Cryptosporidiosis threat under climate change in China:prediction and validation of habitat suitability and outbreak risk for human-derived Cryptosporidium based on ecological niche models  

作　　者：Xu Wang Yanyan Jiang Weiping Wu Xiaozhou He Zhenghuan Wang Yayi Guan Ning Xu Qilu Chen Yujuan Shen Jianping Cao 

机构地区：[1]National Institute of Parasitic Diseases,Chinese Center for Disease Control and Prevention(Chinese Center for Tropical Diseases Research)、Key Laboratory of Parasite and Vector Biology,National Health Commission of the People’s Republic of China、World Health Organization Collaborating Center for Tropical Diseases,Shanghai,200025,China [2]National Institute for Viral Disease Control and Prevention,Chinese Center for Disease Control and Prevention,Beijing,102206,China [3]School of Life Sciences,East China Normal University,Shanghai,200241,China [4]Key Laboratory of Public Health Safety,Fudan University,Ministry of Education,Fudan University Center for Tropical Disease Research,Fudan University School of Public Health,Shanghai,200031,China [5]The School of Global Health,Chinese Center for Tropical Diseases Research,Shanghai Jiao Tong University School of Medicine,Shanghai,200025,China

出　　处：《Infectious Diseases of Poverty》2023年第2期72-86,共15页贫困所致传染病（英文）

基　　金：supported by the National Natural Science Foundation of China(Nos.81971969,82272369 to JC);the Three-Year Public Health Action Plan(2020–2022)of Shanghai(No.GWV-10.1-XK13 to JC);the Research Projects of Shanghai Municipal Health Commission(No.2021Y0213 to XW).

摘　　要：Background Cryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp.,and its transmission is highly influenced by climate factors.In the present study,the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control.Methods The applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011–2019.Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs,namely Maxent,Bioclim,Domain,and Garp.Models were evaluated based on Receiver Operating Characteristic curve,Kappa,and True Skill Statistic coefficients.The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010,and used to analyze the effects of climate factors on Cryptosporidium distribution.The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China.Results The Maxent model(AUC=0.95,maximum Kappa=0.91,maximum TSS=1.00)fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability.The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas,especially in the middle and lower reaches of the Yangtze River,the lower reaches of the Yellow River,and the Huai and the Pearl River Basins(cloglog value of habitat suitability>0.9).Under future climate change,non-suitable habitats for Cryptosporidium will shrink,while highly suitable habitats will expand significantly(χ^(2)=76.641,P<0.01;χ^(2)=86.836,P<0.01),and the main changes will likely be concentrated in the northeastern,southwestern,and northwestern regions.Conclusions The Maxent model is applicable in prediction of Cryptosporidium habitat suitabil

关 键 词：CRYPTOSPORIDIUM CRYPTOSPORIDIOSIS Ecological niche models Climate change One Health MAXENT 

分 类 号：R531[医药卫生—内科学] R181.3[医药卫生—临床医学]