Huang Shumei, Yan Meiying, Kan Biao
School of Public Health, Shandong University, Jinan City, Shandong Province, China.
National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
China CDC Wkly. 2024 May 24;6(21):493-498. doi: 10.46234/ccdcw2024.095.
Over the last 12 years, there has been a consistent decline in the cases of typhoid/paratyphoid fever in China. Studying the epidemiological patterns of these diseases in various provincial-level administrative divisions (PLADs) and examining potential influencing factors can provide crucial information for implementing successful control strategies.
In this study, we analyzed the cases and incidence rates of typhoid/paratyphoid fever reported in various PLADs of China from 2011 to 2022, along with exploring potential influencing factors. We initially studied spatial shifts in the incidence rates through centroid shift analysis. Seasonal variations in typhoid/paratyphoid fever onset were examined using heatmaps. Spatial autocorrelation analysis was utilized to understand the spatial correlations among different PLADs. To assess potential factors, we utilized a generalized estimating equations model that integrated spatial lag effects and sequence comparison analysis.
The study identified significant geographical clustering of typhoid/paratyphoid fever cases in southwestern China. A decrease in incidence rates in the west resulted in a movement of the disease center towards the east. Higher incidence occurred during warmer seasons, highlighting the seasonal pattern of the diseases. Factors such as meteorological conditions and socioeconomic status were probable influencers of typhoid/paratyphoid fever.
The geographical and temporal spread of typhoid/paratyphoid fever can be impacted by meteorological and socioeconomic factors. Enhancing economic conditions, particularly in regions with high disease prevalence, could aid in the prevention and management of these fevers.
在过去12年中,中国伤寒/副伤寒热病例持续下降。研究这些疾病在各省级行政区的流行病学模式并考察潜在影响因素,可为实施成功的防控策略提供关键信息。
在本研究中,我们分析了2011年至2022年中国各省级行政区报告的伤寒/副伤寒热病例及发病率,并探索潜在影响因素。我们首先通过质心偏移分析研究发病率的空间变化。使用热图检查伤寒/副伤寒热发病的季节性变化。利用空间自相关分析了解不同省级行政区之间的空间相关性。为评估潜在因素,我们使用了一个整合空间滞后效应和序列比较分析的广义估计方程模型。
该研究确定中国西南部伤寒/副伤寒热病例存在显著的地理聚集性。西部地区发病率下降导致疾病中心向东移动。发病率在较温暖季节较高,突出了这些疾病的季节性模式。气象条件和社会经济状况等因素可能是伤寒/副伤寒热的影响因素。
伤寒/副伤寒热的地理和时间传播可能受到气象和社会经济因素的影响。改善经济状况,特别是在疾病高发地区,有助于预防和管理这些发热疾病。