Evidence map›Paper›PMID 34135322›Full record

ArticleNature communications2021

Modeling the effectiveness of olfactory testing to limit SARS-CoV-2 transmission.

Daniel B Larremore, Derek Toomre, Roy Parker

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Modeling the Transmission Mitigation Impact of Testing for Infectious Diseases.medRxiv : the preprint server for health sciences · 2024
    Article
  4. Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Daniel B LarremoreDepartment of Computer Science, University of Colorado Boulder, Boulder, CO, USA. daniel.larremore@colorado.edu.ORCID 0000-0001-5273-5234
Derek ToomreDepartment of Cell Biology, Yale University School of Medicine, New Haven, CT, USA. derek.toomre@yale.edu.
Roy ParkerBioFrontiers Institute, University of Colorado Boulder, Boulder, CO, USA. roy.parker@colorado.edu.ORCID 0000-0002-8412-4152

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

A central problem in the COVID-19 pandemic is that there is not enough testing to prevent infectious spread of SARS-CoV-2, causing surges and lockdowns with human and economic toll. Molecular tests that detect viral RNAs or antigens will be unable to rise to this challenge unless testing capacity increases by at least an order of magnitude while decreasing turnaround times. Here, we evaluate an alternative strategy based on the monitoring of olfactory dysfunction, a symptom identified in 76-83% of SARS-CoV-2 infections-including those with no other symptoms-when a standardized olfaction test is used. We model how screening for olfactory dysfunction, with reflexive molecular tests, could be beneficial in reducing community spread of SARS-CoV-2 by varying testing frequency and the prevalence, duration, and onset time of olfactory dysfunction. We find that monitoring olfactory dysfunction could reduce spread via regular screening, and could reduce risk when used at point-of-entry for single-day events. In light of these estimated impacts, and because olfactory tests can be mass produced at low cost and self-administered, we suggest that screening for olfactory dysfunction could be a high impact and cost-effective method for broad COVID-19 screening and surveillance.

Indexed as

AnosmiaCommunicable Disease ControlCost-Benefit AnalysisCOVID-19COVID-19 Nucleic Acid TestingHumansMass ScreeningModels, TheoreticalPrevalenceTime FactorsViral Load

Identifiers

PMID34135322
PMCPMC8209051

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.