Real-time monitoring and predictive modelling of the impact of human behaviour and vaccine characteristics on COVID-19 vaccination in Scotland

尽管新冠肺炎疫苗接种可能会带来革命性的变化，但许多不确定性可能会影响疫苗接种产生影响的速度和范围。目前的证据表明，现有疫苗具有高水平的保护作用，一些证据表明，疫苗还可以减少传播。然而，对证据的评估仍在进行中，可能会出现令人关切的新变种，从而改变整体情况。为了实时评估这一点，我们将在这里讨论两个相互关联的因素：接种疫苗的个人在没有临床症状的情况下散播和传播病毒的可能性，以及接种疫苗的速度及其如何在社区中聚集。我们将与苏格兰公共卫生部门合作，利用疫苗接种、新冠肺炎检测和病例的实时监测，确定地理位置对感染率的影响。废水监测数据将通过比较接种前和接种后的检测率来帮助识别可能的疫苗接种个人，这些信号要么表明可能的传播，要么表明必须考虑的信号，以减少在未来利用废水监测的情况下发生错误警报的可能性。使用适用于苏格兰各地案例的已建立的基于代理的模型，我们将使用这些数据对新冠肺炎案例数量做出短期预测，以支持小灵通规划。长期预测将考虑疫苗诱导和自然免疫、低疫苗接种率的聚集性、后勤和可能的免疫损失。一项在线调查将建立在正在进行的优化研究的基础上，通过苏格兰多重剥夺指数(SIMD)将疫苗接种态度与苏格兰人口统计的容易程度联系起来，绘制出这些地理位置的地图。我们将使用“疫苗接种游戏”的模型来考虑未来可能出现的情景，在这些情景中，犹豫不决、拒绝和难以获得疫苗可能会导致一些社区的接种率较低，从而导致感染水平或暴发风险继续上升。我们将把这些场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的新冠肺炎流行病学有更好的了解，并对流行轨迹有更好的预测，以帮助规划，告知医院和重症监护病房可能面临的压力，并针对疫苗部署和信息策略。我们的结果将更全面地告知疫苗态度、可获得性和疫苗接种率低的地区之间的关系，并改进监测和控制方法。

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.