Evidence map›Paper›PMID 40377264›Full record

ArticleJournal of public health (Oxford, England)2025

A population-based case-control study of COVID-19: methodological considerations on the role of testing bias.

Romain Fantin, Carolina Porras, Amada Aparicio, Juan Carlos Vanegas, Viviana Loria, Melvin Morera, Arturo Abdelnour, Tim Waterboer, Julia Butt, Ruth M Pfeiffer and 5 more

Abstract read
In one paragraph

Article in Journal of public health (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Romain FantinAgencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, 10108 San José, Costa Rica.ORCID 0000-0003-2906-3438
Carolina PorrasAgencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, 10108 San José, Costa Rica.ORCID 0000-0002-4592-3883
Amada AparicioCaja Costarricense de Seguro Social, 10105-1000 San José, Costa Rica.
Juan Carlos VanegasAgencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, 10108 San José, Costa Rica.
Viviana LoriaAgencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, 10108 San José, Costa Rica.
Melvin MoreraCaja Costarricense de Seguro Social, 10105-1000 San José, Costa Rica.
Arturo AbdelnourCaja Costarricense de Seguro Social, 10105-1000 San José, Costa Rica.
Tim WaterboerDivision of Infections and Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.ORCID 0000-0002-0616-6963
Julia ButtDivision of Infections and Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.ORCID 0000-0001-7738-8611
Ruth M PfeifferBiostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), 9609 Medical Center Dr. Room SG Rockville, MD 20850, USA.
D Rebecca PrevotsEpidemiology and Population Studies Section, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), 5601 Fishers LaneRoom 7D10 Rockville, MD 20852, USA.
Mitchell H GailBiostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), 9609 Medical Center Dr. Room SG Rockville, MD 20850, USA.
Allan HildesheimAgencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, 10108 San José, Costa Rica.
Rolando HerreroAgencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, 10108 San José, Costa Rica.
RESPIRA Study Group

Funding

Costa Rican Biomedical Research Agency-Fundacion INCIENSADieter Morszeck FoundationDivisions of Intramural ResearchNational Institute of Allergy and Infectious DiseasesNCI NIH HHS HHSN261201700012I/75N91020F00001NIH HHSScience, Innovation, Technology and Telecommunications Ministry of Costa Rica N°FI-005-20
6 · The paper itself

Abstract

introductionTargeting people at risk of COVID-19 infection has been critical to containing the pandemic. Using only differences in cumulative incidence by sociodemographic groups can be misleading, as it reflects both factors related to infection risk and those related to testing for infection. The aim of this analysis was to disentangle the determinants of both mechanisms.

methodsWe compared the demographic, socioeconomic, and health characteristics of 813 PCR-confirmed COVID-19 cases over age 20 years with 1630 age- sex- and geography-matched population-based controls, both recruited in 2020-2021 in the RESPIRA study. We used antibody results and previous diagnosis to detect infections in population-based controls.

resultsHigh socioeconomic status and being older than 60 years old were negatively associated with seropositivity. Obesity and number of people living in the household were positively associated with seropositivity. Among infected (seropositive) people, diagnosis by PCR was more frequent in employees, and in people with asthma or hypertension, and was negatively associated with the number of people living in the household.

conclusionDifferences between PCR-confirmed cases and non-infected controls reflected differences both in risk of infection, and in PCR-testing in infected people. The possibility of PCR-testing bias in case-control studies of COVID should be considered in future research.

Indexed as

COVID-19COVID-19 TestingAdultAgedBiasCase-Control StudiesFemaleHumansMaleMiddle AgedRisk FactorsSARS-CoV-2Socioeconomic FactorsYoung AdultCosta RicaCOVID-19 serological testingCOVID-19 testingLatin Americamiddle-income countrysocial determinants of health

Identifiers

PMID40377264
PMCPMC12395947

What OpenQuestion holds

Textmetadata
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Registered trials

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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.