Mathematical prediction for measles using Seir Model / Muhammad Lokman Mohd Zulkifli and Nur Syafiqah Din

This Final Year Project focusing in solving and study of the susceptible, exposed, infected and recovered model (S,E,I,R) or measles disease. This project is based on the prediction of (S,E,I,R) measles models. which are used to study the overall to achieve the title and solve the objective Measles is the higher contagious that ca spread in community population depending in the number of people susceptible or infected and depending in their movement in a community. Measles disease data are mostly the lending cases population in England and Wales for 2017.
Firstly, this project formulate the S,E,1,R model of measles by refer to main article. The parameter of model like B. β, μ: α, σ, and γ are used to formulate into the model. The parameter using for represent of the description of measles model.
Furthermore. this project continue to investigate the stability analysis of disease free equilibrium and endemic equilibrium. Before proving the solution to obtained the final answer. investigation of main research is make to show step by step. In solving the analysis stability. re productive number are prove using jacobian matrix to show the reproductive number is disease free equilibrium which is smaller than zero. Next, stability analysis for disease free equilibrium and endemic equilibrium are showed and both system are stable which is the values of λ are negative
Finally. prediction for measles cases are shown using Maple software. Data 2017 are used in the result and prediction until 20027 also shown. Graph between S,E,I,R model and time in 10 years shown in Figure 5.5. Prediction cases for 10 years shown a improvement because of vaccination. Overall, cases for all model were decrease.