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Articles
Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods
Dong Miaoa State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaView further author information
, Ke Daia State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaView further author information
, Guo-Ping Zhaoa State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaView further author information
, Xin-Lou Lia State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaView further author information
, Wen-Qiang Shia State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaView further author information
, Jiu Song Zhanga State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaView further author information
, Yang Yangb Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USAView further author information
, Wei Liua State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaCorrespondence[email protected]
https://orcid.org/0000-0002-9302-8170View further author information
Li-Qun Fanga State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of ChinaCorrespondence[email protected]
View further author information
show allView further author information
Pages 817-826
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Received 10 Feb 2020, Accepted 23 Mar 2020, Published online: 29 Apr 2020
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