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Spatial and temporal analysis of severe fever with thrombocytopenia syndrome in Zhejiang Province, China, 2011 - 2015

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease first discovered in northeast and central China in 2009, and SFTS cases increased year by year in China. This study aimed to identify the spatial and temporal clusters of SFTS in Zhejiang Province, China. We analyze...

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Bibliographic Details
Published in:Journal of infection in developing countries 2019-01, Vol.13 (1), p.35-43
Main Authors: Li, Fudong, He, Fan, Sun, Jimin, Zhai, Yujia, Jiang, Jianmin, Lin, Junfen
Format: Article
Language:English
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Summary:Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease first discovered in northeast and central China in 2009, and SFTS cases increased year by year in China. This study aimed to identify the spatial and temporal clusters of SFTS in Zhejiang Province, China. We analyzed the surveillance data of SFTS in Zhejiang Province during 2011 - 2015. Descriptive statistics were used to analyze the general characteristics and overall trend of SFTS. Circular statistic method was utilized to identify the seasonality. Space-time scan analysis was performed to explore the high risk spatio-temporal clusters of SFTS cases at county level. A total of 194 confirmed SFTS cases were reported in Zhejiang Province during 2011 - 2015. We found a significant increase in overall time trend since 2011. The seasonality was statistically significant (P < 0.001), with a mean date (95% CI) of 21st June (12th ~ 30th in June). Totally 21 (23%) counties reported the occurrence of SFTS, which gradually spread throughout Zhejiang. Three spatio-temporal clusters were detected, with one principle cluster (Daishan County, RR 234.48, June 2013 - November 2015) and two secondary clusters (6 counties, RR 30.73, April - October in 2015; Anji County, RR 373.26, May 2014). Our results suggested that SFTS has increased and spatially expanded over the past years, with a remarkable seasonality. Three spatio-temporal clusters were identified. These findings are important for the improvement of SFTS surveillance and control strategies.
ISSN:1972-2680
2036-6590
1972-2680
DOI:10.3855/jidc.10373