Human Immunodeficiency Virus(HIV) Cases in the Philippines: Analysis and Forecasting
Analaine May A. Tatoy, Roel F. Ceballos

TL;DR
This study analyzes and forecasts the increasing trend of HIV cases in the Philippines using SARIMA modeling, indicating the trend will likely continue without significant change.
Contribution
It identifies the best SARIMA model for forecasting HIV cases in the Philippines based on time series analysis and diagnostic checks.
Findings
HIV cases in the Philippines are increasing and non-stationary.
The SARIMA model effectively forecasts future HIV cases.
Forecasts suggest the current trend will persist.
Abstract
Reports from the Health Department in the Philippines show that cases of Human Immunodeficiency Virus (HIV) are increasing despite management and control efforts by the government. Worldwide, the Philippines has one of the fastest growing number of HIV cases. The aim of the study is to analyze HIV cases by determining the best model in forecasting its future number of cases. The data set was retrieved from National HIV/AIDS and STI Surveillance and Strategic Information Unit (NHSSS) of the Department of Health containing 132 observations. This data set was divided into two parts, one for model building and another for forecast evaluation. The original series has an increasing trend and is nonstationary with indication of non-constant variance. Box-Cox transformation and ordinary differencing were performed on the series. The differenced series is stationary and tentative models were…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsForecasting Techniques and Applications · Data Analysis with R
