Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model

Area of Science:

• Public Health
• Epidemiology
• Health Economics

Background:

• Diabetes poses a significant and growing public health challenge in China.
• Accurate prediction of diabetes prevalence and its economic impact is crucial for resource allocation.

Purpose of the Study:

• To forecast the future number of individuals with diabetes in China.
• To estimate the economic burden associated with diabetes in China.
• To evaluate the utility of the ARIMA model for diabetes prediction.

Main Methods:

• Utilized time-series analysis with the autoregressive integrated moving average (ARIMA) model.
• Employed natural logarithmic transformation for diabetes prevalence data (2000-2018).
• Applied bottom-up and human capital approaches to calculate direct and indirect economic costs.

Main Results:

• The ARIMA model demonstrated strong predictive accuracy for diabetes cases.
• Diabetes prevalence is predicted to increase, reaching approximately 100 million by 2025.
• The estimated economic burden of diabetes is projected to rise, nearing $170 billion by 2025.

Conclusions:

• The escalating diabetes situation in China necessitates proactive public health interventions.
• The ARIMA model is a reliable tool for forecasting diabetes trends.
• Rational allocation of health resources is essential for effective diabetes prevention and control.