The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context
Summary: Background: The family Anaplasmataceae, reclassified under the order Rickettsiales, represents a highly complex group that poses an increasing global threat. However, their infection risk remains poorly understood. We aimed to map the diversity, distribution, and potential infection risk o...
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Elsevier
2025-05-01
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| Series: | EBioMedicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352396425001665 |
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| author | Xiao-Bin Huang Tian Tang Jin-Jin Chen Yuan-Yuan Zhang Chen-Long Lv Qiang Xu Guo-Lin Wang Ying Zhu Yue-Hong Wei Simon I. Hay Li-Qun Fang Wei Liu |
| author_facet | Xiao-Bin Huang Tian Tang Jin-Jin Chen Yuan-Yuan Zhang Chen-Long Lv Qiang Xu Guo-Lin Wang Ying Zhu Yue-Hong Wei Simon I. Hay Li-Qun Fang Wei Liu |
| author_sort | Xiao-Bin Huang |
| collection | DOAJ |
| description | Summary: Background: The family Anaplasmataceae, reclassified under the order Rickettsiales, represents a highly complex group that poses an increasing global threat. However, their infection risk remains poorly understood. We aimed to map the diversity, distribution, and potential infection risk of Anaplasmataceae members. Methods: We searched PubMed, Web of Science, bioRvix, and MedRvix for published articles to extract data on the detection of Anaplasmatacea species in vectors, animals, and humans from 1910 to 2022. We mapped the richness and global distribution of identified Anaplasmatacea species. Machine learning algorithms were applied to determine the ecological and vector-related factors contributing to the occurrence of major Anaplasmatacea members and project their potential risk distributions. Findings: A total of 2605 studies meeting our inclusion criteria were used for data extraction. We identified 85 species of Anaplasmataceae family from 134 tick species, 312 wild animals, and 12 domestic animals. Anaplasma phagocytophilum had the widest range of vectors (97 species), followed by Anaplasma marginale (54 species), Anaplasma bovis (46 species), Anaplasma ovis (37 species), and Anaplasma platys (35 species). Aanaplasma phagocytophilum was also detected in the widest range of wildlife (208 species), followed by Ehrlichia chaffeensis (46 species), Candidatus Neoehrlichia mikurensis (36 species), Ehrlichia canis (35 species), and A. bovis (32 species). In total, 52,315 human cases involving 15 Anaplasmataceae species were recorded, A. phagocytophilum and E. chaffeensis accounted for majority of human infections (66·5% and 32·4%, respectively). According to our modelling analysis, the geographic distribution of six major Anaplasmatacea species is primarily influenced by the projected habitat suitability index of tick vectors and climatic conditions. Among these, A. phagocytophilum presents the highest risk, with an estimated 3·97 billion individuals and 8·95 million km2 area potentially affected. Interpretation: The widespread distribution of Anaplasmataceae species emphasizes the need to enhance identification, surveillance, and diagnosis efforts in high-risk areas, particularly within low-income regions. Funding: The National Key Research and Development Program of China (2023YFC2605603) and the Natural Science Foundation of China (82330103). |
| format | Article |
| id | doaj-art-a25dc987dd9346049cff60c66fa3e58b |
| institution | DOAJ |
| issn | 2352-3964 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EBioMedicine |
| spelling | doaj-art-a25dc987dd9346049cff60c66fa3e58b2025-08-20T03:14:13ZengElsevierEBioMedicine2352-39642025-05-0111510572210.1016/j.ebiom.2025.105722The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in contextXiao-Bin Huang0Tian Tang1Jin-Jin Chen2Yuan-Yuan Zhang3Chen-Long Lv4Qiang Xu5Guo-Lin Wang6Ying Zhu7Yue-Hong Wei8Simon I. Hay9Li-Qun Fang10Wei Liu11State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, China; School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, ChinaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, ChinaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, ChinaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, ChinaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, ChinaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, ChinaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan, ChinaDepartment of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, ChinaDepartment of Health Metrics Sciences, School of Medicine, University of Washington, USA; Institute for Health Metrics and Evaluation, University of Washington, USAState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, China; Corresponding author. State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, China.State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, China; Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, China; Corresponding author. State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, 100071, China.Summary: Background: The family Anaplasmataceae, reclassified under the order Rickettsiales, represents a highly complex group that poses an increasing global threat. However, their infection risk remains poorly understood. We aimed to map the diversity, distribution, and potential infection risk of Anaplasmataceae members. Methods: We searched PubMed, Web of Science, bioRvix, and MedRvix for published articles to extract data on the detection of Anaplasmatacea species in vectors, animals, and humans from 1910 to 2022. We mapped the richness and global distribution of identified Anaplasmatacea species. Machine learning algorithms were applied to determine the ecological and vector-related factors contributing to the occurrence of major Anaplasmatacea members and project their potential risk distributions. Findings: A total of 2605 studies meeting our inclusion criteria were used for data extraction. We identified 85 species of Anaplasmataceae family from 134 tick species, 312 wild animals, and 12 domestic animals. Anaplasma phagocytophilum had the widest range of vectors (97 species), followed by Anaplasma marginale (54 species), Anaplasma bovis (46 species), Anaplasma ovis (37 species), and Anaplasma platys (35 species). Aanaplasma phagocytophilum was also detected in the widest range of wildlife (208 species), followed by Ehrlichia chaffeensis (46 species), Candidatus Neoehrlichia mikurensis (36 species), Ehrlichia canis (35 species), and A. bovis (32 species). In total, 52,315 human cases involving 15 Anaplasmataceae species were recorded, A. phagocytophilum and E. chaffeensis accounted for majority of human infections (66·5% and 32·4%, respectively). According to our modelling analysis, the geographic distribution of six major Anaplasmatacea species is primarily influenced by the projected habitat suitability index of tick vectors and climatic conditions. Among these, A. phagocytophilum presents the highest risk, with an estimated 3·97 billion individuals and 8·95 million km2 area potentially affected. Interpretation: The widespread distribution of Anaplasmataceae species emphasizes the need to enhance identification, surveillance, and diagnosis efforts in high-risk areas, particularly within low-income regions. Funding: The National Key Research and Development Program of China (2023YFC2605603) and the Natural Science Foundation of China (82330103).http://www.sciencedirect.com/science/article/pii/S2352396425001665Anaplasmataceae speciesDistributionRisk predictionModelling analysis |
| spellingShingle | Xiao-Bin Huang Tian Tang Jin-Jin Chen Yuan-Yuan Zhang Chen-Long Lv Qiang Xu Guo-Lin Wang Ying Zhu Yue-Hong Wei Simon I. Hay Li-Qun Fang Wei Liu The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context EBioMedicine Anaplasmataceae species Distribution Risk prediction Modelling analysis |
| title | The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context |
| title_full | The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context |
| title_fullStr | The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context |
| title_full_unstemmed | The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context |
| title_short | The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysisResearch in context |
| title_sort | global distribution and risk prediction of anaplasmataceae species a systematic review and geospatial modelling analysisresearch in context |
| topic | Anaplasmataceae species Distribution Risk prediction Modelling analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2352396425001665 |
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