Table_1_Spatial-temporal analysis of hepatitis E in Hainan Province, China (2013-2022): insights from four major hospitals.XLSX

ObjectiveExploring the Incidence, Epidemic Trends, and Spatial Distribution Characteristics of Sporadic Hepatitis E in Hainan Province from 2013 to 2022 through four major tertiary hospitals in the Province.
MethodsWe collected data on confirmed cases of hepatitis E in Hainan residents admitted to the four major tertiary hospitals in Haikou City from January 2013 to December 2022. We used SPSS software to analyze the correlation between incidence rate and economy, population density and geographical location, and origin software to draw a scatter chart and SAS 9.4 software to conduct a descriptive analysis of the time trend. The distribution was analyzed using ArcMap 10.8 software (spatial autocorrelation analysis, hotspot identification, concentration, and dispersion trend analysis). SAS software was used to build an autoregressive integrated moving average model (ARIMA) to predict the monthly number of cases in 2023 and 2024.
ResultsFrom 2013 to 2022, 1,922 patients with sporadic hepatitis E were treated in the four hospitals of Hainan Province. The highest proportion of patients (n = 555, 28.88%) were aged 50–59 years. The annual incidence of hepatitis E increased from 2013 to 2019, with a slight decrease in 2020 and 2021 and an increase in 2022. The highest number of cases was reported in Haikou, followed by Dongfang and Danzhou. We found that there was a correlation between the economy, population density, latitude, and the number of cases, with the correlation coefficient |r| value fluctuating between 0.403 and 0.421, indicating a linear correlation. At the same time, a scatter plot shows the correlation between population density and incidence from 2013 to 2022, with r2 values fluctuating between 0.5405 and 0.7116, indicating a linear correlation. Global Moran’s I, calculated through spatial autocorrelation analysis, showed that each year from 2013 to 2022 all had a Moran’s I value >0, indicating positive spatial autocorrelation (p < 0.01). Local Moran’s I analysis revealed that from 2013 to 2022, local hotspots were mainly concentrated in the northern part of Hainan Province, with Haikou, Wenchang, Ding’an, and Chengmai being frequent hotspot regions, whereas Baoting, Qiongzhong, and Ledong were frequent cold-spot regions. Concentration and dispersion analysis indicated a clear directional pattern in the average density distribution, moving from northeast to southwest. Time-series forecast modeling showed that the forecast number of newly reported cases per month remained relatively stable in 2023 and 2024, fluctuating between 17 and 19.
ConclusionThe overall incidence of hepatitis E in Hainan Province remains relatively stable. The incidence of hepatitis E in Hainan Province increased from 2013 to 2019, with a higher clustering of cases in the northeast region and a gradual spread toward the southwest over time. The ARIMA model predicted a relatively stable number of new cases each month in 2023 and 2024.

研究目的：依托海南省四家大型三级医院，探究2013-2022年海南省散发性戊型肝炎的发病情况、流行趋势及空间分布特征。
研究方法：收集2013年1月至2022年12月期间，海口市四家大型三级医院收治的海南常住居民戊型肝炎确诊病例数据。采用SPSS软件分析发病率与经济水平、人口密度及地理位置的相关性；使用Origin软件绘制散点图，通过SAS 9.4软件对时间趋势进行描述性分析。利用ArcMap 10.8软件开展分布分析，包括空间自相关分析、热点识别、聚集与离散趋势分析。采用SAS软件构建自回归积分滑动平均模型（ARIMA），对2023年及2024年的月度病例数进行预测。
研究结果：2013-2022年，海南省四家医院共收治散发性戊型肝炎患者1922例。其中50-59岁年龄段患者占比最高（n=555，28.88%）。戊型肝炎年发病率于2013-2019年呈上升趋势，2020、2021年小幅下降，2022年再次回升。病例数最多的地区为海口市，其次为东方市与儋州市。研究发现，经济水平、人口密度、纬度与病例数存在相关性，相关系数|r|值介于0.403至0.421之间，提示存在线性相关。同时，散点图显示2013-2022年人口密度与发病率的相关性，决定系数R²值介于0.5405至0.7116之间，同样提示存在线性相关。通过空间自相关分析计算得到的全局莫兰指数（Global Moran’s I）显示，2013-2022年各年度的莫兰指数值均大于0，表明存在空间正自相关（P<0.01）。局部莫兰指数分析结果显示，2013-2022年局部热点区域主要集中于海南省北部，海口市、文昌市、定安县与澄迈县为高频热点区域；而保亭县、琼中县与乐东县则为高频冷点区域。聚集与离散趋势分析表明，平均密度分布呈现明显的方向模式，由东北向西南延伸。时间序列预测模型结果显示，2023年及2024年的月度新增报告病例数相对稳定，波动范围为17-19例。
研究结论：海南省戊型肝炎整体发病率相对稳定。2013-2019年海南省戊型肝炎发病率呈上升趋势，病例在东北地区聚集性较高，且随时间推移逐渐向西南地区扩散。ARIMA模型预测2023年及2024年的月度新增病例数仍将保持相对稳定。