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Hazards such as fires and floods may destroy and prevent nodes of a wireless sensor network from functioning properly and reporting measurements of interest. Destructions by hazardous events are systematic and hence different from random node and link failures, which are very common in wireless sensor networks due to the fragility of devices and the intermittent degradation in wireless link quality. An information theoretic approach is presented that may be used for detecting systematic node destructions in dense sensor deployments wherein detection by visual inspection of the destroyed sensors on a "sensor map" at a central monitoring station is hard, if not impossible. It is shown that the information theoretic approach combined with the statistical methodology presented can effectively be used for automated triggering of alarms in decision support systems to rapidly contain hazards. It is also shown that as few as approximately 20 close-proximity sensor failures could be considered "unusual" enough to detect a systematic destruction with 90% confidence in dense sensor deployments, and this is observed to be independent of deployment density. Simulations also indicate that connectivity, which is critical in wireless sensor networks for relaying measured data, is with high probability not compromised before detection takes place.