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Ecology of Middle East respiratory syndrome coronavirus, 2012-2020: A machine learning modelling analysis.
Zhang, An-Ran; Li, Xin-Lou; Wang, Tao; Liu, Kun; Liu, Ming-Jin; Zhang, Wen-Hui; Zhao, Guo-Ping; Chen, Jin-Jin; Zhang, Xiao-Ai; Miao, Dong; Ma, Wei; Fang, Li-Qun; Yang, Yang; Liu, Wei.
  • Zhang AR; Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Li XL; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
  • Wang T; Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA.
  • Liu K; Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA.
  • Liu MJ; Department of Medical Research, Key Laboratory of Environmental Sense Organ Stress and Health of the Ministry of Environmental Protection, PLA Strategic Support Force Medical Center, Beijing, China.
  • Zhang WH; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
  • Zhao GP; Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, China.
  • Chen JJ; Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA.
  • Zhang XA; Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA.
  • Miao D; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
  • Ma W; Department of Epidemiology, Logistics College of Chinese People's Armed Police Forces, Tianjin, China.
  • Fang LQ; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
  • Yang Y; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
  • Liu W; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Transbound Emerg Dis ; 2022 Apr 02.
Article in English | MEDLINE | ID: covidwho-1774901
ABSTRACT
The ongoing enzootic circulation of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and North Africa is increasingly raising the concern about the possibility of its recombination with other human-adapted coronaviruses, particularly the pandemic SARS-CoV-2. We aim to provide an updated picture about ecological niches of MERS-CoV and associated socio-environmental drivers. Based on 356 confirmed MERS cases with animal contact reported to the WHO and 63 records of animal infections collected from the literature as of 30 May 2020, we assessed ecological niches of MERS-CoV using an ensemble model integrating three machine learning algorithms. With a high predictive accuracy (area under receiver operating characteristic curve = 91.66% in test data), the ensemble model estimated that ecologically suitable areas span over the Middle East, South Asia and the whole North Africa, much wider than the range of reported locally infected MERS cases and test-positive animal samples. Ecological suitability for MERS-CoV was significantly associated with high levels of bareland coverage (relative contribution = 30.06%), population density (7.28%), average temperature (6.48%) and camel density (6.20%). Future surveillance and intervention programs should target the high-risk populations and regions informed by updated quantitative analyses.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal subject: Veterinary Medicine Year: 2022 Document Type: Article Affiliation country: Tbed.14548

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal subject: Veterinary Medicine Year: 2022 Document Type: Article Affiliation country: Tbed.14548