Department of Big Data in Health Science, Center for Clinical Big Data and Statistics, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Institute for Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
BMC Public Health. 2024 Nov 4;24(1):3041. doi: 10.1186/s12889-024-20411-1.
Intestinal infectious diseases (IIDs) can impact the growth and development of children and weaken adults. This study aimed to establish a spatial panel model to analyze the relationship between factors such as population, economy and health resources, and the incidence of common IIDs. The objective was to provide a scientific basis for the formulation diseases prevention measures.
Data on monthly reported cases of IIDs in each district and county of Zhejiang Province were collected from 2011 to 2021. The spatial distribution trend was plotted, and nine factors related to population, economy and health resources were selected for analysis. A spatial panel model was developed to identify statistically significant spatial patterns of influencing factors (P < 0.05).
The results revealed that each type of IIDs exhibited a certain level of clustering. Each IIDs had a significant radiation effect, HEV (b = 0.28, P < 0.05), bacillary dysentery (b = 0.38, P < 0.05), typhoid (b = 0.36, P < 0.05), other infectious diarrheas (OIDs) (b = 0.28, P < 0.05) and hand, foot and mouth disease (HFMD) (b = 0.39, P < 0.05), indicating that regions with high morbidity rates spread to neighboring areas. Among the population characteristics, density of population acted as a protective factor for bacillary dysentery (b=-1.81, P < 0.05), sex ratio acted as a protective factor for HFMD (b=-0.07, P < 0.05), and aging rate increased the risk of OIDs (b = 2.39, P < 0.05). Urbanization ratio posed a hazard factor for bacillary dysentery (b = 5.17, P < 0.05) and OIDs (b = 0.64, P < 0.05) while serving as a protective factor for typhoid (b=-1.61, P < 0.05) and HFMD (b=-0.39, P < 0.05). Per capita GDP was a risk factor for typhoid (b = 0.54, P < 0.05), but acted as a protective factor for OIDs (b=-0.45, P < 0.05) and HFMD (b=-0.27, P < 0.05). Additionally, the subsistence allowances ratio was a risk factor for HEV (b = 0.24, P < 0.05).
The incidence of IIDs in Zhejiang Province exhibited a certain degree of clustering, with major hotspots identified in Hangzhou, Shaoxing, and Jinhua. It would be essential to consider the spillover effects from neighboring regions and implement targeted measures to enhance disease prevention based on regional development.
肠道传染病（IIDs）会影响儿童的生长发育和成年人的健康。本研究旨在建立一个空间面板模型，以分析人口、经济和卫生资源等因素与常见 IIDs 发病率之间的关系。目的是为制定疾病预防措施提供科学依据。
收集了 2011 年至 2021 年浙江省各区县肠道传染病的月报告病例数据。绘制了空间分布趋势图，并选择了九个与人口、经济和卫生资源相关的因素进行分析。建立了一个空间面板模型，以确定影响因素的统计显著空间模式（P < 0.05）。
结果表明，每种 IIDs 都表现出一定程度的聚集性。每种 IIDs 都具有显著的辐射效应，HEV（b = 0.28，P < 0.05）、细菌性痢疾（b = 0.38，P < 0.05）、伤寒（b = 0.36，P < 0.05）、其他感染性腹泻（OIDs）（b = 0.28，P < 0.05）和手足口病（HFMD）（b = 0.39，P < 0.05），表明高发病率地区向周边地区扩散。在人口特征中，人口密度对细菌性痢疾具有保护作用（b =-1.81，P < 0.05），性别比例对 HFMD 具有保护作用（b =-0.07，P < 0.05），老龄化率增加了 OIDs 的风险（b = 2.39，P < 0.05）。城市化率对细菌性痢疾（b = 5.17，P < 0.05）和 OIDs（b = 0.64，P < 0.05）构成危害因素，对伤寒（b =-1.61，P < 0.05）和 HFMD（b =-0.39，P < 0.05）具有保护作用。人均国内生产总值（GDP）是伤寒（b = 0.54，P < 0.05）的危险因素，但对 OIDs（b =-0.45，P < 0.05）和 HFMD（b =-0.27，P < 0.05）具有保护作用。此外，最低生活保障金比例是 HEV 的危险因素（b = 0.24，P < 0.05）。
浙江省肠道传染病发病率存在一定程度的聚集性，杭州、绍兴和金华等地为主要热点地区。考虑到邻近地区的溢出效应，并根据区域发展情况实施有针对性的疾病预防措施至关重要。
