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

机译：在COVID-19气象参数的影响传播趋势在孟加拉国

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摘要

Abstract 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
机译：抽象的理解的影响气象参数与COVID-19传播可能是一种方便的方法来预测正在进行的大流行对其自适应控制措施。COVID-19病例和之间的联系气象参数和预测COVID-19在较长时间内覆盖传播不同的气候模式。COVID-19情况下,每日记录的降雨,温度、相对湿度和风速2020年4月和5月的数据收集孟加拉国的八个主要部门。基本的统计分析和自动递减使用SPSS工具集成移动平均(ARIMA)应用于评估和探索协会吗气象参数和COVID-19之间病例及其传播的趋势。数量的显著正关联(r = ? 0.24 - -0.58)之间的存在相对湿度和COVID-19病例城市,既有积极的一面,与温度负关联(r = ? ? 0.23到0.72)透露。速度表现出正相关性。描绘COVID-19的预测趋势2020年3月8日传播,从一开始2020年9月,在孟加拉国。的?直到9月之前降低速度稳定说明气象的影响参数。

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