Computer simulation of industrial hazards¹

Abstract

Knox, E. G. (1973).Brit. J. industr. Med.,30, 54-63. Computer simulation of industrial hazards. A computer simulation system for a range of industrial hazards provided for model experiments which manipulated (a) the sub-structure of an exposed population in terms of age-distributions and levels of exposure, (b) the nature of the dose/response relationship, (c) the latent interval and its variability, (d) normal life-table expectations, and (e) employment turnover rates. The development of the system led to clarification of terms and concepts with ambiguous current usages, notably in relation to latency. Distinction is made between the notions of `biological' and `observable' latent intervals.

Hypothetical exercises with the model tested its technical validity and at the same time demonstrated in quantitative terms the relationships between `biological' and `observable' latent intervals, employment turnover rates, total mortalities, and the distribution of illnesses and death between those currently employed in the exposing industry, those employed elsewhere, and those retired. Prospects of success for personnel engineering techniques, which manipulate age-distributions of exposed work people in relation to diseases with long latent intervals, were examined.

Published asbestos cancer data were used as a basis for specific model fitting and resulted in a numerical formulation of the exposure/response relationships. Severe exposure results in an increment of risk of death of about 0·02 unit per person per annum for those exposed for around six years, but with higher rates for shorter exposures and lower rates for longer ones. The mean biological latent interval was about 25 years with a coefficient of variation of about 25%. These suppositions explained a range of published data comprehensively and at the same time predicted that (a) persons exposed at severe levels for a working lifetime of 50 years have a 40% risk of dying from asbestos cancer, and (b) industrial populations with moderate to high turnover rates effect a form of extended dose sharing, and non-linearity of the exposure/response relationship results in substantially more deaths than would be the case if the turnover rate were lower.