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Bayesian geostatistical modelling for mapping schistosomiasis transmission

Vounatsou, P. and Raso, G. and Tanner, M. and N'Goran, E. K. and Utzinger, J.. (2009) Bayesian geostatistical modelling for mapping schistosomiasis transmission. Parasitology, 136 (13). pp. 1695-1705.

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Official URL: http://edoc.unibas.ch/dok/A5843152

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Abstract

Progress has been made in mapping and predicting the risk of schistosomiasis using Bayesian geostatistical inference. Applications primarily focused on risk profiling of prevalence rather than infection intensity, although the latter is particularly important for morbidity control. In this review, the underlying assumptions used in a study mapping Schistosoma mansoni infection intensity in East Africa are examined. We argue that the assumption of stationarity needs to be relaxed, and that the negative binomial assumption might result in misleading inference because of a high number of excess zeros (individuals without an infection). We developed a Bayesian geostatistical zero-inflated (ZI) regression model that assumes a non-stationary spatial process. Our model is validated with a high-quality georeferenced database from western Cote d'Ivoire, consisting of demographic, environmental, parasitological and socio-economic data. Nearly 40% of the 3818 participating schoolchildren were infected with S. mansoni, and the mean egg count among infected children was 162 eggs per gram of stool (EPG), ranging between 24 and 6768 EPG. Compared to a negative binomial and ZI Poisson and negative binomial models, the Bayesian non-stationary ZI negative binomial model showed a better fit to the data. We conclude that geostatistical ZI models produce more accurate maps of helminth infection intensity than the spatial negative binomial ones
Faculties and Departments:03 Faculty of Medicine > Departement Public Health > Sozial- und Präventivmedizin > Malaria Vaccines (Tanner)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Health Interventions > Malaria Vaccines (Tanner)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Health Impact Assessment (Utzinger)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Infectious Disease Modelling > Epidemiology and Transmission Dynamics (Smith)
UniBasel Contributors:Vounatsou, Penelope and Tanner, Marcel and Utzinger, Jürg and Raso, Giovanna
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:Cambridge University Press
ISSN:0031-1820
e-ISSN:1469-8161
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:27 Jul 2018 08:35
Deposited On:14 Sep 2012 06:46

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