Effectiveness and policies analysis of pool testing method for COVID-19
- 7 September 2021
- journal article
- research article
- Published by Emerald in Kybernetes
- Vol. 52 (1), 64-74
- https://doi.org/10.1108/k-01-2021-0052
Abstract
This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully. The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected. If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N). This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round.Keywords
This publication has 22 references indexed in Scilit:
- What China’s coronavirus response can teach the rest of the worldNature, 2020
- First known person-to-person transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the USAThe Lancet, 2020
- Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreakProceedings of the National Academy of Sciences of the United States of America, 2020
- Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemicsInternational Journal of Health Geographics, 2020
- Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, ChinaScience China Life Sciences, 2020
- Feasibility of controlling COVID-19 outbreaks by isolation of cases and contactsThe Lancet. Global Health, 2020
- Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South AmericaEpidemiology and Infection, 2020
- Effects of media reporting on mitigating spread of COVID-19 in the early phase of the outbreakMathematical Biosciences and Engineering, 2020
- A mathematical model for the novel coronavirus epidemic in Wuhan, ChinaMathematical Biosciences and Engineering, 2020
- COVID-19 information propagation dynamics in the Chinese Sina-microblogMathematical Biosciences and Engineering, 2020