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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 τ 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.
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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, 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. COVID-19;Weather variables;Correlation;Meta-analysis.
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OBJECTIVES: The main aim of this study was to find the prevalence of mortality among hospitalized COVID-19 infected patients and associated risk factors for death. METHODS: Three electronic databases including PubMed, Science Direct and Google Scholar were searched to identify relevant cohort studies of COVID-19 disease from January 1, 2020, to August 11, 2020. A random-effects model was used to calculate pooled prevalence rate (PR), risk ratio (RR) and 95% confidence interval (CI) for both effect measures. Cochrane chi-square test statistic Q, [Formula: see text], and [Formula: see text] tests were used to measure the presence of heterogeneity. Publication bias and sensitivity of the included studies were also tested. RESULTS: In this meta-analysis, a total of 58 studies with 122,191 patients were analyzed. The pooled prevalence rate of mortality among the hospitalized COVID-19 patients was 18.88%, 95% CI (16.46-21.30), p < 0.001. Highest mortality was found in Europe [PR 26.85%, 95% CI (19.41-34.29), p < 0.001] followed by North America [PR 21.47%, 95% CI (16.27-26.68), p < 0.001] and Asia [PR 14.83%, 95% CI (12.46- 17.21), p < 0.001]. An significant association were found between mortality among COVID-19 infected patients and older age (> 65 years vs. < 65 years) [RR 3.59, 95% CI (1.87-6.90), p < 0.001], gender (male vs. female) [RR 1.63, 95% CI (1.43-1.87), p < 0.001], ICU admitted patients [RR 3.72, 95% CI (2.70-5.13), p < 0.001], obesity [RR 2.18, 95% CI (1.10-4.34), p < 0.05], hypertension [RR 2.08,95% CI (1.79-2.43) p < 0.001], diabetes [RR 1.87, 95% CI (1.23-2.84), p < 0.001], cardiovascular disease [RR 2.51, 95% CI (1.20-5.26), p < 0.05], and cancer [RR 2.31, 95% CI (1.80-2.97), p < 0.001]. In addition, significant association for high risk of mortality were also found for cerebrovascular disease, COPD, coronary heart disease, chronic renal disease, chronic liver disease, chronic lung disease and chronic kidney disease. CONCLUSION: This meta-analysis revealed that the mortality rate among COVID-19 patients was highest in the European region and older age, gender, ICU patients, patients with comorbidity had a high risk for case fatality. Those findings would help the health care providers to reduce the mortality rate and combat this pandemic to save lives using limited resources.