Dataset Information

Optimizing Benefits of Testing Key Workers for Infection with SARS-CoV-2: A Mathematical Modeling Analysis.

ABSTRACT:

Background

Internationally, key workers such as healthcare staff are advised to stay at home if they or household members experience coronavirus disease 2019 (COVID-19)-like symptoms. This potentially isolates/quarantines many staff without SARS-CoV-2, while not preventing transmission from staff with asymptomatic infection. We explored the impact of testing staff on absence durations from work and transmission risks to others.

Methods

We used a decision-analytic model for 1000 key workers to compare the baseline strategy of (S0) no RT-PCR testing of workers to testing workers (S1) with COVID-19-like symptoms in isolation, (S2) without COVID-19-like symptoms but in household quarantine, and (S3) all staff. We explored confirmatory re-testing scenarios of repeating all initial tests, initially positive tests, initially negative tests, or no re-testing. We varied all parameters, including the infection rate (0.1-20%), proportion asymptomatic (10-80%), sensitivity (60-95%), and specificity (90-100%).

Results

Testing all staff (S3) changes the risk of workplace transmission by -56.9 to +1.0 workers/1000 tests (with reductions throughout at RT-PCR sensitivity ≥65%), and absences by -0.5 to +3.6 days/test but at heightened testing needs of 989.6-1995.9 tests/1000 workers. Testing workers in household quarantine (S2) reduces absences the most by 3.0-6.9 days/test (at 47.0-210.4 tests/1000 workers), while increasing risk of workplace transmission by 0.02-49.5 infected workers/1000 tests (which can be minimized when re-testing initially negative tests).

Conclusions

Based on optimizing absence durations or transmission risk, our modeling suggests testing staff in household quarantine or all staff, depending on infection levels and testing capacities.

SUBMITTER: Sandmann FG

PROVIDER: S-EPMC7454477 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Optimizing Benefits of Testing Key Workers for Infection with SARS-CoV-2: A Mathematical Modeling Analysis.

Sandmann Frank G FG White Peter J PJ Ramsay Mary M Jit Mark M

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20201201 12

<h4>Background</h4>Internationally, key workers such as healthcare staff are advised to stay at home if they or household members experience coronavirus disease 2019 (COVID-19)-like symptoms. This potentially isolates/quarantines many staff without SARS-CoV-2, while not preventing transmission from staff with asymptomatic infection. We explored the impact of testing staff on absence durations from work and transmission risks to others.<h4>Methods</h4>We used a decision-analytic model for 1000 ke ...[more]

PMID: 32634823

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Project description:BackgroundFrom a public health perspective, the identification of individuals with mild respiratory symptoms due to SARS-CoV-2 infection is important to contain the spread of the disease. The objective of this study was to identify volatile organic compounds (VOCs) in exhaled breath common to infection with different variants of the SARS-CoV-2 virus to inform the development of a point-of-care breath test to detect infected individuals with mild symptoms.MethodsA prospective, real-world, observational study was conducted on mildly symptomatic out-patients presenting to community test-sites for RT-qPCR SARS-CoV-2 testing when the Alpha, Beta, and Delta variants were driving the COVID-19 pandemic. VOCs in exhaled breath were compared between PCR-positive and negative individuals using TD-GC-ToF-MS. Candidate VOCs were tested in an independent set of samples collected during the Omicron phase of the pandemic.FindingsFifty breath samples from symptomatic RT-qPCR positive and 58 breath samples from test-negative, but symptomatic participants were compared. Of the 50 RT-qPCR-positive participants, 22 had breath sampling repeated 8-12 weeks later. PCA-X model yielded 12 distinct VOCs that discriminated SARS-CoV-2 active infection compared to recovery/convalescence period, with an area under the receiver operator characteristic curve (AUROC), of 0.862 (0.747-0.977), sensitivity, and specificity of 82% and 86%, respectively. PCA-X model from 50 RT-qPCR positive and 58 negative symptomatic participants, yielded 11 VOCs, with AUROC of 0.72 (0.604-0.803) and sensitivity of 72%, specificity 65.5%. The 11 VOCs were validated in a separate group of SARS-CoV-2 Omicron positive patients' vs healthy controls demonstrating an AUROC of 0.96 (95% CI 0.827-0.993) with sensitivity of 80% specificity of 90%.InterpretationExhaled breath analysis is a promising non-invasive, point-of-care method to detect mild COVID-19 infection.FundingFunding for this study was a competitive grant awarded from the Vancouver Coastal Research Institute as well as funding from the BC Cancer Foundation.

Project description:BackgroundIn order to protect health workers from SARS-CoV-2, there is need to characterise the different types of patient facing health workers. Our first aim was to determine both the infection status and seroprevalence of SARS-CoV-2 in health workers. Our second aim was to evaluate the occupational and demographic predictors of seropositivity to inform the country's infection prevention and control (IPC) strategy.Methods and principal findingsWe invited 713 staff members at 24 out of 35 health facilities in the City of Bulawayo in Zimbabwe. Compliance to testing was defined as the willingness to uptake COVID-19 testing by answering a questionnaire and providing samples for both antibody testing and PCR testing. SARS-COV-2 antibodies were detected using a rapid diagnostic test kit and SAR-COV-2 infection was determined by real-time (RT)-PCR. Of the 713 participants, 635(89%) consented to answering the questionnaire and providing blood sample for antibody testing while 560 (78.5%) agreed to provide nasopharyngeal swabs for the PCR SARS-CoV-2 testing. Of the 635 people (aged 18-73) providing a blood sample 39.1% reported a history of past COVID-19 symptoms while 14.2% reported having current symptoms of COVID-19. The most-prevalent co-morbidity among this group was hypertension (22.0%) followed by asthma (7.0%) and diabetes (6.0%). The SARS-CoV-2 sero-prevalence was 8.9%. Of the 560 participants tested for SARS-CoV-2 infection, 2 participants (0.36%) were positive for SAR-CoV-2 infection by PCR testing. None of the SARS-CoV-2 antibody positive people were positive for SAR-CoV-2 infection by PCR testing.Conclusion and interpretationIn addition to clinical staff, several patient-facing health workers were characterised within Zimbabwe's health system and the seroprevalence data indicated that previous exposure to SAR-CoV-2 had occurred across the full spectrum of patient-facing staff with nurses and nurse aides having the highest seroprevalence. Our results highlight the need for including the various health workers in IPC strategies in health centres to ensure effective biosecurity and biosafety.

Dataset Information

Optimizing Benefits of Testing Key Workers for Infection with SARS-CoV-2: A Mathematical Modeling Analysis.

Background

Methods

Results

Conclusions

Publications

Optimizing Benefits of Testing Key Workers for Infection with SARS-CoV-2: A Mathematical Modeling Analysis.

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