Health protection planning for extreme weather events and natural disasters.

OBJECTIVE: There is a need to develop cost-effective methods to support public health policy makers plan ahead and make robust decisions on protective measures to safeguard against severe impacts of extreme weather events and natural disasters in the future, given competing demands on the social and healthcare resources, large uncertainty associated with extreme events and their impacts, and the opportunity costs associated with making ineffective decisions. DESIGN: The authors combine a physics-based method known as nonextensive statistical mechanics for modeling the probability distribution of systems or processes exhibiting extreme behavior, with a decision-analytical method known as partitioned multiobjective risk method to determine the optimal decision option when planning for potential extreme events. RESULTS: The method is illustrated using a simple hypothetical example. It is shown that partitioning the exceedance probability distribution of health impact into three ranges (low severity/high exceedance probability, moderate severity/medium exceedance probability, and high severity/low exceedance probability) leads to the correct estimation of the conditional expected impact in each range. Multiobjective optimization is used to determine the optimal decision option based on the perspective of the policy maker. CONCLUSION: This method constitutes a robust generic framework for the quantification of impacts and supporting decision-making under scenarios of extreme and catastrophic health risks.

Generalized statistical mechanics approaches to earthquakes and tectonics.

Despite the extreme complexity that characterizes the mechanism of the earthquake generation process, simple empirical scaling relations apply to the collective properties of earthquakes and faults in a variety of tectonic environments and scales. The physical characterization of those properties and the scaling relations that describe them attract a wide scientific interest and are incorporated in the probabilistic forecasting of seismicity in local, regional and planetary scales. Considerable progress has been made in the analysis of the statistical mechanics of earthquakes, which, based on the principle of entropy, can provide a physical rationale to the macroscopic properties frequently observed. The scale-invariant properties, the (multi) fractal structures and the long-range interactions that have been found to characterize fault and earthquake populations have recently led to the consideration of non-extensive statistical mechanics (NESM) as a consistent statistical mechanics framework for the description of seismicity. The consistency between NESM and observations has been demonstrated in a series of publications on seismicity, faulting, rock physics and other fields of geosciences. The aim of this review is to present in a concise manner the fundamental macroscopic properties of earthquakes and faulting and how these can be derived by using the notions of statistical mechanics and NESM, providing further insights into earthquake physics and fault growth processes.