UNASSIGNED: We performed an observational epidemiological study using HB data obtained from the National Notifiable Disease Reporting System (NNDRS). Joinpoint regression analysis was employed to determine the changing trends in the annual incidence. A vector boundary map of Shenyang was used to visualise spatial distribution. Spatial autocorrelation was identified using both global and local Moran\'s autocorrelation coefficients, while hotspot areas were determined using the Getis-Ord statistic.
UNASSIGNED: A combined sum of 4103 HB cases were analysed, and the average level of annual incidence of HB was 5.52 per 100,000. The incidence of HB showed obvious seasonality, with a notable peak observed from April to July (summer peak). The annual incidence in Shenyang has been on the rise since 2013, with an annual percentage change (APC) of 6.39% (95%CI 1.29%, 12.39%). Xinmin County exhibited the most elevated average annual incidence rate, with Faku County ranking second. The average annual incidence in rural areas exhibited a significantly greater disparity compared to suburban areas (P < 0.001), whereas the incidence rate in suburban areas demonstrated a significantly higher contrast when compared to urban areas (P < 0.001). A clustered distribution of the annual incidence of HB was observed for all years from 2013 to 2022. Abnormally high values were found in suburban areas, and no abnormally high values were found after 2017. The low-low clustering areas were found in urban as well as suburban areas from 2013 to 2022. Hotspots (P < 0.05) were located in rural areas, while cold spots (P < 0.05) were found in both urban and suburban areas. Since 2020, there have been no hotspots in Shenyang.
UNASSIGNED: Rural areas are high-risk areas for HB and may be key to controlling HB epidemics. Although the annual incidence of HB in rural areas has increased, owing to the stability of spatial relationships and the disappearance of hotspots, there is little possibility of outbreaks; however, stricter monitoring should be applied in rural areas to prevent the emergence of new transmission routes.
■我们使用从国家法定疾病报告系统(NDRS)获得的HB数据进行了观察性流行病学研究。采用Joinpoint回归分析确定年发病率的变化趋势。沈阳矢量边界图用于可视化空间分布。使用全局和局部Moran的自相关系数识别空间自相关,而热点区域是使用Getis-Ord统计量确定的。
■分析了4103例合并的HB病例,乙型肝炎的年平均发病率为5.52/10万。乙型肝炎的发病率表现出明显的季节性,在4月至7月(夏季高峰)观察到明显的高峰。沈阳市的年发病率自2013年以来呈上升趋势,年百分比变化(APC)为6.39%(95CI1.29%,12.39%)。新民县年平均发病率最高,法库县排名第二。与郊区相比,农村地区的年平均发病率差异显著(P<0.001)。而与城市地区相比,郊区地区的发病率显示出明显更高的对比度(P<0.001)。从2013年到2022年的所有年份都观察到了HB年发病率的聚集分布。在郊区发现异常高的值,并且在2017年之后没有发现异常高的值。从2013年到2022年,在城市和郊区发现了低-低聚集区域。热点(P<0.05)位于农村,城市和郊区均有寒点(P<0.05)。2020年以来,沈阳没有热点。
■农村地区是乙型肝炎的高风险地区,可能是控制乙型肝炎流行的关键。尽管农村地区每年的HB发病率有所上升,由于空间关系的稳定性和热点的消失,爆发的可能性很小;然而,应在农村地区实施更严格的监测,以防止新的传播途径的出现。