Interuniversity Institute of Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium.
Artificial Intelligence Lab, Department of computer science, Vrije Universiteit Brussel, Brussels, Belgium.
PLoS Comput Biol. 2021 Mar 9;17(3):e1008688. doi: 10.1371/journal.pcbi.1008688. eCollection 2021 Mar.
Outbreaks of SARS-CoV-2 are threatening the health care systems of several countries around the world. The initial control of SARS-CoV-2 epidemics relied on non-pharmaceutical interventions, such as social distancing, teleworking, mouth masks and contact tracing. However, as pre-symptomatic transmission remains an important driver of the epidemic, contact tracing efforts struggle to fully control SARS-CoV-2 epidemics. Therefore, in this work, we investigate to what extent the use of universal testing, i.e., an approach in which we screen the entire population, can be utilized to mitigate this epidemic. To this end, we rely on PCR test pooling of individuals that belong to the same households, to allow for a universal testing procedure that is feasible with the limited testing capacity. We evaluate two isolation strategies: on the one hand pool isolation, where we isolate all individuals that belong to a positive PCR test pool, and on the other hand individual isolation, where we determine which of the individuals that belong to the positive PCR pool are positive, through an additional testing step. We evaluate this universal testing approach in the STRIDE individual-based epidemiological model in the context of the Belgian COVID-19 epidemic. As the organisation of universal testing will be challenging, we discuss the different aspects related to sample extraction and PCR testing, to demonstrate the feasibility of universal testing when a decentralized testing approach is used. We show through simulation, that weekly universal testing is able to control the epidemic, even when many of the contact reductions are relieved. Finally, our model shows that the use of universal testing in combination with stringent contact reductions could be considered as a strategy to eradicate the virus.
SARS-CoV-2 的爆发正在威胁着全球多个国家的医疗体系。SARS-CoV-2 疫情的初步控制依赖于非药物干预措施,如社交距离、远程办公、口罩和接触者追踪。然而,由于无症状传播仍然是疫情的一个重要驱动因素,接触者追踪工作难以完全控制 SARS-CoV-2 疫情。因此,在这项工作中,我们研究了广泛检测(即对全体人群进行筛查的方法)在多大程度上可以用于减轻这种疫情。为此,我们依赖于对属于同一家庭的个体进行 PCR 测试混合,以实现一种可行的通用测试程序,同时利用有限的测试能力。我们评估了两种隔离策略:一方面是混合隔离,即隔离属于阳性 PCR 测试池的所有个体;另一方面是个体隔离,即通过额外的测试步骤确定属于阳性 PCR 池的个体中哪些是阳性的。我们在 STRIDE 基于个体的流行病学模型中评估了这种通用测试方法,并考虑了比利时 COVID-19 疫情的情况。由于组织广泛检测具有挑战性,我们讨论了与样本提取和 PCR 测试相关的不同方面,以证明在使用分散式测试方法时,广泛检测的可行性。我们通过模拟表明,即使许多接触减少措施得到缓解,每周进行广泛检测仍能够控制疫情。最后,我们的模型表明,将广泛检测与严格的接触减少措施结合使用,可以被视为一种消灭病毒的策略。