Spatial and Temporal Mapping of COVID-19 Pandemic Using GIS Technique: A Case Study of Italy Authors M. Farhan Ul Moazzam

Abstract

Coronavirus pandemic disease (COVID-19) has spread globally. Presently, there is insufficient data regarding clinical studies and its epidemiological features. However, it is comprehended that most of the COVID-19 infected patients show mild to moderate symptoms which improve without any medical assistance attributing to enhanced immune system by generating antibodies against the viral antigens. In this comparative study, the active cases, recovered cases, deaths, and total confirmed cases from January 2020 to 23rd August 2021 have been analyzed using a geospatial technique inverse distance weighting (IDW). Until latter, the total number of COVID-19 cases reported in Italy were 4,168,699 including 128,715 deceased, 3,904,429 recovered and 135,555 cases were still active carriers. Out of total cases 20.76% were reported in Lombardia region with a death rate of 26.26%. This mortality rate was found higher in comparison with rate followed by Emilia-Romagna (10.35%), Piemonte (9.10%), and Vento (9.06%). While percentage of recovery was found variable i.e. in Lombardia 20.98%, followed by Veneto 10.89%, Campania 10.88% and Emilia-Romagna 9.72%. COVID-19 evolution in Italy has majorly affected the urban area i.e., Rome, Milan, Naples, Bologna, and Florence. Geospatial technology played a vital statistical role by tracking infected patients, active cases, and the recovered cases. Thus, it is acknowledged that geospatial techniques are an important tool in statistical evaluation of disease spread and their control among populations

Spatial distribution and mapping of COVID-19 pandemic in Afghanistan using GIS technique

“…Nooristan province ranks the lowest in the number of active infections but again Kabul stands at the top in the number of mortalities which accounts for the highest death rate in the country. The correlation between population and number of cases, deaths, and recoveries has a positive relationship which is also observed in another study (Ganasegeran et al 2021a , b ; Moazzam et al 2021 ). A very strong correlation was found between the population density and the COVID-19 variables which is very necessary for officials in establishing new healthcare centers and providing guidelines to the community based on the density of the disease-prone areas.…”

Spatial Autocorrelation of COVID-19 in Slovakia

“…It is documented for us by studies that are published in various regions of the world. As an example, we present studies from Italy [ 8 , 9 , 10 ], Turkey [ 11 ], Algeria [ 12 ], India [ 13 ], Indonesia [ 14 ], Kuwait [ 15 ], China [ 16 ], and Canada [ 17 ]. In the space of the V4 countries, contributions were made from the environment of the Czech Republic [ 18 , 19 , 20 ], Poland [ 21 ], Hungary [ 22 , 23 ], and Slovakia [ 24 , 25 , 26 ].…”