Open AccessThe Forecasting Model with Climate Variables of the Re-emerging Disease Rate in Elderly Patients
Author(s) -
Nipaporn Chutiman,
Pannarat Guayjarernpanishk,
Monchaya Chiangpradit,
Piyapatr Busababodhin,
Saowanee Rattanawan,
Butsakorn Kong-ied
Publication year - 2021
Publication title -
wseas transactions on environment and development
Language(s) - English
Resource type - Journals
eISSN - 2224-3496
pISSN - 1790-5079
DOI - 10.37394/232015.2021.17.81
Subject(s) - relative humidity , population , incidence (geometry) , statistics , air temperature , time series , maximum temperature , box–jenkins , geography , environmental science , climatology , mathematics , meteorology , autoregressive integrated moving average , medicine , environmental health , geometry , geology
This research forecasted the incidence rate per 100,000 elderly population with food poisoning, pneumonia, and fever of unknown origin in Khon Kaen Province and Roi Et Province in the northeastern part of Thailand. In the study, the time series forecasting with Box-Jenkins Method (SARIMA model) and Box-Jenkins Method with climate variables, i.e total monthly rainfall, maximum average monthly temperature, average relative humidity, minimum average monthly temperature and average temperature (SARIMAX model) was performed. The study results revealed that the forecasting accuracy was closely similar to the model without the climate variables in the combined analysis although such climate variables had relationship with the incidence rate per 100,000 elderly population with food poisoning, pneumonia, and fever of unknown origin. Therefore, the appropriate model should be the SARIMA model because it is easier for analysis but with higher forecasting accuracy than the SARIMAX model.