Dataset Information


Effects of meteorological parameters on COVID-19 transmission trends in Bangladesh



Understanding the influence of meteorological parameters in relation to COVID-19 transmission may be a convenient way to predict the ongoing pandemic towards its adaptive control measures. This study aims to explore the association between COVID-19 cases and meteorological parameters and to predict COVID-19 transmission for an extended period covering different climatic patterns. The number of COVID-19 cases, daily records of rainfall, temperature, relative humidity and wind speed data were collected for April and May 2020 from the eight major divisions in Bangladesh. The basic statistical analyses and auto regressive integrated moving average (ARIMA) using SPSS tool were applied to evaluate and explore association between meteorological parameters and COVID-19 cases and its transmission trend. A greater number of significant positive associations (r = 0.24–0.58) is found to exist between the relative humidity and COVID-19 cases across the cities, while with temperature both positive and negative associations (r = − 0.23 to 0.72) were revealed. Furthermore, both the rainfall and wind speed exhibit positive correlations. ARIMA model portrayed predictive trend of COVID-19 transmission, from its inception on 8 March 2020 to September 2020, in Bangladesh. The month of July showed the highest daily COVID-19 cases prior to lowering at steady rate till September illustrating the influnce of meteorological parameters.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s42398-021-00195-5.

PROVIDER: S-EPMC8180358 | BioStudies |

REPOSITORIES: biostudies

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