Are Individuals Really so Diverse or is our Mental Model that Enhances Diversity in Others? A perspective for Modeling Non-communicable Diseases

IDs modeling has always taken into account population-scale factors because there is the assumption that the disease is acting in the same way within the same homogenous population. Thus, there is a strong focus on the pathogen that is believed to be the most important driving factor of disease incidence regardless of individual diversity.
For non-communicable disease a strong focused has always been placed at individuals because of the high complexity and diversity of disease-causing factors. Thus, a lot of attention has been placed on care and clinical monitoring considering the difficulty to stop the disease as much as for IDs.
Firstly, we argue that no inference can be made from individual to populations in a linear sense (and vipers) but certainly population scale information is necessary to predict health trajectories of individuals. Thus, we argue that differences among individuals can be high but not random nor chaotic; thus, it is possible to identify the set of exposure factors and their average persistence time (i.e., exposure time for a population) that contribute to the occurrence of diseases. If it is true that genes make up just from 5 to 10 percent of our diseases (on average) the information about socio-environmental context should allow us to predict the healthcare trajectory of a population without any clinical / biological data.
At the end the difference between IDs and NCDs is related to the difference in exposure time and latency time of the disease that are typically very large for NCDs.



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