About: Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments

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About: Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments
Creator	Narayanan, Krishna Banerjee, Sayantan Frost, Isabel Heidarzadeh, Anoosheh John, Jacob Laxminarayan, Ramanan Tseng, Katie
Source	MedRxiv
abstract	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.
has issue date	2020-04-06(xsd:dateTime)
bibo:doi	10.1101/2020.04.03.20051995
has license	medrxiv
sha1sum (hex)	9844f67f10c860b4525c462b9d8f13f3f6b3290d
schema:url	https://doi.org/10.1101/2020.04.03.20051995
resource representing a document's title	Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments
resource representing a document's body	covid:9844f67f10c860b4525c462b9d8f13f3f6b3290d#body_text
is schema:about of	named entity 'rapid' named entity 'Countries' named entity 'prevalence' named entity 'ENVIRONMENTS' named entity 'CONTAINMENT' named entity 'TESTING' named entity 'ESTIMATES' named entity 'COST' named entity 'PANDEMIC' named entity 'CAUSING' named entity 'POOLING' named entity 'DATA' named entity 'NEED' named entity 'VIRUS' named entity 'PRIOR TO' named entity 'LIMITED' named entity 'GENERATE' named entity 'RT-PCR' named entity 'RESOURCE' named entity 'SAMPLES' named entity 'POOLING' named entity 'LABORATORY RESOURCES' named entity 'REQUIRED' named entity 'POTENTIAL' named entity 'NGS' named entity 'TESTS' named entity 'PREVALENCE' named entity 'COMMUNITIES' named entity 'BACKGROUND' named entity 'INDIVIDUAL' named entity 'NUMBER OF' named entity 'EQUIPMENT' named entity 'COUNTRIES' named entity 'RT-PCR' named entity 'TO REDUCE' named entity 'HUMAN' named entity 'SPREAD' named entity 'COVID-19' named entity 'CHINA' named entity 'ANALYSIS' named entity 'SAMPLES' named entity 'ENABLE' named entity 'TECHNIQUE' named entity 'CONDUCTING' named entity 'WORLDWIDE' named entity 'RAPID' covid:arg/9844f67f10c860b4525c462b9d8f13f3f6b3290d named entity 'causing' named entity 'virus' named entity 'generate' named entity 'RT-PCR' named entity 'NGS' named entity 'infection rate' named entity 'RT-PCR' named entity 'PCR' named entity 'probability' named entity 'public health' named entity 'RT-PCR' named entity 'medRxiv' named entity 'antibodies' named entity 'virus' named entity 'coronaviruses' named entity 'medRxiv' named entity 'RT-PCR' named entity 'sample size' named entity 'COVID' named entity 'membrane filter' named entity 'infection' named entity 'Wuhan, China' named entity 'infection rate' named entity 'false alarms' named entity 'epidemiology' named entity 'SARS' named entity 'NGS' named entity 'virus' named entity 'Europe' named entity 'probability' named entity 'binary search tree' named entity 'COVID'

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