What is 'hot spot analysis' and how is it used in risk management?

• A. A global warming projection method used to forecast climate zones.
• B. A spatial statistics technique (Getis-Ord Gi*) to identify clusters of high-risk values that warrant targeted mitigation or monitoring.
• C. A method to erase high-risk data from maps.
• D. A non-spatial risk ranking.

Answer: (B)

Hot spot analysis is a spatial statistics approach that looks at how risk values are laid out across geographic space to find where high values cluster together. In risk management, you map a risk score by location and use the Getis-Ord Gi* statistic to evaluate each site in the context of its neighbors. If a location sits in a neighborhood where many adjacent sites also show high risk, the Gi* statistic produces a high z-score and a low p-value, signaling a hotspot. These hotspots point to areas that should be prioritized for mitigation, closer monitoring, or targeted interventions because the elevated risk isn’t randomly scattered but concentrated in specific places.

This method helps allocate limited resources where they’re most needed and can be applied to various domains—environmental hazards, public health, infrastructure resilience, or security—by revealing persistent or emerging clusters over time. It’s distinct from simply ranking risk without considering location, and it’s not about projecting climate or erasing data. When using hot spot analysis, remember the results depend on how you define neighborhoods, data quality, and the need to account for multiple testing and spatial scale.