The effect of weather data on the spread of COVID-19 in Jordan.

Abstract

This study aims to analyze the correlation between the daily confirmed COVID-19 cases in Jordan and metrological parameters including the average daily temperature (°C), maximum ambient temperature (°C), relative humidity (%), wind speed (m/s), pressure (kPa), and average daily solar radiation (W/m2). This covers the first and the second waves in Jordan. The data were obtained from both the Jordanian Ministry of health and the Jordan Metrological Department. In this work, the Spearman correlation test was used for data analysis, since the normality assumption was not fulfilled. It was found that the most effective weather parameters on the active cases of COVID-19 in the initial wave transmission was the average daily solar radiation (r = − 0.503; p = 0.000), while all other tests for other parameters failed. In the second wave of COVID-19 transmission, it was found that the most effective weather parameter on the active cases of COVID-19 was the maximum temperature (r = 0.394; p = 0.028). This was followed by wind speed (r = 0.477; p = 0.007), pressure (r = − 0.429; p = 0.016), and average daily solar radiation (r = − 0.757; p = 0.000). Furthermore, the independent variable importance of multilayer perceptron showed that wind speed has a direct relationship with active cases. Conversely, areas characterized by low values of pressure and daily solar radiation exposure have a high rate of infection. Finally, a global sensitivity analysis using Sobol analysis showed that daily solar radiation has a high rate of active cases that support the virus’ survival in both wave transmissions.