Evidence map›Paper›PMID 34793320›Full record

ArticleJMIR public health and surveillance2021

Patterns of SARS-CoV-2 Testing Preferences in a National Cohort in the United States: Latent Class Analysis of a Discrete Choice Experiment.

Rebecca Zimba, Matthew L Romo, Sarah G Kulkarni, Amanda Berry, William You, Chloe Mirzayi, Drew A Westmoreland, Angela M Parcesepe, Levi Waldron, Madhura S Rane and 5 more

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Syringe Services Participants' Preferences for Wound Care, HIV/Hepatitis C Virus Screening, and Opioid Use Disorder Treatment: A Discrete Choice Experiment.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 2 institutions in 1 country.

Rebecca ZimbaInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0001-5278-3930
Matthew L RomoInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-3038-0644
Sarah G KulkarniInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-0807-339X
Amanda BerryInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0001-9084-7771
William YouInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-9081-2322
Chloe MirzayiInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-9817-2868
Drew A WestmorelandInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0003-4085-7941
Angela M ParcesepeDepartment of Maternal and Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, United States.ORCID 0000-0002-4321-125X
Levi WaldronInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0003-2725-0694
Madhura S RaneInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-8179-9103
Shivani KochharInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-2752-5582
McKaylee M RobertsonInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-8426-6572
Andrew R MarokoInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-9398-2386
Christian GrovInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0001-6871-3531
Denis NashInstitute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, United States.ORCID 0000-0002-3280-5386
The Graduate Center, CUNY · USUniversity of North Carolina at Chapel Hill · US

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
Following a U.S. National Cohort of Vulnerable Men to Improve HIV Prevention and CareUH3AI133675 · NIAID · GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY · PI GROV, CHRISTIAN · 2019 to 2021
$6.9M
NIAID NIH HHS UH3 AI133675NICHD NIH HHS P2C HD050924
6 · The paper itself

Abstract

backgroundInadequate screening and diagnostic testing in the United States throughout the first several months of the COVID-19 pandemic led to undetected cases transmitting disease in the community and an underestimation of cases. Though testing supply has increased, maintaining testing uptake remains a public health priority in the efforts to control community transmission considering the availability of vaccinations and threats from variants.

objectiveThis study aimed to identify patterns of preferences for SARS-CoV-2 screening and diagnostic testing prior to widespread vaccine availability and uptake.

methodsWe conducted a discrete choice experiment (DCE) among participants in the national, prospective CHASING COVID (Communities, Households, and SARS-CoV-2 Epidemiology) Cohort Study from July 30 to September 8, 2020. The DCE elicited preferences for SARS-CoV-2 test type, specimen type, testing venue, and result turnaround time. We used latent class multinomial logit to identify distinct patterns of preferences related to testing as measured by attribute-level part-worth utilities and conducted a simulation based on the utility estimates to predict testing uptake if additional testing scenarios were offered.

resultsOf the 5098 invited cohort participants, 4793 (94.0%) completed the DCE. Five distinct patterns of SARS-CoV-2 testing emerged. Noninvasive home testers (n=920, 19.2% of participants) were most influenced by specimen type and favored less invasive specimen collection methods, with saliva being most preferred; this group was the least likely to opt out of testing. Fast-track testers (n=1235, 25.8%) were most influenced by result turnaround time and favored immediate and same-day turnaround time. Among dual testers (n=889, 18.5%), test type was the most important attribute, and preference was given to both antibody and viral tests. Noninvasive dual testers (n=1578, 32.9%) were most strongly influenced by specimen type and test type, preferring saliva and cheek swab specimens and both antibody and viral tests. Among hesitant home testers (n=171, 3.6%), the venue was the most important attribute; notably, this group was the most likely to opt out of testing. In addition to variability in preferences for testing features, heterogeneity was observed in the distribution of certain demographic characteristics (age, race/ethnicity, education, and employment), history of SARS-CoV-2 testing, COVID-19 diagnosis, and concern about the pandemic. Simulation models predicted that testing uptake would increase from 81.6% (with a status quo scenario of polymerase chain reaction by nasal swab in a provider's office and a turnaround time of several days) to 98.1% by offering additional scenarios using less invasive specimens, both viral and antibody tests from a single specimen, faster turnaround time, and at-home testing.

conclusionsWe identified substantial differences in preferences for SARS-CoV-2 testing and found that offering additional testing options would likely increase testing uptake in line with public health goals. Additional studies may be warranted to understand if preferences for testing have changed since the availability and widespread uptake of vaccines.

Indexed as

COVID-19SARS-CoV-2Cohort StudiesCOVID-19 TestingHumansLatent Class AnalysisPandemicsProspective StudiesUnited StatescohortCOVID-19diagnosticdiscrete choicediscrete choice experimentlatent class analysispatternpreferencepublic healthSARS-CoV-2testingtransmissiontrendUnited Statesuptakevaccine

Identifiers

PMID34793320
PMCPMC8722498
OpenAlexW3211475027

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.