Model approaches to evaluating potential mechanisms of parasite diffusion Open Access

Belle, Jessica Hartmann (2013)

Permanent URL: https://etd.library.emory.edu/concern/etds/h128nd81v?locale=en
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Abstract

Environmental parasites, including the trematode that causes schistosomiasis, are capable of dispersing across a landscape through environmental pathways, in particular hydrological networks. Yet our understanding of how environmental dispersion of parasites influences patterns of human disease is limited. In this thesis, several conceptualizations of environmental dispersion from putative sources of transmission were formulated and tested as to their ability to explain patterns of schistosomiasis incidence in Sichuan province, China. The dispersion models explored included: Euclidean dispersion; dispersion limited to downstream movement, where risk is determined by the nearest source; and dispersion occurring downstream of each source with exponentially decreasing likelihood, where the contributions of all upstream sources are summed. Each conceptualization of dispersion was used to generate exposure estimates for each location across a grid covering Sichuan Province. Statistical models were constructed to examine associations between each exposure estimate and the spatial distribution of cases reported to China's National Infectious Disease Reporting system in Sichuan province for the period of January 1, 2005 through December 31, 2011. A zero-inflated negative binomial modeling framework was used, and model fit was evaluated based on the Akaike information criterion (AIC). The models including dispersion of any kind performed better than the model with no dispersion. The model including dispersion occurring with exponentially decreasing likelihood downstream of each source, with a median dispersal distance of 1,200 m, performed slightly better than the other dispersion models based on AIC. However, the differences in the AIC values between the different dispersion models were small. The residuals from each of the models were also examined for evidence of spatial auto-correlation, however the distributions of the residual values were highly skewed, and calculation of a global Moran's I index was not possible. This paper makes methodological contributions to the literature despite the modest conclusions drawn, namely through the representation of anisotropic dispersion from a potential source in a regression framework where it could be directly related to spatial patterns of disease.

Table of Contents

Page Section

1 Introduction

4 Methods

8 Results

12 Discussion

15 Conclusion

16 Works Cited

21 Tables and Figures

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