Evidence map›Paper›PMID 37163163›Full record

ArticleHeliyon2023

Evaluation of workplace infection prevention and control measures for COVID-19: A prospective cohort study in Japan.

Kazushirou Kurogi, Kazunori Ikegami, Hajime Ando, Ayako Hino, Mayumi Tsuji, Yu Igarashi, Tomohisa Nagata, Keiji Muramatsu, Yoshihisa Fujino

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

Article in Heliyon, 2023. 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
2.3field-weighted citation impact, top 11% 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

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 1 institution in 1 country.

Kazushirou KurogiDepartment of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Kazunori IkegamiDepartment of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Hajime AndoDepartment of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Ayako HinoDepartment of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Mayumi TsujiDepartment of Environmental Health, School of Medicine, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Yu IgarashiDisaster Occupational Health Center, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Tomohisa NagataDepartment of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Keiji MuramatsuDepartment of Public Health, School of Medicine, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
Yoshihisa FujinoDepartment of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, 1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-8555, Japan.
University of Occupational and Environmental Health Japan · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Encouraging the implementation of infection prevention and control (IPC) measures has been necessary to prevent workplace infections caused by the coronavirus disease 2019 (COVID-19). However, the effectiveness of these measures in reducing infections has not been thoroughly evaluated. We evaluated employees' COVID-19 infection rates in relation to the implementation of IPC measures at their workplaces to identify effective workplace measures. Methods: This prospective cohort study was conducted between December 2020 and December 2021 using Internet-based self-assessment questionnaires, with 11,982 participants included from the baseline. To estimate whether implementing workplace IPC measures was associated with COVID-19 incidence rates among participants, we estimated multivariate-adjusted relative risk (RR) using a log-binomial model. Results: After adjusting for sex, age, education, household members, occupation-related factors, and personal preventive behaviors, requesting ill employees to refrain from going to work showed significantly lower COVID-19 infection rates than not requesting it (RR: 0.56, 95% CI: 0.34-0.91, Conclusions: Employees restricted from reporting to work when ill had significantly lower COVID-19 infection rates than those who did not follow this measure. The results indicated that not coming to work when ill was effective in reducing COVID-19 infections at the workplace. We suggest that companies proactively adopt this policy and encourage their employees to comply with it.

Indexed as

COVID-19 infectionInfection controlInfection preventionProspective cohort studyWorkplace evaluation

Identifiers

PMID37163163
PMCPMC10156382
OpenAlexW4367856527

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.