The main aim of Special Issue is to shown best examples of the application of advanced geospatial methods, cartographic, GIS to understand the impact of COVID-19 on specific areas. These impacts should relate to the social, spatial, health, geospatial, economic, environmental and others impacts. The COVID-19 has effused more globally and rapidly than previous outbreaks. The key role in this epidemic diffusion between territories has rising international connectivity and urbanization. At the beginning of the pandemic the largest number of reported cases per capita have had countries from highly globalized nations with a high level of urbanization and human mobility (e.g. the United Kingdom and the United States Italy, Spain,). Globalization positively linked to the reported number of COVID-19 cases in that more globalized countries experience greater exposure to epidemics. Second way of spatial spread is hierarchical diffusion, which is characterized by expansion from large settlements to smaller ones. Large urban areas are experiencing greater expansion due to the larger number of people, their closer proximity and increased movement. The spread of infectious disease is influenced by differences in population characteristics - population size, level of development, household size and age structure, etc.

Infectious diseases spread through space and time through inherent geographical processes. Geographical dimension with interdisciplinary dimensions (social geography, math, medicine) in post-pandemic time and new technologies and methods: spatio-temporal analysis, health and social geography, environmental variables, data mining, web-based mapping, etc.

The main objectives are increasing usefulness of the spatial analysis in the field, especially in the field of the Geography of Health with Geographic Information Systems (GIS) and its shows in investigation and management of COVID 19. The GIS, Cartography, Spatial Analysis and Statistics for COVID 19 could help us for different epidemiological control, especially COVID 19 through of analysis of factors that can influence the contagion pattern, such as dynamic (population flows), data management (big data), its visualization and presentation via GIS, data management (big data), its visualization and presentation via GIS, urbanization - situations of the epidemic and contagion relationships in the city (research population density in megalopolis), analysis of spatio-temporal statistics, etc.

The themes about health and disease of COVID 19:

(1) Medical researcher, GIS Analyst in Public Health, Epidemiologist, Health Professional, Health Geographer - The vulnerability of the population to the epidemics (as detect, characterize) and map contagion focuses. Also, one of the one of aim could be to examine the level of randomness of the spatial distribution of those infected, identify, and based on disaggregated data which is the spatial pattern observed in the distribution of those infected by COVID-19 in research area(s).

(2) Big Data analytics, Mapping Covid19 cases in specific areas, Cartographic theory and applications, Geospatial web portal and services, geostatistics and applications, GIS for environment and health, government and public services, Urban GIS and disease, Spatiotemporal dynamic analysis and simulation, Environmental health and disease - using GIS for detection, characterized the areas of greatest danger, to explore possible explanatory factors, and to determine the vulnerability of the population; spatial distribution, and analysis concentration of infected people in the closest neighborhoods in research area(s), Give proposal for precise methodological criteria for create maps (epidemiological, spatial patterns, distribution, infected areas, etc.), Determinate characteristics areas of the infected and the distance between cases.

(3) Others: population/regional studies, urban and regional analysis, tourism and environmental analysis, etc. (mobile phone data, social media data, remote sensing, etc.) and geospatial methods, including machine learning, big data analytics, space-time modelling and simulation, environmental modelling, and data visualization).