كنفرانس بين المللی مهندسی صنايع و سيستم ها

صفحه اصلی / یازدهمین كنفرانس بين المللی مهندسی صنايع و سيستم ها

Modeling trends and forecasting future incidence of end stage renal disease in the U.S.

نویسندگان :

Vahab Deimekar Haghighi¹

1- دانشگاه صنعتی امیرکبیر

کلمات کلیدی :

Time series،End stage renal disease،Autoregressive integrated moving average،Autocorrelation function،Forecasting،Minitab

چکیده :

This study employs time series modeling to analyze and forecast the incidence of End Stage Renal Disease (ESRD) in the United States over the period from 2002 to 2022. Utilizing annual incidence data sourced from the reputable United States Renal Data System (USRDS), the research reveals an overall fluctuating yet upward trend in ESRD cases, peaking at 136,171 in 2021 before a slight decline in 2022. Through rigorous examination of the autocorrelation (ACF) and partial autocorrelation (PACF) functions, and guided by the corrected Akaike Information Criterion (AICc) as the model selection criterion, the ARIMA(2,0,1) model was identified as the optimal fit. The stationarity of the data was confirmed by the Dickey-Fuller test, indicating no need for differencing. Forecasts for 2023 to 2027 suggest a gradual decline in ESRD incidence, potentially reflecting improvements in healthcare, earlier diagnosis, and demographic shifts. These findings underscore the critical importance of continuous surveillance and the implementation of targeted prevention and management strategies to sustain and enhance the encouraging trend toward reduced ESRD incidence.