A Nonadaptive Combinatorial Group Testing Strategy to Facilitate Health Care Worker Screening during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) OutbreakCitation formats

  • External authors:
  • John H McDermott
  • Duncan Stoddard
  • Peter J Woolf
  • David Gokhale
  • Algy Taylor

Standard

A Nonadaptive Combinatorial Group Testing Strategy to Facilitate Health Care Worker Screening during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Outbreak. / McDermott, John H; Stoddard, Duncan; Woolf, Peter J; Ellingford, Jamie M; Gokhale, David; Taylor, Algy; Demain, Leigh A M; Newman, William G; Black, Graeme.

In: The Journal of molecular diagnostics : JMD, Vol. 23, No. 5, 01.05.2021, p. 532-540.

Research output: Contribution to journalArticlepeer-review

Harvard

APA

Vancouver

Author

McDermott, John H ; Stoddard, Duncan ; Woolf, Peter J ; Ellingford, Jamie M ; Gokhale, David ; Taylor, Algy ; Demain, Leigh A M ; Newman, William G ; Black, Graeme. / A Nonadaptive Combinatorial Group Testing Strategy to Facilitate Health Care Worker Screening during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Outbreak. In: The Journal of molecular diagnostics : JMD. 2021 ; Vol. 23, No. 5. pp. 532-540.

Bibtex

@article{fb5946b60df340ecab9e6bebdb4e0090,
title = "A Nonadaptive Combinatorial Group Testing Strategy to Facilitate Health Care Worker Screening during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Outbreak",
abstract = "Routine testing for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in health care workers (HCWs) is critical. Group testing strategies to increase capacity facilitate mass population testing but do not prioritize turnaround time, an important consideration for HCW screening. We propose a nonadaptive combinatorial (NAC) group testing strategy to increase throughput while facilitating rapid turnaround. NAC matrices were constructed for sample sizes of 700, 350, and 250. Matrix performance was tested by simulation under different SARS-CoV-2 prevalence scenarios of 0.1% to 10%. NAC matrices were compared versus Dorfman sequential (DS) group testing approaches. NAC matrices performed well at low prevalence levels, with an average of 97% of samples resolved after a single round of testing via the n = 700 matrix at a prevalence of 1%. In simulations of low to medium (0.1% to 3%) prevalence, all NAC matrices were superior to the DS strategy, measured by fewer repeated tests required. At very high prevalence levels (10%), the DS matrix was marginally superior, although both group testing approaches performed poorly at high prevalence levels. This strategy maximizes the proportion of samples resolved after a single round of testing, allowing prompt return of results to HCWs. This methodology may allow laboratories to adapt their testing scheme based on required throughput and the current population prevalence, facilitating a data-driven testing strategy.",
keywords = "COVID-19/diagnosis, COVID-19 Testing/economics, Disease Outbreaks, Health Personnel, Humans, Mass Screening/economics, SARS-CoV-2/isolation & purification",
author = "McDermott, {John H} and Duncan Stoddard and Woolf, {Peter J} and Ellingford, {Jamie M} and David Gokhale and Algy Taylor and Demain, {Leigh A M} and Newman, {William G} and Graeme Black",
note = "Funding Information: Supported by the Manchester NIHR BRC grant ISBRC-1215-20007 (W.G.N.) and a postdoctoral research fellowship from the Health Education England Genomics Education Programme (HEE GEP) (J.M.E.). Publisher Copyright: {\textcopyright} 2021 Association for Molecular Pathology and American Society for Investigative Pathology",
year = "2021",
month = may,
day = "1",
doi = "10.1016/j.jmoldx.2021.01.010",
language = "English",
volume = "23",
pages = "532--540",
journal = "The Journal of Molecular Diagnostics",
issn = "1525-1578",
publisher = "Association of Molecular Pathology",
number = "5",

}

RIS

TY - JOUR

T1 - A Nonadaptive Combinatorial Group Testing Strategy to Facilitate Health Care Worker Screening during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Outbreak

AU - McDermott, John H

AU - Stoddard, Duncan

AU - Woolf, Peter J

AU - Ellingford, Jamie M

AU - Gokhale, David

AU - Taylor, Algy

AU - Demain, Leigh A M

AU - Newman, William G

AU - Black, Graeme

N1 - Funding Information: Supported by the Manchester NIHR BRC grant ISBRC-1215-20007 (W.G.N.) and a postdoctoral research fellowship from the Health Education England Genomics Education Programme (HEE GEP) (J.M.E.). Publisher Copyright: © 2021 Association for Molecular Pathology and American Society for Investigative Pathology

PY - 2021/5/1

Y1 - 2021/5/1

N2 - Routine testing for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in health care workers (HCWs) is critical. Group testing strategies to increase capacity facilitate mass population testing but do not prioritize turnaround time, an important consideration for HCW screening. We propose a nonadaptive combinatorial (NAC) group testing strategy to increase throughput while facilitating rapid turnaround. NAC matrices were constructed for sample sizes of 700, 350, and 250. Matrix performance was tested by simulation under different SARS-CoV-2 prevalence scenarios of 0.1% to 10%. NAC matrices were compared versus Dorfman sequential (DS) group testing approaches. NAC matrices performed well at low prevalence levels, with an average of 97% of samples resolved after a single round of testing via the n = 700 matrix at a prevalence of 1%. In simulations of low to medium (0.1% to 3%) prevalence, all NAC matrices were superior to the DS strategy, measured by fewer repeated tests required. At very high prevalence levels (10%), the DS matrix was marginally superior, although both group testing approaches performed poorly at high prevalence levels. This strategy maximizes the proportion of samples resolved after a single round of testing, allowing prompt return of results to HCWs. This methodology may allow laboratories to adapt their testing scheme based on required throughput and the current population prevalence, facilitating a data-driven testing strategy.

AB - Routine testing for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in health care workers (HCWs) is critical. Group testing strategies to increase capacity facilitate mass population testing but do not prioritize turnaround time, an important consideration for HCW screening. We propose a nonadaptive combinatorial (NAC) group testing strategy to increase throughput while facilitating rapid turnaround. NAC matrices were constructed for sample sizes of 700, 350, and 250. Matrix performance was tested by simulation under different SARS-CoV-2 prevalence scenarios of 0.1% to 10%. NAC matrices were compared versus Dorfman sequential (DS) group testing approaches. NAC matrices performed well at low prevalence levels, with an average of 97% of samples resolved after a single round of testing via the n = 700 matrix at a prevalence of 1%. In simulations of low to medium (0.1% to 3%) prevalence, all NAC matrices were superior to the DS strategy, measured by fewer repeated tests required. At very high prevalence levels (10%), the DS matrix was marginally superior, although both group testing approaches performed poorly at high prevalence levels. This strategy maximizes the proportion of samples resolved after a single round of testing, allowing prompt return of results to HCWs. This methodology may allow laboratories to adapt their testing scheme based on required throughput and the current population prevalence, facilitating a data-driven testing strategy.

KW - COVID-19/diagnosis

KW - COVID-19 Testing/economics

KW - Disease Outbreaks

KW - Health Personnel

KW - Humans

KW - Mass Screening/economics

KW - SARS-CoV-2/isolation & purification

U2 - 10.1016/j.jmoldx.2021.01.010

DO - 10.1016/j.jmoldx.2021.01.010

M3 - Article

C2 - 33549858

VL - 23

SP - 532

EP - 540

JO - The Journal of Molecular Diagnostics

JF - The Journal of Molecular Diagnostics

SN - 1525-1578

IS - 5

ER -