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Intrathecal cytokine levels and blood-cerebrospinal fluid (CSF) barrier function were studied in 91 Trypanosoma brucei rhodesiense-infected patients. The CSF concentration of the cellular immune activation marker neopterin and the cytokines IL-6 and IL-10 were increased over control and post-treatment levels in all patients, with maximal levels observed in late-stage (meningoencephalitic) individuals. Analysis of CSF/serum concentration quotients indicated that IL-10 and neopterin were derived from central nervous system synthesis in at least 25% of the patients. Blood-CSF barrier dysfunction occurred in 64% of late-stage patients but not in early-stage patients. While the high level of neopterin observed in the late-stage patient CSF is indicative of widespread cellular activation, the increased levels of IL-6 and IL-10 suggest that counter-inflammatory cellular responses may be important in the regulation of neuropathogenesis in late-stage human African trypanosomiasis.

Summary 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 Vegetation Index (NDVI) and Landsat band 5 were derived as unclassified measures of vegetation density and soil moisture, respectively. GIS functions were used to determine the areas of land cover types and mean NDVI and band 5 values within 1.5 km radii of 389 villages where sleeping sickness incidence had been estimated. Analysis using backward binary logistic regression found proximity to swampland and low population density to be predictive of reported sleeping sickness presence, with distance to the sleeping sickness hospital as an important confounding variable. These findings demonstrate the potential of remote sensing and GIS to characterize village-level risk of sleeping sickness in endemic regions.

We have carried out a study of risk factors for early detection of Trypanosoma brucei rhodesiense sleeping sickness. Records of sleeping sickness patients from 1987 to 2001 from Tororo and Busia districts in Uganda were reviewed for their village of origin and clinical stage (early or late). All villages that reported sleeping sickness and fixed post-diagnostic sleeping sickness health units in Tororo and Busia districts were geo-referenced. The spatial distribution of early and late stage patient detection by health units was analysed using Geographical Information Systems (GIS). Of 1316 sleeping sickness patients admitted at the Livestock Health Research Institute and Busolwe hospitals and Lumino health centre from Tororo and Busia districts, 471 (35.8%) were early stage, 825 (62.7%) were late stage, while 20 (1.5%) were not staged. Five hundred and eighty-five (44.5%) came from within a 10km radius of the reporting health units. After multivariate analysis, the proportion of early stage patients detected was found to be significantly associated with patients originating from within a 10km radius of the health unit ( [Formula: see text] ), with adults (>19 years) ( [Formula: see text] ), and with annual parish incidence ( [Formula: see text] ). Application of GIS and the early to late stages ratio are an informative and powerful means of determining efficiency of surveillance of sleeping sickness.