README
Disease Spread
In 1978 the British Medical Journal reported on an outbreak of influenza at a British boarding school. There were 1000 students. The outbreak began with one infected student.
We want to study the spread of the disease through the population of this school. The total population may be divided into three: the infecteds (i), those who have recovered (r), and those who are still susceptible (s) to get the disease.
We will study the disease on a period of tm days. One model of propagation uses 3 differential equations:
(1) s'(t) = -b * s(t) * i(t)
(2) i'(t) = b * s(t) * i(t) - a * i(t)
(3) r'(t) = a * i(t)
where s(t), i(t), r(t) are the susceptibles, infecteds, recovereds
at time t and s'(t), i'(t), r'(t) the corresponding derivatives.
b and a are constants: b is representing a number of contacts
which can spread the disease and a is a fraction of the infecteds
that will recover.
We can transform equations (1), (2), (3) in finite differences.
For more info see here and additional sources here
(I) S[k+1] = S[k] - dt * b * S[k] * I[k]
(II) I[k+1] = I[k] + dt * (b * S[k] * I[k] - a * I[k])
(III) R[k+1] = R[k] + dt * I[k] *a
The interval [0, tm] will be divised in n small intervals of
length dt = tm/n. Initial conditions here could be : S0 = 999, I0 = 1, R0 = 0 Whatever S0 and I0, R0 (number of recovereds
at time 0) is always 0.
The function epidemic will return the maximum number of infecteds as an integer (truncate to integer the result of max(I)).
Example:
tm = 14 ;n = 336 ;s0 = 996 ;i0 = 2 ;b = 0.00206 ;a = 0.41
epidemic(tm, n, s0, i0, b, a) --> 483
Notes: You will pass the tests if abs(actual - expected) <= 1
Keeping track of the values of susceptibles, infecteds and recovereds you can plot the solutions of the 3 differential equations. See an example below on the plot.