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Open Access Research article

Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China

Yin-Jun Li1, Xin-Lou Li1, Song Liang2, Li-Qun Fang1* and Wu-Chun Cao1*

Author Affiliations

1 State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing 100071, People’s Republic of China

2 Department of Environmental and Global Health, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA

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BMC Infectious Diseases 2013, 13:547  doi:10.1186/1471-2334-13-547

Published: 16 November 2013

Abstract

Background

Human brucellosis incidence in China has been increasing dramatically since 1999. However, epidemiological features and potential factors underlying the re-emergence of the disease remain less understood.

Methods

Data on human and animal brucellosis cases at the county scale were collected for the year 2004 to 2010. Also collected were environmental and socioeconomic variables. Epidemiological features including spatial and temporal patterns of the disease were characterized, and the potential factors related to the spatial heterogeneity and the temporal trend of were analysed using Poisson regression analysis, Granger causality analysis, and autoregressive distributed lag (ADL) models, respectively.

Results

The epidemic showed a significantly higher spatial correlation with the number of sheep and goats than swine and cattle. The disease was most prevalent in grassland areas with elevation between 800–1,600 meters. The ADL models revealed that local epidemics were correlated with comparatively lower temperatures and less sunshine in winter and spring, with a 1–7 month lag before the epidemic peak in May.

Conclusions

Our findings indicate that human brucellosis tended to occur most commonly in grasslands at moderate elevation where sheep and goats were the predominant livestock, and in years with cooler winter and spring or less sunshine.

Keywords:
Infectious diseases; Pandemics; Disease outbreaks; Risk assessment; Public health