Predicting COVID-19 cases using SARS-CoV-2 RNA in air, surface swab and wastewater samples
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Abstract
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SciScore for 10.1101/2022.03.14.22272314: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Field Sample Permit: Since there are two access points to YLV, we conducted daily (active) air sampling and surface swab sampling in both lobbies. Sex as a biological variable not detected. Randomization COVID-19 surveillance: Students residing at the YLV dormitory were randomly screened 2-3 days/week using nasal swabs which were analyzed using RT-PCR. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations …SciScore for 10.1101/2022.03.14.22272314: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Field Sample Permit: Since there are two access points to YLV, we conducted daily (active) air sampling and surface swab sampling in both lobbies. Sex as a biological variable not detected. Randomization COVID-19 surveillance: Students residing at the YLV dormitory were randomly screened 2-3 days/week using nasal swabs which were analyzed using RT-PCR. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Results of this research must be interpreted with caution due to the following limitations. First, some of the samples analyzed could be false negatives due to low concentrations of virus quantified from the sample or due to inhibition during sample preparation and analysis. Second, SARS-CoV-2 recovery from the samples can be subject to bias due to a low recovery rate from air, surface swab and wastewater samples. Third, COVID-19 case data can also be subject to bias because of the limited testing of students. For example, many days when SARS-CoV-2 was detected in the environmental samples, but COVID-19 cases were not reported. Routine daily testing of students was not implemented, especially during weekends. Finally, SARS-CoV-2 concentrations in the environmental samples were not adjusted for potential confounders, such as local meteorological conditions, ventilation and airborne particulate matter which have been shown to impact SARS-CoV-2 concentrations in air and on surface swabs [23, 25]. Despite these limitations this research provides insight into the merit and application of environmental microbiome surveillance for emerging disease-causing pathogens and their management.
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.
- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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