Email updates

Keep up to date with the latest news and content from BMC Infectious Diseases and BioMed Central.

Open Access Highly Accessed Research article

Investigating the effects of climatic variables and reservoir on the incidence of hemorrhagic fever with renal syndrome in Huludao City, China: a 17-year data analysis based on structure equation model

Peng Guan1, Desheng Huang12, Miao He3, Tiefeng Shen4, Junqiao Guo5 and Baosen Zhou1*

Author Affiliations

1 Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110001, PR China

2 Department of Mathematics, College of Basic Medical Sciences, China Medical University, Shenyang 110001, PR China

3 Information Center, the First Affiliated Hospital, China Medical University, Shenyang 110001, PR China

4 Division of Infectious Diseases Control, Huludao Municipal Center for Disease Control and Prevention, Huludao 125000, PR China

5 Liaoning Provincial Center for Disease Control and Prevention, Shenyang 110005, PR China

For all author emails, please log on.

BMC Infectious Diseases 2009, 9:109  doi:10.1186/1471-2334-9-109

Published: 8 July 2009

Abstract

Background

HFRS is a serious public health problem in China and the study on HFRS is important in China for its large population. The present study aimed to explore the impact of climatic variables and reservoir on the incidence of HFRS in Huludao City, an epidemic focus of the disease in northeastern China.

Methods

Structure Equation Model (SEM), a statistical technique for testing and estimating causal relationships, was conducted based on climatic variables, virus-carrying index among rodents, and incidence of HFRS in the city during the period 1990 to 2006. The linear structural relationships (LISREL) software (Scientific Software International, Lincolnwood, IL) was used to fit SEMs.

Results

Temperature, precipitation, relative humidity and virus-carrying index among rodents have shown positive correlations with the monthly incidence of HFRS, while air pressure had a negative correlation with the incidence. The best-fit SEM model fitted well with the data-based correlation matrix, P value was more than 0.56, root mean square error of approximation (RMSEA) equaled to 0, goodness-of-fit index (GFI) was more than 0.99.

Conclusion

Climate and reservoirs have affected the incidence of HFRS in Huludao City, located in northeastern China. Climate affects HFRS incidence mainly through the effect on reservoir in the study area. HFRS prevention and control should give more consideration to rodent control and climate variations.