Belloir Antoine, Blanquart François
Ecole Polytechnique, Route de Saclay, 91120 Palaiseau, France.
Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France; Infection Antimicrobials Modelling Evolution, UMR 1137, INSERM, Université de Paris, Paris, France.
Epidemics. 2021 Jun;35:100445. doi: 10.1016/j.epidem.2021.100445. Epub 2021 Feb 19.
To better control the SARS-CoV-2 pandemic, it is essential to quantify the impact of control measures and the fraction of infected individuals that are detected. To this end we developed a deterministic transmission model based on the renewal equation and fitted the model to daily case and death data in the first few months of 2020 in 79 countries and states, representing 4.2 billions individuals. Based on a region-specific infection fatality ratio, we inferred the time-varying probability of case detection and the time-varying decline in transmissiblity. As a validation, the predicted total number of infected was close to that found in serosurveys; more importantly, the inferred probability of detection strongly correlated with the number of daily tests per inhabitant, with 50 % detection achieved with 0.003 daily tests per inhabitants. Most of the decline in transmission was explained by the reductions in transmissibility (social distancing), which avoided 10 millions deaths in the regions studied over the first four months of 2020. In contrast, symptom-based testing and isolation of positive cases was not an efficient way to control the spread of the disease, as a large part of transmission happens before symptoms and only a small fraction of infected individuals was typically detected. The latter is explained by the limited number of tests available, and the fact that increasing test capacity often increases the probability of detection less than proportionally. Together these results suggest that little control can be achieved by symptom-based testing and isolation alone.
为了更好地控制新冠疫情，量化防控措施的影响以及已检测出的感染个体比例至关重要。为此，我们基于更新方程开发了一个确定性传播模型，并将该模型与2020年头几个月79个国家和地区（代表42亿人口）的每日病例和死亡数据进行拟合。基于特定地区的感染致死率，我们推断出随时间变化的病例检测概率以及随时间变化的传播性下降情况。作为验证，预测的感染总数与血清学调查结果相近；更重要的是，推断出的检测概率与人均每日检测次数密切相关，人均每日0.003次检测时可实现50%的检测率。传播率的下降主要是由于传播性降低（社交距离措施），在2020年的前四个月，这一措施在所研究的地区避免了1000万例死亡。相比之下，基于症状的检测和对阳性病例的隔离并非控制疾病传播的有效方式，因为很大一部分传播发生在出现症状之前，而且通常只有一小部分感染个体能被检测出来。后者的原因在于可用检测数量有限，以及增加检测能力往往不会使检测概率成比例增加。这些结果共同表明，仅靠基于症状的检测和隔离几乎无法实现有效防控。
