| Literature DB >> 35627479 |
Yueli Mei1,2, Xiuyun Guo1, Zhihao Chen1, Yingzhi Chen3.
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.Entities:
Keywords: COVID-19; containment; healthcare workers; monitoring mechanism
Mesh:
Year: 2022 PMID: 35627479 PMCID: PMC9141359 DOI: 10.3390/ijerph19105943
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1PRISMA flowchart showing the selection process.
Figure 2Included articles published between April 2020 and March 2022.
Figure 3Study locations of the included articles.
Study characteristics.
| No. | Study Characteristics and Summary Report | |
|---|---|---|
| 1 | Author | Zhang et al. [ |
| Month/Year | April 2020 | |
| Country | US | |
| Study Type | Observational study | |
| Measures | Syndromic Surveillance: A web-based mobile responsive HCW symptom screening application | |
| Results | Over a 7-day period, having quickly identified 0.36% symptomatic HCWs that otherwise could have come to work, increasing efficiency and effectiveness | |
| 2 | Author | Hunter et al. [ |
| Month/Year | April 2020 | |
| Country | UK | |
| Study Type | Observational study | |
| Measures | Testing: Testing of staff with compatible symptoms and conveying results rapidly via email | |
| Results | In 3 weeks, enabled 1414 (out of 1654) HCWs to return more rapidly to service | |
| 3 | Author | Treibel et al. [ |
| Month/Year | May 2020 | |
| Country | UK | |
| Study Type | Observational study | |
| Measures | Testing: Testing the asymptomatic HCWs especially during potential new waves of infection | |
| Results | Asymptomatic HCWs should be given easy access to testing, especially during new waves of infection | |
| 4 | Author | Wee et al. [ |
| Month/Year | May 2020 | |
| Country | Singapore | |
| Study Type | Observational study | |
| Measures | Syndromic Surveillance: Ongoing syndromic surveillance and centralized reporting of fever and ARI symptoms | |
| Results | Over a 16-week period, 14 cases of HCW infection and 4 clusters detected | |
| 5 | Author | Garzaro et al. [ |
| Month/Year | May 2020 | |
| Country | Italy | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: HCWs identified as low risk of exposure to self-monitor symptoms including cough, fever, dyspnoea, anosmia; | |
| Results | The monitoring measures having significantly reduced time between exposure, warning, and testing ( | |
| 6 | Author | Rivett et al. [ |
| Month/Year | May 2020 | |
| Country | UK | |
| Study Type | Observational Study | |
| Measures | Testing: Comprehensive testing of both symptomatic & asymptomatic HCWs | |
| Results | Data suggesting the true asymptomatic carriage rate being 0.5% | |
| 7 | Author | Khalil et al. [ |
| Month/Year (Accepted) | May 2020 | |
| Country | UK | |
| Study Type | Observational Study | |
| Measures | Testing: Universal testing of HCWs | |
| Results | 34% positive HCW cases being asymptomatic while 59% symptomatic HCWs tested negative, indicating crucial needs for routine testing of all HCWs to (1) identify asymptomatic infected HCWs in an early stage, and (2) mitigate staff shortages due to unnecessary quarantine | |
| 8 | Author | Flynn et al. [ |
| Month/Year | May 2020 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Testing: A drive-through testing model | |
| Results | The drive-through testing model having increased test efficiency, avoided long lines, conserved PPE | |
| 9 | Author | Buchtele et al. [ |
| Month/Year | May 2020 | |
| Country | Austria | |
| Study Type | Observational Study | |
| Measures | Contact Tracing & Exposure Management: Extensive contact tracing implemented among HCWs caring for immunocompromised patients, with all those having face-to-face contact with the confirmed case since the case’s onset of symptoms to get tested regardless of length of exposure | |
| Results | Extensive contact tracing and mass testing having prevented further spread of nosocomial transmission | |
| 10 | Author | Ho et al. [ |
| Month/Year | May 2020 | |
| Country | Singapore | |
| Study Type | Observational Study | |
| Measures | Contact Tracing & Exposure Management: RTLS-based (real-time location systems) contact tracing demonstrated having better validity than traditional EMR-based (electronic medical record) methods; | |
| Results | An integration of RTLS and EMR providing the best performance for contact tracing with a sensitivity of 77.8% and a specificity of 73.4% | |
| 11 | Author | Yombi et al. [ |
| Month/Year | May 2020 | |
| Country | Belgium | |
| Study Type | Observational Study | |
| Measures | Testing: Fever as a criterion for testing | |
| Results | Fever having a positive impact on the yield of PCR for SARS-CoV-2 ( | |
| 12 | Author | Blain et al. [ |
| Month/Year | June 2020 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Testing: A test-retest strategy | |
| Results | 11% asymptomatic HCWs with negative PCR results developing antibodies later in time | |
| 13 | Author | Wang et al. [ |
| Month/Year | July 2020 | |
| Country | Singapore | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: A comprehensive HCW sickness surveillance system: online reporting platform, medical screening, and testing for all the symptomatic HCWs | |
| Results | Despite enhanced monitoring mechanism, no HCW was identified with infection, suggesting universal testing of HCWs not necessary for hospitals with adequate PPE protocol | |
| 14 | Author | Villanueva et al. [ |
| Month/Year | July 2020 | |
| Country | Philippines | |
| Study Type | Observational Study | |
| Measures | Testing: Criteria for testing: close contact with or high-risk exposure to a COVID-19 case, presence of symptoms | |
| Results | Early screening for HCW infection having reduced nosocomial transmission | |
| 15 | Author | Mehta et al. [ |
| Month/Year | July 2020 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Contact Tracing & Exposure Management: Aggressive contact tracing enabling the identification & monitoring of asymptomatic and/or pre-symptomatic HCWs | |
| Results | Aggressive and effective contact tracing providing greater yield than mass testing of every individual | |
| 16 | Author | Kacmaz et al. [ |
| Month/Year | August 2020 | |
| Country | Turkey | |
| Study Type | Observational Study | |
| Measures | Testing: rapid antibody testing | |
| Results | Reliability of antibody testing needing further validation but useful in COVID-19 screening among HCWs to evaluate IPC measures and prevent intra-hospital infection | |
| 17 | Author | Tong et al. [ |
| Month/Year | August 2020 | |
| Country | China (Mainland) | |
| Study Type | Observational Study | |
| Measures | Testing: A combination of PCR testing, serological testing, and radiological assessment conducted among HCWs caring for COVID-19 patients in the early stage of the outbreak | |
| Results | With the measures taken, no nosocomial infection detected | |
| 18 | Author | Racine-Brzostek et al. [ |
| Month/Year | September 2020 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Testing: PCR + antibody testing | |
| Results | 100% PCR positive HCWs tested positive for antibody testing | |
| 19 | Author | Del Castillo et al. [ |
| Month/Year | September 2020 | |
| Country | Italy | |
| Study Type | Observational Study | |
| Measures | Testing: Serological testing followed by PCR testing if positive to IgG | |
| Results | Serological IgG testing combined with PCR testing found to be a valid screening intervention | |
| 20 | Author | Ho et al. [ |
| Month/Year | September 2020 | |
| Country | Singapore | |
| Study Type | Observational Study | |
| Measures | Contact Tracing & Exposure Management: Utility of surveillance technologies such as RTLS and CCTV systems to enhance HCW exposure management | |
| Results | ||
| 21 | Author | Chong et al. [ |
| Month/Year | October 2020 | |
| Country | Malaysia | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: HCWs with identifiable exposure risk under daily syndromic surveillance (self-assessment and self-reporting of symptoms through an online system) for 14 days since last exposure to an infection | |
| Results | In a period of 5 months, 2401 risk assessments carried out among 1408 HCWs | |
| 22 | Author | Chen et al. [ |
| Month/Year | November 2020 | |
| Country | China (Taiwan) | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: Centralized reporting of fever and ARI symptoms | |
| Results | With the measures taken, no HCW infection detected | |
| 23 | Author | Domeracki et al. [ |
| Month/Year | November 2020 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Testing: PCR cycle threshold (Ct) data used for HCW return to work (RTW) decisions | |
| Results | Initial Ct data significantly correlated with the time period between first diagnosis and RTW clearance (r = −0.80, | |
| 24 | Author | Buising et al. [ |
| Month/Year | November 2020 | |
| Country | Australia | |
| Study Type | Observational Study | |
| Measures | Testing: Frequent testing of HCWs and patients in wards with outbreaks and quick turnaround time for test results | |
| Results | Rapid and accessible testing enabling real-time outbreak management | |
| 25 | Author | Coppeta et al. [ |
| Month/Year | December 2020 | |
| Country | Italy | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: Exposed HCWs placed under an active syndromic surveillance program | |
| Results | Typical symptoms presented in 92% HCW positive cases, but in only 33.3% negative cases ( | |
| 26 | Author | Mullins et al. [ |
| Month/Year | January 2021 | |
| Country | US | |
| Study Type | Experimental Study | |
| Measures | Testing: Parallel orthogonal testing of (1) Ortho Vitros Test, a commercial immunodiagnostic system, and (2) UMMC ELISA, a manually developed ELISA for total SARS-CoV-2 antibodies and full-length spike ectodomain protein | |
| Results | Positive predictive value: Ortho Vitros (82.2%), UMMC ELISA (100%) | |
| 27 | Author | Cheng et al. [ |
| Month/Year | March 2021 | |
| Country | China (Hong Kong) | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: electronic syndromic surveillance system activated since the 1st imported case | |
| Results | Infection rate of HCWs (0.46‰) significantly lower than that of general population (0.71‰) ( | |
| 28 | Author | Monsalud et al. [ |
| Month/Year | March 2021 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Contact Tracing & Exposure Management: (1) high-risk exposure HCWs (having participated in aerosol-generating procedures without adequate PPE; ongoing exposure to infected household members) required to self-quarantine and PCR testing; (2) low-risk exposure HCWs (all the other exposed HCWs) placed under surveillance | |
| Results | 7.6% low-risk exposure HCWs identified as PCR-positive | |
| 29 | Author | Wan et al. [ |
| Month/Year | March 2021 | |
| Country | Malaysia | |
| Study Type | Observational Study | |
| Measures | Contact Tracing & Exposure Management: (1) contact tracing initiated once a COVID-19 case identified, collating info on the movement of the case 48 h before the onset of symptoms/diagnosis, forming a list of contacts; (2) level of risk of the contacts assessed and classified into different groups; (3) detailing management algorithm for low/medium/high-risk HCWs | |
| Results | Risk-based assessment with high sensitivity (100%) and specificity (72%) | |
| 30 | Author | Fernandes et al. [ |
| Month/Year | April 2021 | |
| Country | Brazil | |
| Study Type | Observational Study | |
| Measures | Testing: PCR testing for the symptomatic HCWs and, if negative, a 2nd PCR test after the 5th day since symptom onset | |
| Results | The 2nd PCR testing having detected 4.9% of the positive cases | |
| 31 | Author | Kolwijck et al. [ |
| Month/Year | April 2021 | |
| Country | The Netherlands | |
| Study Type | Observational Study | |
| Measures | Testing: Antigen test for symptomatic HCWs, and (1) if tested positive, considered COVID-19 infection; (2) if tested negative, followed by PCR testing | |
| Results | The antigen-based testing strategy proved to be effective and easy to implement, with 72.5% sensitivity and 97% negative predictive value | |
| 32 | Author | Lamb et al. [ |
| Month/Year | July 2021 | |
| Country | UK | |
| Study Type | Observational Study | |
| Measures | Testing: Mass antigen testing for HCWs, followed by PCR testing if antigen tested positive | |
| Results | Antigen testing proven to be an effective screening tool, with a positive predictive value of 94.21% | |
| 33 | Author | Azami et al. [ |
| Month/Year | July 2021 | |
| Country | Malaysia | |
| Study Type | Observational Study | |
| Measures | Testing: PCR + serological testing | |
| Results | With measures taken, nosocomial infection having reduced, with an HCW infection rate of 0.5% | |
| 34 | Author | Wee et al. [ |
| Month/Year | August 2021 | |
| Country | Singapore | |
| Study Type | Observational Study | |
| Measures | Testing: Rostered routine testing for HCWs + mass screening of all inpatients | |
| Results | Enhancing early identification and contact tracing for HCW cases | |
| 35 | Author | Diel et al. [ |
| Month/Year | October 2021 | |
| Country | Germany | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: Exposed HCWs required to self-observe COVID-19-related symptoms | |
| Results | Monitoring exposed HCWs with the measures in this study greatly reducing costs by 87.0%, compared with sending the exposed HCWs into quarantine | |
| 36 | Author | Hong et al. [ |
| Month/Year | October 2021 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: HCWs confirmed with exposure registered for twice-a-day symptom monitoring for 14 days via email | |
| Results | 22.2% exposures detected by EHR report, which would have been neglected based on traditional contact tracing methods | |
| 37 | Author | Cordioli et al. [ |
| Month/Year | February 2022 | |
| Country | Italy | |
| Study Type | Observational Study | |
| Measures | Syndromic Surveillance: Monitoring COVID-19 pathognomonic signs and symptoms | |
| Results | Using a 3-diagnostic criterion (PCR + serological testing + pathognomonic presentation) to assess infection prevalence: | |
| 38 | Author | Tande et al. [ |
| Month/Year | March2022 | |
| Country | US | |
| Study Type | Observational Study | |
| Measures | Testing: Rapid antigen test for infected HCWs who meet the criteria to return to work, on the 5th day (or later) since symptom onset/diagnosis of COVID-19 | |
| Results | The rapid antigen test, helpful to guide return-to-work decisions, having reduced isolation time by 2 days/person | |
Risk-of-bias assessment.
| Author and Year | Bias Due to Confounding | Bias in Selection of Participants into the Study | Bias in Classification of Interventions | Bias Due to Deviations from Intended Interventions | Bias Due to Missing Data | Bias in Measurement of Outcomes | Bias in Selection of the Reported Result | Overall Risk of Bias |
|---|---|---|---|---|---|---|---|---|
| Zhang et al. [ | Low | Low | Low | Low | Moderate | Low | Low | Low |
| Hunter et al. [ | Moderate | Moderate | Low | Low | Moderate | Moderate | Low | Moderate |
| Treibel et al. [ | Moderate | Moderate | Low | Low | Low | Low | Moderate | Moderate |
| Wee et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Garzaro et al. [ | Low | Low | Low | Low | Low | Low | Low | Low |
| Rivett et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Khalil et al. [ | Moderate | Low | Low | Low | Moderate | Low | Low | Low |
| Flynn et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Buchtele et al. [ | Moderate | Moderate | Low | Low | Low | Low | Low | Low |
| Ho et al. [ | Moderate | Moderate | Low | Low | Moderate | Low | Low | Low |
| Yombi et al. [ | Moderate | Moderate | Low | Low | Moderate | Low | Moderate | Moderate |
| Blain et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Wang et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Villanueva et al. [ | Moderate | Moderate | Low | Low | Low | Low | Moderate | Low |
| Mehta et al. [ | Moderate | Moderate | Low | Low | Low | Low | Moderate | Moderate |
| Kacmaz et al. [ | Moderate | Moderate | Low | Low | Low | Moderate | Low | Low |
| Tong et al. [ | Moderate | Moderate | Low | Low | Low | Moderate | Low | Low |
| Racine-Brzostek et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Del Castillo et al. [ | Moderate | Low | Low | Low | Moderate | Low | Moderate | Low |
| Ho et al. [ | Moderate | Moderate | Low | Low | Moderate | Low | Low | Low |
| Chong et al. [ | Moderate | Moderate | Low | Low | Low | Low | Low | Low |
| Chen et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Domeracki et al. [ | Moderate | Moderate | Low | Low | Low | Low | Low | Low |
| Buising et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Coppeta et al. [ | Moderate | Low | Low | Low | Low | Low | Moderate | Low |
| Mullins et al. [ | Low | Low | Low | Low | Low | Low | Low | Low |
| Cheng et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Monsalud et al. [ | Moderate | Moderate | Low | Low | Low | Low | Moderate | Low |
| Wan et al. [ | Moderate | Low | Low | Low | Moderate | Low | Low | Low |
| Fernandes et al. [ | Moderate | Moderate | Low | Low | Low | Low | Moderate | Moderate |
| Kolwijck et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
| Lamb et al. [ | Moderate | Low | Low | Low | Moderate | Low | Low | Low |
| Azami et al. [ | Moderate | Moderate | Low | Low | Moderate | Low | Low | Low |
| Wee et al. [ | Moderate | Moderate | Low | Low | Low | Low | Moderate | Low |
| Diel et al. [ | Low | Low | Low | Low | Low | Low | Low | Low |
| Hong et al. [ | Moderate | Low | Low | Low | Low | Low | Moderate | Low |
| Cordioli et al. [ | Low | Low | Low | Low | Low | Low | Low | Low |
| Tende et al. [ | Moderate | Low | Low | Low | Low | Low | Low | Low |
Figure 4HCW monitoring workflow framework.
Figure 5Different testing strategies.