Evidence map›Paper›PMID 38324519›Full record

ArticlePLOS global public health2024

Self-tests for COVID-19: What is the evidence? A living systematic review and meta-analysis (2020-2023).

Apoorva Anand, Fiorella Vialard, Aliasgar Esmail, Faiz Ahmad Khan, Patrick O'Byrne, Jean-Pierre Routy, Keertan Dheda, Nitika Pant Pai

Abstract read
In one paragraph

Article in PLOS global public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

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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

8 authors.

Apoorva AnandCentre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Fiorella VialardCentre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.ORCID https://orcid.org/0000-0001-8575-436X
Aliasgar EsmailCentre for Lung Infection and Immunity, Division of Pulmonology, UCT Lung Institute and Department of Medicine, University of Cape Town, Cape Town, Western Cape, South Africa.
Faiz Ahmad KhanCentre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Patrick O'ByrneFaculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada.
Jean-Pierre RoutyInfectious Diseases and Immunity in Global Health, Research Institute of McGill University Health Centre, Montreal, Quebec, Canada.
Keertan DhedaCentre for Lung Infection and Immunity, Division of Pulmonology, UCT Lung Institute and Department of Medicine, University of Cape Town, Cape Town, Western Cape, South Africa.
Nitika Pant PaiCentre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.ORCID https://orcid.org/0000-0002-4672-0500

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 self-testing strategy (COVIDST) can rapidly identify symptomatic and asymptomatic SARS-CoV-2-infected individuals and their contacts, potentially reducing transmission. In this living systematic review, we evaluated the evidence for real-world COVIDST performance. Two independent reviewers searched six databases (PubMed, Embase, Web of Science, World Health Organization database, Cochrane COVID-19 registry, Europe PMC) for the period April 1st, 2020, to January 18th, 2023. Data on studies evaluating COVIDST against laboratory-based conventional testing and reported on diagnostic accuracy, feasibility, acceptability, impact, and qualitative outcomes were abstracted. Bivariate random effects meta-analyses of COVIDST accuracy were performed (n = 14). Subgroup analyses (by sampling site, symptomatic/asymptomatic infection, supervised/unsupervised strategy, with/without digital supports) were conducted. Data from 70 included studies, conducted across 25 countries with a median sample size of 817 (range: 28-784,707) were pooled. Specificity and DOR was high overall, irrespective of subgroups (98.37-99.71%). Highest sensitivities were reported for: a) symptomatic individuals (73.91%, 95%CI: 68.41-78.75%; n = 9), b) mid-turbinate nasal samples (77.79%, 95%CI: 56.03-90.59%; n = 14), c) supervised strategy (86.67%, 95%CI: 59.64-96.62%; n = 13), and d) use of digital interventions (70.15%, 95%CI: 50.18-84.63%; n = 14). Lower sensitivity was attributed to absence of symptoms, errors in test conduct and absence of supervision or a digital support. We found no difference in COVIDST sensitivity between delta and omicron pre-dominant period. Digital supports increased confidence in COVIDST reporting and interpretation (n = 16). Overall acceptability was 91.0-98.7% (n = 2) with lower acceptability reported for daily self-testing (39.5-51.1%). Overall feasibility was 69.0-100.0% (n = 5) with lower feasibility (35.9-64.6%) for serial self-testing. COVIDST decreased closures in school, workplace, and social events (n = 4). COVIDST is an effective rapid screening strategy for home-, workplace- or school-based screening, for symptomatic persons, and for preventing transmission during outbreaks. These data will guide COVIDST policy. Our review demonstrates that COVIDST has paved the way for self-testing in pandemics worldwide.

Identifiers

PMID38324519
PMCPMC10849237

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.