Abstract
This study examines the relationship between climatic factors and the prevalence of COVID-19 in Bangladesh. The Pearson correlation coefficient, the Spearman correlation coefficient, and Kendall's correlation coefficient have all been used to assess the intensity and direction of the relationship between climatic factors and COVID-19. The lagged effects of climatic parameters on COVID-19 daily confirmed cases from Bangladesh are being investigated using the Auto Regressive Distributed Lag (ARDL) model. As a result, one non-climatic variable, such as a daily lab test, is considered a control variable. As climatic variables, average temperature (°C), average humidity (percent), average rainfall (mm), and average wind speed (km/h) were well chosen and the same time one environmental variable (a proxy of air quality) like average particulate matter (\({PM}_{2.5})\) is considered into account. The time series data used in this analysis was from May 1, 2020, to April 14, 2021. The findings of correlation analysis indicate that there is an important /strong, significant, and positive relationship between COVID-19 widespread and temperature (°C), humidity (percent), rainfall (mm), and wind speed (km/h), whereas there is a negative, weak, and significant relationship between \({PM}_{2.5}\) and COVID-19 widespread. In addition, the ARDL findings suggest that temperature (°C), \({PM}_{2.5}\), and wind speed (km/h) have major lag effects on COVID-19 in Bangladesh, while humidity (percent) and rainfall (mm) have negligible lag effects. This study will be helpful to environmental activists and policymakers in creating future sustainable improvement plans for climate and weather conditions in Bangladesh.
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IBM SPSS and Eviews 10 were utilized for statistical analysis and code will be provided to the corresponding author upon reasonable request.
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Acknowledgements
We are grateful to the Bangladesh Meteorological Department (BMD) for making the day wise datasets used in this study available on request. We are also thankful to Miyan Research Institute, International University of Business Agriculture and Technology (IUBAT).
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Conceptualization and approval: Rehana Parvin; methodology: Rehana Parvin; software: Rehana Parvin; analysis: Rehana Parvin; data curation: Rehana Parvin; validation: Rehana Parvin; draft preparation: Rehana Parvin; visualization: Rehana Parvin; review and editing: Rehana Parvin; supervision: Rehana Parvin.
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Highlights
• The climatic conditions and the propagation of COVID-19 were analyzed using correlation analysis.
• The lag effects of climatic conditions on COVID-19 were investigated using the ARDL model.
• COVID-19 occurrences were shown to be linked to temperature, rainfall, and wind speed.
• The distribution of COVID-19 is inversely linked with \({PM}_{2.5}\).
• Temperature, wind speed, and rainfall all have significant lag effects on COVID-19.
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Parvin, R. COVID-19 and the impact of climatic parameters: a case study of Bangladesh. Theor Appl Climatol 155, 645–659 (2024). https://doi.org/10.1007/s00704-023-04656-1
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DOI: https://doi.org/10.1007/s00704-023-04656-1