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Geostatistical model-based predictions of helminthiases risk to assist control interventions

Chammartin, Frédérique. Geostatistical model-based predictions of helminthiases risk to assist control interventions. 2014, PhD Thesis, University of Basel, Faculty of Science.

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Official URL: http://edoc.unibas.ch/diss/DissB_11118

Abstract

A reduction in the burden caused by helminthic infections has been incorporated into the Millennium Development Goals (MDG). A good knowledge and understanding of the geographical distribution of the infections and reliable high resolution risk estimates are needed for cost-effective planning, targeting and monitoring of control interventions.
The work presented in this PhD thesis develops and implements the Bayesian geostatistical methodology for modelling helminthiases risk with a particular emphasis on Bayesian variable selection, the modelling of large spatial dataset and the spatio-temporal aspects of the distribution. Our applications focus on soil-transmitted helminth infections in Latin America where limited information on the geographical distribution and infection risk have hampered adequate control measures, as well as on schistosomiasis in Côte d’Ivoire, a country where implementation of interventions suffered from a decade of political instabilities.
This thesis provides important baseline information for control programmes and a benchmark upon which further estimates could be compared, as soon as new data become available and interventions are progressing.
Advisors:Utzinger, Jürg
Committee Members:Vounatsou, Penelope and Bergquist, Robert
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Eco System Health Sciences > Health Impact Assessment (Utzinger)
Item Type:Thesis
Thesis no:11118
Bibsysno:Link to catalogue
Number of Pages:174 S.
Language:English
Identification Number:
Last Modified:30 Jun 2016 10:57
Deposited On:24 Mar 2015 13:37

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