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Is there an association between household birthdays, which likely correspond to informal social gatherings, and COVID-19 infection?
This cross-sectional study used administrative health care data on 2.9 million households from the first 45 weeks of 2020 and found that, among households in the top decile of county COVID-19 prevalence, those with birthdays had 8.6 more diagnoses per 10 000 individuals compared with households without a birthday, a relative increase of 31% of county-level prevalence, an increase in COVID-19 diagnoses of 15.8 per 10 000 persons after a child birthday, and an increase in COVID-19 diagnoses of 5.8 per 10 000 among households with an adult birthday.
This study suggests that events that lead to small and informal social gatherings, such as birthdays, and in particular, children’s birthdays, are a potentially important source in SARS-CoV-2 transmission.
Many policies designed to stop the spread of COVID-19 address formal gatherings, such as workplaces and dining locations. Informal social gatherings are a potentially important mode of SARS-CoV-2 transmission, but studying their role in transmission is challenged by data and methodological limitations; birthdays offer an opportunity to empirically quantify the potential role of small social gatherings in COVID-19 spread.
To assess the association between social gatherings and SARS-CoV-2 transmission by studying whether COVID-19 rates increase after birthdays in a household.
Design, Setting, and Participants
This cross-sectional study used nationwide data from January 1 to November 8, 2020, from 2.9 million US households with private insurance to compare COVID-19 infections between households with and without a birthday in the preceding 2 weeks, stratified according to county-level COVID-19 prevalence in that week and adjusting for household size and both week- and county-specific differences. The study also compared how birthday-associated infection rates differed by type of birthday (eg, child vs adult birthday, or a milestone birthday such as a 50th birthday), county-level precipitation on the Saturday of each week (which could move gatherings indoors), political leanings in the county, and state shelter-in-place policies.
Main Outcomes and Measures
Household-level COVID-19 infection.
Among the 2.9 million households in the study, in the top decile of counties in COVID-19 prevalence, households with a birthday in the 2 weeks prior had 8.6 more diagnoses per 10 000 individuals (95% CI, 6.6-10.7 per 10 000 individuals) compared with households without a birthday in the 2 weeks prior, a relative increase of 31% above the county-level prevalence of 27.8 cases per 10 000 individuals, vs 0.9 more diagnoses per 10 000 individuals (95% CI, 0.6-1.3 per 10 000 individuals) in the fifth decile (P < .001 for interaction). Households in the tenth decile of COVID-19 prevalence had an increase in COVID-19 diagnoses of 15.8 per 10 000 persons (95% CI, 11.7-19.9 per 10 000 persons) after a child birthday, compared with an increase of 5.8 per 10 000 persons (95% CI, 3.7-7.9 per 10 000 persons) among households with an adult birthday (P < .001 in a test of interactions). No differences were found by milestone birthdays, county political leaning, precipitation, or shelter-in-place policies.
Conclusions and Relevance
This cross-sectional study suggests that birthdays, which likely correspond with social gatherings and celebrations, were associated with increased rates of diagnosed COVID-19 infection within households in counties with high COVID-19 prevalence.
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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.
Accepted for Publication: May 1, 2021.
Published Online: June 21, 2021. doi:10.1001/jamainternmed.2021.2915
Corresponding Author: Anupam B. Jena, MD, PhD, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115 (firstname.lastname@example.org).
Author Contributions: Drs Whaley and Jena had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Whaley, Cantor, Jena.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Whaley, Jena.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Whaley, Cantor, Jena.
Obtained funding: Whaley.
Administrative, technical, or material support: Whaley, Pera, Jena.
Conflict of Interest Disclosures: Dr Whaley reported receiving consulting fees from Doximity outside the submitted work. Dr Jena reported receiving personal fees from Pfizer, Bioverativ, Bristol Myers Squibb, Merck, Janssen, Edwards Life Sciences, Novartis, Amgen, Eli Lilly, Vertex, AstraZeneca, Celgene, Tesaro, Sanofi Aventis, Precision Health Economics, and Analysis Group outside the submitted work. No other disclosures were reported.
Funding/Support: Support was provided by grant 1K01AG061274 from the National Institutes on Aging (Dr Whaley).
Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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