Evidence map›Paper›PMID 33790635›Full record

ArticleInternational journal of general medicine2021

Characteristics and Behaviors Associated with Prevalent SARS-CoV-2 Infection.

Sidney Aung, Eric Vittinghoff, Gregory Nah, Noah D Peyser, Mark J Pletcher, Jeffrey E Olgin, Gregory M Marcus

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. A common allele of HLA mediates asymptomatic SARS-CoV-2 infection.medRxiv : the preprint server for health sciences · 2022
    Article
  3. Review
  4. Article
  5. Article
  6. Digital Citizen Science for Responding to COVID-19 Crisis: Experiences from Iran.International journal of environmental research and public health · 2021
    Article
  7. Article
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

7 authors at 1 institution in 1 country.

Sidney AungDivision of Cardiology, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-7491-314X
Eric VittinghoffDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Gregory NahDivision of Cardiology, University of California, San Francisco, San Francisco, CA, USA.
Noah D PeyserDivision of Cardiology, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0003-4529-8325
Mark J PletcherDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Jeffrey E OlginDivision of Cardiology, University of California, San Francisco, San Francisco, CA, USA.
Gregory M MarcusDivision of Cardiology, University of California, San Francisco, San Francisco, CA, USA.
University of California, San Francisco · US

Funding

The Health ePeople Resource for Mobilized ResearchU2CEB021881 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARCUS, GREGORY M, OLGIN, JEFFREY E · 2015 to 2020
$10.3M
MHC Variation in Host Response to SARS-CoV2 and COVID-19 OutcomesR01AI159260 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HOLLENBACH, JILL ALLISON · 2021 to 2025
$4.0M
NIAID NIH HHS R01 AI159260
6 · The paper itself

Abstract

introductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (Covid-19), has been a serious threat to global health. Previous work has focused primarily on hospitalized patients or on identifying risk factors for disease severity and mortality once the infection has taken place. We sought to leverage the ubiquity of smartphones and mobile applications to study risk factors for Covid-19 infection in a large, geographically heterogenous cohort.

methodsWe analyzed data obtained from the Covid-19 Citizen Science (CCS) Study, a worldwide, mobile application-based cohort. After employing forward selection to identify variables with p values < 0.1, multivariable logistic regression models were utilized to identify independent risk factors associated with prevalent SARS-CoV-2 infection.

resultsAmong 36,041 participants in 113 countries and all 50 states in the US, 484 participants had prevalent SARS-CoV-2 infection. After multivariable adjustment, being a healthcare worker, living with at least one school-aged child, having pets at home, and having immunodeficiency were each associated with an increased odds of SARS-CoV-2. The association between pets and prevalent SARS-CoV-2 was driven by dog ownership. After adjustment for the same covariates, Asian or Pacific Islander race, receiving a flu shot within the past year, increased level of education, and smoking or vaping marijuana within the last 30 days were each associated with a lower odds of SARS-CoV-2.

conclusionWe identified various characteristics and behaviors, many of which are potentially modifiable, associated with prevalent SARS-CoV-2 infection in a world-wide mobile application-based cohort.

Indexed as

cohort studyCOVID-19digital healthepidemiologymobile applications

Identifiers

PMID33790635
PMCPMC8006955
OpenAlexW3138744508

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.