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Mapping the probability of schistosomiasis and associated uncertainty, West Africa.

Clements AC, Garba A, Sacko M, Touré S, Dembelé R, Landouré A, Bosque-Oliva E, Gabrielli AF, Fenwick A - Emerging Infect. Dis. (2008)

Bottom Line: We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for annual mass praziquantel distribution.Parasitologic surveys were conducted in Burkina Faso, Mali, and Niger, 2004-2006, and predictions were made by using Bayesian geostatistical models.Clusters with >50% probability of having >50% prevalence were delineated in each country.

View Article: PubMed Central - PubMed

Affiliation: School of Population Health, University of Queensland, Herston, Queensland, Australia. a.clements@uq.edu.au

ABSTRACT
We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for annual mass praziquantel distribution. Parasitologic surveys were conducted in Burkina Faso, Mali, and Niger, 2004-2006, and predictions were made by using Bayesian geostatistical models. Clusters with >50% probability of having >50% prevalence were delineated in each country.

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Related in: MedlinePlus

Predicted probability of prevalence of infection with Schistosoma hematobium being >50% in Burkina Faso, Mali, and Niger in boys ages 13–16 years; results are based on a Bayesian geostatistical model. The red areas had a low degree of uncertainty that predicted prevalence was >50%, and the blue areas had a high degree of uncertainty that predicted prevalence was >50%.
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Figure 2: Predicted probability of prevalence of infection with Schistosoma hematobium being >50% in Burkina Faso, Mali, and Niger in boys ages 13–16 years; results are based on a Bayesian geostatistical model. The red areas had a low degree of uncertainty that predicted prevalence was >50%, and the blue areas had a high degree of uncertainty that predicted prevalence was >50%.

Mentions: Bayesian probability maps were produced for each sex and age group, but for illustrative purposes we present predicted probability of prevalence >50% in boys ages 13–16 years (the group with the highest infection prevalence; Figure 2). Large clusters of prediction locations with a high probability (i.e., >50%; indicative of low uncertainty) of prevalence being >50% intervention threshold were located in a mid-latitudinal band across Mali, running from western to central regions, and in the Niger River valley region of Niger. Smaller clusters were located in various parts of southern and eastern Mali, northwestern and northeastern Burkina Faso, and south-central Niger.


Mapping the probability of schistosomiasis and associated uncertainty, West Africa.

Clements AC, Garba A, Sacko M, Touré S, Dembelé R, Landouré A, Bosque-Oliva E, Gabrielli AF, Fenwick A - Emerging Infect. Dis. (2008)

Predicted probability of prevalence of infection with Schistosoma hematobium being >50% in Burkina Faso, Mali, and Niger in boys ages 13–16 years; results are based on a Bayesian geostatistical model. The red areas had a low degree of uncertainty that predicted prevalence was >50%, and the blue areas had a high degree of uncertainty that predicted prevalence was >50%.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2609896&req=5

Figure 2: Predicted probability of prevalence of infection with Schistosoma hematobium being >50% in Burkina Faso, Mali, and Niger in boys ages 13–16 years; results are based on a Bayesian geostatistical model. The red areas had a low degree of uncertainty that predicted prevalence was >50%, and the blue areas had a high degree of uncertainty that predicted prevalence was >50%.
Mentions: Bayesian probability maps were produced for each sex and age group, but for illustrative purposes we present predicted probability of prevalence >50% in boys ages 13–16 years (the group with the highest infection prevalence; Figure 2). Large clusters of prediction locations with a high probability (i.e., >50%; indicative of low uncertainty) of prevalence being >50% intervention threshold were located in a mid-latitudinal band across Mali, running from western to central regions, and in the Niger River valley region of Niger. Smaller clusters were located in various parts of southern and eastern Mali, northwestern and northeastern Burkina Faso, and south-central Niger.

Bottom Line: We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for annual mass praziquantel distribution.Parasitologic surveys were conducted in Burkina Faso, Mali, and Niger, 2004-2006, and predictions were made by using Bayesian geostatistical models.Clusters with >50% probability of having >50% prevalence were delineated in each country.

View Article: PubMed Central - PubMed

Affiliation: School of Population Health, University of Queensland, Herston, Queensland, Australia. a.clements@uq.edu.au

ABSTRACT
We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for annual mass praziquantel distribution. Parasitologic surveys were conducted in Burkina Faso, Mali, and Niger, 2004-2006, and predictions were made by using Bayesian geostatistical models. Clusters with >50% probability of having >50% prevalence were delineated in each country.

Show MeSH
Related in: MedlinePlus