values or beliefs, or because they are part of the same community underserved by public health. We can identify three different approaches to analysing a patient-level dataset made available through contacts at Public Health England (PHE): i/ The description of the previous outbreaks, ii/ An investigation of the importance of social networks and clustering of susceptibles iii/ The modifications of the spread of the virus due to social behaviour changes. To perform this analysis, we will apply quantitative skills in mathematics, statistics and computation to the patient-level dataset. This work aims to reconstruct a probabilistic transmission network to gain insights of the spread of the virus at an individual level. Genetic sequence data routinely collected by PHE will be used to enhance the accuracy of the probabilistic transmission trees, and to point out the proximity between two cases (same index case, direct transmission between them...). We will use cutting-edge phylogenetic tools to generate a probabilistic transmission tree and track common features to describe the individuals able to catalyse the spread of the virus. Finally, using data on social mixing patterns, demography and social behaviour changes, we aim to quantify processes that lead to modifications in the dynamics of transmission of childhood diseases in the community. This will lead to a health economics analysis of vaccination campaigns' impact, to determine the cost-effectiveness of different interventions.Potential benefitsAll of these analyses will provide important insights into the recent spread of measles in the United Kingdom and the potential future risks of spreading of the virus in the country. We expect the proposed studies to lead to suggestions for improved vaccination strategies towards elimination and mitigation of outbreak risk. On a broader scale, as the United Kingdom is a good example of the complications Western European countries are facing to fully eradicate measles virus, this study will also give insight on how control measures should be used to reduce the risk of
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Probabilistic reconstruction of measles transmission clusters from routinely collected surveillance data
根据常规收集的监测数据对麻疹传播集群进行概率重建
DOI:
10.1101/2020.02.13.20020891
发表时间:
2020
期刊:
影响因子:
--
作者:
[Robert A]
通讯作者:
Robert A
The measles crisis in Europe-the need for a joined-up approach.
欧洲的麻疹危机——需要采取联合行动。
DOI:
10.1016/s0140-6736(19)31039-6
发表时间:
2019
期刊:
Lancet (London, England)
影响因子:
--
作者:
[Robert A]
通讯作者:
Robert A
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