The COVID-19 pandemic raised the need to prepare for the possibility of a new pandemic stemming from an unknown "Disease X."The extent to which an epidemic will spread depends on the complex interplay of various human and environmental factors. Previous studies focused on analyzing the effects of individual parameters on disease transmission. Based on empirical COVID-19 data from South Korea, we develop a comprehensive modeling framework incorporating the population density, inter-city human mobility, the location of the initial outbreak, social distancing, and mass gathering events, with the primary goal to assess the transmission risks at a quantitative level. Systematic computations reveal the emergence of a group structure among all possible spreading scenarios: they are organized into three distinct groups with well-defined boundaries. This group structure underscores the importance of individualized risk assessment strategies for cities based on their unique characteristics, leading to intervention policies tailored to their specific circumstances.