预测 1 型和 2 型糖尿病患者患病率的 Arima 模型:乔斯大学教学医院案例研究

Termen Nanfwang Yunana, K. E. Lasisi, A. M. Kwami, Douglas Jah Pam, Sheyi Mafolasire, Chibuike John Echebiri, Friday Ezekiel Danung, S. Gambo
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摘要

糖尿病是人类健康的巨大负担,患者人数的增加可能导致医疗急救需求的上升。由于具备区分 1 型和 2 型糖尿病标准实验室检测试剂盒的医院数量有限,因此必须预测未来的发病率,并做好适当的资源规划。乔斯大学教学医院每月的糖尿病患者人数采用自回归综合移动平均(ARIMA)模型进行拟合。数据集从 2010 年 1 月至 2020 年 12 月。使用自回归整合移动平均模型,根据贝叶斯信息标准(BIC)和 Ljung-Box Q 统计量对几个模型进行了评估。结果发现,ARIMA(3, 1, 1) 更适合用于描述和预测 1 型糖尿病的未来趋势,而 ARIMA(1,1,1) 则是预测 2 型糖尿病未来患病率的较好模型。因此,建议的模型将有助于适当规划和分配应急资源。
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Arima Model to Predict the Prevalence of Diabetes Type 1 and Type 2 Patients: A Case Study of Jos University Teaching Hospital
Diabetes Mellitus is a huge burden for human health, increasing number of patient is likely to result in rising demand for the medical emergencies. Due to limited number of hospitals with standard laboratory test kits to differentiate between type 1 and type 2 diabetes it is important to forecast the future incidences and prepare with proper resource planning. The monthly number of Diabetes patients obtained from Jos University Teaching Hospital is fitted by autoregressive integrated moving average (ARIMA) model. Dataset starting from January, 2010 to December,2020. Using ARIMA, several models were evaluated based on the Bayesian Information Criterion (BIC) and Ljung-Box Q statistics. ARIMA(3, 1, 1) is found to be better and used to describe and predict the future trends of Diabetes  type 1 and ARIMA(1,1,1) is a better model to predict the future prevalence of diabetes type 2. Therefore, the proposed model will help in the appropriate planning and allocation of resources for emergencies.
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