Prevalence and predictors of HIV infection among female sex workers in Kaiyuan City, Yunnan Province, China

Wang, H.; Chen, R.Y.; Ding, G.; Ma, Y.; Ma, J.; Jiao, J.Hua.; Wu, Z.; Sharp, G.B.; Wang, N.

International Journal of Infectious Diseases Ijid Official Publication of the International Society for Infectious Diseases 13(2): 162-169


ISSN/ISBN: 1201-9712
PMID: 18718801
DOI: 10.1016/j.ijid.2008.05.1229
Accession: 023409524

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Spatial epidemiological tools are increasingly being applied to emerging viral zoonoses (EVZ), partly because of improving analytical methods and technologies for data capture and management, and partly because the demand is growing for more objective ways of allocating limited resources in the face of the emerging threat posed by these diseases. This review documents applications of geographical information systems (GIS), remote sensing (RS) and spatially-explicit statistical and mathematical models to epidemiological studies of EVZ. Landscape epidemiology uses statistical associations between environmental variables and diseases to study and predict their spatial distributions. Phylogeography augments epidemiological knowledge by studying the evolution of viral genetics through space and time. Cluster detection and early warning systems assist surveillance and can permit timely interventions. Advanced statistical models can accommodate spatial dependence present in epidemiological datasets and can permit assessment of uncertainties in disease data and predictions. Mathematical models are particularly useful for testing and comparing alternative control strategies, whereas spatial decision-support systems integrate a variety of spatial epidemiological tools to facilitate widespread dissemination and interpretation of disease data. Improved spatial data collection systems and greater practical application of spatial epidemiological tools should be applied in real-world scenarios.