Evidence map›Paper›PMID 36962883›Full record

ArticlePLOS global public health2023

Aligning staff schedules, testing, and isolation reduces the risk of COVID-19 outbreaks in carceral and other congregate settings: A simulation study.

Christopher M Hoover, Nicholas K Skaff, Seth Blumberg, Rena Fukunaga

Open access · goldFull text read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 39% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Rates of SARS-CoV-2 transmission between and into California state prisons.medRxiv : the preprint server for health sciences · 2023
    Article
  3. 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

4 authors at 3 institutions in 1 country.

Christopher M HooverFrancis I. Proctor Foundation, University of California, San Francisco, San Francisco, California, United States of America.ORCID https://orcid.org/0000-0003-1976-8493
Nicholas K SkaffCenters for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Seth BlumbergFrancis I. Proctor Foundation, University of California, San Francisco, San Francisco, California, United States of America.ORCID https://orcid.org/0000-0001-5495-4238
Rena FukunagaCenters for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Centers for Disease Control and Prevention · USSan Francisco General Hospital · USUniversity of California, San Francisco · US

Funding

ACL HHS U01CK000590NCEZID CDC HHS U01 CK000590
6 · The paper itself

Abstract

COVID-19 outbreaks in congregate settings remain a serious threat to the health of disproportionately affected populations such as people experiencing incarceration or homelessness, the elderly, and essential workers. An individual-based model accounting for individual infectiousness over time, staff work schedules, and testing and isolation schedules was developed to simulate community transmission of SARS-CoV-2 to staff in a congregate facility and subsequent transmission within the facility that could cause an outbreak. Systematic testing strategies in which staff are tested on the first day of their workweek were found to prevent up to 16% more infections than testing strategies unrelated to staff schedules. Testing staff at the beginning of their workweek, implementing timely isolation following testing, limiting test turnaround time, and increasing test frequency in high transmission scenarios can supplement additional mitigation measures to aid outbreak prevention in congregate settings.

Identifiers

PMID36962883
PMCPMC10022395
OpenAlexW4313598927

What OpenQuestion holds

Textfull text, public
LicenceCC0
measurements read35
identifiers read7
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.