Forecasting the number of patients with the disease due to the effects of air pollution and its relationship with air pollution levels, Chiang Rai province
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Abstract
BACKGROUND:In 2023, Chiang Rai Province had 231,390 patients due to the effects of air pollution, ranking second in Regional Health 1 after Chiang Mai Province. Studying such impacts is important for spatial public health management.
OBJECTIVE:To predict the number of monthly patients of 12 disease groups due to the effects of air pollution and the number of monthly chronic obstructive pulmonary disease (COPD) patients in 2024 using the Box-Jenkins method and find the relationship between the number of patients and air quality.
METHODS:The monthly patients and air quality data collected from the Ministry of Public Health database and the Pollution Control Department, respectively. The time series analysis model ARIMA was created with the auto.arima() function and calculate the correlation with the jamovi statistical analysis program.
RESULTS:Using data on the number of patients for 36 months from 2021 to 2023,a model to predict the number of monthly patients of 12 disease groups due to the effects of air pollutionwas ARIMA(1,0,1)(1,1,0)12with drift and a mean absolute percentage error (MAPE) of 6.28, and a model to predict the number of monthly COPD patients was ARIMA (1,0,0)(0,1,0) 12 MAPE 7.30.The data on the number of patients and the monthly average of dust particles no larger than 10 microns (PM10) and dust particles no more than 2.5 microns (PM2.5) in the same period were from July 2020 to October 2023. The Spearman correlation of overall monthly patients and monthly average PM 10 and PM2.5 ranged from 0.17 to 0.39, with poor to faircorrelation.The Spearman correlation between the number of monthly COPD patients and monthly averages of PM10and PM2.5 ranged from 0.43 to 0.60 (p-value <.01), with faircorrelation.
CONCLUSIONS AND RECOMMENDATIONS:MAPE less than 10 isamong the criteria for good prediction. Verifying the forecast results with the actual values thatwill be reported by the Ministry of Public Health is necessary in order to develop a model with higher accuracy.
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