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Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments
Narayanan Krishna.
Frost Isabel.
Heidarzadeh Anoosheh.
Tseng Katie K.
Banerjee Sayantan.
John Jacob.
Laxminarayan Ramanan.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1101/2020.04.03.20051995
Background: COVID-19 originated in China and has quickly spread worldwide causing a pandemic. Countries need rapid data on the prevalence of the virus in communities to enable rapid containment. However, the equipment, human and laboratory resources required for conducting individual RT-PCR is prohibitive. One technique to reduce the number of tests required is the pooling of samples for analysis by RT-PCR prior to testing. Methods: We conducted a mathematical analysis of pooling strategies for infection rate classification using group testing and for the identification of individuals by testing pooled clusters of samples. Findings: On the basis of the proposed pooled testing strategy we calculate the probability of false alarm, the probability of detection, and the average number of tests required as a function of the pool size. We find that when the sample size is 256, with a maximum pool size of 64, with only 7.3 tests on the average, we can distinguish between prevalences of 1% and 5% with a probability of detection of 95% and probability of false alarm of 4%. Interpretation: The pooling of RT-PCR samples is a cost-effective technique for providing much-needed course-grained data on the prevalence of COVID-19. This is a powerful tool in providing countries with information that can facilitate a response to the pandemic that is evidence-based and saves the most lives possible with the resources available.
www.medrxiv.org
2020
Artículo
https://www.medrxiv.org/content/medrxiv/early/2020/04/06/2020.04.03.20051995.full.pdf
Inglés
VIRUS RESPIRATORIOS
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