Evidence map›Paper›PMID 41347851›Full record

ArticleAmerican journal of epidemiology2026

Assessing SARS-CoV-2 transmission in African households from the reanalysis of serosurveys.

Lina Cristancho-Fajardo, Antoine Nkuba-Ndaye, Erica Simons, Nathanaël Hozé, Emilande Guichet, Yves Asuni Izia, Francis Ateba Ndongo, Placide Mbala-Kingebeni, Abou Aissata Soumah, Jacques Muzinga and 13 more

Abstract read
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Article in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

23 authors.

Lina Cristancho-FajardoMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, INSERM U1332, CNRS UMR2000, Paris, France.ORCID 0000-0001-7216-4037
Antoine Nkuba-NdayeInstitut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo.ORCID 0000-0003-2850-7498
Erica SimonsEpicentre, Paris, France.ORCID 0009-0004-2175-2954
Nathanaël HozéMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, INSERM U1332, CNRS UMR2000, Paris, France.ORCID 0000-0002-3977-8966
Emilande GuichetTransVIHMI, University of Montpellier, Institut de Recherche pour le Développement (IRD), INSERM, Montpellier, France.ORCID 0000-0003-0380-2044
Yves Asuni IziaMédecins Sans Frontières, Paris, France.
Francis Ateba NdongoDivision of Operational Research in Health, Ministry of Public Health of Cameroon, Yaoundé, Cameroon.ORCID 0000-0002-0745-1715
Placide Mbala-KingebeniInstitut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo.ORCID 0000-0003-1556-3570
Abou Aissata SoumahCentre de Recherche et de Formation en Infectiologie de Guinée (CERFIG), Université Gamal Abdel Nasser de Conakry, Conakry, Guinea.ORCID 0009-0009-1027-2302
Jacques MuzingaLaboratoire National de Lubumbashi, Lubumbashi, Democratic Republic of the Congo.ORCID 0000-0002-4483-116X
Paul Tshiminyi-MunkambaInstitut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo.
Mamadou Saliou Kalifa DialloTransVIHMI, University of Montpellier, Institut de Recherche pour le Développement (IRD), INSERM, Montpellier, France.ORCID 0000-0002-9742-8702
Anne-Cécile Zoung-Kanyi BissekDivision of Operational Research in Health, Ministry of Public Health of Cameroon, Yaoundé, Cameroon.ORCID 0009-0004-2300-0748
Sheila Makiala-MandandaInstitut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo.ORCID 0000-0002-4261-4399
Abdoulaye ToureCentre de Recherche et de Formation en Infectiologie de Guinée (CERFIG), Université Gamal Abdel Nasser de Conakry, Conakry, Guinea.ORCID 0000-0003-2269-6611
Steve Ahuka-MundekeInstitut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo.ORCID 0009-0009-5210-864X
Ahidjo AyoubaTransVIHMI, University of Montpellier, Institut de Recherche pour le Développement (IRD), INSERM, Montpellier, France.ORCID 0000-0002-5081-1632
Jean-François EtardTransVIHMI, University of Montpellier, Institut de Recherche pour le Développement (IRD), INSERM, Montpellier, France.ORCID 0000-0002-4873-0788
Martine PeetersTransVIHMI, University of Montpellier, Institut de Recherche pour le Développement (IRD), INSERM, Montpellier, France.ORCID 0000-0001-6738-8730
Benjamin RocheMIVEGEC, Université de Montpellier, IRD, CNRS, Montpellier, France.ORCID 0000-0001-7975-4232
Birgit NikolayEpicentre, Paris, France.ORCID 0000-0003-1291-7599
Eric DelaporteTransVIHMI, University of Montpellier, Institut de Recherche pour le Développement (IRD), INSERM, Montpellier, France.ORCID 0000-0002-1822-9853
Simon CauchemezMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, INSERM U1332, CNRS UMR2000, Paris, France.ORCID 0000-0001-9186-4549

Funding

Agence Française de Développement and the Ministère de l'Europe et des Affaires Etrangères, Francethe European Commission under the EU4Health programme 2021-2027 101102733-DURABLEthe European Union's Horizon 2020 research and innovation program under VEOthe INCEPTION projectthe Investissement d'Avenir program, the Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases ANR-10-LABX-62-IBEID
6 · The paper itself

Abstract

Household transmission studies provided key insights on SARS-CoV-2 transmission in high-income countries but were rarely implemented in Africa. To help fill this gap, we analyzed SARS-CoV-2 seroprevalence studies with a household-based recruitment, focusing on households with ≤7 members, in four Sub-Saharan African cities: Kinshasa (82 households, 370 individuals), Lubumbashi (225 households, 970 individuals), Conakry (149 households, 649 individuals), and Yaoundé (311 households, 1183 individuals), between late 2020 and mid-2021. Using an extended chain-binomial model accounting for missing serology, we estimated both the probability of community-acquired infection and within-household transmission. The proportion infected in the community rose sharply over time, reaching up to 73% by June 2021. Household transmission varied by location, with secondary attack rates ranging from 8.9% to 26.7%, and households accounting for 9% to 28% of infections. Simulations showed that including households with missing serology improved the precision of estimates without introducing bias. Secondary attack rate estimates were consistent with findings from South Africa and slightly lower than global pooled estimates, mostly from high-income settings, suggesting different transmission dynamics in African contexts. Our approach for handling missing serology can improve transmission estimates accuracy.

Indexed as

COVID-19Family CharacteristicsAdolescentAdultAfrica South of the SaharaChildFemaleHumansMaleMiddle AgedSARS-CoV-2Seroepidemiologic StudiesYoung Adultchain-binomial modelCOVID-19household transmissionmissing dataserosurveys

Identifiers

PMID41347851
PMCPMC13149013

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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.