Clusters of spatial, temporal, and space-time distribution of hemorrhagic fever with renal syndrome in Liaoning Province, Northeastern China

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• 作者：Wei Wu (1)
  Junqiao Guo (2)
  Peng Guan (1)
  Yingwei Sun (2)
  Baosen Zhou (1)
  
• 刊名：BMC Infectious Diseases
• 出版年：2011
• 出版时间：December 2011
• 年：2011
• 卷：11
• 期：1
• 全文大小：713KB
• 参考文献：1. Schmaljohn CS, Dalrymple JM: Analysis of Hantaan virusRNA: evidence for a new genus of Bunyaviridae. / Virology 1983, 131:482鈥?91. CrossRef
  2. Liu YX, Feng D, Zhang Q, Jia N, Zhao ZT, De Vlas SJ, Li J, Zhang PH, Yang H, Min JS, Feng PT, Ma SB, Cao WC: Key differentiating features between scrub typhus and hemorrhagic fever with renal syndrome in northern China. / Am J Trop Med Hyg 2007, 76:801鈥?05.
  3. Chen HX, Qiu FX: Epidemiologic surveillance on the hemorrhagic fever with renal syndrome in China. / Chin Med J 1993, 106:857鈥?63.
  4. Chen HX, Qiu FX, Dong BJ, Ji SZ, Li YT, Wang Y, Wang HM, Zuo GF, Tao XX, Gao SY: Epidemiological studies on hemorrhagic fever with renal syndrome in China. / J Infect Dis 1986, 154:394鈥?98. CrossRef
  5. Yan L, Fang LQ, Huang HG, Zhang LQ, Feng D, Zhao WJ, Zhang WY, Li XW, Cao WC: Landscape elements and Hantaan virus-related hemorrhagic fever with renal syndrome, People's Republic of China. / Emerg Infect Dis 2007, 13:1301鈥?306.
  6. Song G: Epidemiological progresses of hemorrhagic fever with renal syndrome in China. / Chin Med J (Engl) 1999, 112:472鈥?77.
  7. Zuo SQ, Zhang PH, Jiang JF, Zhan L, Wu XM, Zhao WJ, Wang RM, Tang F, Dun Z, Cao WC: Seoul Virus in Patients and Rodents from Beijing, China. / Am J Trop Med Hyg 2008, 78:833鈥?37.
  8. Cousens S, Smith PG, Ward H, Everington D, Knight RS, Zeidler M, Stewart G, Smith-Bathgate EA, Macleod MA, Mackenzie J, Will RG: Geographical distribution of variant Creutzfeldt-Jakob disease in Great Britain, 1994鈥?000. / Lancet 2001, 357:1002鈥?007. CrossRef
  9. Chaput EK, Meek JI, Heimer R: Spatial analysis of human granulocytic ehrlichiosis near Lyme, Connecticut. / Emerg Infect Dis 2002, 8:943鈥?48.
  10. Fang L, Yan L, Liang S, de Vlas SJ, Feng D, Han X, Zhao W, Xu B, Bian L, Yang H, Gong P, Richardus JH, Cao W: Spatial analysis of hemorrhagic fever with renal syndrome in China. / BMC Infect Dis 2006, 6:77鈥?6. CrossRef
  11. Martin K, Eric JF, Barry AM, Laurence SF: Breast cancer clusters in the northeastern United States: a geographic analysis. / Am J Epidemiol 1997, 146:161鈥?70.
  12. Zhan FB, Lin H: Geographic patterns of cancer mortality clusters in Texas, 1990 to 1997. / Tex Med 2003, 99:58鈥?4.
  13. Thomas AJ, Carlin BP: Late detection of breast and colorectal cancer in Minnesota counties: an application of spatial smoothing and clustering. / Stat Med 2003, 22:113鈥?27. CrossRef
  14. Fukuda Y, Umezaki M, Nakamura K, Takano T: Variations in societal characteristics of spatial disease clusters: examples of colon, lung and breast cancer in Japan. / Int J Health Geogr 2005, 4:16鈥?8. CrossRef
  15. Kuehl KS, Loffredo CA: A cluster of hypoplastic left heart malformation in Baltimore, Maryland. / Pediatr Cardiol 2006, 27:25鈥?1. CrossRef
  16. Donnan PT, Parratt JD, Wilson SV, Forbes RB, O'Riordan JI, Swingler RJ: Multiple sclerosis in Tayside, Scotland: detection of clusters using a spatial scan statistic. / Mult Scler 2005, 11:403鈥?08. CrossRef
  17. Ala A, Stanca CM, Bu-Ghanim M, Ahmado I, Branch AD, Schiano TD, Odin JA, Bach N: Increased prevalence of primary biliary cirrhosis near superfund toxic waste sites. / Hepatology 2006, 43:525鈥?31. CrossRef
  18. Kulldorff M, Information Management Services, Inc: SaTScanTM v6.0: Software for the spatial and space-time scan statistics. [http://www.satscan.org/]
  19. Lin H, Liu Q, Guo J, Zhang J, Wang J, Chen H: Analysis of the geographic distribution of HFRS in Liaoning Province between 2000 and 2005. / BMC Public Health 2007, 7:207鈥?14. CrossRef
  20. Anselin L, Syabri I, Kho Y: GeoDa: An Introduction to Spatial Data Analysis. [http://www.csiss.org/]
  21. Bi P, Wu X, Zhang F, Parton KA, Tong S: Seasonal rainfall variability, the incidence of hemorrhagic fever with renal syndrome, and prediction of the disease in low-lying areas of China. / Am J Epidemiol 1998, 148:276鈥?81.
  22. Bi P, Tong S, Donald K, Parton K, Ni J: Climatic, reservoir and occupational variables and the transmission of hemorrhagic fever with renal syndrome in China. / Int J Epidemiol 2002, 31:189鈥?93. CrossRef
  23. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/11/229/prepub
  
• 作者单位：Wei Wu (1)
  Junqiao Guo (2)
  Peng Guan (1)
  Yingwei Sun (2)
  Baosen Zhou (1)
  
  1. Department of Epidemiology, School of Public Health, China Medical University, Shenyang, PR China
  2. Liaoning Provincial Center for Disease Control and Prevention, Shenyang, PR China
  

文摘

Background Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by Hantavirus, with characteristics of fever, hemorrhage, kidney damage, and hypotension. HFRS is recognized as a notifiable public health problem in China, and Liaoning Province is one of the most seriously affected areas with the most cases in China. It is necessary to investigate the spatial, temporal, and space-time distribution of confirmed cases of HFRS in Liaoning Province, China for future research into risk factors. Methods A cartogram map was constructed; spatial autocorrelation analysis and spatial, temporal, and space-time cluster analysis were conducted in Liaoning Province, China over the period 1988-2001. Results When the number of permutation test was set to 999, Moran's I was 0.3854, and was significant at significance level of 0.001. Spatial cluster analysis identified one most likely cluster and four secondary likely clusters. Temporal cluster analysis identified 1998-2001 as the most likely cluster. Space-time cluster analysis identified one most likely cluster and two secondary likely clusters. Conclusions Spatial, temporal, and space-time scan statistics may be useful in supervising the occurrence of HFRS in Liaoning Province, China. The result of this study can not only assist health departments to develop a better prevention strategy but also potentially increase the public health intervention's effectiveness.