# The Assessment of COVID-19 Vulnerability Risk for Crisis Management
## 3 Results and Discussion
### Validation  
The validation of results was performed in two stages: the first stage was the juxtaposition of CVI and confirmed cases in the time presented. The second stage was the comparison of CVI and COVID-19 active cases. The validation was performed according to the data from Table 6.  
Figure 14 shows the CVI and confirmed cases in selected days on Berlin, Brandenburg, Nordrhein-Westfalen. According to Figure 14 the COVID-19 vulnerability risk in Berlin and Brandenburg, Nordrhein-Westfalen on the first three bars (4 March 2020, 12 May 2020, and 12 August 2020) was growing constantly and this, despite the constant number of new cases, suggests that some actions or preventive steps should be taken in order to reduce the large increase in COVID-19 infections that occurred on the following days: 12 November 2020, 12 February 2021, and 12 May 2021. The above shows that the growing or high value of the COVID-19 vulnerability risk index predicts an upcoming pandemic wave that can be foreseen in a short period of time. Figure 15 shows the CVI and confirmed cases in selected days on Berlin, Brandenburg, Nordrhein-Westfalen. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & & & & & & & & & \\ \hline Berlin & Cases & 7 & 2 & 111 & 1132 & 485 & 510 & 358 & 713 \\  & CVI & 5.52 & 5.67 & 5.86 & 6.34 & 6.03 & 5.95 & 5.67 & 5.74 \\ \hline Brandenburg & Cases & 1 & 5 & 8 & 452 & 374 & 397 & 116 & 685 \\  & CVI & 3.09 & 3.13 & 3.21 & 3.59 & 3.63 & 3.43 & 3.13 & 3.43 \\ \hline Nordrhein-Westfalen & Cases & 115 & 201 & 413 & 4615 & 1881 & 3108 & 1886 & 2284 \\  & CVI & 3.59 & 3.81 & 3.82 & 4.56 & 4.26 & 4.32 & 3.81 & 3.82 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: CVI and new COVID-19 Cases in time for Berlin, Brandenburg, Nordrhein-Westfalen. Figure 15: CVI and COVID-19 confirmed cases in (**a**) Berlin, (**b**) Brandenburg and (**c**) Nordrhein-Westfalen. The chart analysis reveals a positive exponential trend between CVI and the number of confirmed cases with the R\({}^{2}\) value of 0.92 respectively (Figure 16). The study has the following known limitations:  
* Weights summary estimation was based on the AHP method. In this regard, it is essential to pay attention to the problem of criteria selection key and criteria quantity. The increase in criteria quantity would result in a more precise view of the situation in terms of several factors. However, more criteria will cause difficulties in performing analysis due to the lack of available data. If the number of criteria will be decreased--the analysis would be more general, but the data acquisition problem will be less probable. * Criteria proposed by the authors, and calculated weights create a perspective, focused on health care state image and selected population statistics. This excludes the possibility of insight and of estimating the influence of other factors on pandemic situation. The presented approach and selected criteria include the static criteria groups that allow for early vulnerability risk detection (e.g., in risk of shortage of hospital beds) and furthermore dynamic criteria group for tracking the progress of pandemic in time (new cases). * The performed analysis was limited to the inference at the strategic level, which results from the limited detailed data access. Obtaining the data in subregions division would allow for more precise identification of pandemic vulnerability risk and would result in appropriate crisis response ensuring public safety. The authors argued that there is quite an immerse gap in the possibilities of conducting spatiotemporal analysis caused to the lack of accurate data. More detailed data are required to prepare recommendations for the selected subregion. The comparison of the obtained results with the results of works by other authors reveals that those criteria that provide a thematic direction for the analysis results and data are important for the results. As far as the proposed methodology is concerned, data obtained from open data sources were used.