Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica.


Journal

Communications medicine
ISSN: 2730-664X
Titre abrégé: Commun Med (Lond)
Pays: England
ID NLM: 9918250414506676

Informations de publication

Date de publication:
22 Jul 2023
Historique:
received: 20 09 2022
accepted: 21 06 2023
medline: 23 7 2023
pubmed: 23 7 2023
entrez: 22 7 2023
Statut: epublish

Résumé

Variability in household secondary attack rates and transmission risks factors of SARS-CoV-2 remain poorly understood. We conducted a household transmission study of SARS-CoV-2 in Costa Rica, with SARS-CoV-2 index cases selected from a larger prospective cohort study and their household contacts were enrolled. A total of 719 household contacts of 304 household index cases were enrolled from November 21, 2020, through July 31, 2021. Blood specimens were collected from contacts within 30-60 days of index case diagnosis; and serum was tested for presence of spike and nucleocapsid SARS-CoV-2 IgG antibodies. Evidence of SARS-CoV-2 prior infections among household contacts was defined based on the presence of both spike and nucleocapsid antibodies. We fitted a chain binomial model to the serologic data, to account for exogenous community infection risk and potential multi-generational transmissions within the household. Overall seroprevalence was 53% (95% confidence interval (CI) 48-58%) among household contacts. The estimated household secondary attack rate is 34% (95% CI 5-75%). Mask wearing by the index case is associated with the household transmission risk reduction by 67% (adjusted odds ratio = 0.33 with 95% CI: 0.09-0.75) and not sharing bedroom with the index case is associated with the risk reduction of household transmission by 78% (adjusted odds ratio = 0.22 with 95% CI 0.10-0.41). The estimated distribution of household secondary attack rates is highly heterogeneous across index cases, with 30% of index cases being the source for 80% of secondary cases. Modeling analysis suggests that behavioral factors are important drivers of the observed SARS-CoV-2 transmission heterogeneity within the household. When living in the same house with known SARS-CoV-2 cases, household members may change their behavior and adopt preventive measures to reduce the spread of SARS-CoV-2. To understand how behavioral factors affect SARS-CoV-2 spreading in household settings, we focused on household members of individuals with laboratory-confirmed SARS-CoV-2 infections and followed the way SARS-CoV-2 spread within the household, by looking at who had antibodies against the virus, which means they were infected. We also asked participants detailed questions about their behavior and applied mathematical modeling to evaluate its impact on SARS-CoV-2 transmission. We found that mask-wearing by the SARS-CoV-2 cases, and avoiding sharing a bedroom with the infected individuals, reduces SARS-CoV-2 transmission. However, caring for SARS-CoV-2 cases, and prolonged interaction with infected individuals facilitate SARS-CoV-2 spreading. Our study helps inform what behaviors can help reduce SARS-CoV-2 transmission within a household.

Autres résumés

Type: plain-language-summary (eng)
When living in the same house with known SARS-CoV-2 cases, household members may change their behavior and adopt preventive measures to reduce the spread of SARS-CoV-2. To understand how behavioral factors affect SARS-CoV-2 spreading in household settings, we focused on household members of individuals with laboratory-confirmed SARS-CoV-2 infections and followed the way SARS-CoV-2 spread within the household, by looking at who had antibodies against the virus, which means they were infected. We also asked participants detailed questions about their behavior and applied mathematical modeling to evaluate its impact on SARS-CoV-2 transmission. We found that mask-wearing by the SARS-CoV-2 cases, and avoiding sharing a bedroom with the infected individuals, reduces SARS-CoV-2 transmission. However, caring for SARS-CoV-2 cases, and prolonged interaction with infected individuals facilitate SARS-CoV-2 spreading. Our study helps inform what behaviors can help reduce SARS-CoV-2 transmission within a household.

Identifiants

pubmed: 37481623
doi: 10.1038/s43856-023-00325-6
pii: 10.1038/s43856-023-00325-6
pmc: PMC10363136
doi:

Types de publication

Journal Article

Langues

eng

Pagination

102

Investigateurs

Amada Aparicio (A)
Karla Moreno (K)
Roy Wong (R)
Melvin Morera (M)
Arturo Abdelnour (A)
Alejandro Calderón (A)
Kattia Camacho (K)
Gabriela Ivankovich (G)
Adriana Yock (A)
Roberto Castro (R)
Bernal Cortés (B)
Viviana Loría (V)
Rebecca Ocampo (R)
Cristina Barboza-Solis (C)
Romain Fantin (R)

Commentaires et corrections

Type : UpdateOf

Informations de copyright

© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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Auteurs

Kaiyuan Sun (K)

Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health (NIH), Bethesda, MD, USA. kaiyuan.sun@nih.gov.

Viviana Loria (V)

Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica.

Amada Aparicio (A)

Caja Costarricense de Seguro Social, San José, Costa Rica.

Carolina Porras (C)

Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica.

Juan Carlos Vanegas (JC)

Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica.

Michael Zúñiga (M)

Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica.

Melvin Morera (M)

Caja Costarricense de Seguro Social, San José, Costa Rica.

Carlos Avila (C)

Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica.

Arturo Abdelnour (A)

Caja Costarricense de Seguro Social, San José, Costa Rica.

Mitchell H Gail (MH)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA.

Ruth Pfeiffer (R)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA.

Jeffrey I Cohen (JI)

Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda, MD, USA.

Peter D Burbelo (PD)

National Institute of Dental and Craniofacial Research, NIH, Bethesda, MD, USA.

Mehdi A Abed (MA)

National Institute of Dental and Craniofacial Research, NIH, Bethesda, MD, USA.

Cécile Viboud (C)

Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health (NIH), Bethesda, MD, USA.

Allan Hildesheim (A)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA.

Rolando Herrero (R)

Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica.

D Rebecca Prevots (DR)

Epidemiology and Population Studies Unit, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, NIAID, NIH, Bethesda, MD, USA. rprevots@niaid.nih.gov.

Classifications MeSH