To explain this spreading divergence we have to apply the theory of Probability( P)of an event as Mathematical probability ie = ( p/p+ q ) where p=number of ways that the event can occur ,q= number of ways of non-occurrence of the event . Let us consider a simple event is a composite one . The probability of a composite event as a product of the individual simple probabilities ie P( A ) So the event building composite probabibility( 4 ) will be equal to P(A ) ^2
=( p/p+q ) ^ 2 ______equation ( 1 ) .
Now considering composite Probability as Union of two individual probabilities we get :
P( A )U P ( A ) = P( A ) Union P ( A ) = P ( A ) ^2 =[ P( A )] ^2 U[ P ( A ) ^2 ]= P( A ) ^4 =........
....[P ( A )^n ]___________________equation ( 2 ) [ n =Integer = 0,1, 2 .............].
This is known as divergence theorem of Probability.
From the theorem [equation ( 2 ) so data can be generated by the following equation derived from probability statistics .
Viral load or density function becomes (y ) = [ P (A ) ] ^ n = 1+ P ( A ) + P( A ) ^2 +...........P( A ) ^n
_____________________________equation ( 3 )
Taking differential operator ( D = d/dx ) on y = D ( y )= f’(y ) = n* [ P( A ) ]^(n-1 )
f’’( y ) = n(n-1)*[P( A ) ]^( n-2 ) , f’’’( y ) = n(n-1)( n-2 ) [ P(A )^( n-3 )
Using Taylor’s expansion ( 7 ) series Σ Dn ( y ) = f’(y) +f’’(y) +f ‘’’( y ) + ................Infinity ____________equation ( 4)
Finally validating the probability density in terms of bio energetic probability ( 9 ) by Nernst’s
Theorem as ∆S = Change in entropy = K Ln[P ( A )^n ], Where K= Boltzmann Constant _____
______________equation ( 5 ) ,the randomness of spreading of infection . This randomness
can be also explained by the bio energetic state function Entropy ( 9 ).