论文标题
从每日死亡率数据中推断出英国的COVID-19致命感染轨迹：在英国封锁之前，感染已经下降了吗？
Inferring UK COVID-19 fatal infection trajectories from daily mortality data: were infections already in decline before the UK lockdowns?
论文作者
论文摘要
每天新感染的数量是有效流行管理的关键数量。可以通过测试随机种群样本相对直接估计它。没有这种直接的流行病学测量，需要使用其他方法来推断新病例的数量是否可能增加或减少：例如，使用从临床对疾病的临床反应中收集的数据估算病原体有效繁殖数R，R。对于COVID-19（SARS-COV-2），此类R估计在很大程度上取决于建模假设，因为可用的临床病例数据是机会性观察数据，这些数据是严重的时间混淆。鉴于此困难，回顾性地重建最小损害的可用数据感染的时间过程，使用最少的先验假设。贝叶斯反问题方法适用于英国对第一波联想19死亡的数据，疾病持续时间分布表明，在全英国锁定之前（2020年3月24日），致命的感染正在下降，瑞典的致命感染仅在一天之后才开始下降。使用Flaxman等人的模型对英国数据进行分析。 （2020年，自然584）在放宽其先前的R上的假设下给出了相同的结果，这表明在英国不完全锁定的非药物干预措施（NPI）的作用增强。随后的两个锁定似乎发生了类似的模式。自从原始出版以来获得的英国主要统计监视调查的估计值支持这些结果。该论文的复制代码可在DOI/10.1111/BIOM.13462的支持信息中获得。
The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the number of new cases is likely to be increasing or decreasing: for example, estimating the pathogen effective reproduction number, R, using data gathered from the clinical response to the disease. For Covid-19 (SARS-CoV-2) such R estimation is heavily dependent on modelling assumptions, because the available clinical case data are opportunistic observational data subject to severe temporal confounding. Given this difficulty it is useful to retrospectively reconstruct the time course of infections from the least compromised available data, using minimal prior assumptions. A Bayesian inverse problem approach applied to UK data on first wave Covid-19 deaths and the disease duration distribution suggests that fatal infections were in decline before full UK lockdown (24 March 2020), and that fatal infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. (2020, Nature 584) gives the same result under relaxation of its prior assumptions on R, suggesting an enhanced role for non pharmaceutical interventions (NPIs) short of full lock down in the UK context. Similar patterns appear to have occurred in the subsequent two lockdowns. Estimates from the main UK Covid statistical surveillance surveys, available since original publication, support these results. Replication code for the paper is available in the supporting information of doi/10.1111/biom.13462.
