A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries: The devil is in the detail

Shola Adeyemi, Usame Yakutcan, Eren Demir, Adekunle O. Adeoti

Research output: Contribution to conferencePosterpeer-review

Abstract

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 strictly between -0.5 and 0.5, and these are weak correlations. An interesting finding is the correlation between stringency index and each of the COVID-19 outcomes, the strongest being between stringencyvindex 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.
Original languageEnglish
Publication statusPublished - 4 Aug 2020
EventClimatological, Meteorological and Environmental factors in the COVID-19 pandemic Symposium - Virtual
Duration: 4 Aug 20206 Aug 2020
https://public.wmo.int/en/events/meetings/covid-19-symposium

Conference

ConferenceClimatological, Meteorological and Environmental factors in the COVID-19 pandemic Symposium
Period4/08/206/08/20
OtherAn international virtual symposium on drivers, predictability and actionable information.
Internet address

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