Evidence map›Paper›PMID 35627479›Full record

SynthesisInternational journal of environmental research and public health2022

An Effective Mechanism for the Early Detection and Containment of Healthcare Worker Infections in the Setting of the COVID-19 Pandemic: A Systematic Review and Meta-Synthesis.

Yueli Mei, Xiuyun Guo, Zhihao Chen, Yingzhi Chen

Abstract readSystematic Review
In one paragraph

Synthesis in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Yueli MeiSchool of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China.ORCID 0000-0002-2670-0596
Xiuyun GuoSchool of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China.
Zhihao ChenSchool of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China.
Yingzhi ChenSchool of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China.ORCID 0000-0001-9087-9861

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has exposed healthcare workers (HCWs) to serious infection risks. In this context, the proactive monitoring of HCWs is the first step toward reducing intrahospital transmissions and safeguarding the HCW population, as well as reflecting the preparedness and response of the healthcare system. As such, this study systematically reviewed the literature on evidence-based effective monitoring measures for HCWs during the COVID-19 pandemic. This was followed by a meta-synthesis to compile the key findings, thus, providing a clearer overall understanding of the subject. Effective monitoring measures of syndromic surveillance, testing, contact tracing, and exposure management are distilled and further integrated to create a whole-process monitoring workflow framework. Taken together, a mechanism for the early detection and containment of HCW infections is, thus, constituted, providing a composite set of practical recommendations to healthcare facility leadership and policy makers to reduce nosocomial transmission rates while maintaining adequate staff for medical services. In this regard, our study paves the way for future studies aimed at strengthening surveillance capacities and upgrading public health system resilience, in order to respond more efficiently to future pandemic threats.

Indexed as

COVID-19Influenza, HumanContact TracingHealth PersonnelHumansPandemicscontainmentCOVID-19healthcare workersmonitoring mechanism

Identifiers

PMID35627479
PMCPMC9141359

What OpenQuestion holds

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LicenceCC BY
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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.