School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel.
Sci Rep. 2021 Mar 18;11(1):6279. doi: 10.1038/s41598-021-85458-1.
The Corona virus disease has significantly affected lives of people around the world. Existing quarantine policies led to large-scale lock-downs because of the slow tracking of the infection paths, and indeed we see new waves of the disease. This can be solved by contact tracing combined with efficient testing policies. Since the number of daily tests is limited, it is crucial to exploit them efficiently to improve the outcome of contact tracing (technological or human-based epidemiological investigations). We develop a controlled testing framework to achieve this goal. The key is to test individuals with high probability of being infected to identify them before symptoms appear. These probabilities are updated based on contact tracing and test results. We demonstrate that the proposed method could reduce the quarantine and morbidity rates compared to existing methods by up to a 50%. The results clearly demonstrate the necessity of accelerating the epidemiological investigations by using technological contact tracing. Furthermore, proper use of the testing capacity using the proposed controlled testing methodology leads to significantly improved results under both small and large testing capacities. We also show that for small new outbreaks controlled testing can prevent the large spread of new waves. Author contributions statement: The authors contributed equally to this work, including conceptualization, analysis, methodology, software, and drafting the work.
冠状病毒病已极大地影响了世界各地人们的生活。由于对感染途径的追踪缓慢，现有的隔离政策导致了大规模的封锁，而事实上，我们看到了该病的新一波疫情。这可以通过接触者追踪与高效的检测策略相结合来解决。由于每日检测数量有限，因此有效地利用它们来改善接触者追踪的结果（基于技术或人类的流行病学调查）至关重要。我们开发了一个受控测试框架来实现这一目标。关键是要对高感染可能性的个体进行测试，以便在出现症状之前发现他们。这些概率基于接触者追踪和测试结果进行更新。我们证明，与现有方法相比，所提出的方法可将隔离和发病率降低多达 50%。结果清楚地表明，需要通过使用技术接触者追踪来加速流行病学调查。此外，通过使用所提出的受控测试方法，合理利用测试能力，可在小测试和大测试能力下都显著改善结果。我们还表明，对于小型新疫情，受控测试可以防止新疫情的大规模传播。作者贡献声明：作者对此项工作贡献相等，包括概念化、分析、方法、软件和起草工作。
