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Journal Article 2001

Identification of human-infective trypanosomes in animal reservoir of sleeping sickness in Uganda by means of serum-resistance-associated (SRA) gene

Autor: Welburn, S.C. Picozzi, K. Fèvre, Eric M. Coleman, P.G. Odiit, M. Carrington, M. Maudlin, I.

Background: The expansion of sleeping sickness caused by Trypanosoma brucei rhodesiense (T. rhodesiense) beyond its traditional focus in southeast Uganda, has been linked with large-scale livestock restocking. To assess the risk presented to the human population by domestic livestock, human-infe...

Enlace original: https://cgspace.cgiar.org/handle/10568/29166

Investigación en Agricultura

CATTLE

MAN

TRYPANOSOMA BRUCEI

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Welburn, S.C. , Picozzi, K. , Fèvre, Eric M. , Coleman, P.G. , Odiit, M. , Carrington, M. , Maudlin, I. , [Identification of human-infective trypanosomes in animal reservoir of sleeping sickness in Uganda by means of serum-resistance-associated (SRA) gene] , Identification of human-infective trypanosomes in animal reservoir of sleeping sickness in Uganda by means of serum-resistance-associated (SRA) gene

Journal Article 2006

Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda

Autor: Odiit, M. Bessell, P.R. Fèvre, Eric M. Robinson, Timothy P. Kinoti, J. Coleman, P.G. Welburn, S.C. McDermott, John J. Woolhouse, Mark E.J.

Geographic information systems (GIS) and remote sensing were used to identify villages at high risk for sleeping sickness, as defined by reported incidence. Landsat Enhanced Thematic Mapper (ETM) satellite data were classified to obtain a map of land cover, and the Normalised Difference Vegetatio...

Enlace original: https://cgspace.cgiar.org/handle/10568/29673

Investigación en Agricultura

TRYPANOSOMA RHODESIENSE

TRYPANOSOMIASIS

GEOGRAPHICAL INFORMATION SYSTEMS

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Odiit, M. , Bessell, P.R. , Fèvre, Eric M. , Robinson, Timothy P. , Kinoti, J. , Coleman, P.G. , Welburn, S.C. , McDermott, John J. , Woolhouse, Mark E.J. , [Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda] , Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda

Journal Article 2005

Quantifying the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness cases

Autor: Odiit, M. Coleman, P.G. Liu, W.C. McDermott, John J. Fèvre, Eric M. Welburn, S.C. Woolhouse, Mark E.J.

To formally quantify the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness (SS) during an epidemic in Uganda, a decision tree (under-detection) model was developed; concurrently, to quantify the subset of undetected cases that sought health care but were not diagnosed, ...

Enlace original: https://cgspace.cgiar.org/handle/10568/29792

Investigación en Agricultura

TRYPANOSOMA BRUCEI

TRYPANOSOMA RHODESIENSE

TRYPANOSOMIASIS

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Odiit, M. , Coleman, P.G. , Liu, W.C. , McDermott, John J. , Fèvre, Eric M. , Welburn, S.C. , Woolhouse, Mark E.J. , [Quantifying the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness cases] , Quantifying the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness cases

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Identification of human-infective trypanosomes in animal reservoir of sleeping sickness in Uganda by means of serum-resistance-associated (SRA) gene

Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda

Quantifying the level of under-detection of Trypanosoma brucei rhodesiense sleeping sickness cases