Conventional Classification of diseases Let us see conventionally how the diseases are classified:

1. Conventional Classification of diseases Let us see conventionally how the diseases are classified: Infectious diseases Genetic diseases Nutritional diseases Endocrine diseases Mind diseases etc.

2. Examples of Snags in Disease Classification Infectious Disease is not a Nutritional Disease Nutritional Disease is not an Endocrine Disease Each disease is being attributed to one cause etc This creates lot of problems

3. Reality It is seen sometimes that Certain hormones reverse viral encephalitis Let us hypothesize that Viral encephalitis is due to endocrine problem + viral infection

4. Viral Encephalitis hypothesis At least one of the factor creating endocrine problem (genetic, drug, malnutrition, stress, improper lifestyle etc) + One of the viral infection (West Nile virus or Japanese Encephalitis Virus or Herpes Simplex Virus or Chandipura Virus or Measles or Mumps or Chicken pox or Rubella or Cytomegalovirus or HIV etc)

5. Solution to the disease If endocrine disorder precedes viral infection then Rectifying endocrine disorder would prevent encephalitis due to all viruses, Hypothetical solution could be preventing stress, fortified foods, sunbath or eating hypoglycaemic foods Simple solution but complicated research Normal Delivery

6. Alternative approach Several vaccines to prevent viral encephalitis And for each viral vaccine Scientists may perform several studies Yet results could be disappointing Simple research but complicated solution Caesarian

7. Prevention is better than cure Certain diseases make patient vulnerable Preventing the disease through vaccine for a specific disease Means Preventing the specific disease As well as Preventing several front-end events

8. Prenatal preventive steps to avoid adult disease Metabolic imprinting and programming Prenatal and early postnatal development can affect susceptibility to various adult-onset chronic diseases http://history.enotes.com/food-encyclopedia/metabolic-imprinting-programming

9. Hunt for panacea It is one of the objective of Disease Informatics

10. Priors and posteriors Health policy can not be full-proof Unless Priors and Posteriors Are estimated Appropriate Health policy document can not be prepared unless Disease Informatics shapes well

11. Disease denominator Quite a low incidence rate of a particular disease is result of the big denominator

12. Why big denominator? The disease causative agent is not considered as a component. It is assumed that it is the whole story Diseases are really complex http://www.wordinfo.info/words/index/info/view_unit/1/?letter=B&spage=3

13. Component  Sufficient Component to which Population exposed is Part of sufficient causal mechanism Prof. Kenneth Rothman Button is not sufficient cause to switch on or switch off the light.

14. Sufficient causal mechanisms.> 1 Sufficient causal mechanisms could be more than 1 Component investigated may not share all mechanisms By Kenneth J. Rothman and Sander Greenland Prof. Sander Greenland Three sufficient causes of disease.

15. No wiring no switching on of bulb Encephalitis associated with viruses (Bulb lights) Occurs in those individuals Who are predisposed (wiring is completed) And one of the several viruses (button) Triggers the disease (Switch on the bulb)

16. Why newer viruses emerge? Examine priors Viruses can not emerge outside the host Antioxidant deficiency in host could lead to emergence of new viruses Dr. Melinda Beck http://www.jacn.org/cgi/content/abstract/20/suppl_5/384S

17. Disease Definition The disease definitions require set of intersection of some factors (component causes) as denominators to make the definition complete

18. What is seen in viral encephalitis? Most of the encephalitic diseases attributed to viruses Have low incidence because Virus is not enough to cause the disease But it may be required InSouth Africa a large outbreak of west Nile affected an estimated 18 000 peopleof all ages, yet only one case of encephalitis was reported. http://bmj.bmjjournals.com/cgi/content/full/326/7394/865

19. Component and sufficient causes Which component causes come together (?) To make sufficient causal mechanism for disease (?) This is the challenge in Spatial Epidemiology and For the Disease Informatics Groups

20. Requirement of team effort Define complex diseases thereby Identifying all the targets to combat disease and Design a holistic solution

21. Disease features The disease as it is understood today has Shared + Variable features

22. Conventional disease definition 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

23. Communicable diseases In case of communicable diseases The conventional approaches to have the definition of disease in 3 phases Suspected, Probable and Confirmed and Arriving at a single cause (!!!)

24. Why modern approach? Conventional approach has Yet to generate feasible solutions for Most of the real life health problems

25. Rigid Disease Definitions One cause- one effect It is like expecting honesty from an individual Who has undergone a forced marriage

26. Where lies the solution? Considering simultaneously The non-communicable components of the disease Could really change this picture and Help in designing the health strategy

27. Multiple morbidities Sufficient cause approach could be fruitfully used if role of multiple morbidities in the outcome is precisely recognized

28. Components working together It is not A + B It is A + B + AB

29. An interaction can override any main effects When there is an interaction along with main effects, we must reexamine the main effects to see if they are really worth paying attention to. Famous statistician Keppel quoted by M. Plonsky

30. Factors working together Statistical interaction isa property of which linear model the researcher selects, nota property of the population, risk factors, or outcome. http://ajp.psychiatryonline.org/cgi/content/full/158/6/848

31. Defining the diseases The purposes of defining the diseases are To understand exactly what those are So that those are prevented or reversed

32. The basis of Disease Informatics 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)

33. Modern Epidemiology Epidemiologists Rothman and Greenland emphasize that the "One cause − one effect" understanding is A simplistic misbelief

34. Baseline for Disease Informatics “Existence of chain or web consisting of many component causes” Connotes lot of information and Could be difficult to handle manually Here goes the role of information scientists

35. Gurus Drs. Abhay and Rani Bang and their colleagues have Successfully provided solutions to several health problems By performing on multiple morbidities Dr. Abhay Bang of Gadchiroli

36. Approach After identifying several causes of an infant death and having realized that prevention of any cause could have saved the infant, Abhay and Rani Bang started working to solve the riddle.

37. www.indianngos.com/districts/gadchiroli.htm Gadchiroli The Gadchiroli approach could be fruitfully used if Role of multiple morbidities as pointed out by Drs. Bangs and their colleagues in the outcome is precisely recognized Dr. Rani Bang www.ashoka.org

38. Bayesian again To tackle the problem of Multiple morbidities Multiple hypotheses are required Alternatively, Disease Complex needs to be defined Rather than several simple diseases

39. Disease burden Burden of several diseases rely on Certain backend events of Disease Causal Chain

40. Backend vs. Frontend measures Frontend event measures are like Pruning the branches of disease tree while Backend event measures uproot the tree

41. Disease Causal Chains The Disease Causal Chains should be studied as A spatial epidemiological problem for All the diseases together Present in the locality.

42. Solving problem of Disease Complex Disease Causal Chain It could be developed as powerful technique To handle disease complex

43. Target identification Disease Causal Chain displays Several targets to solve health problem And not just the one

44. Antiviral Investigation HTS antiviral assays on New Chemical Entities These assays does not nullify The traditionally established utility of certain formulations

45. What is neglected? The ability of Traditionally established remedy to alter Disease Causal Chain Dr. Raghunath A Mashelkar

46. Who suffers? Patients are deprived of Several nutraceuticals and functional foods or Lifestyle modalities capable of Preventing or reversing the viral disease Dr. V Prakash

47. Side effects Patients of viral diseases are subjected to Consuming drugs having Tremendous side effects Nutraceuticals and functional foods Have lesser side effects

48. Disease Informatics It is the application of Information Science in Defining the diseases with least error, Identifying most of the targets to Combat a cluster of diseases (Disease Causal Chain) and Designing a holistic solution (Health strategy) to the problem Depending the severity of the disease

49. Reference • Disease informatics for setting up Disease definition, drawing Disease Causal Chain / Web, marking Risk Events, Backend and Frontend Events, and Health Problem Solutions http://bmj.bmjjournals.com/cgi/eletters/331/7516/566#134452

50. Thank you This presentation is dedicated to Dr. Ulhas V Wagh