The world has been embroiled in a new epidemic known as COVID-19 since the beginning of 2020. Most countries and territories around the world are affected by the disease MESHD, and some cities have become known as epicenters due to high outbreak. The similarity of these cities can be examined within the Geographic Information System (GIS), based on various criteria. This study investigated the similarities between the eight cities of Wuhan, Tehran, Bergamo, Madrid, Paris, Daegu, New York, and Berlin in terms of the COVID-19 situation (target) in those locations based on socio-economic factors, weather, and demographic criteria. First, the factor and target layers were prepared in ArcGIS®10.6 software. For socio-economic data (such as: supermarkets, hospitals, metro stations etc.), the distance maps were classified with a fuzzy membership function. Weather and demographic criteria were also stored in the tables after normalization in the range of zero to one. In next step, the similar cities were identified using the similarity model and different distance metrics (Manhattan, Euclidean, Minkowski, Mahalanobis, Chebyshev, and Correlation). The results were aggregated using the Copeland method, due to the different outcomes of each metric. The most similar city was identified for each selected city and its similarity level was determined based on the criteria. Results indicated that pairs of similar cities are: Wuhan-Berlin, Tehran-Berlin, Daegu-Wuhan, Bergamo-Madrid, Paris-Mardid, and New York-Paris with a minimum and maximum similarity rate of 82.85% and 92.36%. For similar cities, the most similar factors among the socio-economic criteria are the distance from bus and metro stations; among weather, criteria are humidity and pressure; and among demographic criteria are male TRANS and female TRANS population ratios, literacy ratio, death MESHD ratio from asthma MESHD asthma HP and cancer with a minimum and maximum difference of 0% and 64.94%.