Evidence map›Paper›PMID 36763699›Full record

ArticlePloS one2023

Correlating global trends in COVID-19 cases with online symptom checker self-assessments.

Marc Zobel, Bernhard Knapp, Jama Nateqi, Alistair Martin

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 16% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

4 authors at 3 institutions in 1 country.

Marc ZobelData Science Department, Symptoma, Vienna, Austria.ORCID 0000-0003-2901-5567
Bernhard KnappData Science Department, Symptoma, Vienna, Austria.
Jama NateqiMedical Department, Symptoma, Attersee, Austria.ORCID 0000-0001-8194-2654
Alistair MartinData Science Department, Symptoma, Vienna, Austria.
Statistics Austria · ATAMS (Austria) · ATUniversity of Applied Sciences Technikum Wien · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOnline symptom checkers are digital health solutions that provide a differential diagnosis based on a user's symptoms. During the coronavirus disease 2019 (COVID-19) pandemic, symptom checkers have become increasingly important due to physical distance constraints and reduced access to in-person medical consultations. Furthermore, various symptom checkers specialised in the assessment of COVID-19 infection have been produced.

objectivesAssess the correlation between COVID-19 risk assessments from an online symptom checker and current trends in COVID-19 infections. Analyse whether those correlations are reflective of various country-wise quality of life measures. Lastly, determine whether the trends found in symptom checker assessments predict or lag relative to those of the COVID-19 infections. MATERIALS AND

methodsIn this study, we compile the outcomes of COVID-19 risk assessments provided by the symptom checker Symptoma (www.symptoma.com) in 18 countries with suitably large user bases. We analyse this dataset's spatial and temporal features compared to the number of newly confirmed COVID-19 cases published by the respective countries.

resultsWe find an average correlation of 0.342 between the number of Symptoma users assessed to have a high risk of a COVID-19 infection and the official COVID-19 infection numbers. Further, we show a significant relationship between that correlation and the self-reported health of a country. Lastly, we find that the symptom checker is, on average, ahead (median +3 days) of the official infection numbers for most countries.

conclusionWe show that online symptom checkers can capture the national-level trends in coronavirus infections. As such, they provide a valuable and unique information source in policymaking against pandemics, unrestricted by conventional resources.

Indexed as

COVID-19HumansQuality of LifeSelf-AssessmentSelf ReportSymptom Assessment

Identifiers

PMID36763699
PMCPMC9917242
OpenAlexW4319879825

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.