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In the field of epidemiology, the causal mechanisms responsible for diseases can be understood using the causal pie model.This conceptual model was introduced by Ken Rothman to communicate how constellations of component causes can lead to a sufficient cause to lead to a condition of interest and that reflection on these sets could improve epidemiological study design.
The concept of component causes is part of the broader causal pie model proposed by epidemiologist Kenneth Rothman. [1] In this model, each disease is the result of multiple causal pies, each representing a combination of component causes. A single factor can be a component cause in multiple sufficient causes [2] for different diseases.
The argument proposes that there are different motives behind defining causality; the Bradford Hill criteria applied to complex systems such as health sciences are useful in prediction models where a consequence is sought; explanation models as to why causation occurred are deduced less easily from Bradford Hill criteria because the instigation ...
Judea Pearl defines a causal model as an ordered triple ,, , where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U ...
Other times there is not a single cause for a disease, but instead a chain of causation from an initial trigger to the development of the clinical disease. An etiological agent of disease may require an independent co-factor, and be subject to a promoter (increases expression) to cause disease.
Kenneth J. Rothman (born November 2, 1945) [1] is an American epidemiologist. He is a professor of epidemiology at the Boston University School of Public Health , as well as a Distinguished Fellow at RTI International , where he is Vice President for Epidemiologic Research at RTI Health Solutions .
For example, if a contact network can be approximated with an Erdős–Rényi graph with a Poissonian degree distribution, and the disease spreading parameters are as defined in the example above, such that is the transmission rate per person and the disease has a mean infectious period of , then the basic reproduction number is = [22] [23 ...
For the full specification of the model, the arrows should be labeled with the transition rates between compartments. Between S and I, the transition rate is assumed to be (/) / = /, where is the total population, is the average number of contacts per person per time, multiplied by the probability of disease transmission in a contact between a susceptible and an infectious subject, and / is ...