Model-based spatial-temporal mapping of opisthorchiasis in endemic countries of Southeast Asia.
Model-based spatial-temporal mapping of opisthorchiasis in endemic countries of Southeast Asia.
复制标题
基于模型的东南亚流行国家阿片吸虫病时空测绘
作者：
Zhao TT;Feng YJ;Doanh PN;Sayasone S;Khieu V;Nithikathkul C;Qian MB;Hao YT;Lai YS
后睾吸虫病是东南亚一个被忽视的危险。高分辨率的疾病风险地图至关重要，但尚未在东南亚提供。分别通过系统回顾文献和开放获取数据库收集地理参考疾病数据和潜在影响因素数据。贝叶斯时空联合模型被开发用于分析点和区域一级的疾病数据，在结合潜在影响因素和时空随机效应的logit回归中。基于模型的风险映射确定了整个研究地区的低，中，高流行率的地区。尽管总体人群调整后的估计患病率呈下降趋势，但估计共有1239万人（95%贝叶斯可信区间[BCI]：10.10-15.06）感染O. 2018年，在四个主要流行国家（即，泰国、老挝、柬埔寨和越南），强调了该疾病在研究地区的公共卫生重要性。高分辨率风险图为后睾吸虫病控制干预措施的空间定位提供了宝贵的信息。
Opisthorchiasis is an overlooked danger to Southeast Asia. High-resolution disease risk maps are critical but have not been available for Southeast Asia. Georeferenced disease data and potential influencing factor data were collected through a systematic review of literatures and open-access databases, respectively. Bayesian spatial-temporal joint models were developed to analyze both point- and area-level disease data, within a logit regression in combination of potential influencing factors and spatial-temporal random effects. The model-based risk mapping identified areas of low, moderate, and high prevalence across the study region. Even though the overall population-adjusted estimated prevalence presented a trend down, a total of 12.39 million (95% Bayesian credible intervals [BCI]: 10.10–15.06) people were estimated to be infected with O. viverrini in 2018 in four major endemic countries (i.e., Thailand, Laos, Cambodia, and Vietnam), highlighting the public health importance of the disease in the study region. The high-resolution risk maps provide valuable information for spatial targeting of opisthorchiasis control interventions.