Correlation between COVID-19 and weather variables: A meta-analysis

Abstract

Background

COVID-19 has significantly impacted humans worldwide in recent times. Weather variables have a remarkable effect on COVID-19 spread all over the universe.

Objectives

The aim of this study was to find the correlation between weather variables with COVID-19 cases and COVID-19 deaths.

Methods

Five electronic databases such as PubMed, Science Direct, Scopus, Ovid (Medline), and Ovid (Embase) were searched to conduct the literature survey from January 01, 2020, to February 03, 2022. Both fixed-effects and random-effects models were used to calculate pooled correlation and 95% confidence interval (CI) for both effect measures. Included studies heterogeneity was measured by Cochrane chi-square test statistic Q, $I^2$ and ${\tau }^2$ . Funnel plot was used to measure publication bias. A Sensitivity analysis was also carried out.

Results

Total 38 studies were analyzed in this study. The result of this analysis showed a significantly negative impact on COVID-19 fixed effect incidence and weather variables such as temperature (r = -0.113***), relative humidity (r = -0.019***), precipitation (r = -0.143***), air pressure (r = -0.073*), and sunlight (r = -0.277***) and also found positive impact on wind speed (r = 0.076***) and dew point (r = 0.115***). From this analysis, significant negative impact was also found for COVID-19 fixed effect death and weather variables such as temperature (r = -0.094***), wind speed (r = -0.048**), rainfall (r = -0.158***), sunlight (r = -0.271***) and positive impact for relative humidity (r = 0.059***).

Conclusion

This meta-analysis disclosed significant correlations between weather and COVID-19 cases and deaths. The findings of this analysis would help policymakers and the health professionals to reduce the cases and fatality rate depending on weather forecast techniques and fight this pandemic using restricted assets.

Abstract

COVID-19; Weather variables; Correlation; Meta-analysis.