Study of climatology parameters on COVID-19 outbreak in Jordan

摘要

To control the spread of COVID-19 disease and reduce its mortality, an early and precise diagnose of this disease is of significant importance. Emerging research data show that the current COVID-19 pandemic may be affected by environmental conditions. Therefore, the impact of weather parameters on COVID-19 distribution should be explored to predict its development in the next few months. This research aims to study the association between the daily confirmed COVID-19 cases in the three major cities of Jordan; Amman, Zarqa, and Irbid and climate indicators to include the average daily temperature (degrees C), wind speed (m/s), relative humidity (), pressure (kPa), and the concentration of four pollutants (CO, NO2, PM10, and SO2). The data were obtained from the World Air Quality Project website and the Jordanian Ministry of Environment. A total of 305 samples for each city was used to conduct the data analysis using multiple linear regression and a feedforward artificial neural network. It was concluded that the multiple linear regression and feedforward artificial neural network could forecast the COVID-19 confirmed cases in the case studies; Amman, Irbid, and Zarqa. Finally, global sensitivity analysis using Sobol analysis indicated that pressure in Amman and Zarqa and the concentration of NO2 in Irbid has a high rate of positive cases that supports the virus's spread.