Forecasting Dengue Incidence Utilizing Geographic Information System and Autoregressive Integrated Moving Average Models

In the health discipline, forecasting is gaining importance due to its capability of anticipating the spread of diseases. The Philippine government launched the dengue surveillance map to help detect the spread of the disease. However, technology-based solutions to forecast dengue cases do not exist in the country. This study aimed to forecast the possible outbreak of dengue in Ozamiz City from 2016 to 2020 using a web-based technology system that generates maps and allows the input of new records of dengue cases to update the forecasting patterns. This study utilized the Geographic Information System (GIS) to map the spread of dengue outbreak and the Autoregressive Integrated Moving Average (ARIMA) to forecast the extent of dengue occurrence. The data included in this study were the dengue cases reported in seven hospitals in Ozamiz City on a monthly basis from January 2008 up to the second quarter of 2015. Based on the collected data, dengue incidence is lower in rural than in urban barangays. However, a rapid increase in dengue incidence in rural barangays is evident in the five-year forecast. This information can aid the community in designing and implementing preventive measures to address dengue epidemics during the forecasted year or season.

 

Keywords: epidemic, health, map, outbreak, technology