Group testing for SARS-CoV-2 allows for up to 10-fold efficiency increase across realistic scenarios and testing strategies is a research paper (2020). On theSindex it has a DataRank of 0.396. It has been cited 13 times.
We provide a comparison of general strategies for group testing in view of their application to medical diagnosis in the current COVID-19 pandemic. We find significant efficiency gaps between different group testing strategies in realistic scenarios for SARS-CoV-2 testing, highlighting the need for an informed decision of the pooling protocol depending on estimated prevalence, target specificity, and high- vs. low-risk population. For example, using one of the presented methods, all 1.47 million inhabitants of Munich, Germany, could be tested using only around 141 thousand tests if an infection rate up to 0.4% is assumed. Using 1 million tests, the 6.69 million inhabitants from the city of Rio de Janeiro, Brazil, could be tested as long as the infection rate does not exceed 1%. Altogether this work may help provide a basis for efficient upscaling of current testing procedures, fine grained towards the desired study population, e.g. cross-sectional versus health-care workers and adapted mixtures thereof. For comparative visualization and querying of the precomputed results we provide an interactive web application. The source code for computation is open and freely available.
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Base Score Contribution
0.396
From this paper's citation signal
Citation Network Contribution
0
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Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.