西伯利亚西部和俄罗斯联邦乌拉尔地区猫毛绦虫感染的时空风险:基于调查和监测数据的联合贝叶斯模型研究

IF 5.5 1区 医学
Wen-Long Zhang, Yuan-Hong Zeng, Ying-Si Lai
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引用次数: 0

摘要

背景:对于居住在西伯利亚西部和俄罗斯联邦乌拉尔地区的人口来说,由猫角绦虫感染的蛇绦虫病是一个重要但尚未得到充分研究的公共卫生问题。本研究旨在生成高分辨率的时空疾病风险图,以指导上述地区的预防策略。方法:通过系统评价和俄罗斯联邦卫生部的年度报告,收集研究区域的流行病学数据和反映年发病率的监测数据。从不同的开放获取数据源下载了环境、社会经济和人口数据。通过对调查和监测数据的联合分析,结合潜在影响因素和时空随机效应,建立了一种先进的多变量贝叶斯地统计建模方法,在高分辨率时空上对狐伊蚊感染风险进行估计。绘制了5 × 5 km2分辨率的年时空感染风险图。结果:最终数据集包括76个调查数据点和303个监测数据点。结论:俄罗斯联邦西西伯利亚和乌拉尔地区高分辨率狐伊蚊感染风险图有效地反映了该地区狐伊蚊的感染风险特征,提示近年来该地区狐伊蚊感染风险仍然较高,为制定空间目标控制和预防策略提供了重要依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial-temporal risk of Opisthorchis felineus infection in Western Siberia and the Ural Region of Russian Federation: a joint Bayesian modelling study based on survey and surveillance data.

Background: Opisthorchiasis infected by Opisthorchis felineus has represented a significant but understudied public health issue for the population residing in Western Siberia and the Ural Region of the Russian Federation. This study aimed to produce high-resolution spatial-temporal disease risk maps for guiding prevention strategy in the above region.

Methods: Data on prevalence and surveillance data reflecting reported annual incidence rate of O. felineus infection in the study region were collected through systematic review and the annual reports of the Ministry of Health of the Russian Federation. Environmental, socioeconomic and demographic data were downloaded from different open-access data sources. An advanced multivariate Bayesian geostatistical modeling approach was developed to estimate the O. felineus infection risk at high-resolution spatial-temporal by joint analysis of survey and surveillance data, incorporating potential influencing factors and spatial-temporal random effects. The annual spatial-temporal risk maps of O. felineus infection at a resolution of 5 × 5 km2 were produced.

Results: The final dataset included 76 locations of survey data and 303 locations of surveillance data on O. felineus infection. The infection risk was high (> 25%) in most part of central and eastern regions, and relatively low (< 25%) in most part of western region, while temporal variations were observed across the sub-regions in recent decades. Particularly, in the densely populated eastern region, there was an increased trend of infection risk from 30.46% (95% Bayesian credible intervals, BCI 10.78-53.45%) in 1980 to 53.39% (95% BCI 13.77-91.93%) in 2019 and gradually transformed into high-risk. In the study region (excluding the western region due to data sparsity), the population-adjusted estimated prevalence was 46.61% (95% BCI 15.09-76.50%) in 2019, corresponding to approximately 7.91 million (95% BCI 2.56-12.98 million) people infected.

Conclusions: The high-resolution risk maps of O. felineus in Western Siberia and the Ural Region of the Russian Federation have effectively captured the risk profiles, suggesting the infection risk remains high in recent years and providing substantial evidence for spatial-target control and preventive strategies.

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来源期刊
Infectious Diseases of Poverty
Infectious Diseases of Poverty INFECTIOUS DISEASES-
自引率
1.20%
发文量
368
期刊介绍: Infectious Diseases of Poverty is an open access, peer-reviewed journal that focuses on addressing essential public health questions related to infectious diseases of poverty. The journal covers a wide range of topics including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies and application. It also considers the transdisciplinary or multisectoral effects on health systems, ecohealth, environmental management, and innovative technology. The journal aims to identify and assess research and information gaps that hinder progress towards new interventions for public health problems in the developing world. Additionally, it provides a platform for discussing these issues to advance research and evidence building for improved public health interventions in poor settings.
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