Defining the diseases

The purposes of defining the diseases are to understand exactly what those are so that those are prevented or reversed. The basis of Disease Informatics is to operate on the fact that “most outcomes — whether disease or death — are caused by a chain or web consisting of many component causes”. This has been denoted as Disease Causal Chain (DiCC). Epidemiologists Rothman and Greenland emphasize that the "one cause − one effect" understanding is a simplistic misbelief.

In case of communicable diseases, the conventional approaches to have the definition of disease in 3 phases, i.e. suspected, probable and confirmed and arriving at a single cause. This approach has yet to generate feasible solutions for most of the real life health problems. Considering simultaneously the non-communicable components of the disease could really change this picture and help in designing the health strategy. The same approach could be fruitfully used if role of multiple morbidities in the outcome is precisely recognized.

Quite a low incidence rate of a particular disease is result of the big denominator. The specific component that is considered as a disease causative agent to which population exposed is not enough to explain the total disease or most part of the disease. The disease definitions require intersection of some factors as denominator to make the definition complete and specific.

Which intersection of risk factors could lead to the specific disease definition? This is the challenge in Spatial Epidemiology and for the Disease Informatics. Hence a team effort to define complex diseases thereby identifying all the targets to combat disease and design a holistic solution is absolutely necessary. The disease as it is understood today has shared + variable features. The universally shared features as against spatiality are generally considered for diseases definition. However, the most optimum solutions are spatiality dependent, shared by local people than universal.

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