PDF(Pubmed)
Abstract：
UNASSIGNED: Exploring 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.
UNASSIGNED: We 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.
UNASSIGNED: From 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.
UNASSIGNED: The 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.
UNASSIGNED: We 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.
UNASSIGNED: From 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.
UNASSIGNED: The 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.
摘要：
■探索发病率，流行病趋势,2013-2022年海南省四大三级医院散发性戊型肝炎的空间分布特征。
■我们收集了2013年1月至2022年12月海口市四大三级医院收治的海南居民戊型肝炎确诊病例数据。采用SPSS软件对发病率与经济、人口密度和地理位置，和origin软件绘制散点图，SAS9.4软件对时间趋势进行描述性分析。使用ArcMap10.8软件分析分布(空间自相关分析，热点识别,浓度,和分散趋势分析)。采用SAS软件构建自回归综合移动平均模型(ARIMA),预测2023年和2024年的月度病例数。
■2013年至2022年，海南省四所医院共收治散发性戊型肝炎患者1,922例。50-59岁的患者比例最高（n=555，28.88%）。戊型肝炎的年发病率从2013年到2019年有所上升，2020年和2021年略有下降，2022年有所上升。报告病例最多的是海口,其次是东方和Dan州。我们发现经济之间存在相关性，人口密度，纬度,以及案件的数量，相关系数|r|值在0.403和0.421之间波动，表示线性相关。同时,散点图显示了2013年至2022年人口密度与发病率之间的相关性,r2值在0.5405~0.7116之间波动,表明呈线性关系.全球Moran\'sI,通过空间自相关分析计算，结果表明，从2013年到2022年，每年的Moran\sI值都>0，表明正的空间自相关（p<0.01）。当地Moran\I分析显示,2013年至2022年,当地热点地区主要集中在海南省北部,与海口,文昌,丁安，澄迈是热点地区，而保亭,琼中,乐东是多发冷区。浓度和分散分析表明，平均密度分布有明显的方向模式，从东北向西南移动。时间序列预测模型显示，2023年和2024年每月新报告病例数的预测相对稳定，在17至19之间波动。
■海南省戊型肝炎的总体发病率保持相对稳定。2013年至2019年海南省戊型肝炎发病率呈上升趋势，东北地区病例聚集性较高，随着时间的推移逐渐向西南方向扩散。ARIMA模型预测2023年和2024年每个月的新病例数量相对稳定。
■我们收集了2013年1月至2022年12月海口市四大三级医院收治的海南居民戊型肝炎确诊病例数据。采用SPSS软件对发病率与经济、人口密度和地理位置，和origin软件绘制散点图，SAS9.4软件对时间趋势进行描述性分析。使用ArcMap10.8软件分析分布(空间自相关分析，热点识别,浓度,和分散趋势分析)。采用SAS软件构建自回归综合移动平均模型(ARIMA),预测2023年和2024年的月度病例数。
■2013年至2022年，海南省四所医院共收治散发性戊型肝炎患者1,922例。50-59岁的患者比例最高（n=555，28.88%）。戊型肝炎的年发病率从2013年到2019年有所上升，2020年和2021年略有下降，2022年有所上升。报告病例最多的是海口,其次是东方和Dan州。我们发现经济之间存在相关性，人口密度，纬度,以及案件的数量，相关系数|r|值在0.403和0.421之间波动，表示线性相关。同时,散点图显示了2013年至2022年人口密度与发病率之间的相关性,r2值在0.5405~0.7116之间波动,表明呈线性关系.全球Moran\'sI,通过空间自相关分析计算，结果表明，从2013年到2022年，每年的Moran\sI值都>0，表明正的空间自相关（p<0.01）。当地Moran\I分析显示,2013年至2022年,当地热点地区主要集中在海南省北部,与海口,文昌,丁安，澄迈是热点地区，而保亭,琼中,乐东是多发冷区。浓度和分散分析表明，平均密度分布有明显的方向模式，从东北向西南移动。时间序列预测模型显示，2023年和2024年每月新报告病例数的预测相对稳定，在17至19之间波动。
■海南省戊型肝炎的总体发病率保持相对稳定。2013年至2019年海南省戊型肝炎发病率呈上升趋势，东北地区病例聚集性较高，随着时间的推移逐渐向西南方向扩散。ARIMA模型预测2023年和2024年每个月的新病例数量相对稳定。
