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, Doctoral Thesis, University of Basel, Faculty of Science.


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

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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) > Former Units within Swiss TPH > Health Impact Assessment (Utzinger)
UniBasel Contributors:Utzinger, Jürg and Vounatsou, Penelope
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:11118
Thesis status:Complete
Number of Pages:174 S.
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edoc DOI:
Last Modified:22 Apr 2018 04:31
Deposited On:24 Mar 2015 13:37

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