LAB 11: MODELING OF EPIDEMIC PROPORTIONS AND INITIAL-VALUE ODE PROBLEMS

Mathematics:

Mathematical modeling of infection diseases among human's population is based on solving the initial-value problem for a system of ordinary differential equations. A mathematical model divides a total population into groups of people interacting to each other with respect to a particular infection disease and describes the number of people in each group as a function of time. This project exploits a lethal disease when the total number of population is divided into four groups: not-yet-infected, infected, medicated and dead people. The infection is assumed to result from contacts with an infected individual.

Denote the time as t, the number of susceptible (not-yet-infected) people as S = S(t), the number of infected people as I = I(t), the number of medicated people as M = M(t), and the number of dead people as D = D(t). The total number of population is N = S + I + M + D. If the natural birth and death processes are neglected on the time intervals when the infection disease blows up, spreads out and eventially disappears, then N is constant in time t.

Suppose a is the rate at which the disease spreads per day and also that the number of people who gets infected is proportional to the number of interactions between susceptible (S) and infected (I) people. Then, the rate, at which the number of susceptible people S(t) decreases, is:

= - a S(t) I(t)

Suppose r is the death rate of infected people per day and also that the number of dead people is proportional to the number of infected people (I). Then, the rate at which the number of dead people D(t) increases, is:

= r I(t)

Suppose b is the constant number of shots per day that save people's lives and that people who received the medicine can no longer be infected and are not contageous. Then, the rate, at which the number of medicated people M(t) increases, is constant as:

= b

Since the medicine is given only to sick people, it is natural to assume that b < I(t) for any t > 0. The rate, at which the number of infected people I(t) changes, can be found from the condition that the total number of people N remains unchanged for any time t > 0:

= a S(t) I(t) – r I(t) – b

By summing all four differential equations above, we confirm that:

= +  +  +  = 0.

Objectives:

·         Understand how to solve the initial-value problems for systems of differential equations

·         Exploit modeling of the epidemic proportions with the Euler method (discrete differences)

·         Exploit modeling of the epidemic proportions with MATLAB ODE solvers (Runge-Kutta and Adams)

#### MATLAB script for modeling of the epidemic proportions with the Euler method

In numerical methods of solving the initial-value problem for systems of differential equations, the solution is to be found at discrete times: t0,t1,t2,…tn, starting with the initial time t0 = 0 and ending at the final time tn = T. If the discrete times are taken with a constant step size: h = t1 – t0 = t2 – t1 = … = tn – tn-1, the derivative of any function f'(tk) at any time t = tk can be approximated by the first forward divided difference:

f'(tk) =

This is the Euler method for solving the system of differential equations. Replacing the first derivatives by the first forward differences at the times t = tk for k = 1,2,…,n; the system of differential equations becomes the discrete dynamical system, which is suitable for numerical iterations (loops):

Sk+1 = Sk – h a Sk Ik

Dk+1 = Dk + h r Ik

Mk+1 = Mk + h b

Ik+1 = Ik + h a Sk Ik – h r Ik – h b

Again, the total number of people is preserved: Nk+1 = Nk. A typical pattern of dynamical behaviour of the number of susceptible (S) and infected (I) people is shown as a function of time t:

Steps in writing the MATLAB script:

1. Define N = 10000, a = 6.90675*10-5, r = 0.1, b = 10.
2. Define at time t = 0, the initial values as I0 = 20, D0 = 0, M0 = 0, and S0 = N – I0.
3. Define a final time T = 50 (days) and the step size h = 0.1 (days). Find how many iterations n are needed to start at t = 0 and to end at t = T.
4. Run a loop in k = 1,2,…,n and find the number of susceptible (S), died (D), medicated (M) and infected (I) people at all discrete times t = tk between t = 0 and t = T. Save vectors t, S, D, M, and I.
5. Plot vectors S, D, M, and I versus t on four different graphs.
6. Plot the phase plane of S versus I with the particular solution for 0  t  T.

Exploiting the MATLAB script:

1. Using computations in the script, find the number of survived people after 15 days.
2. Run computations with no medicine (b = 0) and find the number of survived people after 15 days.

The number of survived people at any time t is

R(t) = S(t) + M(t) + I(t) = N – D(t)

The number of survived people after 15 days is R = 6673 for b = 0 and R = 8582 for b = 10.

#### MATLAB script for for modeling of the epidemic proportions with MATLAB ODE solvers

MATLAB ODE solvers include:

·         ode23: based on the variable-step Runge-Kutta method of second and third order

·         ode45: based on the variable-step Runge-Kutta method of fourth and fifth order

·         ode113: based on the Adams method of the variable order from one to thirteen

·         ode15s: based on the implicit methods of the variable order for stiff differential equations

Steps in writing the MATLAB script:

1. Define the system of differential equations in a separate function M-file "epidem" with two input arguments: t as scalar and y = [S,D,M,I] as vector, and with one output argument ydot as vector-column of the right-hand-sides of the system of differential equations. Parameters a, b, r can be defined in the body of the function file.
2. Define initial and final times: t0 and T.
3. Define a vector for initial values: y0 = [S0,D0,M0,I0].
4. Call MATLAB ODE Runge-Kutta solver "ode23" to solve the system of differential equations.
5. Retrive the output of the ODE solver "ode23" and plot S, D, M, and I as functions of t.
6. Plot the phase plane of S versus I with the particular solution for 0 < t < T.

Exploiting the MATLAB script:

1. Compare the values for the number of survivors after T = 15 days with b = 0 and b = 10 obtained by the Euler method and by the ODE solver "ode23"
2. Call other MATLAB solvers "ode45", "ode113", and "ode15s" for the same computations.

QUIZ:

1. Fill the table of data values for the number of survivors.

 Euler method ode23 ode45 ode113 ode15s b = 0 6673 b = 10 8582

1. Compute and plot functions S, D, M, and I for longer time interval (T = 100). Explain the behaviour of S, D, M, and I in terms of the mathematical model of the epidemic proportions.
2. Call MATLAB ODE solver "ode23" with tolerance control of the absolute global error to be smaller than 10-10. Find the values for the number of survived people after T = 15 days with b = 0 and b = 10.