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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

Author

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  • Yueli Mei

    (School of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China
    Shanghai Jiao Tong University-Yale University Joint Center for Health Policy, Shanghai Jiao Tong University, Shanghai 200030, China)

  • Xiuyun Guo

    (School of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China)

  • Zhihao Chen

    (School of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China)

  • Yingzhi Chen

    (School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China)

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.

Suggested Citation

  • Yueli Mei & Xiuyun Guo & Zhihao Chen & Yingzhi Chen, 2022. "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," IJERPH, MDPI, vol. 19(10), pages 1-20, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:10:p:5943-:d:815055
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    References listed on IDEAS

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    1. Israel Edem Agbehadji & Bankole Osita Awuzie & Alfred Beati Ngowi & Richard C. Millham, 2020. "Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing," IJERPH, MDPI, vol. 17(15), pages 1-16, July.
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    4. Roland Diel & Norbert Hittel & Albert Nienhaus, 2021. "Point-of-Care COVID-19 Antigen Testing in Exposed German Healthcare Workers—A Cost Model," IJERPH, MDPI, vol. 18(20), pages 1-13, October.
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