Evidence map›Paper›PMID 33300008›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Household factors and the risk of severe COVID-like illness early in the US pandemic.

Denis Nash, Saba Qasmieh, McKaylee Robertson, Madhura Rane, Rebecca Zimba, Sarah Kulkarni, Amanda Berry, William You, Chloe Mirzayi, Drew Westmoreland and 6 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. 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, 8 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 3 institutions in 1 country.

Denis NashInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Saba QasmiehInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
McKaylee RobertsonInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Madhura RaneInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Rebecca ZimbaInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Sarah KulkarniInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Amanda BerryInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
William YouInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Chloe MirzayiInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Drew WestmorelandInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Angela ParcesepeDepartment of Maternal and Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA.
Levi WaldronInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Shivani KochharInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Andrew R MarokoInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Christian GrovInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
CHASING COVID Cohort Study Team
City University of New York · USThe Graduate Center, CUNY · USUniversity of North Carolina at Chapel Hill · US

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
Following a U.S. National Cohort of Vulnerable Men to Improve HIV Prevention and CareUH3AI133675 · NIAID · GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY · PI GROV, CHRISTIAN · 2019 to 2021
$6.9M
NIAID NIH HHS UH3 AI133675NICHD NIH HHS P2C HD050924
6 · The paper itself

Abstract

objectiveTo investigate the role of children in the home and household crowding as risk factors for severe COVID-19 disease.

methodsWe used interview data from 6,831 U.S. adults screened for the Communities, Households and SARS/CoV-2 Epidemiology (CHASING) COVID Cohort Study in April 2020.

resultsIn logistic regression models, the adjusted odds ratio [aOR] of hospitalization due to COVID-19 for having (versus not having) children in the home was 10.5 (95% CI:5.7-19.1) among study participants living in multi-unit dwellings and 2.2 (95% CI:1.2-6.5) among those living in single unit dwellings. Among participants living in multi-unit dwellings, the aOR for COVID-19 hospitalization among participants with more than 4 persons in their household (versus 1 person) was 2.5 (95% CI:1.0-6.1), and 0.8 (95% CI:0.15-4.1) among those living in single unit dwellings.

conclusionEarly in the US SARS-CoV-2 pandemic, certain household exposures likely increased the risk of both SARS-CoV-2 acquisition and the risk of severe COVID-19 disease.

Identifiers

PMID33300008
PMCPMC7724676
OpenAlexW3109669240

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.