Real-time monitoring and predictive modelling of the impact of human behaviour and vaccine characteristics on COVID-19 vaccination in Scotland
人类行为和疫苗特征对苏格兰 COVID-19 疫苗接种影响的实时监测和预测建模
基本信息
- 批准号:ES/W001489/1
- 负责人:
- 金额:$ 33.05万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2021
- 资助国家:英国
- 起止时间:2021 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
While COVID-19 vaccination will likely be transformative, many uncertainties may influence how quickly and comprehensively vaccination will have an impact. Current evidence suggests high levels of protection from the available vaccines, with some evidence that it also reduces transmission. However the evaluation of the evidence is ongoing, with the potential for new variants of concern to change the overall picture. To evaluate this in real time, we shall address here two interlinked factors: the potential for vaccinated individuals to shed and transmit virus without displaying clinical symptoms, and the rate of vaccination uptake and how it may cluster in communities. We shall work with Public Health Scotland, to exploit real-time monitoring of vaccine uptake, COVID-19 testing and cases, to identify geographical localised impacts on infection rates. Wastewater surveillance data will help to identify possible shedding of vaccinated individuals by comparing detection rates before and after vaccination, with a signal either indicating potential for transmission or a signal that must be accounted for to reduce the likelihood of false alarms in future situations where wastewater surveillance is being utilised. Using an established agent-based model fitted to cases across Scotland, we shall use these data to make short term forecasts for COVID-19 case numbers to support PHS planning. Long-term projections will consider vaccine-induced and natural immunity, clustering of low vaccine uptake, logistics, and possible loss of immunity. An online survey will build on the ongoing OPTIMUM study by correlating vaccination attitudes and ease of access to Scottish demography, mapping these geographically via the Scottish index of multiple deprivation (SIMD). We shall use models of 'vaccination games' to consider possible future scenarios where combinations of hesitancy, refusal and difficulties of access could result in lower uptake rates in some communities and therefore continued higher levels of infection or risk of outbreaks. We shall embed these scenarios into our simulation models. From this project, we shall have a more refined understanding of COVID-19 epidemiology in Scotland under vaccination, and better predictions of epidemic trajectories to aid in planning, to inform possible stresses on hospitals and ICU, and to target vaccine deployment and information strategies. Our results will more generally inform relationships amongst vaccine attitudes, accessibility, and regions of low vaccine uptake and refine approaches to surveillance and control.
虽然COVID-19疫苗接种可能会带来变革,但许多不确定性可能会影响疫苗接种产生影响的速度和全面性。目前的证据表明,现有疫苗的保护水平很高,一些证据表明,它也减少了传播。然而,对证据的评估正在进行中,新的令人担忧的变异可能会改变整体情况。为了真实的评估这一点,我们将在这里解决两个相互关联的因素:接种疫苗的个体在没有表现出临床症状的情况下传播病毒的可能性,以及接种疫苗的速度和它如何在社区中聚集。我们将与苏格兰公共卫生部合作,利用对疫苗接种、COVID-19检测和病例的实时监测,以确定地理位置对感染率的影响。废水监测数据将有助于通过比较接种疫苗前后的检测率来确定接种疫苗个体可能的脱落,其中信号要么指示潜在的传播,要么指示必须考虑的信号,以减少未来使用废水监测的情况下误报的可能性。我们将使用一个适合苏格兰各地病例的基于代理人的既定模型,利用这些数据对COVID-19病例数量进行短期预测,以支持PHS规划。长期预测将考虑疫苗诱导的和自然的免疫力,低疫苗摄取的聚集,物流和可能的免疫力丧失。一项在线调查将建立在正在进行的OPTIMUM研究的基础上,将疫苗接种态度与苏格兰人口统计学的便利性相关联,并通过苏格兰多重剥夺指数(SIMD)在地理上绘制这些地图。我们将使用“疫苗接种游戏”模型来考虑未来可能出现的情况,即犹豫、拒绝和难以获得疫苗的组合可能导致某些社区的接种率较低,因此感染水平或爆发风险持续较高。我们将把这些情景嵌入到我们的模拟模型中。通过这个项目,我们将对苏格兰接种疫苗后的COVID-19流行病学有更深入的了解,并更好地预测流行轨迹,以帮助规划,为医院和ICU可能面临的压力提供信息,并有针对性地部署疫苗和制定信息战略。我们的研究结果将更普遍地告知疫苗态度,可及性和低疫苗摄取地区之间的关系,并改进监测和控制方法。
项目成果
期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Time intervals between COVID-19 cases, and more severe outcomes
- DOI:10.1101/2022.10.31.22281769
- 发表时间:2022-11
- 期刊:
- 影响因子:0
- 作者:A. Wood;R. Kao
- 通讯作者:A. Wood;R. Kao
Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data
使用精细病例数据评估两波 SARS-CoV-2 中人口统计风险因素的重要性
- DOI:10.1101/2022.08.03.22278013
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Wood A
- 通讯作者:Wood A
The impact of signal variability on epidemic growth rate estimation from wastewater surveillance data
- DOI:10.1101/2023.03.07.23286904
- 发表时间:2023-03
- 期刊:
- 影响因子:0
- 作者:E. Colman;R. Kao
- 通讯作者:E. Colman;R. Kao
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{{ truncateString('Rowland Kao', 18)}}的其他基金
Flu Trailmap (Transmission and risk of avian influenza: learning more to advance preparedness)
流感路线图(禽流感的传播和风险:了解更多信息以做好准备)
- 批准号:
BB/Y007352/1 - 财政年份:2023
- 资助金额:
$ 33.05万 - 项目类别:
Research Grant
Developing better modelling inference tools to inform disease control for bovine Tuberculosis using epidemiological and pathogen genetic information.
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- 批准号:
BB/W007290/1 - 财政年份:2022
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$ 33.05万 - 项目类别:
Research Grant
US-UK Collab: Mycobacterial Transmission Dynamics in Agricultural Systems: Integrating Phylogenetics, Epidemiology, Ecology, and Economics
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BB/M01262X/2 - 财政年份:2017
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$ 33.05万 - 项目类别:
Research Grant
Joint estimation of epidemiological and genetic processes for Mycobacterium bovis transmission dynamics in cattle and badgers
联合评估牛和獾中牛分枝杆菌传播动态的流行病学和遗传过程
- 批准号:
BB/L010569/2 - 财政年份:2017
- 资助金额:
$ 33.05万 - 项目类别:
Research Grant
Bilateral BBSRC-SFI: Tackling a multi-host pathogen problem - phylodynamic analyses of the epidemiology of M. bovis in Britain and Ireland
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BB/P010598/1 - 财政年份:2017
- 资助金额:
$ 33.05万 - 项目类别:
Research Grant
US-UK Collab: Mycobacterial Transmission Dynamics in Agricultural Systems: Integrating Phylogenetics, Epidemiology, Ecology, and Economics
美英合作:农业系统中的分枝杆菌传播动力学:整合系统发育学、流行病学、生态学和经济学
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BB/M01262X/1 - 财政年份:2014
- 资助金额:
$ 33.05万 - 项目类别:
Research Grant
Joint estimation of epidemiological and genetic processes for Mycobacterium bovis transmission dynamics in cattle and badgers
联合评估牛和獾中牛分枝杆菌传播动态的流行病学和遗传过程
- 批准号:
BB/L010569/1 - 财政年份:2014
- 资助金额:
$ 33.05万 - 项目类别:
Research Grant
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