# The Assessment of COVID-19 Vulnerability Risk for Crisis Management
## 1 Introduction
Those are followed with conclusions on the use of heterogeneous data sources and remotely sensed data to improve the analysis results, [53; 55; 56], furthermore, authors show that the potential improvement in the accuracy of GIS-based analysis can be achieved by applying a dedicated approach, for example, neural network [54], integrated uncertainty-sensitivity analysis approach, and attributed model of criteria weights [56]. Figure 1: Weighted network visualisation of associations between terms within “crisis management spatial analysis” keyword relations (own study). Pandemic situation publications are considering the causes and potential effects of COVID-19. Researchers show the positive associations between new COVID-19 cases and death cases linked to several factors: public transport usage [15; 23; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60], temperature and humidity [21; 61], age, sex, blood group, had influenza [50; 62; 63], poverty [64], and socio-cultural factors [65]. Furthermore, the juxtaposition of virus transmission acceleration in several countries in relation to the global policy and government responses, human mobility, environmental impact, socioeconomic, lockdown, migration, and vaccination was delivered [20; 59; 66; 67] based on the developed spatiotemporal data matrix of factors and open data sources. The above leads to the determination of the most significant factors, enabling the prediction and modelling of the spatial patterns of virus spread. The researchers commonly use spatial statistic tools such as linear and non-linear regression [50], Bayesian Belief Networks [68], Adaboost algorithm [69], Potential Model [70], Joinpoint analysis [71], machine learning [50; 72] in modelling COVID-19 spatial pattern. As a result, it is possible to forecast the COVID spread and to deliver an effective response in cluster containment for crisis situations with intelligent computing [20; 62; 70; 73; 74]. Publications considering the effects of the pandemic show the use of socioeconomic data collection on daily new COVID-19 cases to link them to real gross domestic product, unemployment rate, housing prices, export and import, energy system environment [73; 75; 76; 77; 78; 79]. In the analysed publications on the subject of crisis management, the following problems are considered: the definition of risk, vulnerability, and hazard [80], the analysis of the existing crisis situation, and the management process [2; 32; 38; 65; 81; 82; 83]. The pivotal role of crisis management is to ensure public safety, in the matter of a pandemic, it is closely related to the capacity of the healthcare system [84; 85; 44; 86]. Therefore, crisis management has to eliminate the possibility of an overload of the healthcare system, so that the number of new hospitalisations does not exceed the capacity of the healthcare system in a given area, as shown in Figure 2. Therefore, it is necessary to efficiently manage the available forces (medical staff, volunteers, services) and resources (infrastructure, equipment, equipment, and material reserves, restrictions, vaccinations) in time. Thus, it was assumed that the essential knowledge on the pandemic situation and COVID-19 vulnerability should be considered in a spatiotemporal approach. This determined the aim of our research: to estimate the vulnerability index based on selected criteria along with the determination of its change over time in order to assess the threat caused by COVID-19 in the given area. This will extend the approach presented [31]. Figure 2: Healthcare system capacity and possible new cases. Based on a comprehensive analysis of the literature, the aim of this article was to answer the following questions:  
* What information can a study of the spatiotemporal vulnerability and risk provide? * What is the influence of selected criteria on the final value of the COVID-19 vulnerability? * What direction of changes over time can be observed in the distribution and concentration of vulnerability risk?