4.5 Article

Atmospheric Moisture Variability and Transmission of Hemorrhagic Fever with Renal Syndrome in Changsha City, Mainland China, 1991-2010

Journal

PLOS NEGLECTED TROPICAL DISEASES
Volume 7, Issue 6, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pntd.0002260

Keywords

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Funding

  1. Key Discipline Construction Project in Hunan Province [2008001]
  2. Scientific Research Fund of the Hunan Provincial Education Department [11K037]
  3. Hunan Provincial Natural Science Foundation of China [11JJ3119]
  4. Science and Technology Planning Project of Hunan Province, China [2010SK3007]
  5. Key Subject Construction Project of Hunan Normal University (geographic information systems)
  6. Key Project of Hunan Provincial Education Department
  7. National Natural Science Foundation of China

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Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by environmental determinants. This study aimed to explore the association between atmospheric moisture variability and the transmission of hemorrhagic fever with renal syndrome (HFRS) for the period of 1991-2010 in Changsha, China. Methods and Findings: Wavelet analyses were performed by using monthly reported time series data of HFRS cases to detect and quantify the periodicity of HFRS. A generalized linear model with a Poisson distribution and a log link model were used to quantify the relationship between climate and HFRS cases, highlighting the importance of moisture conditions. There was a continuous annual oscillation mode and multi-annual cycle around 3-4 years from 1994 to 1999. There was a significant association of HFRS incidence with moisture conditions and the Multivariate El Nino-Southern Oscillation Index (MEI). Particularly, atmospheric moisture has a significant effect on the propagation of HFRS; annual incidence of HFRS was positively correlated with annual precipitation and annual mean absolute humidity. Conclusions: The final model had good accuracy in forecasting the occurrence of HFRS and moisture condition can be used in disease surveillance and risk management to provide early warning of potential epidemics of this disease.

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