Forecasting the Monthly Cases of Human Immunodeficiency Virus (HIV) of the Philippines

摘要

Objective: To build a best model in forecasting the monthly cases of Human Immunodeficiency Virus (HIV) of the Philippines. Methods/Statistical Analysis: The researchers gathered time series data which is monthly HIV new cases from January 2011 to December 2015 from the monthly records of HIV/AIDS new cases in the Philippines from the HIV/ AIDS and ART Registry of the Philippines (HARP) under the umbrella of Department of Health. The researchers utilized advanced statistical tool in developing the model using Univariate Box-Jenkins method in forecasting the HIV cases per month. Findings: The result shows that the monthly cases of HIV in the Philippines has an upward trend, it was observed that the highest peak was on June 2015 with 772 new cases. From the given time, December 2015, It shows that it increases by 82.39% number of HIV cases at the end of December 2016. Satisfying the assumptions of the said method and its model diagnostic checking, the researchers came up with the best model based on AIC is SARIMA (2,1,0) (0,0,1)[12] with drift. The model is Number of HIV Cases (Predicted) = (24.19) Inflation (All Items)– (61.39) Inflation(Health). The developed model of the researchers could help the Department of Health in allocating line item budget for the implementation of prevention projects for HIV cases and intensify measures in monitoring such cases. Applications/Improvements: Results from the study can be a basis/evidence to raise awareness about the epidemic cases of HIV in the country. Researchers suggest that a time series analysis of HIV cases by gender be explored.