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Persistent Spatio-Temporal Outage Hotspot Detection for Infrastructure Resilience Planning
- Source
- arXiv — Computers and Society
- Published
- Last verified
- 19 Aug 2026
- Confidence
- High
- Evidence
- Original document retained
- Reading time
- 1 min
- Country
- International
- Relevant to
- Research & Evidence, Technology & Data, Risk & Compliance, Strategy & Planning
Executive summary
What happened, and why should leadership care?
Research from arXiv presents a novel data-driven geospatial framework designed to identify persistent spatio-temporal outage hotspots within interdependent power-communication networks. This framework integrates the analysis of recurring vulnerability with the impact of cascading failures, utilizing a national power outage dataset from 2015-2023. A key contribution is the Hotspot Persistence Index (HPI) for identifying consistently vulnerable counties, refined into regional failure scenarios for infrastructure resilience planning.
Why this matters
Why is this strategically important?
This research provides a critical tool for understanding and anticipating systemic vulnerabilities in essential infrastructure, particularly in the face of increasing extreme weather events. By identifying persistent outage hotspots and potential cascading impacts, it enables proactive and targeted resilience planning, thereby mitigating long-term operational and economic disruptions.
Key insights
What should be noted from the evidence?
- Extreme weather events cause persistent geographic patterns of power-grid disruption.
- Traditional outage hotspot detection and infrastructure cascade modeling are often treated as separate domains.
- A new data-driven geospatial framework links persistent outage vulnerability with downstream cascade impact in interdependent power-communication networks.
- The Hotspot Persistence Index (HPI) is introduced as a severity-aware metric to identify counties repeatedly emerging as outage hotspots.
- The framework employs a multi-scale DBSCAN refinement to convert county-level hotspots into geographically interpretable regional failure scenarios.
Evidence and confidence
How far can this assessment be trusted?
High confidence. Named institution, original document retained and analysis corroborated.
Analysis is prepared editorially by Aziz Shuaib Ausi. The original publication remains the authoritative record, and executive judgement remains entirely human.
Source
Where does this originate?
Reported by arXiv — Computers and Society · International. This briefing summarises the publication for executive use; the document itself is not reproduced here.
Read the original publication