4.7 Article

Mathematical Model and Optimization Methods of Wide-Scale Pooled Sample Testing for COVID-19

期刊

MATHEMATICS
卷 10, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/math10071183

关键词

COVID-19; nucleic acid testing; individual-sample testing; pooled testing; mass testing; probabilistic analysis

资金

  1. National Natural Science Foundation of China [51808559]
  2. Natural Science Foundation of Hunan Province [2019JJ50770]

向作者/读者索取更多资源

This study introduces the experience of pooled nucleic acid testing in China, presents two main pooled testing methods used in Wuhan and Qingdao, and proposes an improved pentagram mini-pooled testing method to speed up testing process and reduce costs. The study mathematically examines the principles and applicability conditions of pooled COVID-19 testing, providing a reference for other countries with different infection rates.
Currently, coronavirus disease 2019 (COVID-19) has become the most severe infectious disease affecting the world, which has spread around the world to more than 200 countries in 2020. Until the number of COVID-19 vaccines is insufficient, nucleic acid testing is considered as an effective way to screen virus carriers and control the spread of the virus. Considering that the medical resources and infection rates are different across various countries and regions, if all infected areas adopt the traditional individual nucleic acid testing method, the workload will be heavy and time-consuming. Therefore, this will not lead to the control of the pandemic. After Wuhan completed a citywide nucleic acid testing in May 2020, China basically controlled the spread of COVID-19 and entered the post-epidemic period. Since then, although some cities in China, such as Qingdao, Xinjiang, Beijing, and Dalian, have experienced a local epidemic resurgence, the pandemic was quickly suppressed through wide-scale pooled nucleic acid testing methods. Combined with the successful experience of mass nucleic acid testing in China, this study introduces two main pooled testing methods used in two cities with a population of more than ten million people, Wuhan's five-in-one and Qingdao's ten-in-one rapid pooled testing methods. This study proposes an improved method for optimising the second round of ten-in-one pooled testing, known as the pentagram mini-pooled testing method, which speeds up the testing process (as a result of reducing the numbers of testing by 40%) and significantly reduces the cost. Qingdao's optimised ten-in-one pooled testing method quickly screens out the infections by running fewer testing samples. This study also mathematically examines the probabilistic principles and applicability conditions for pooled testing of COVID-19. Herein, the study theoretically determines the optimal number of samples that could successfully be combined into a pool under different infection rates. Then, it quantitatively discusses the applicability and principles for choosing the pooled testing instead of individual testing. Overall, this research offers a reference for other countries with different infection rates to help them in implementing the mass testing for COVID-19 to reduce the spread of coronavirus.

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