Spatial Analysis of COVID 19 in KSA Related to Air Pollution Factor

The pathogen of the disease COVID-19 is the extreme acute respiratory syndrome COVID-19 especially in the elderly and asthmatics. In our study, we examine if long-term exposure to air pollution raises the infection situations of COVID-19 in kingdom of Saudi Arabia (KSA). Through our studies, we proved that there is an associative relationship among the air pollution factor besides, the spread of COVID-19. As the results showed that compounds of air pollution such as Carbon monoxide (CO), Ozone (O3), Sulphur dioxide (SO2), Nitrogen dioxide (NO2), and PARTICLES (PM10), are severely related to the occurrence of COVID-19 due to the rate of the ratio of these areas more in the areas with the most prevalence of cases of COVID-19, so we used in our study the SIR model. It is considered one of the easiest, most reliable tools, consisting of three compartments;prone, contaminated, and removed. Besides, we utilized the Runge-Kutta method. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Spatio-Temporal Analysis of the Spread COVID-19 in Saudi Arabia

A novel Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. In most cases, the COVID-19 virus spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes. Moreover, it specifically targets the patient's respiratory system. To date, there are no specific vaccines or treatments for COVID-19. However, many ongoing clinical trials are evaluating potential therapies. In this paper, we provide a spatial-temporal analysis of the COVID-19 spread in Saudi Arabia as a case study. Two data sets are used and processed, one supplied by the WHO organization and the second from the ministry of health of Saudi Arabia. This study presents a spatial and temporal analysis of the spread of Coronavirus disease (COVID-19) in Saudi Arabia. This kind of viral outbreaks requires early elucidation, understanding its details, clarifying the virus's classification, and its genetic origin for strategic planning, containment, and treatment. In our proposed approach, we use Scatter Plots, Moran Scatter Plots to locate the spread of (COVID-19) on the Saudi Arabia map for spatial analysis. Further, we forecast the spreading using ARIMA (Autoregressive Integrated Moving Average), it is a complex model to estimate regression models in python language. The proposed model shows incredible ability in representing the virus spread pattern with a small error margin of less than 11%. © 2020 IEEE.