optimizing benefits of testing key workers for infection with sars cov 2 a mathematical CORD-Papers-2022-06-02 (Version 1)

Title: 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-19like symptoms in isolation (S2) without COVID-19like 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 (0.120%) proportion asymptomatic (1080%) sensitivity (6095%) and specificity (90100%). 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 989.61995.9 tests/1000 workers. Testing workers in household quarantine (S2) reduces absences the most by 3.06.9 days/test (at 47.0210.4 tests/1000 workers) while increasing risk of workplace transmission by 0.0249.5 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.
Published: 2020-07-07
Journal: Clin Infect Dis
DOI: 10.1093/cid/ciaa901
DOI_URL: http://doi.org/10.1093/cid/ciaa901
Author Name: Sandmann Frank G
Author link: https://covid19-data.nist.gov/pid/rest/local/author/sandmann_frank_g
Author Name: White Peter J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/white_peter_j
Author Name: Ramsay Mary
Author link: https://covid19-data.nist.gov/pid/rest/local/author/ramsay_mary
Author Name: Jit Mark
Author link: https://covid19-data.nist.gov/pid/rest/local/author/jit_mark
sha: c5f8ee601cc236a880c76c77355c7689acbf0216
license: no-cc
license_url: [no creative commons license associated]
source_x: Medline; PMC
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/
pubmed_id: 32634823
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/32634823
pmcid: PMC7454477
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454477
url: https://doi.org/10.1093/cid/ciaa901 https://www.ncbi.nlm.nih.gov/pubmed/32634823/
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Keywords Extracted from Text Content: ≥65 −0.5 −56.9 SARS-CoV-2 coronavirus disease 2019 (COVID-19)-like 989.6-1995.9 ≥65 coronavirus diseasea 2019 upper respiratory tract isolation/quarantine self-isolate for line implications-for non-COVID-19 989.6-1995.9 S3B UK children F. G. S. patients COVID-19 S2C Figure 3 coronavirus 2 × Supplementary Table 1 Figure 2 coronavirus disease 2019 −56.9 households people tracheal S1C SARS-CoV-2 virus [1] [2] [3] [4 LRTI individuals [1] −0.5 M. R. SARS-CoV-2 [1, 3] Figures 2 and 190.7 self-isolate
Extracted Text Content in Record: First 5000 Characters: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. Since the first reports in December 2019, the newly emerged respiratory coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic with widespread community transmission in many countries. Because of the global spread of a newly emerged virus, and no antivirals or vaccines being available, the World Health Organization and many public health agencies internationally advise individuals to stay at home if either they or a household member experiences symptoms of COVID-19, to mitigate the community spread of the pandemic SARS-CoV-2 virus [1] [2] [3] [4] . As COVID-19 symptoms are nonspecific, not all individuals staying at home will be infected, and testing workers for SARS-CoV-2 would enable uninfected individuals to remain available for work [5] [6] [7] . This is particularly important for workers whose occupational roles are critical to the functioning of society and the COVID-19 response (so-called "key workers"), including in health and social care, transport, education, public safety, government, utilities, and food production and delivery [8, 9] . Additionally, asymptomatic SARS-CoV-2 likely contributes to transmission [10] , which could be reduced by testing. Capacity for (extensive) testing may be limited [11, 12] , however, and is also required by patients. Targeted testing and optimizing testing strategies are thus important internationally. For key workers, the crucial question faced is whether to concentrate on testing staff for infection with SARS-CoV-2 who present as cases with COVID-19-like symptoms, staff who are asymptomatic but quarantining at home, or all staff regardless of symptom status or quarantine. We used a decision-analytic model to explore the impact of different testing strategies for SARS-CoV-2 infection by swabbing and reverse transcriptase-polymerase chain reaction (RT-PCR) on (1) the duration key workers such as healthcare staff spend in household isolation, (2) the numbers of staff at work who may spread SARS-CoV-2, (3) the testing accuracy (ie, the proportion of true positive and true negative results among all tests), and (4) the required numbers of tests. We varied the proportion of key workers and their households with infectious and detectable SARS-CoV-2 infection at any given time between 0.1% and 20% (base value: 2% [13] ), reflecting different levels of mitigation and including the expected prevalence of 5.8% when an assumed 80% of the workers and household members become infected over the course of a 3-month epidemic, with a mean duration of infectiousness of 6.5 days [14] (0.80 × 6.5 days/90 days = 0.058). We considered between 10% and 80% of SARS-CoV-2 infections to be asymptomatic or subclinical (base value: 18%) [10] , between 10% and 80% of cases to involve COVID-19-like symptoms of a high fever (base value: 47%) [11] , and between 0% and 20% of infections to be too severe for isolation at home and to require hospitalization (base value: 4.4%) [14] . Another 10% of workers are assumed to experience COVID-19-like symptoms from other respiratory illnesses [6] , of whom 2% are assumed to become hospitalized [15] . Furthermore, key workers without symptoms but with
Keywords Extracted from PMC Text: upper respiratory tract −56.9 people −0.5 Figure 1 children SARS-CoV-2 households S3B 's COVID-19 S1C Figures 2 and self-isolate non–COVID-19 Supplementary Table 1 S1–S3 COVID-19–like patients LRTI self-isolate for × isolation/quarantine S2C [1, 3] individuals 989.6–1995.9
Extracted PMC Text Content in Record: First 5000 Characters:We varied the proportion of key workers and their households with infectious and detectable SARS-CoV-2 infection at any given time between 0.1% and 20% (base value: 2% [13]), reflecting different levels of mitigation and including the expected prevalence of 5.8% when an assumed 80% of the workers and household members become infected over the course of a 3-month epidemic, with a mean duration of infectiousness of 6.5 days [14] (0.80 × 6.5 days/90 days = 0.058). We considered between 10% and 80% of SARS-CoV-2 infections to be asymptomatic or subclinical (base value: 18%) [10], between 10% and 80% of cases to involve COVID-19–like symptoms of a high fever (base value: 47%) [11], and between 0% and 20% of infections to be too severe for isolation at home and to require hospitalization (base value: 4.4%) [14]. Another 10% of workers are assumed to experience COVID-19–like symptoms from other respiratory illnesses [6], of whom 2% are assumed to become hospitalized [15]. Furthermore, key workers without symptoms but with symptomatic household contacts need to self-isolate (49% of key workers in the United Kingdom live with children and a partner [9]; the rates of illness in household members and key workers were assumed to be the same). RT-PCR test sensitivity (proportion of infected individuals testing positive) was varied between 60% and 95% (with an assumed base value of 75%), and specificity (proportion of uninfected individuals testing negative) was varied between 90% and 100% (base value: 90%) [16, 17]. All input parameters of the model were varied in sensitivity analyses. Our static decision-analytic model followed 1000 key workers to compare the baseline strategy of no testing and self-isolating based on COVID-19–like symptoms alone (S0) with 3 strategies of testing: (S1) key workers with COVID-19–like symptoms in isolation, (S2) key workers without COVID-19–like symptoms but in household quarantine due to exposure to symptomatic household contacts, and (S3) one-off testing all key workers, including those without COVID-19–like symptoms or household exposure. In addition, we explored 5 confirmatory re-testing scenarios for each strategy: repeating (A) all initial tests, (B) initially positive tests [18], (C) initially negative tests, (D) no re-testing [5, 18, 19], or (E) no re-testing but additional isolation for 2 weeks for laboratory-confirmed cases without severe symptoms [1] (Table 1, Figure 1). For strategy S2, we also explored in a separate scenario analysis testing the symptomatic household contact of the key worker in household quarantine (as the index case who required the household to quarantine). International guidance recommends key workers with COVID-19–like symptoms to self-isolate for 7 days, and workers in household quarantine for 14 days [1, 3]. We assumed symptomatic workers who tested negative to self-isolate for 3 days on account of their presumed non–COVID-19 acute respiratory illness [20]. Symptomatic workers in symptomatic households are assumed to stay an additional 2 days at home (for an equal chance of who became symptomatic first [21, 22]). Key workers in household quarantine who tested negative are assumed to self-isolate for 7 days until the infectivity of the case at home is assumed to have ended [14]. We explored different values for the durations in isolation and quarantine in sensitivity analyses (for more details, see Figure 1 and Supplementary Table 1). In order to optimize the testing strategies in reducing staff absences and workplace transmission risk it is important to consider the efficiency of the number of tests performed. Figures 2 and 3 present the main findings for the 3 different testing strategies (S1–S3) in terms of changes in absence duration and the transmission risk per test against the baseline of no testing (S0). Note that negative values of change thus represent desirable reductions (in transmission risk or days in isolation; indicated in white-shaded areas). Also, the impact of the variation in key epidemiological parameters (the proportion of infected workers and asymptomatic in Figure 2 and the RT-PCR specificity and sensitivity in Figure 3) is illustrated with the different sizes and fading of the shapes, with smaller shapes that are fading out representing increasing parameter values. All other parameters were kept at their base value, and their impact on results are presented in the Supplementary Material and discussed below (note that the variation of results for all other disease parameters is captured within the range of these 4 key parameters). Testing workers with COVID-19–like symptoms (S1) may reduce absences by 0.9–3.6 days per test for those uninfected with SARS-CoV-2 or with false-negative results; the latter may increase transmission risk to others when back at work by 0.2–189.8 infected workers per 1000 tests (depending on the rate of infection) (Figure 2). Re-testing negatives (S1C) increases the transmission risk the least (0.2–28.3
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