A time series analysis of tuberculosis incidences in Pasig City, Philippines

Ma. Carlota B. Decena; Michelle Anne C. Tolentino; Cael A. Lincuna

doi:10.32890/jcia2023.2.2.5

Authors

Ma. Carlota B. Decena University of Santo Tomas
Michelle Anne C. Tolentino University of Santo Tomas
Cael A. Lincuna University of Santo Tomas

DOI:

https://doi.org/10.32890/jcia2023.2.2.5

Keywords:

autoregressive integrated moving average, cubic spline interpolation, incidence, tuberculosis

Abstract

Tuberculosis (TB) is a serious infectious disease caused by Mycobacterium Tuberculosis that mainly affects the lungs but can also attack various body organs. Globally, it has been reported that the annual number of people provided with TB treatment has grown from 6 million in 2015 to 7 million in 2018 and then 7.1 million in 2019 (WHO, 2020). In the Philippines alone, there had been an estimated 500,000 incident cases of TB in 2019. The study's objectives are to develop a model that indicates the occurrence of TB in Pasig City, determine the incidence rate in terms of gender and age of TB patients, and obtain the projected number of TB cases that will occur in 2021. In this study, only age and gender were considered in the demographic profile of the TB patients. Note that the data were organized per year and grouped according to age and gender. Since data gathered from the Pasig City Health Office (PCHO) is annually tallied, researchers used cubic spline interpolation to get data points between the given data to create an Autoregressive Integrated Moving Average (ARIMA) model. Consequently, it was used to forecast the projected number of TB patients for 2021 compared to the actual data obtained in PCHO. The results present the best fit ARIMA model per age group followed by the predicted number of cases in 2021. It is worth noting that AG2M and AG3M have the least accurate model based on the Root Mean Square Error (RMSE), a measure of accuracy between the projected value and the actual, due to their proportion.

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