Risk assessment of societal resilience in Ukraine’s frontlines areas

This report marks the first comprehensive risk assessment process for societal resilience in Ukraine, offering data that can be used for practical risk mitigation efforts as well as for subsequent comparisons. 

It presents an analysis of expert assessments provided by 88 respondents regarding the impact of particular events (threats) on societal resilience in their respective oblasts, along with the likelihood of these threats occurring within the next 12 months. Based on these inputs, risk registries have been developed for the following five targeted oblasts: Odesa, Kherson, Mykolaiv, Zaporizhzhia, and Kharkiv.

These oblasts are either partially occupied, recently de-occupied, or located close to the frontline.

The first section outlines the overall framework for assessing risks to societal resilience, detailing the methodology, core principles, and structure of the assessment process.

The second section presents a consolidated analysis of expert responses, including their strategies for mitigating risks.

The third section offers an overview of the most acute risks identified in each of the five oblasts initially selected for the assessment.

The Annexes contain full data sets from the survey, offering detailed insight into the risk environment affecting societal resilience in the five targeted oblasts.

Since the beginning of the full-scale invasion of Ukraine by the Russian Federation, numerous changes have occurred in Ukrainian society. However, the core element that anchors all these transformations is resilience — understood here as the interaction between the state and society aimed at preserving statehood and fostering a civic nation.

Time is a critical variable in resilience: short-term impact and sustained pressure over time are fundamentally different phenomena. The core threat, the armed aggression of a neighbouring country, is systemic in nature, with no clearly defined time horizon.

Below is a brief summary of the key findings derived through expert input.

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