dc.contributor.author
Pikovski, Alexander
dc.contributor.author
Bentele, Kajetan
dc.date.accessioned
2020-11-05T12:29:57Z
dc.date.available
2020-11-05T12:29:57Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/28776
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-28525
dc.description.abstract
Diagnostic testing for the novel coronavirus is an important tool to fight the coronavirus disease (Covid-19) pandemic. However, testing capacities are limited. A modified testing protocol, whereby a number of probes are 'pooled' (i.e. grouped), is known to increase the capacity for testing. Here, we model pooled testing with a double-average model, which we think to be close to reality for Covid-19 testing. The optimal pool size and the effect of test errors are considered. The results show that the best pool size is three to five, under reasonable assumptions. Pool testing even reduces the number of false positives in the absence of dilution effects.
en
dc.format.extent
4 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
epidemiology
en
dc.subject
laboratory tests
en
dc.subject
mathematical modelling
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
Pooling of coronavirus tests under unknown prevalence
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
e183
dcterms.bibliographicCitation.doi
10.1017/S0950268820001752
dcterms.bibliographicCitation.journaltitle
Epidemiology & Infection
dcterms.bibliographicCitation.volume
148
dcterms.bibliographicCitation.url
https://doi.org/10.1017/S0950268820001752
refubium.affiliation
Physik
refubium.funding
Open Access in Konsortiallizenz - Cambridge
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
0950-2688
dcterms.isPartOf.eissn
1469-4409
refubium.resourceType.provider
WoS-Alert