At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR-based tests? A systematic review of individual participant data
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Abstract
Background
Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA) using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity.
Methods
We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv, and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites.
Results
Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from − 6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 and 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset.
Conclusions
RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated.
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SciScore for 10.1101/2020.07.13.20152793: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Search strategy and article selection: Search strings were designed and conducted subsequently in PubMed, LitCOVID and medRxiv by an experienced information specialist (NR). PubMedsuggested: (PubMed, RRID:SCR_004846)Study, participant characteristics, and ROB were extracted in Microsoft Excel (KG, JS, SG, JA, AW, SM). Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)Data analysis used STATA (14.2 StataCorp LP, Texas, USA). STATAsuggested: (Stata, RRID:SCR_012763)StataCo…SciScore for 10.1101/2020.07.13.20152793: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Search strategy and article selection: Search strings were designed and conducted subsequently in PubMed, LitCOVID and medRxiv by an experienced information specialist (NR). PubMedsuggested: (PubMed, RRID:SCR_004846)Study, participant characteristics, and ROB were extracted in Microsoft Excel (KG, JS, SG, JA, AW, SM). Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)Data analysis used STATA (14.2 StataCorp LP, Texas, USA). STATAsuggested: (Stata, RRID:SCR_012763)StataCorpsuggested: (Stata, RRID:SCR_012763)Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Box 1 provides an overview of the major methodological limitations and their potential impact on study results. A major source of bias is that all but one study 18 restricted inclusion to participants with confirmed SARS-CoV-2 infection based on at least one positive RT-PCR test, meaning that the percentage of positive RT-PCR testing is likely to be overestimated. Lack of technical details, for example of how samples are taken and RT-PCR tests performed, limit the applicability of findings to current testing. Compared to real life, studies were likely to use more invasive sampling methods, use experienced staff to obtain samples, and sample participants in hospital settings where sample handling could be standardised. Consequently, estimates of test performance are likely to be overestimated compared to real-world clinical use and in community population testing including self-test kits. These limitations have important implications for how testing strategies should be implemented and in particular how a negative RT-PCR test result should be interpreted. Putting the findings into context of literature: The accuracy of RT-PCR testing is limited by sampling sites used, methods and the need to test as soon as possible from symptom onset in order to detect the virus. Previous studies have established that in COVID-19 infection viral loads typically peak just before symptoms and at symptom onset3. To our knowledge, there has been no prior systematic review of RT- PCR using IPD to ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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