English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Repeated asymptomatic screening for SARS-CoV-2 promises to control spread ofthe virus but would require too many resources to implement at scale. Grouptesting is promising for screening more people with fewer test resources:multiple samples tested together in one pool can be excluded with one negativetest result. Existing approaches to group testing design for SARS-CoV-2asymptomatic screening, however, do not consider dilution effects: that falsenegatives become more common with larger pools. As a consequence, they mayrecommend pool sizes that are too large or misestimate the benefits ofscreening. Modeling dilution effects, we derive closed-form expressions for theexpected number of tests and false negative/positives per person screened undertwo popular group testing methods: the linear and square array methods. We findthat test error correlation induced by a common viral load across anindividual's samples results in many fewer false negatives than would beexpected from less realistic but more widely assumed independent errors. Thisinsight also suggests that false positives can be controlled through repeatedtests without significantly increasing false negatives. Using these closed-formexpressions to trace a Pareto frontier over error rates and tests, we designtesting protocols for repeated asymptomatic screening of a large population. Weminimize disease prevalence by optimizing a time-varying pool sizes andscreening frequency constrained by daily test capacity and a false positivelimit. This provides a testing protocol practitioners can use for mitigatingCOVID-19. In a case study, we demonstrate the effectiveness of this methodologyin controlling spread.

Group Testing Enables Asymptomatic Screening for COVID-19 Mitigation: Feasibility and Optimal Pool Size Selection with Dilution Effects