The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention^1,2,3,4,5,6, but its epidemiological impact has remained uncertain⁷. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications: 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches: modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000–450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000–914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.

COVID-19 大流行见证了数字接触者追踪的出现，以帮助防止疾病的传播。手机应用程序记录应用程序用户之间的接近事件，当用户的 COVID-19 测试呈阳性时，可以立即通知他们最近的联系人。理论证据支持这一新的公共卫生干预措施^1,2,3,4,5,6，但其流行病学影响仍不确定⁷. 在这里，我们调查了从 2020 年 9 月 24 日发布到 2020 年 12 月底，国民健康服务 (NHS) COVID-19 应用程序对英格兰和威尔士的影响。它被大约 1650 万用户定期使用（占 28%总人口），并发送了大约 170 万份暴露通知：每个指示病例 4.2 份同意接触者追踪。我们估计，应用程序通知的个人随后出现症状并检测呈阳性的比例（二次发病率 (SAR)）为 6%，与手动追踪密切接触者的 SAR 相似。我们使用两种互补方法估算了应用程序避免的案例数量：基于通知和 SAR 的建模估计为 284,000（95% 的敏感性分析范围为 108,000–450,000），与相匹配的邻近地方当局的统计比较得出的估计值为 594,000（95% 置信区间为 317,000–914,000）。对于每个同意通知其联系人的案例，大约避免了一个案例。我们估计，应用程序使用率每增加一个百分点，案例数量就会减少 0.8%（使用建模）或 2.3%（使用统计分析）。这些发现支持在等待疫苗全面保护的人群中继续开发和部署此类应用程序。8%（使用建模）或 2.3%（使用统计分析）。这些发现支持在等待疫苗全面保护的人群中继续开发和部署此类应用程序。8%（使用建模）或 2.3%（使用统计分析）。这些发现支持在等待疫苗全面保护的人群中继续开发和部署此类应用程序。