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Background and methodology: Due to geographic overlap of malaria and visceral leishmaniasis (VL), co-infections may exist but have been poorly investigated. To describe prevalence, features and risk factors for VL-malaria co-infections, a case-control analysis was conducted on data collected at Amudat Hospital, Uganda (2000–2006) by Médecins sans Frontières. Cases were identified as patients with laboratory-confirmed VL and malaria at hospital admission or during hospitalization; controls were VL patients with negative malaria smears. A logistic regression analysis was performed to study the association between patients' characteristics and the occurrence of the co-infection. Results: Of 2414 patients with confirmed VL, 450 (19%) were positively diagnosed with concomitant malaria. Most co-infected patients were males, residing in Kenya (69%). While young age was identified by multivariate analysis as a risk factor for concurrent VL and malaria, particularly the age groups 0–4 (odds ratio (OR): 2.44; 95% confidence interval (CI): 1.52–3.92) and 5–9 years (OR: 2.23, 95% CI: 1.45-3-45), mild (OR: 0.53; 95% CI: 0.32–0.88) and moderate (OR: 0.45; 95% CI: 0.27–0.77) anemia negatively correlated with the co-morbidity. VL patients harboring skin infections were nearly three times less likely to have the co-infection (OR: 0.35; 95% CI: 0.17–0.72), as highlighted by the multivariate model. Anorexia was slightly more frequent among co-infected patients (OR: 1.71; 95% CI: 0.96–3.03). The in-hospital case-fatality rate did not significantly differ between cases and controls, being 2.7% and 3.1% respectively (OR: 0.87; 95% CI: 0.46–1.63). Conclusions: Concurrent malaria represents a common condition among young VL patients living in the Pokot region of Kenya and Uganda. Although these co-morbidities did not result in a poorer prognosis, possibly due to early detection of malaria, a positive trend towards more severe symptoms was identified, indicating that routine screening of VL patients living in malaria endemic-areas and close monitoring of co-infected patients should be implemented. Author Summary: Visceral leishmaniasis (VL) and malaria are two major parasitic diseases sharing a similar demographic and geographical distribution. In areas where both diseases are endemic, such as Sudan, Uganda, India and Bangladesh, co-infection cases have been reported, but features and risk factors associated with these co-morbidities remain poorly characterized. In the present study, routinely collected data of VL patients admitted to Amudat Hospital, Uganda, were used to investigate the magnitude of VL-malaria co-infections and identify possible risk factors. Nearly 20% of the patients included in this study were found to be co-infected with VL and malaria, indicating that this is a common condition among VL patients living in malaria endemic areas. Young age (≤9 years) was identified as an important risk factor for contracting the VL-malaria co-infection, while being anemic or carrying a skin infection appeared to negatively correlate with the co-morbidity. Co-infected patients presented with slightly more severe symptoms compared to mono-infected patients, but had a similar prognosis, possibly due to early diagnosis of malaria as a result of systematic testing. In conclusion, these results emphasize the importance of performing malaria screening amongst VL patients living in malaria-endemic areas and suggest that close monitoring of co-infected patients should be implemented. [ABSTRACT FROM AUTHOR]

Background: Active case detection through mass community screening is a major control strategy against human African trypanosomiasis (HAT, sleeping sickness) caused by T. brucei gambiense. However, its impact can be limited by incomplete attendance at screening sessions (screening coverage) and diagnostic inaccuracy. Methods: We developed a model-based approach to estimate the true prevalence and the fraction of cases detected during mass screening, based on observed prevalence, and adjusting for incomplete screening coverage and inaccuracy of diagnostic algorithms for screening, confirmation and HAT stage classification. We applied the model to data from three Médecins Sans Frontières projects in Uganda (Adjumani, Arua-Yumbe) and Southern Sudan (Kiri). Results: We analysed 604 screening sessions, targeting about 710 000 people. Cases were about twice as likely to attend screening as non-cases, with no apparent difference by stage. Past incidence, population size and repeat screening rounds were strongly associated with observed prevalence. The estimated true prevalence was 0.46% to 0.90% in Kiri depending on the analysis approach, compared to an observed prevalence of 0.45%; 0.59% to 0.87% in Adjumani, compared to 0.92%; and 0.18% to 0.24% in Arua-Yumbe, compared to 0.21%. The true ratio of stage 1 to stage 2 cases was around two-three times higher than that observed, due to stage misclassification. The estimated detected fraction was between 42.2% and 84.0% in Kiri, 52.5% to 79.9% in Adjumani and 59.3% to 88.0% in Arua-Yumbe. Conclusions: In these well-resourced projects, a moderate to high fraction of cases appeared to be detected through mass screening. True prevalence differed little from observed prevalence for monitoring purposes. We discuss some limitations to our model that illustrate several difficulties of estimating the unseen burden of neglected tropical diseases. [ABSTRACT FROM AUTHOR]

Background: Algorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. There is insufficient evidence on the relative accuracy of these algorithms. This paper presents estimates of the accuracy of five algorithms used by past Médecins Sans Frontières programmes in the Republic of Congo, Southern Sudan and Uganda. Methodology and Principal Findings: The sequence of tests in each algorithm was programmed into a probabilistic model, informed by distributions of the sensitivity, specificity and staging accuracy of each test, constructed based on a literature review. The accuracy of algorithms was estimated in a baseline scenario and in a worst-case scenario introducing various near worst-case assumptions. In the baseline scenario, sensitivity was estimated as 85–90% in all but one algorithm, with specificity above 99.9% except for the Republic of Congo, where CATT serology was used as independent confirmation test: here, positive predictive value (PPV) was estimated at <50% in realistic active screening prevalence scenarios. Furthermore, most algorithms misclassified about one third of true stage 1 cases as stage 2, and about 10% of true stage 2 cases as stage 1. In the worst-case scenario, sensitivity was 75–90% and PPV no more than 75% at 1% prevalence, with about half of stage 1 cases misclassified as stage 2. Conclusions: Published evidence on the accuracy of widely used tests is scanty. Algorithms should carefully weigh the use of serology alone for confirmation, and could enhance sensitivity through serological suspect follow-up and repeat parasitology. Better evidence on the frequency of low-parasitaemia infections is needed. Simulation studies should guide the tailoring of algorithms to specific scenarios of HAT prevalence and availability of control tools. Author Summary: Gambiense human African trypanosomiasis (HAT, sleeping sickness) usually features low prevalence. The two stages of the disease require different treatments, and stage 2 is fatal if untreated. HAT diagnosis must therefore be highly sensitive (i.e., detect as many true cases as possible) and specific (i.e., minimize false positives). HAT diagnostic algorithms are complex and involve several tests to screen for, confirm and stage infection. We analyzed five algorithms used by Médecins Sans Frontières HAT programmes. We combined published data on the accuracy of each test in the algorithm with a computer program that simulates all possible algorithm branches. We found that all algorithms had reasonable sensitivity (85–90%); specificity was high (>99.9%) except for the Republic of Congo, where confirmation did not rely on microscopic evidence, resulting in frequent false positives (but also higher sensitivity). Algorithms misclassified about one third of stage 1 cases as stage 2, but stage 2 classification was highly accurate. The use of serology alone for confirmation merits caution. HAT diagnosis could be made more sensitively by following up serological suspects and repeating microscopic examinations. Computer simulations can help to adapt algorithms to local conditions in each HAT programme, such as the prevalence of infection and operational constraints. [ABSTRACT FROM AUTHOR]

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Background: The durations of untreated stage 1 (early stage, haemo-lymphatic) and stage 2 (late stage, meningo-encephalitic) human African trypanosomiasis (sleeping sickness) due to Trypanosoma brucei gambiense are poorly quantified, but key to predicting the impact of screening on transmission. Here, we outline a method to estimate these parameters. Methods: We first model the duration of stage 1 through survival analysis of untreated serological suspects detected during Médecins Sans Frontières interventions in Uganda and Sudan. We then deduce the duration of stage 2 based on the stage 1 to stage 2 ratio observed during active case detection in villages within the same sites. Results: Survival in stage 1 appears to decay exponentially (daily rate = 0.0019; mean stage 1 duration = 526 days [95%CI 357 to 833]), possibly explaining past reports of abnormally long duration. Assuming epidemiological equilibrium, we estimate a similar duration of stage 2 (500 days [95%CI 345 to 769]), for a total of nearly three years in the absence of treatment. Conclusion: Robust estimates of these basic epidemiological parameters are essential to formulating a quantitative understanding of sleeping sickness dynamics, and will facilitate the evaluation of different possible control strategies. [ABSTRACT FROM AUTHOR]

Between September 2003 and April 2004, the supply of antimonial drugs to Amudat Hospital, in north–eastern Uganda, was interrupted and all cases of visceral leishmaniasis presenting at the hospital could only be treated with amphotericin B deoxycholate (AmB). This allowed the safety and effectiveness of the AmB to be evaluated, in comparison with an historical cohort of patients treated, at the same hospital, with meglumine antimoniate (SbV). Demographic and clinical data were collected before and after treatment. Adverse effects were recorded passively in all the subjects, and actively, using a standardized questionnaire, in a sub-group of the patients given AmB. The in hospital case-fatality 'rates' were 4.8% [95% confidence interval (CI) = 2.4%–8.8%] among the 210 patients treated with AmB and 3.7% (CI = 1.4%–7.9%) among the 161 patients treated with SbV (P>0.20). Adverse effects requiring treatment interruption were rare in both cohorts. Treatment failures (i.e. non-responses or relapses) were observed in 2.9% (CI = 1.2%–6.4%) of the patients treated with AmB and 1.2% (CI = 0.1%–4.4%) of the patients treated with SbV (P>0.20). For the treatment of visceral leishmaniasis in Uganda, AmB therefore had a similar effectiveness and safety profile to that of meglumine antimoniate. [ABSTRACT FROM AUTHOR]