Epidemiology of Production Diseases

Prevention and control of production diseases requires a profound knowledge on the epidemiology of the respective disease or disease complex. The objective of this chapter is therefore to introduce important epidemiological concepts and their application to production diseases. When investigating the causal factors which lead to production disease, it is important to keep in mind that, by definition, production diseases are not caused by a single pathogen or factor but rather by a combination of component causes and factors predisposing for disease. Causality should therefore be defined as a range of evidence rather than a direct relation between a factor and disease. Methods of descriptive epidemiology are an important basis to understand disease. Frequency of disease should be expressed in relation to the population at risk, as an incidence or prevalence. Describing the distribution of disease over time and location is helpful for forming hypotheses on factors contributing to disease risk. Many epidemiological methods exist for analyzing associations between disease and risk factors. These methods range from simple descriptive measures such as relative risk and odds ratios to statistical models such as regression models and more advanced methodologies such as Bayesian methods and machine learning algorithms. For production diseases with infectious etiology, methods from infectious disease epidemiology such as SIR (susceptible-infectious-resistant) models, agent-based models, or network models can also be applied.