Assessment of Emergency Response Policy Based on Markov Process

Abstract

Major accidents not only endanger the health and safety of the population, but also bring bad influence to the environment around. In order to mitigate the adverse effects, emergency response policy (ERP) and corresponding protection action should be established. To maximize its effectiveness, ERP should be evaluated and optimized, while the most important criteria is minimizing the health consequence of the accident. A discrete state stochastic Markov process was used to simulate the movement of the evacuees in this paper. Solution of the Markov process provided the expected distribution of the evacuees in the area as a function of time. Then, according to the way how extreme phenomena impact individual and the dose-response relationship, the people’s health effects were calculated, so that the accident’s health consequence was determined. Finally, different emergency response policies were evaluated with corresponding health consequence, so that the emergency policy can be optimized.