COVID-19 mortality: positive correlation with cloudiness but no correlation with sunlight and latitude in Europe
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Abstract
We systematically investigated an ongoing debate about the possible correlation between SARS-CoV-2 (COVID-19) epidemiological outcomes and solar exposure in European countries, in the period of March – December 2020. For each country, we correlated its mortality data with: i) objective sky cloudiness (as cloud fraction) derived from satellite weather data, ii) solar insolation (watt/square metre at ground level), iii) latitude. We found a positive correlation between the monthly mortality rate and the overall cloudiness in that month (Pearson’s r(35)=.68, P<.001; averaged linear model fitting the data, adjusted R2 =0.45). In an additional month-by-month analysis, 17% to 59% of the variance in COVID-19 mortality/million appears to be predicted by the cloudiness fraction of the sky, except in the last two months of 2020. We did not find any statistical significant correlation with insolation, nor with latitude of the countries, when the “latitude of a country” was precisely defined as the average landmass location (country centroid). The unexpected correlation found between cloudiness and mortality could perhaps be explained by the following: 1) heavy cloudiness is linked with colder outdoor surfaces, which might aid virus survival; 2) reduced evaporation rate; 3) moderate pollution may be linked to both cloudiness and mortality; and 4) large-scale behavioural changes due to cloudiness (which perhaps drives people to spend more time indoors and thus facilitates indoor contamination).
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SciScore for 10.1101/2021.01.27.21250658: (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
No key resources detected.
Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:We are aware that this study has limitations: we did not investigate the precipitation rate, wind velocity, air pressure, air pollution and density (these are factors that are under scrutiny for their possible impact on COVID-19 epidemiology). We acknowledge that our observational retrospective study is limited: temporal …
SciScore for 10.1101/2021.01.27.21250658: (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
No key resources detected.
Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:We are aware that this study has limitations: we did not investigate the precipitation rate, wind velocity, air pressure, air pollution and density (these are factors that are under scrutiny for their possible impact on COVID-19 epidemiology). We acknowledge that our observational retrospective study is limited: temporal autocorrelation cannot be excluded over longer periods of time. The possibility of spatial autocorrelation was not researched by this study. Cloudiness might be a confounding factor in the previous studies that related vitamin D synthesis to latitude and sunlight. The authors support the current guidelines that in patients with vitamin D deficiency this should be treated irrespective of any link with respiratory infections. We are also aware that different countries took different governmental responses to the COVID-19 crisis, which has lead to different epidemiological outcomes. Last, we urge the reader not to extrapolate these results because we only investigated these variables in 37 European countries, not in the entire world. Additionally, this investigation was time-limited for 6 months; the story is developing, and we wait to see what it is the impact of an entire seasonal cycle. We plan to update the analysis as new data become available (see Data Availability Statements below). We hope that these results will bring a warning about the possible impact of extended cloudiness on COVID-19 transmission.
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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