Some statistical aspects of the Covid-19 response

Simon N. Wood, Ernst C. Wit, Paul M. McKeigue, Danshu Hu, Beth Flood, Lauren Corcoran, Thea Abou Jawad
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Abstract

This paper discusses some statistical aspects of the U.K. Covid-19 pandemic response, focussing particularly on cases where we believe that a statistically questionable approach or presentation has had a substantial impact on public perception, or government policy, or both. We discuss the presentation of statistics relating to Covid risk, and the risk of the response measures, arguing that biases tended to operate in opposite directions, overplaying Covid risk and underplaying the response risks. We also discuss some issues around presentation of life loss data, excess deaths and the use of case data. The consequences of neglect of most individual variability from epidemic models, alongside the consequences of some other statistically important omissions are also covered. Finally the evidence for full stay at home lockdowns having been necessary to reverse waves of infection is examined, with new analyses provided for a number of European countries.
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Covid-19 反应的一些统计问题
本文讨论了英国 Covid-19 大流行应对措施的一些统计方面的问题,尤其侧重于我们认为统计上有问题的方法或表述对公众看法或政府政策或两者都产生了重大影响的案例。我们讨论了与 Covid 风险和应对措施风险有关的统计数据的表述,认为偏差往往会朝着相反的方向发展,即过分强调 Covid 风险,而轻视应对措施风险。我们还讨论了有关生命损失数据、超额死亡和病例数据使用的一些问题。我们还讨论了在流行病模型中忽略大多数个体变异性的后果,以及其他一些统计学上重要的忽略所造成的后果。最后,研究人员通过对一些欧洲国家进行新的分析,探讨了为扭转感染浪潮而有必要实施全面居家封锁的证据。
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