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Evacuation Risks: A Tentative Approach for Quantification
Author(s) -
Bastien M. C.,
Dumas M.,
Laporte J.,
Parmentier N.
Publication year - 1985
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1985.tb00151.x
Subject(s) - population , poison control , accident (philosophy) , demography , sample (material) , poisson distribution , injury prevention , statistics , occupational safety and health , poisson regression , sample size determination , geography , forensic engineering , medical emergency , environmental health , medicine , mathematics , engineering , philosophy , chemistry , epistemology , chromatography , pathology , sociology
This study tries to assess the risk of deaths and injuries from motor vehicle accidents associated with an evacuation of population groups in case of nuclear plant accidents. The risk per person–km is evaluated using: (a) data from previous evacuation: information from Soufriere evacuation (Guadeloupe Island 1976) and Mississauga (1979), added to Hans and Sell's data: no road accident occurred for a sample of 1,500,000 persons; (b) national recording system for motor vehicle accident: the rates of 2.2 10 ‐8 deaths per person–km and 32 10 ‐8 injuries per person–km is calculated as an average. These last rates in France overestimate the number of casualties. A reasonable hypothesis is to assume that the probability of road accident occurrence follows a Poisson distribution, as these events are independent and unfrequent, as no accident was observed in a sample of 1,500,000 persons the probability is between 0 and an upper value of 0.24 10 ‐8 deaths per person‐km and 3.29 10 ‐8 injuries per person–km. The average and maximum population involved within different radii around French and U.S. Nuclear power sites are taken as a sample size in order to study the total risk of deaths and injuries in the hypothesis of an evacuation being necessary to protect the populations.