Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD).

Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models.

For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions (\({R_{0}}\) at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected.

When DCT is deployed in a population with an ongoing outbreak where \(\mathcal{O}\) (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.

接触者追踪是许多国家为遏制 SARS-CoV-2 传播而采用的几种策略之一。数字接触者追踪 (DCT) 使用手机应用程序等工具来提高追踪速度和覆盖范围。我们在一个大的流行病学参数空间中模拟了 DCT 对病毒传播的影响，这与当前有关 SARS-CoV-2 的文献一致。我们还将 DCT 与随机测试 (RT) 和社交距离 (SD) 相结合进行建模。

建模是通过两个独立开发的基于个体的（随机）模型完成的，这些模型使用蒙特卡洛技术，相互进行基准测试并针对两种类型的确定性模型进行基准测试。

目前对无症状 SARS-CoV-2 携带者数量（约 40%）、其传染性（与有症状携带者相似）、干预前的繁殖数（\({R_{0}}\)至少3) 我们发现 DCT 必须与 SD 和/或 RT 等其他干预措施相结合，才能将再生数降低到 1 以下。至少有60%的人口必须使用DCT系统，其效果才会显着。就其本身而言，DCT 无法将再生数降至 1 以下，除非几乎整个人口都使用 DCT 系统并严格遵守检疫和检测方案。由于 DCT 系统的使用率较低，DCT 仍然减少了感染人数。

当 DCT 部署在正在爆发的人群中，其中\(\mathcal{O}\) (0.1%) 的人群已经被感染时，DCT 干预的收益是以需要高达 15% 的人员投入为代价的。即使有足够的检测能力来检测每个被追踪的人，在疫情期间平均每天要隔离（以应对被追踪）的人口。