An illness has broken out in a population of 10,000 people total. The population is broken up into four age groups: Group 1: ages 0 - 18 Group 2: ages 19 - 40 Group 3: ages 41 - 65 Group 4: 66 and over The population is modeled by an SEIR model. The governing equations of the i age groups are given as: dS(i)/dt = -1(i)S(i) DE(i)/dt = (i)S(i) - yE(i) dI(i)/dt = yE(i) - I(i) dR(i)/dt = oli) Such that l(i) = (b(i)*I(i))/N(i) and such that S(i), E(i), I(i) and R(i) are the susceptible, exposed, infectious and recovered individuals for the ith age group. Assume the following for the parameter values: o= 1/4 #standard infectious time y = 1/6 #standard exposure time Ntotal = 10,000 Age N(1) B(i) Group 1 3200 0.3 Group 2 3700 0.4 Group 3 2000 0.2 Group 4 1100 0.1 Use Python to write a code that solves the system of equations for the four age groups AND plots a case versus time graph to predict the spread of the disease, with the mentioned four age groups. An illness has broken out in a population of 10,000 people total. The population is broken up into four age groups: Group 1: ages 0 - 18 Group 2: ages 19 - 40 Group 3: ages 41 - 65 Group 4: 66 and over The population is modeled by an SEIR model. The governing equations of the i age groups are given as: dS(i)/dt = -1(i)S(i) DE(i)/dt = (i)S(i) - yE(i) dI(i)/dt = yE(i) - I(i) dR(i)/dt = oli) Such that l(i) = (b(i)*I(i))/N(i) and such that S(i), E(i), I(i) and R(i) are the susceptible, exposed, infectious and recovered individuals for the ith age group. Assume the following for the parameter values: o= 1/4 #standard infectious time y = 1/6 #standard exposure time Ntotal = 10,000 Age N(1) B(i) Group 1 3200 0.3 Group 2 3700 0.4 Group 3 2000 0.2 Group 4 1100 0.1 Use Python to write a code that solves the system of equations for the four age groups AND plots a case versus time graph to predict the spread of the disease, with the mentioned four age groups