QUANTIFYING CRITICAL PARAMETER IN DISEASE TRANSMISSION - Kok, Woon Chee (Universiti Malaysia Sarawak, (UNIMAS), 2015)
Today, world features an excessive of biological epidemic phenomena. Infectious diseases are the leading cause of death for human beings which includes malaria, Hand, Foot and Mouth disease, tuberculosis and many others. Therefore, the study of these diseases is important. Over the past century, researchers discover and formulate many models to observe the behavior of disease. Mathematical disease model can estimate the number of infected, forecast the outbreak periods, identify the transmission and recovered rates. Apart from that, effectiveness for vaccination can also be estimated with the aim to aid in public health decisions. Among the challenges to formulate an accurate model is in quantifying some critical parameters. The conventional parameter estimation methods take times and it is computationally expensive. The main contribution of this project is Statistical Modeling Approach towards epidemic fitting of different model such as SIR model in modeling infectious disease. In order to gain more understanding on the approach, the complete data set about Hand, Foot and Mouth Disease provided by Sarawak State Health Department has been used to quantify transmission coefficient with Maximum Likelihood Estimation. This method involves analytical method and numerical method. For numerical method, R programming algorithms were implemented to estimate the parameter faster and easier. Finally, a prototype has been developed to serve as a calculator for researchers to enable them to quantify a parameter easily.