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.

翻译：本文探讨了英国新冠疫情应对中的若干统计问题，重点关注那些我们认为在统计方法或数据呈现上存在疑问、并对公众认知或政府政策（或两者兼有）产生实质性影响的案例。我们讨论了新冠风险相关统计数据及应对措施风险的呈现方式，指出统计偏差往往呈现相反方向：夸大新冠风险的同时低估应对措施的风险。文中还探讨了生命损失数据呈现、超额死亡数据以及病例数据使用等方面的问题。同时分析了流行病模型中忽视个体差异所导致的后果，以及其他若干重要统计疏漏的影响。最后，通过为多个欧洲国家提供新的分析数据，本文检验了全面居家封锁措施对逆转感染浪潮必要性的证据。