Risk mapping of clonorchiasis in the People's Republic of China: A systematic review and Bayesian geostatistical analysis.
Risk mapping of clonorchiasis in the People's Republic of China: A systematic review and Bayesian geostatistical analysis.
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DOI：
10.1371/journal.pntd.0005239
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发表时间：
2017-03
影响因子：
3.8
通讯作者：
Vounatsou P
中科院分区：
文献类型：
--
作者：
Lai YS;Zhou XN;Pan ZH;Utzinger J;Vounatsou P
华支睾吸虫病是最重要的食源性吸虫病之一，在中华人民共和国有1200多万人患病。中国）。需要对华支睾吸虫感染进行明确的空间风险评估，以便有针对性地采取控制干预措施。地理参考调查数据有关的感染流行的C。中华民国从2000年起，中国通过PubMed、ISI Web of Science、中国国家知识网和万方数据的系统综述获得，时间为2000年1月1日至2016年1月10日，不受语言或研究设计的限制。其他疾病数据由上海中国疾病预防控制中心寄生虫病研究所提供。从遥感和其他数据来源提取了环境和社会经济代用指标。进行贝叶斯变量选择，以确定最重要的C。中国风险应用地统计学模型来量化感染风险与疾病预测因子之间的关联，并预测整个P.R.的感染风险。高空间分辨率下的中国（在网格单元大小为5×5 km的网格上）。我们获得了中国633个独特地点的华支睾吸虫病调查数据。中国我们观察到C.随着时间的推移，中华感染有所增加，特别是从2005年开始。我们估计，大约有1480万（95%贝叶斯可信区间1380 - 1580万）人在公共关系中。中国也有C. sinensis 2010.高度流行区（≥ 20%）集中在该国南部和东北部。感染风险最高和感染人数最多的省份是广东、广西和黑龙江。我们的研究结果为指导华支睾吸虫病的防治提供了空间相关信息。中国C.近年来中国华支睾吸虫病感染的发生促使中国政府更加重视华支睾吸虫病的公共卫生重要性，并将干预措施针对高危地区。华支睾吸虫病是一种重要的食源性吸虫病，据估计，在中国有超过1200万人受到影响。关于疾病发生地点的准确信息有助于确定应实施控制干预措施的优先领域。我们从最近的华支睾吸虫病调查中收集数据，并应用贝叶斯地统计模型来制作基于模型的中国华支睾吸虫病高分辨率风险地图。我们发现，从2005年起，感染风险呈上升趋势。我们估计，2010年中国约有1480万人感染了华支睾吸虫。C.预测中华绒螯蟹主要集中在广东、广西和黑龙江省。我们的研究结果表明，中国政府应更加重视华支睾吸虫病的公共卫生重要性，并应在高风险地区实施具体的控制措施。
Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People’s Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions. Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km). We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8–15.8 million) people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20%) were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang. Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to pay more attention to the public health importance of clonorchiasis and to target interventions to high-risk areas. Clonorchiasis is an important food-borne trematodiases and it has been estimated that more than 12 million people in China are affected. Precise information on where the disease occurs can help to identify priority areas for where control interventions should be implemented. We collected data from recent surveys on clonorchiasis and applied Bayesian geostatistical models to produce model-based, high-resolution risk maps for clonorchiasis in China. We found an increasing trend of infection risk from 2005 onwards. We estimated that approximately 14.8 million people in China were infected with Clonorchis sinensis in 2010. Areas where the high prevalence of C. sinensis was predicted were concentrated in the provinces of Guangdong, Guangxi, and Heilongjiang. Our results suggest that the Chinese government should pay more attention on the public health importance of clonorchiasis and that specific control efforts should be implemented in high-risk areas.