Abstract
Mechanistic and biologically based mathematical models of chronic and behavioral disease processes aim to capture the main mechanistic or biological features of the disease development, and to connect these with epidemiological outcomes. These approaches have a long history in epidemiological research and are complementary to traditional epidemiological or statistical approaches to investigate the role of risk factor exposures on disease risk.In the article by Simonetto et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX–XXXX)), the authors present a mechanistic, process-oriented, model to investigate the role of smoking, hypertension and dyslipidemia on the development of atherosclerotic lesions and their progression to myocardial infarction (MI). Their approach builds on and brings to cardiovascular disease the ideas and perspectives of earlier mechanistic and biologically based models for the epidemiology of cancer and other chronic diseases, providin g important insights into the mechanisms and epidemiology of smoking related MI.We argue that although mechanistic modeling approaches have demonstrated their value and place in epidemiology, they are highly underutilized. We call for efforts to grow mechanistic and biologically based modeling research, expertise and awareness in epidemiology, including the development of training and collaboration opportunities to attract more students and researchers from STEM areas into the epidemiology field.
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