COVID-19 era, Preventive effect of no going out against co-infection of the seasonal influenza virus and SARS-CoV-2
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Abstract
In the situation where expansion of coronavirus infectious disease-2019 (COVID-19) does not stop, there is concern about co-infection of people with the seasonal influenza infections from late autumn to winter 2020. Therefore, the importance of supplying vaccines against the seasonal influenza has been pointed out all over the world. As an example in Japan, the number of people infected with the seasonal influenza, hand-foot-and-mouth disease (HFMD), epidemic keratoconjunctivitis, and pharyngoconjunctival fever (PCF), which are the seasonal infectious diseases in the 2020 season, has decreased remarkably compared to the number of people infected each year. It is believed that the significant reduction in the number of people infected with these seasonal infectious diseases is a result of the pervasive hand washing, wearing masks and maintaining social distance in COVID-19 rea. To examine the correlation between the three factors of the number of people with each seasonal infectious disease, the mask wearing rate, and the outing rate, we created a three-dimensional scatter plot based on these three factors using principal component analysis. Our research findings demonstrated preventive effect of no going out against co-infection with the seasonal influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
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SciScore for 10.1101/2020.09.27.20202739: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources 3 To examine the correlation between the three factors of the number of people with each seasonal infectious disease, the mask wearing rate, and the outing rate, we created a three-dimensional scatter plot based on these three factors using Minner3D Enterprise-Miner3D1.m3d (XLSTAT by Addinsoft, Mindware Inc., Okayama, Japan). XLSTATsuggested: (XLSTAT, RRID:SCR_016299)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: An explicit section about …SciScore for 10.1101/2020.09.27.20202739: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources 3 To examine the correlation between the three factors of the number of people with each seasonal infectious disease, the mask wearing rate, and the outing rate, we created a three-dimensional scatter plot based on these three factors using Minner3D Enterprise-Miner3D1.m3d (XLSTAT by Addinsoft, Mindware Inc., Okayama, Japan). XLSTATsuggested: (XLSTAT, RRID:SCR_016299)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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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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