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Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods.

ABSTRACT: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing spread. Currently SFTS transmission has expanded beyond Asian countries, however, with definitive global extents and risk patterns remained obscure. Here we established an exhaustive database that included globally reported locations of human SFTS cases and the competent vector, Haemaphysalis longicornis (H. longicornis), as well as the explanatory environmental variables, based on which, the potential geographic range of H. longicornis and risk areas for SFTS were mapped by applying two machine learning methods. Ten predictors were identified contributing to global distribution for H. longicornis with relative contribution ≥1%. Outside contemporary known distribution, we predict high receptivity to H. longicornis across two continents, including northeastern USA, New Zealand, parts of Australia, and several Pacific islands. Eight key drivers of SFTS cases occurrence were identified, including elevation, predicted probability of H. longicornis presence, two temperature-related factors, two precipitation-related factors, the richness of mammals and percentage coverage of water bodies. The globally model-predicted risk map of human SFTS occurrence was created and validated effective for discriminating the actual affected and unaffected areas (median predictive probability 0.74 vs. 0.04, P < 0.001) in three countries with reported cases outside China. The high-risk areas (probability ≥50%) were predicted mainly in east-central China, most parts of the Korean peninsula and southern Japan, and northern New Zealand. Our findings highlight areas where an intensive vigilance for potential SFTS spread or invasion events should be advocated, owing to their high receptibility to H. longicornis distribution.

SUBMITTER: Miao D

PROVIDER: S-EPMC7241453 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSevere fever with thrombocytopenia syndrome (SFTS), caused by the Dabie bandavirus (DBV), formerly known as the SFTS virus (SFTSV), is characterized by rapid progression, high morbidity, and mortality. This study aims to analyze the current research status, hotspots, and trends of SFTS since 2009 through bibliometrics, focusing on original research and providing valuable references and inspirations for future basic research, prevention and control of SFTS.MethodsThe Web of Science Core Collection (WOSCC) was used to extract global papers on SFTS from 2009 to 2024. VOSviewer and CiteSpace software were also used to process and visualize results.ResultsA total of 760 publications relevant to SFTS were reviewed. Among these publications, the most active country, author, and publication type included China, Liu Wei, and original articles, respectively. Among the institutions, the National Institute of Infectious Diseases emerged as the top publisher. The most frequently used keywords were "China," "Bunyavirus," and "person-to-person transmission." The bibliometric analysis reviewed and summarized the research results in the field of SFTS and demonstrated the research trends in the field. In addition, the study revealed the current research hotspots and predicted the future research frontiers and potential challenges in the field of SFTS, which will provide references for further exploring and investigating the SFTS-related mechanisms and inspire new therapeutic strategies.ConclusionBibliometric visualization provides an overview of research advances, hotspots, and trends regarding SFTS and consolidates existing knowledge. SFTS research is in a phase of rapid development, and the number of annual publications in the field is growing steadily and rapidly. This is laying the groundwork for further research and providing new ideas for clinicians engaged in SFTS-related therapies and researchers working to improve public health. Currently, researchers are focused on elucidating the biology of SFTS, exploring antibodies, delving into pathogenesis, and investigating specific therapies.

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Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods.

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