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OBJECTIVE: Current COVID-19 guidelines recommend symptom-based screening and regular nasopharyngeal (NP) testing for healthcare personnel in high-risk settings. We sought to estimate case detection percentages with various routine NP and saliva testing frequencies. DESIGN: Simulation modelling study. METHODS: We constructed a sensitivity function based on the average infectiousness profile of symptomatic COVID-19 cases to determine the probability of being identified at the time of testing. This function was fitted to reported data on the percent positivity of symptomatic COVID-19 patients using NP testing. We then simulated a routine testing program with different NP and saliva testing frequencies to determine case detection percentages during the infectious period, as well as the pre-symptomatic stage. RESULTS: Routine bi-weekly NP testing, once every two weeks, identified an average of 90.7% (SD: 0.18) of cases during the infectious period and 19.7% (SD: 0.98) during the pre-symptomatic stage. With a weekly NP testing frequency, the corresponding case detection percentages were 95.9% (SD: 0.18) and 32.9% (SD: 1.23), respectively. A 5-day saliva testing schedule had a similar case detection percentage as weekly NP testing during the infectious period, but identified about 10% more cases (mean: 42.5%; SD: 1.10) during the pre-symptomatic stage. CONCLUSION: Our findings highlight the utility of routine non-invasive saliva testing for frontline healthcare workers to protect vulnerable patient populations. A 5-day saliva testing schedule should be considered to help identify silent infections and prevent outbreaks in nursing homes and healthcare facilities.
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?:doi
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?:doi
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10.1101/2020.11.27.20240044
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document_parses/pdf_json/6a73b2d59ba69b5e7860d76bc6e2099fe30bf0a8.json; document_parses/pdf_json/c9716763ac122aaa37fb783508cdc18fccd567a7.json; document_parses/pdf_json/386887c382c4d8adcbacc60bf4d22f75835d0b6a.json
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document_parses/pmc_json/PMC7709182.xml.json
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MedRxiv; Medline; PMC; WHO
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Routine saliva testing for the identification of silent COVID-19 infections in healthcare workers
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