Conventional Classification of diseases

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 Infect
ious 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 Preve
nting 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/metabo
lic-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_uni
t/1/?letterBspage3
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.gt 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
In South Africa a large outbreak of west Nile
affected an estimated 18 000 people of 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 is a property of which
linear model the researcher selects, not a
property of the population, risk factors, or
outcome.
http//ajp.psychiatryonline.org/cgi/content/full/1
58/6/848
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
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/331/7516/5
66134452
50
Thank you
This presentation is dedicated to Dr. Ulhas V Wagh