Abstract
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 (°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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
