A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries
# Background Eleven out of 13 published articles reported temperature and humidity as factors that could reduce the daily confirmed COVID-19 cases among many other findings. However, there are significant caveats, related to statistical assumptions and the spatial-temporal nature of the data. # Me...
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| Format: | Article |
| Language: | English |
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Inishmore Laser Scientific Publishing Ltd
2020-07-01
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| Series: | Journal of Global Health Reports |
| Online Access: | https://doi.org/10.29392/001c.13693 |
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| author | Shola Adeyemi Usame Yakutcan Eren Demir |
| author_facet | Shola Adeyemi Usame Yakutcan Eren Demir |
| author_sort | Shola Adeyemi |
| collection | DOAJ |
| description | # Background
Eleven out of 13 published articles reported temperature and humidity as factors that could reduce the daily confirmed COVID-19 cases among many other findings. However, there are significant caveats, related to statistical assumptions and the spatial-temporal nature of the data.
# Methods
Associative and causative analyses of data was conducted for 10 countries representing 6 continents of the world, with data obtained between January 22, 2020 to April 30, 2020. Daily confirmed cases, number of deaths, recovered cases, lockdown stringency index, and several meteorological factors are considered. Also, a Granger-Causality test was performed to check if any COVID-19 outcomes are influenced by itself and not by any or combination of maximum temperature, humidity, wind speed and stringency index.
# Results
Most of the associations reported in the literature, between meteorological parameters and COVID-19 pandemic are weak evidence, need to be interpreted with caution, as most of these articles neglected the temporal spatial nature of the data. Based on our findings, most of the correlations no matter which coefficient is used are mostly and strictly between -0.5 and 0.5, and these are weak correlations. An interesting finding is the correlation between stringency and each of the COVID-19 outcomes, the strongest being between stringency and confirmed cases, 0.80 (0.78, 0.82) P<.0001. Similarly, wind speed is weakly associated with recovery rate, 0.22 (0.16, 0.28) P<.0001. Lastly, the Granger-Causality test of no dependencies was accepted at P=0.1593, suggesting independence among the parameters.
# Conclusions
Although many articles reported association between meteorological parameters and COVID-19, they mainly lack strong evidence and clear interpretation of the statistical results (e.g. underlying assumption, confidence intervals, a clear hypothesis). Our findings showed that, without effective control measures, strong outbreaks are likely in more windy climates and summer weather, humidity or warmer temperature will not substantially limit pandemic growth. |
| format | Article |
| id | doaj-art-ffb21b0d25ff4fbc966dd8a92bae4adf |
| institution | DOAJ |
| issn | 2399-1623 |
| language | English |
| publishDate | 2020-07-01 |
| publisher | Inishmore Laser Scientific Publishing Ltd |
| record_format | Article |
| series | Journal of Global Health Reports |
| spelling | doaj-art-ffb21b0d25ff4fbc966dd8a92bae4adf2025-08-20T02:40:07ZengInishmore Laser Scientific Publishing LtdJournal of Global Health Reports2399-16232020-07-01410.29392/001c.13693A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countriesShola AdeyemiUsame YakutcanEren Demir# Background Eleven out of 13 published articles reported temperature and humidity as factors that could reduce the daily confirmed COVID-19 cases among many other findings. However, there are significant caveats, related to statistical assumptions and the spatial-temporal nature of the data. # Methods Associative and causative analyses of data was conducted for 10 countries representing 6 continents of the world, with data obtained between January 22, 2020 to April 30, 2020. Daily confirmed cases, number of deaths, recovered cases, lockdown stringency index, and several meteorological factors are considered. Also, a Granger-Causality test was performed to check if any COVID-19 outcomes are influenced by itself and not by any or combination of maximum temperature, humidity, wind speed and stringency index. # Results Most of the associations reported in the literature, between meteorological parameters and COVID-19 pandemic are weak evidence, need to be interpreted with caution, as most of these articles neglected the temporal spatial nature of the data. Based on our findings, most of the correlations no matter which coefficient is used are mostly and strictly between -0.5 and 0.5, and these are weak correlations. An interesting finding is the correlation between stringency and each of the COVID-19 outcomes, the strongest being between stringency and confirmed cases, 0.80 (0.78, 0.82) P<.0001. Similarly, wind speed is weakly associated with recovery rate, 0.22 (0.16, 0.28) P<.0001. Lastly, the Granger-Causality test of no dependencies was accepted at P=0.1593, suggesting independence among the parameters. # Conclusions Although many articles reported association between meteorological parameters and COVID-19, they mainly lack strong evidence and clear interpretation of the statistical results (e.g. underlying assumption, confidence intervals, a clear hypothesis). Our findings showed that, without effective control measures, strong outbreaks are likely in more windy climates and summer weather, humidity or warmer temperature will not substantially limit pandemic growth.https://doi.org/10.29392/001c.13693 |
| spellingShingle | Shola Adeyemi Usame Yakutcan Eren Demir A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries Journal of Global Health Reports |
| title | A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries |
| title_full | A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries |
| title_fullStr | A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries |
| title_full_unstemmed | A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries |
| title_short | A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries |
| title_sort | statistical assessment of association between meteorological parameters and covid 19 pandemic in 10 countries |
| url | https://doi.org/10.29392/001c.13693 |
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