Association between Climate Parameters and COVID-19 Pandemic in Jordan

Abstract 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 (0C), wind speed (m/s), relative humidity (%), pressure (kPa), and the concertation of the four pollutants (CO, NO2, PM10 and SO2). The data were obtained from both the World Air Quality Project website and the Jordanian Ministry of Environment. In this work, the multiple linear regression and feedforward artificial neural network were used for data analysis. It was concluded that the multiple linear regression and feedforward artificial neural network had the capability to 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.