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Background: In 2007, a novel bunyavirus was found in Henan Province, China and named fever, thrombocytopenia and leukocytopenia syndrome virus (FTLSV); since then, FTLSV has been found in ticks and animals in many Chinese provinces. Human-to-human transmission has been documented, indicating that FTLSV should be considered a potential public health threat. Determining the historical spread of FTLSV could help curtail its spread and prevent future movement of this virus., Method/principal Findings: To examine the pattern of FTLSV evolution and the origin of outbreak strains, as well to examine the rate of evolution, the genome of 12 FTLSV strains were sequenced and a phylogenetic and Bayesian phylogeographic analysis of all available FTLSV sequences in China were performed. Analysis based on the FTLSV L segment suggests that the virus likely originated somewhere in Huaiyangshan circa 1790 (95% highest probability density interval: 1756-1817) and began spreading around 1806 (95% highest probability density interval: 1773-1834). Analysis also indicates that when FTLSV arrived in Jiangsu province from Huaiyangshan, Jiangsu Province became another source for the spread of the disease. Bayesian factor test analysis identified three major transmission routes: Huaiyangshan to Jiangsu, Jiangsu to Liaoning, and Jiangsu to Shandong. The speed of FTLSV movement has increased in recent decades, likely facilitated by modern human activity and ecosystem changes. In addition, evidence of RNA segment reassortment was found in FTLSV; purifying selection appears to have been the dominant force in the evolution of this virus., Conclusion: Results presented in the manuscript suggest that the Huaiyangshan area is likely be the origin of FTLSV in China and identified probable viral migration routes. These results provide new insights into the origin and spread of FTLSV in China, and provide a foundation for future virological surveillance and control.

The Fever, Thrombocytopenia and Leukopenia Syndrome (FTLS) is caused by a bunyavirus known as the FTLS virus (FTLSV), which was recently discovered in China. We examined the epidemiological and etiological features of 637 laboratory-confirmed cases of FTLS with onset from January 2011 to December 2012 in Henan Province, China. The highest incidence of FTLS occurred between May and August: 76.5% of all laboratory-confirmed cases occurred during those four months. Of the laboratory-confirmed cases, 60.9% were in the 46-69 years old age groups; 96.1% (612/637) occurred in farmers; 98.1% (625/637) were reported from Xinyang Prefecture. During the same time period, 2047 cases were reported in China. The nucleotide and amino acid sequences of FTLSV strains identified during 2011-2012 in Henan Province were ≥ 96% identical. This findings provides insight for developing public-health interventions for the control and prevention of FTLS in epidemic area.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is a serious infectious disease with a fatality of up to 30%. To identify the severity of SFTS precisely and quickly is important in clinical practice. Methods: From June to July 2020, 71 patients admitted to the Infectious Department of Joint Logistics Support Force No. 990 Hospital were enrolled in this study. The most frequently observed symptoms and laboratory parameters on admission were collected by investigating patients' electronic records. Decision trees were built to identify the severity of SFTS. Accuracy and Youden's index were calculated to evaluate the identification capacity of the models. Results: Clinical characteristics, including body temperature (p = 0.011), the size of the lymphadenectasis (p = 0.021), and cough (p = 0.017), and neurologic symptoms, including lassitude (p<0.001), limb tremor (p<0.001), hypersomnia (p = 0.009), coma (p = 0.018) and dysphoria (p = 0.008), were significantly different between the mild and severe groups. As for laboratory parameters, PLT (p = 0.006), AST (p<0.001), LDH (p<0.001), and CK (p = 0.003) were significantly different between the mild and severe groups of SFTS patients. A decision tree based on laboratory parameters and one based on demographic and clinical characteristics were built. Comparing with the decision tree based on demographic and clinical characteristics, the decision tree based on laboratory parameters had a stronger prediction capacity because of its higher accuracy and Youden's index. Conclusion: Decision trees can be applied to predict the severity of SFTS. [ABSTRACT FROM AUTHOR]