Warning Systems and Risk Reduction
A probabilistic method is proposed to assess the efficiency of warning systems in terms of costs and risk reduction. This evaluation is based both on the quality of the signal and the human response to warnings. The quality of the signal is described by probabilities of correct warnings, Type I errors, and Type II errors. Human response depend on the memory that people have kept of past warnings and is described here by a Markov model. On our hypothetical example concerning a fume detector in a chemical plant, the results show that the optimum sensitivity is at an intermediate position between extreme levels.
Key WordsWarning Systems Risk Analysis Probability Signals Memory Cost-Benefit Analysis
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