Pooled testing of traced contacts under superspreading dynamics.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
08
10
2021
accepted:
10
03
2022
revised:
07
04
2022
pubmed:
29
3
2022
medline:
12
4
2022
entrez:
28
3
2022
Statut:
epublish
Résumé
Testing is recommended for all close contacts of confirmed COVID-19 patients. However, existing pooled testing methods are oblivious to the circumstances of contagion provided by contact tracing. Here, we build upon a well-known semi-adaptive pooled testing method, Dorfman's method with imperfect tests, and derive a simple pooled testing method based on dynamic programming that is specifically designed to use information provided by contact tracing. Experiments using a variety of reproduction numbers and dispersion levels, including those estimated in the context of the COVID-19 pandemic, show that the pools found using our method result in a significantly lower number of tests than those found using Dorfman's method. Our method provides the greatest competitive advantage when the number of contacts of an infected individual is small, or the distribution of secondary infections is highly overdispersed. Moreover, it maintains this competitive advantage under imperfect contact tracing and significant levels of dilution.
Identifiants
pubmed: 35344547
doi: 10.1371/journal.pcbi.1010008
pii: PCOMPBIOL-D-21-01826
pmc: PMC8989305
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1010008Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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