Association between hemorrhagic fever with renal syndrome epidemic and climate factors in Heilongjiang Province, China

Li, Chang-Ping, Cui, Zhuang, Li, Shen-Long, Magalhaes, Ricardo J., Wang, Bao-Long, Zhang, Cui, Sun, Hai-Long, Li, Cheng-Yi, Huang, Liu-Yu, Ma, Jun and Zhang, Wen-Yi (2013) Association between hemorrhagic fever with renal syndrome epidemic and climate factors in Heilongjiang Province, China. American Journal of Tropical Medicine and Hygiene, 89 5: 1006-1012. doi:10.4269/ajtmh.12-0473


Author Li, Chang-Ping
Cui, Zhuang
Li, Shen-Long
Magalhaes, Ricardo J.
Wang, Bao-Long
Zhang, Cui
Sun, Hai-Long
Li, Cheng-Yi
Huang, Liu-Yu
Ma, Jun
Zhang, Wen-Yi
Title Association between hemorrhagic fever with renal syndrome epidemic and climate factors in Heilongjiang Province, China
Journal name American Journal of Tropical Medicine and Hygiene   Check publisher's open access policy
ISSN 0002-9637
1476-1645
Publication date 2013
Sub-type Article (original research)
DOI 10.4269/ajtmh.12-0473
Open Access Status DOI
Volume 89
Issue 5
Start page 1006
End page 1012
Total pages 7
Place of publication Deerfield, IL, United States
Publisher American Society of Tropical Medicine and Hygiene
Collection year 2014
Language eng
Abstract The purpose of this study was to quantify the relationship between climate variation and transmission of hemorrhagic fever with renal syndrome (HFRS) in Heilongjiang Province, a highly endemic area for HFRS in China. Monthly notified HFRS cases and climatic data for 2001-2009 in Heilongjiang Province were collected. Using a seasonal autoregressive integrated moving average model, we found that relative humidity with a one-month lag (β = -0.010, P = 0.003) and a three-month lag (β = 0.008, P = 0.003), maximum temperature with a two-month lag (β = 0.082, P = 0.028), and southern oscillation index with a two-month lag (β = -0.048, P = 0.019) were significantly associated with HFRS transmission. Our study also showed that predicted values expected under the seasonal autoregressive integrated moving average model were highly consistent with observed values (Adjusted R2 = 83%, root mean squared error = 108). Thus, findings may help add to the knowledge gap of the role of climate factors in HFRS transmission in China and also assist national local health authorities in the development/refinement of a better strategy to prevent HFRS transmission. Copyright
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
School of Public Health Publications
 
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