Department for Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Department for Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Epidemics. 2022 Sep;40:100614. doi: 10.1016/j.epidem.2022.100614. Epub 2022 Jul 21.
COVID-19 related non-pharmaceutical interventions (NPIs) led to a suppression of RSV circulation in winter 2020/21 in the UK and an off-season resurgence in Summer 2021. We explore how the parameters of RSV epidemiology shape the size and dynamics of post-suppression resurgence and what we can learn about them from the resurgence patterns observed so far.
We developed an age-structured dynamic transmission model of RSV and sampled the parameters governing RSV seasonality, infection susceptibility and post-infection immunity, retaining simulations fitting the UK's pre-pandemic epidemiology by a set of global criteria consistent with likelihood calculations. From Spring 2020 to Summer 2021 we assumed a reduced contact frequency, returning to pre-pandemic levels from Spring 2021. We simulated transmission forwards until 2023 and evaluated the impact of the sampled parameters on the projected trajectories of RSV hospitalisations and compared these to the observed resurgence.
Simulations replicated an out-of-season resurgence of RSV in 2021. If unmitigated, paediatric RSV hospitalisation incidence in the 2021/22 season was projected to increase by 30-60% compared to pre-pandemic levels. The increase was larger if infection risk was primarily determined by immunity acquired from previous exposure rather than age-dependent factors, exceeding 90 % and 130 % in 1-2 and 2-5 year old children, respectively. Analysing the simulations replicating the observed early outbreak in 2021 in addition to pre-pandemic RSV data, we found they were characterised by weaker seasonal forcing, stronger age-dependence of infection susceptibility and higher baseline transmissibility.
COVID-19 mitigation measures in the UK stopped RSV circulation in the 2020/21 season and generated immunity debt leading to an early off-season RSV epidemic in 2021. A stronger dependence of infection susceptibility on immunity from previous exposure increases the size of the resurgent season. The early onset of the RSV resurgence in 2021, its marginally increased size relative to previous seasons and its decline by January 2022 suggest a stronger dependence of infection susceptibility on age-related factors, as well as a weaker effect of seasonality and a higher baseline transmissibility. The pattern of resurgence has been complicated by contact levels still not back to pre-pandemic levels. Further fitting of RSV resurgence in multiple countries incorporating data on contact patterns will be needed to further narrow down these parameters and to better predict the pathogen's future trajectory, planning for a potential expansion of new immunisation products against RSV in the coming years.
COVID-19 相关的非药物干预（NPIs）导致 2020/21 年冬季英国 RSV 传播受到抑制，并在 2021 年夏季出现淡季反弹。我们探讨了 RSV 流行病学的参数如何影响反弹后的规模和动态，以及从目前观察到的反弹模式中我们可以了解到什么。
我们开发了一种 RSV 的年龄结构动态传播模型，并对 RSV 季节性、感染易感性和感染后免疫力的参数进行了抽样，保留了通过一套与似然计算一致的全球标准拟合英国大流行前流行病学的模拟。从 2020 年春季到 2021 年夏季，我们假设接触频率降低，从 2021 年春季开始恢复到大流行前水平。我们向前模拟传播，直到 2023 年，并评估抽样参数对 RSV 住院预测轨迹的影响，并将这些预测与观察到的反弹进行比较。
模拟复制了 2021 年 RSV 的淡季反弹。如果不加控制，与大流行前水平相比，2021/22 季节儿科 RSV 住院发病率预计将增加 30-60%。如果感染风险主要由以前暴露获得的免疫力决定，而不是由年龄相关因素决定，那么增加幅度会更大，1-2 岁和 2-5 岁儿童的增幅分别超过 90%和 130%。对模拟 2021 年早期暴发的情况进行分析，同时对大流行前 RSV 数据进行分析，我们发现这些情况的特点是季节性驱动因素较弱，感染易感性对年龄的依赖性较强，基线传染性较高。
英国的 COVID-19 缓解措施阻止了 2020/21 年 RSV 的传播，并产生了免疫债务，导致 2021 年夏季提前出现 RSV 疫情。感染易感性对以前暴露获得的免疫力的依赖性增强会增加反弹季节的规模。2021 年 RSV 反弹的早期发生、与前几个季节相比略有增加以及到 2022 年 1 月的下降表明，感染易感性对年龄相关因素的依赖性更强，季节性和基线传染性的影响更弱。接触水平尚未恢复到大流行前水平，使得反弹模式更加复杂。需要进一步拟合多个国家的 RSV 反弹情况，纳入接触模式数据，以进一步缩小这些参数的范围，并更好地预测病原体未来的轨迹，为未来几年 RSV 新免疫产品的潜在扩展做好规划。
