Evidence map›Paper›PMID 33568097›Full record

ArticleBMC infectious diseases2021

Incidence and risk factors of COVID-19-like symptoms in the French general population during the lockdown period: a multi-cohort study.

Fabrice Carrat, Mathilde Touvier, Gianluca Severi, Laurence Meyer, Florence Jusot, Nathanael Lapidus, Delphine Rahib, Nathalie Lydié, Marie-Aline Charles, Pierre-Yves Ancel and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 48 citations in OpenAlex.

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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

15 authors at 4 institutions in 2 countries.

Fabrice CarratSorbonne Université, Inserm, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, 27 rue Chaligny, 75571 CEDEX 12, Paris, France. fabrice.carrat@iplesp.upmc.fr.ORCID http://orcid.org/0000-0002-8672-7918
Mathilde TouvierSorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France.
Gianluca SeveriCESP UMR1018, Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Villejuif, Paris, France.
Laurence MeyerUniversité Paris Saclay, Inserm, CESP U1018, Le Kremlin Bicêtre, Paris, France.
Florence JusotUniversité Paris-Dauphine, PSL-Research University, LEDa, Paris, France.
Nathanael LapidusSorbonne Université, Inserm, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, 27 rue Chaligny, 75571 CEDEX 12, Paris, France.
Delphine RahibSanté publique France, Saint-Maurice, France.
Nathalie LydiéSanté publique France, Saint-Maurice, France.
Marie-Aline CharlesIned, Inserm, EFS, UMS Elfe, Aubervilliers, Paris, France.
Pierre-Yves AncelObstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Epidemiology and Statistics Sorbonne Paris Cité, INSERM U1153, Paris Descartes University, Paris, France.
Alexandra RouquetteDepartment of Statistics, Computer Science and Applications, University of Florence, Florence, Italy.
Xavier de LamballerieUnité des Virus Emergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, IHU Méditerranée Infection, 13005, Marseille, France.
Marie ZinsParis University, Paris, France.
Nathalie BajosIRIS, Inserm/EHESS/CNRS, Aubervilliers, France.
SAPRIS study group
Inserm · FRCentre National de la Recherche Scientifique · FRInstitut national d'études démographiques · FRSanté Publique France · FR

Funding

Agence Nationale de la Recherche ANR-10-COHO-06Agence Nationale de la Recherche ANR-20-COVI-000Fondation pour la Recherche Médicale (FR) 20RR052-00INSERM C20-26
6 · The paper itself

Abstract

backgroundOur main objectives were to estimate the incidence of illnesses presumably caused by SARS-CoV-2 infection during the lockdown period and to identify the associated risk factors.

methodsParticipants from 3 adult cohorts in the general population in France were invited to participate in a survey on COVID-19. The main outcome was COVID-19-Like Symptoms (CLS), defined as a sudden onset of cough, fever, dyspnea, ageusia and/or anosmia, that lasted more than 3 days and occurred during the 17 days before the survey. We used delayed-entry Cox models to identify associated factors.

resultsBetween April 2, 2020 and May 12, 2020, 279,478 participants were invited, 116,903 validated the questionnaire and 106,848 were included in the analysis. Three thousand thirty-five cases of CLS were reported during 62,099 person-months of follow-up. The cumulative incidences of CLS were 6.2% (95% Confidence Interval (95%CI): 5.7%; 6.6%) on day 15 and 8.8% (95%CI 8.3%; 9.2%) on day 45 of lockdown. The risk of CLS was lower in older age groups and higher in French regions with a high prevalence of SARS-CoV-2 infection, in participants living in cities > 100,000 inhabitants (vs rural areas), when at least one child or adolescent was living in the same household, in overweight or obese people, and in people with chronic respiratory diseases, anxiety or depression or chronic diseases other than diabetes, cancer, hypertension or cardiovascular diseases.

conclusionThe incidence of CLS in the general population remained high during the first 2 weeks of lockdown, and decreased significantly thereafter. Modifiable and non-modifiable risk factors were identified.

Indexed as

Communicable Disease ControlAdolescentAdultAgedChildCohort StudiesComorbidityCoughCOVID-19FemaleFeverFranceHumansIncidenceMaleMiddle AgedCohortCOVID-19General populationIncidenceRisk factorsSARS-CoV-2

Identifiers

PMID33568097
PMCPMC7875161
OpenAlexW3126187449

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.