Comparison of data-fitting models for schistosomiasis: a case study in Xingzi, China

Hu, Yi and Xiong, Cheng-Long and Zhang, Zhi-Jie and Bergquist, Robert and Wang, Zeng-Liang and Gao, Jie and Li, Rui and Tao, Bo and Jiang, Qiu-Lin and Jiang, Qingwu (2013) Comparison of data-fitting models for schistosomiasis: a case study in Xingzi, China. Geospatial Health, 8 (1). pp. 125-132. ISSN 1970-7096

[img]
Preview
PDF
Paper_3.pdf - Published Version

Download (806kB)
Official URL: http://www.geospatialhealth.unina.it/articles/v8i1...

Abstract

When modelling prevalence data, epidemiological studies usually employ either Gaussian, binomial or Poisson models. However, reasons are seldom given in the literature why the chosen model was felt to be the most appropriate. In this study, we compared all three models for fitting schistosomiasis risk in Xingzi county, Jiangxi province, People’s Republic of China. Parasitological data from conventional surveys were available for 36,208 individuals aged between 6 and 65 years from 42 sampled villages and used in combination with environmental data to map the spatial patterns of schistosomiasis risk. The results show that the Poisson model fitted the data best and this model identified the role of environmental risk factors in explaining the geographical variation of schistosomiasis risk. These factors were further used to develop a predictive map, which has important implications for the control and eventual elimination of schistosomiasis in the People’s Republic of China

Item Type: Article
Subjects: 600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici) > 614 Medicina legale; incidenza delle malattie; Medicina preventiva pubblica > 614.4 Incidenza delle malattie e misure pubblica per prevenirle (classificare qui l'Epidemiologia, l'Epidemiologia clinica)
Depositing User: Chiara D'Arpa
Date Deposited: 30 Jul 2014 14:33
Last Modified: 30 Jul 2014 14:33
URI: http://eprints.bice.rm.cnr.it/id/eprint/9388

Actions (login required)

View Item View Item