MODELLING THE SPREAD OF PNEUMONIA IN THE PHILIPPINES USING SUSCEPTIBLE-INFECTED-RECOVERED (SIR) MODEL WITH DEMOGRAPHIC CHANGES

Abstract

Epidemic modeling is an important tool used by mathematicians in analyzing the rate of spread of an epidemic by taking in account of the parameters and vectors that facilitate the transmission rate of the disease. The measurement of the average transmission rate through mathematical analysis helps in finding the proper approach of disease control methods in mitigating the spread of diseases. The study aims to analyze and predict the rate of transmission of the global epidemic pneumonia in the Philippines population through epidemic modeling. The study methodology used the standard epidemic model known as the SIR model to quantify real-world data on pneumonia cases into a set of differential equations while taking in consideration of changes in the population experienced due to demographic change. The study yielded results that suggested positive correlation in real-world data and the modeled data points mostly for SIR models that assumed linear change in the infection rate and recovery rate. In addition, the implementation of population models showed increases in the infection rate and the recovery rate due to increasing trend observed in the given population. The study evaluated linear rate SIR assuming exponential population growth as the most applicable epidemic model from the selection in modeling real-world epidemic data. In addition, the study compared the effectiveness of using quarantine method and vaccination method in mitigating the spread of pneumonia.