Evidence map›Paper›PMID 32511531›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Risk of COVID-19 among frontline healthcare workers and the general community: a prospective cohort study.

Long H Nguyen, David A Drew, Amit D Joshi, Chuan-Guo Guo, Wenjie Ma, Raaj S Mehta, Daniel R Sikavi, Chun-Han Lo, Sohee Kwon, Mingyang Song and 20 more

Registry-linked trialAbstract 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. It is linked to trial NCT04477213 (Risk Profiling of the Occupational Exposure of COVID-19 to Healthcare Workers- A Multicentric Retrospective Study), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

NCT04477213 completednot on this mapstarted 2021, after this paper: background citation

Risk Profiling of the Occupational Exposure of COVID-19 to Healthcare Workers- A Multicentric Retrospective Study

TypeobservationalSponsorNMC Specialty HospitalRan2021 to 2021Enrolled286ConditionsCOVID19, Healthcare Workers
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

30 authors.

Long H NguyenDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
David A DrewDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Amit D JoshiDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Chuan-Guo GuoDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Wenjie MaDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Raaj S MehtaDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Daniel R SikaviDepartment of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Chun-Han LoDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Sohee KwonDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Mingyang SongDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.
Lorelei A MucciDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Meir J StampferDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Walter C WillettDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
A Heather EliassenDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Jaime E HartChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Jorge E ChavarroDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Janet W Rich-EdwardsDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Richard DaviesZoe Global Limited. London, U.K.
Joan CapdevilaZoe Global Limited. London, U.K.
Karla A LeeDepartment of Twin Research and Genetic Epidemiology, King's College London, London, U.K.
Mary Ni LochlainnDepartment of Twin Research and Genetic Epidemiology, King's College London, London, U.K.
Thomas VarsavskySchool of Biomedical Engineering & Imaging Sciences, King's College London. London, U.K.
Mark S GrahamSchool of Biomedical Engineering & Imaging Sciences, King's College London. London, U.K.
Carole H SudreSchool of Biomedical Engineering & Imaging Sciences, King's College London. London, U.K.
M Jorge CardosoSchool of Biomedical Engineering & Imaging Sciences, King's College London. London, U.K.
Jonathan WolfZoe Global Limited. London, U.K.
Sebastien OurselinSchool of Biomedical Engineering & Imaging Sciences, King's College London. London, U.K.
Claire J StevesDepartment of Twin Research and Genetic Epidemiology, King's College London, London, U.K.
Tim D SpectorDepartment of Twin Research and Genetic Epidemiology, King's College London, London, U.K.
Andrew T ChanDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA.

Funding

Integrating lifecourse approaches, biologic and digital phenotypes in support of heart and lung disease epidemiologic researchU01HL145386 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI CHAVARRO, JORGE EDUARDO, MANSON, JOANN ELISABETH · 2019 to 2025
$17.8M
NHLBI NIH HHS U01 HL145386
6 · The paper itself

Abstract

Background: Data for frontline healthcare workers (HCWs) and risk of SARS-CoV-2 infection are limited and whether personal protective equipment (PPE) mitigates this risk is unknown. We evaluated risk for COVID-19 among frontline HCWs compared to the general community and the influence of PPE. Methods: We performed a prospective cohort study of the general community, including frontline HCWs, who reported information through the COVID Symptom Study smartphone application beginning on March 24 (United Kingdom, U.K.) and March 29 (United States, U.S.) through April 23, 2020. We used Cox proportional hazards modeling to estimate multivariate-adjusted hazard ratios (aHRs) of a positive COVID-19 test. Findings: Among 2,035,395 community individuals and 99,795 frontline HCWs, we documented 5,545 incident reports of a positive COVID-19 test over 34,435,272 person-days. Compared with the general community, frontline HCWs had an aHR of 11·6 (95% CI: 10·9 to 12·3) for reporting a positive test. The corresponding aHR was 3·40 (95% CI: 3·37 to 3·43) using an inverse probability weighted Cox model adjusting for the likelihood of receiving a test. A symptom-based classifier of predicted COVID-19 yielded similar risk estimates. Compared with HCWs reporting adequate PPE, the aHRs for reporting a positive test were 1·46 (95% CI: 1·21 to 1·76) for those reporting PPE reuse and 1·31 (95% CI: 1·10 to 1·56) for reporting inadequate PPE. Compared with HCWs reporting adequate PPE who did not care for COVID-19 patients, HCWs caring for patients with documented COVID-19 had aHRs for a positive test of 4·83 (95% CI: 3·99 to 5·85) if they had adequate PPE, 5·06 (95% CI: 3·90 to 6·57) for reused PPE, and 5·91 (95% CI: 4·53 to 7·71) for inadequate PPE. Interpretation: Frontline HCWs had a significantly increased risk of COVID-19 infection, highest among HCWs who reused PPE or had inadequate access to PPE. However, adequate supplies of PPE did not completely mitigate high-risk exposures. Funding: Zoe Global Ltd., Wellcome Trust, EPSRC, NIHR, UK Research and Innovation, Alzheimer's Society, NIH, NIOSH, Massachusetts Consortium on Pathogen Readiness.

Identifiers

PMID32511531
PMCPMC7273299

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

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.