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We describe 2 spatially distinct foci of human African trypansomiasis in eastern Uganda. The Tororo and Soroti foci of Trypanosoma brucei rhodesiense infection were genetically distinct as characterized by 6 microsatellite and 1 minisatellite polymorphic markers and were characterized by differences in disease progression and hostimmune response. In particular, infections with the Tororo genotype exhibited an increased frequency of progression to and severity of the meningoencephalitic stage and higher plasma interferon ( IFN)-gamma concentration, compared with those with the Soroti genotype. We propose that the magnitude of the systemic IFN-gamma response determines the time at which infected individuals develop central nervous system infection and that this is consistent with the recently described role of IFN-gamma in facilitating blood-brain barrier transmigration of trypanosomes in an experimental model of infection. The identification of trypanosome isolates with differing disease progression phenotypes provides the first field-based genetic evidence for virulence variants in T. brucei rhodesiense.

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.

There is an urgent need for cost-effective strategies for the sustainable control of Trypanosoma brucei rhodesiense (Rhodesian) sleeping sickness, which is a fatal zoonotic disease that has caused devastating epidemics during the past century. Sleeping sickness continues to be controlled by crisis management, using active case detection, treatment and vector control - activities that occur only during major epidemics; during the intervening periods, farmers and communities must fend for themselves. There are several methods for assessing the burden of this disease and there is a series of farmer-led methodologies that can be applied to reduce the burden of human and animal trypanosomiases.

Objective To determine, through the use of molecular diagnostic tools, whether the two species of parasite that cause human African trypanosomiasis have become sympatric.Design Blood sampling of all available patients between June 2001 and June 2005 in central Uganda and between July and September 2003 in northwest Uganda and analysis of subcounty sleeping sickness records in Uganda between 1985 and 2005.Setting Sleeping sickness treatment centres in central and northwest Uganda and in south Sudan.Participants Patients presenting at the treatment centres and diagnosed as having sleeping sickness.Main outcome measure Classification of parasites from patients from each disease focus as either Trypanosoma brucei rhodesiense (acute form) or T b gambiense (chronic form).Results Blood from 231 patients with sleeping sickness in central Uganda and from 91 patients with sleeping sickness in northwest Uganda and south Sudan were screened for T b rhodesiense (detection of SRA gene) and T b gambiense (detection of TgsGP gene). All samples from central Uganda were classified as T b rhodesiense, and all samples from northwest Uganda and south Sudan were identified as T b gambiense.Conclusions The two focuses of human African trypanosomiasis remain discrete, but the area of Uganda affected by the acute form of human sleeping sickness has increased 2.5-fold since 1985, spreading to three new districts within the past five years through movement of infected livestock. Without preventive action targeted at the livestock reservoir of this zoonotic disease, it is likely that the two disease focuses will converge. This will have a major impact on diagnosis and treatment of this neglected disease. Real time monitoring is recommended, using molecular diagnostic tools (at a regional surveillance centre, for example) targeted at both livestock and human patients.

The mechanisms underlying virulence in human African trypanosomiasis are poorly understood, although studies with experimental mice suggest that unregulated host inflammatory responses are associated with disease severity. We identified two trypanosomiasis foci with dramatically different disease virulence profiles. In Uganda, infections followed an acute profile with rapid progression to the late stage (meningoencephalitic infection) in the majority of patients (86.8%). In contrast, infections in Malawi were of a chronic nature, in which few patients progressed to the late stage (7.1%), despite infections of several months' duration. All infections were confirmed to beTrypanosoma brucei rhodesienseby testing for the presence of the serum resistance-associated (SRA) gene, but trypanosomes isolated from patients in Uganda or Malawi were distinguished by anSRAgene polymorphism. The two disease profiles were associated with markedly different levels of tumor necrosis factor alpha (TNF-α) and transforming growth factor β (TGF-β) in plasma. In Uganda but not Malawi early-stage TNF-α was elevated, while in Malawi but not Uganda early-stage TGF-β was elevated. Thus, rapid disease progression in Uganda is associated with TNF-α-mediated inflammatory pathology, whereas in the milder disease observed in Malawi this may be ameliorated by counterinflammatory cytokines. These differing host responses may result either from differing virulence phenotypes of northern and southern trypanosomes or from immune response polymorphisms in the different host populations.

Purpose of review Sleeping sickness has re-emerged as a serious problem in sub-Saharan Africa, with an estimated 100000 deaths each year. South Sudan, the Democratic Republic of Congo and Angola have experienced serious epidemics of the Gambian form of the disease. The control of Gambian sleeping sickness, which relies primarily on active case finding followed by chemotherapy, is being threatened by problems of drug resistance. Recently, Rhodesian sleeping sickness has also posed a health risk to travellers visiting game parks in East Africa. Recent findings Because of war-related constraints, which have prevented case detection, the prevalence of Gambian sleeping sickness commonly exceeds 5% and reached 29% in one focus in south Sudan. The incidence of Gambian infections refractory to melarsoprol treatment has also risen sharply in northern Uganda, northern Angola and southern Sudan, with failure rates as high as 26.9%. Molecular techniques based on the gene for human serum resistance (SRA) have enabled the identification of human infective parasites in the domestic animal reservoir. This molecular tool has shown that the Rhodesian form of the disease is being carried in cattle northwards in Uganda towards areas endemic for the Gambian form. The coalescence of distributions of the chronic and acute forms of the disease will present problems for both control and treatment. Summary This review surveys the molecular tools that are improving our understanding of the epidemiology of sleeping sickness, and highlights the search for new diagnostics and drugs to deal with the disease.

Sleeping sickness, caused by two trypanosome subspecies, Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense, is a parasitic disease transmitted by the tsetse fly in sub-Saharan Africa. We report on a recent outbreak of T b rhodesiense sleeping sickness outside the established south-east Ugandan focus, in Soroti District where the disease had previously been absent. Soroti District has been the subject of large-scale livestock restocking activities and, because domestic cattle are important reservoirs of T b rhodesiense, we investigated the role of cattle in the origins of the outbreak.We identified the origins of cattle entering the outbreak area in the 4 years preceding the outbreak. A matched case-control study was conducted to assess whether the distance of villages from the main market involved with restocking was a risk factor for sleeping sickness. We investigated the spatial clustering of sleeping sickness cases at the start of the outbreak.Over 50% (1510 of 2796) of cattle traded at the market were reported to have originated from endemic sleeping sickness areas. The case-control study revealed that distance to the cattle market was a highly significant risk factor for sleeping sickness (p0.001) and that there was a significant clustering of cases (27 of 28) close to the market at the start of the outbreak (p0.001). As the outbreak progressed, the average distance of cases moved away from the cattle market (0.014 km per day, 95% CI 0.008-0.020 km per day, p0.001).The results are consistent with the disease being introduced by cattle infected with T b rhodesiense imported to the market from the endemic sleeping sickness focus. The subsequent spread of the disease away from the market suggests that sleeping sickness is becoming established in this new focus. Public health measures directed at controlling the infection in the animal reservoir should be considered to prevent the spread of sleeping sickness.

BACKGROUND: The expansion of sleeping sickness caused by Trypanosoma brucei 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-infective T b rhodesiense must be distinguished from non-human-infective T brucei brucei, since both parasites can be present in cattle. We investigated the use of a simple genetic marker to characterise parasites collected from cattle in villages within the new sleeping sickness focus in Soroti District, Uganda. METHODS: 70 T brucei sl samples of known human infectivity status collected from human beings and cattle in Tororo District, Uganda, from 1989 to 1991 were screened for the presence of the human-serum-resistance-associated (SRA) gene by conventional PCR. In 2000-01, blood samples from 200 randomly selected cattle in six villages and two markets in Soroti District were screened for T brucei sl parasites by PCR; positive samples were screened for the presence of the SRA gene. FINDINGS: The SRA gene was present in all 29 samples from patients with sleeping sickness in Tororo District. Of the 41 samples collected from cattle at the same time, the SRA gene was present in the eight samples that tested resistant to human serum in vitro, whereas it was absent from all 33 isolates that were sensitive to human serum in vitro. Of the 200 cattle sampled in Soroti District, we estimated that up to 18% (95% CI 12-23) were infected with T b rhodesiense. INTERPRETATION: Detection of the SRA gene could provide the basis for a simple diagnostic test to enable targeted control of T b rhodesiense in the domestic livestock reservoir, thereby reducing the public-health burden of sleeping sickness in east Africa.

Background Sleeping sickness (HAT) caused by T.b. rhodesiense is a major veterinary and human public health problem in Uganda. Previous studies have investigated spatial risk factors for T.b. rhodesiense at large geographic scales, but none have properly investigated such risk factors at small scales, i.e. within affected villages. In the present work, we use a case-control methodology to analyse both behavioural and spatial risk factors for HAT in an endemic area. Methods The present study investigates behavioural and occupational risk factors for infection with HAT within villages using a questionnaire-based case-control study conducted in 17 villages endemic for HAT in SE Uganda, and spatial risk factors in 4 high risk villages. For the spatial analysis, the location of homesteads with one or more cases of HAT up to three years prior to the beginning of the study was compared to all non-case homesteads. Analysing spatial associations with respect to irregularly shaped geographical objects required the development of a new approach to geographical analysis in combination with a logistic regression model. Results The study was able to identify, among other behavioural risk factors, having a family member with a history of HAT (p = 0.001) as well as proximity of a homestead to a nearby wetland area (p < 0.001) as strong risk factors for infection. The novel method of analysing complex spatial interactions used in the study can be applied to a range of other diseases. Conclusion Spatial risk factors for HAT are maintained across geographical scales; this consistency is useful in the design of decision support tools for intervention and prevention of the disease. Familial aggregation of cases was confirmed for T. b. rhodesiense HAT in the study and probably results from shared behavioural and spatial risk factors amongmembers of a household.

Background Zoonotic sleeping sickness, or HAT (Human African Trypanosomiasis), caused by infection with Trypanosoma brucei rhodesiense, is an under-reported and neglected tropical disease. Previous assessments of the disease burden expressed as Disability-Adjusted Life Years (DALYs) for this infection have not distinguished T.b. rhodesiense from infection with the related, but clinically distinct Trypanosoma brucei gambiense form. T.b. rhodesiense occurs focally, and it is important to assess the burden at the scale at which resource-allocation decisions are made. Methods The burden of T.b. rhodesiense was estimated during an outbreak of HAT in Serere, Uganda. We identified the unique characteristics affecting the burden of rhodesiense HAT such as age, severity, level of under-reporting and duration of hospitalisation, and use field data and empirical estimates of these to model the burden imposed by this and other important diseases in this study population. While we modelled DALYs using standard methods, we also modelled uncertainty of our parameter estimates through a simulation approach. We distinguish between early and late stage HAT morbidity, and used disability weightings appropriate for the T.b. rhodesiense form of HAT. We also use a model of under-reporting of HAT to estimate the contribution of un-reported mortality to the overall disease burden in this community, and estimate the cost-effectiveness of hospital-based HAT control. Results Under-reporting accounts for 93% of the DALY estimate of rhodesiense HAT. The ratio of reported malaria cases to reported HAT cases in the same health unit was 133:1, however, the ratio of DALYs was 3:1. The age productive function curve had a close correspondence with the HAT case distribution, and HAT cases occupied more patient admission time in Serere during 1999 than all other infectious diseases other than malaria. The DALY estimate for HAT in Serere shows that the burden is much greater than might be expected from its relative incidence. Hospital based control in this setting appears to be highly cost-effective, highlighting the value of increasing coverage of therapy and reducing under-reporting. Conclusion We show the utility of calculating DALYs for neglected diseases at the local decision making level, and emphasise the importance of improved reporting systems for acquiring a better understanding of the burden of neglected zoonotic diseases.

Sleeping sickness is a parasitic, vector-borne disease, carried by the tsetse fly and prevalent in sub-Saharan Africa. The disease continues to pose a public health burden in Uganda, which experienced a widespread outbreak in 1900-1920, and a more recent outbreak in 1976-1989. The disease continues to spread to uninfected districts.This paper compares the spatial distributions of sleeping in Uganda for the 1900-1920 outbreak period with current disease foci, and discusses information gaps and implications arising for future research, prevention and control.Population census records for 1911 and sleeping sickness records from Medical and Sanitary Reports of the Ugandan Protectorate for 1905-1936 were extracted from the Uganda Archives. Current sleeping sickness distribution data were provided by the Ministry of Health, Uganda. These were used to develop sleeping sickness distribution maps for comparison between the early 1900s and the early 2000s.The distribution of sleeping sickness from 1905-1920 shows notable differences compared to the current distribution of disease. In particular, archival cases were recorded in south-west and central Uganda, areas currently free of disease. The disease focus has moved from lakeshore Buganda (1905-1920) to the Busoga and south-east districts.Archival sleeping sickness distributions indicate the potential for a much wider area of disease risk than indicated by current disease foci. This is compounded by an absence of tsetse distribution data, continued political instability in north-central Uganda, continued spread of disease into new districts, and evidence of the role of livestock movements in spreading the parasite. These results support concerns as to the potential mergence of the two disease foci in the south-east and north-west of the country.

Summary 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, a deterministic (subset) model was developed. The values of the under-detection model parameters were estimated from previously published records of the duration of symptoms prior to presentation and the ratio of early to late stage cases in 760 SS patients presenting at LIRI hospital, Tororo, Uganda during the 1988–1990 epidemic of SS. For the observed early to late stage ratio of 0.47, we estimate that the proportion of under-detection in the catchment area of LIRI hospital was 0.39 (95% CI 0.37–0.41) i.e. 39% of cases are not reported. Based on this value, it is calculated that for every one reported death of SS, 12.0 (95% CI 11.0–13.0) deaths went undetected in the LIRI hospital catchment area – i.e. 92% of deaths are not reported. The deterministic (subset) model structured on the possible routes of a SS infection to either diagnosis or death through the health system or out of it, showed that of a total of 73 undetected deaths, 62 (CI 60–64) (85%) entered the healthcare system but were not diagnosed, and 11 (CI 11–12) died without seeking health care from a recognized health unit. The measure of early to late stage presentation provides a tractable measure to determine the level of rhodesiense SS under-detection and to gauge the effects of interventions aimed at increasing treatment coverage.

The epidemic of Trypanosoma brucei rhodesiense sleeping sickness in eastern Uganda, which began in 1998 as a result of movements of the livestock reservoir of the parasite, has continued to spread. An additional 133 000 people have been put at risk of infection in Kaberamaido, another newly affected district. The few resources committed to control interventions in Soroti district have failed to contain the epidemic. The high prevalence of the parasite in cattle presents a significant risk for transmission to human beings and further spread of this neglected zoonotic disease. Targeted interventions are urgently needed to control epidemics and reduce the high mortality resulting from sleeping sickness.

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.

For those with sleeping sickness, the consequences of delayed diagnosis include poor prognosis at treatment and an increased risk of tsetse infection. Data on their socio-demographic and clinical characteristics, health-seeking behaviour and delays in presentation and diagnosis were collected from 119 diagnosed cases of rhodesiense sleeping sickness in eastern Uganda. The median total delay, from onset of the illness to diagnosis, was 60 days. The median service-provider delay (30 days) was markedly longer than the median patient delay (17 days). Each of these delays was, however, considerable and independently associated with patients presenting with late-stage sleepiness, giving odds ratios and (95% confidence intervals) of 7.29 (3.10-17.14) and 2.98 (1.38-6.43), respectively. A blood examination at the first visit was also associated with the service-provider delay (odds ratio = 0.45; 95% confidence interval = 0.22-0.95). Most of the patients (77.4%) had either been referred to the local sleeping-sickness hospital by other members of their community or presented at the hospital on their own initiative; few had been referred by other components of the local health system. The results are disappointing, not only in showing long delays in diagnosis (and therefore in treatment) but also in indicating that much of the delay is attributable to the service provider failing to diagnose sleeping sickness among symptomatic individuals.

Plasma and cerebrospinal fluid (CSF) concentrations of nitrate and the cytokines interferon (IFN)-gamma, tumor necrosis factor (TNF)-alpha, interleukin (IL)-10, and IL-4 were measured in 91 African trypanosomiasis patients before and after treatment. Nitrate levels overall were not significantly elevated over those for control persons, but a marginal increase in plasma nitrate was detected in patients reporting illness of

Sleeping sickness presents clinically as two distinct diseases, reflecting the fact that two very different trypanosomes are responsible. The African Rift separating East and West Africa defines the distribution of the two diseases. In this review, Susan Welburn, Eric Fevre, Paul Coleman, Martin Odiit and Ian Maudlin discuss the biology and distribution of these two diseases in relation to the evolution of hominids in Africa.