54 research outputs found

    Human African trypanosomiasis amongst urban residents in Kinshasa: a case-control study.

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    BACKGROUND: Increasing numbers of human African trypanosomiasis (HAT) cases have been reported in urban residents of Kinshasa, Democratic Republic Congo since 1996. We set up a case-control study to identify risk factors for the disease. METHODS: All residents of the urban part of Kinshasa with parasitologically confirmed HAT and presenting for treatment to the city's specialized HAT clinics between 1 August, 2002 and 28 February, 2003 were included as cases. We defined the urban part as the area with contiguous habitation and a population density >5000 inhabitants per square kilometre. A digital map of the area was drawn based on a satellite image. For each case, two serologically negative controls were selected, matched on age, sex and neighbourhood. Logistic regression models were fitted to control for confounding. RESULTS: The following risk factors were independently associated with HAT: travel, commerce and cultivating fields in Bandundu, and commerce and cultivating fields in the rural part of Kinshasa. No association with activities in the city itself was found. DISCUSSION: In 2002, the emergence of HAT in urban residents of Kinshasa appears mainly linked to disease transmission in Bandundu and rural Kinshasa. We recommend to intensify control of these foci, to target HAT screening in urban residents to people with contact with these foci, to increase awareness of HAT amongst health workers in the urban health structures and to strengthen disease surveillance

    The Unknown Risk of Vertical Transmission in Sleeping Sickness—A Literature Review

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    Children with human African trypanosomiasis (HAT) present with a range of generally non-specific symptoms. Late diagnosis is frequent with often tragic outcomes. Trypanosomes can infect the foetus by crossing the placenta. Unequivocal cases of congenital infection that have been reported include newborn babies of infected mothers who were diagnosed with HAT in the first 5 days of life and children of infected mothers who had never entered an endemic country themselves

    The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

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    We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

    Interaction of aluminium and drought stress on root growth and crop yield on acid soils

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    Prevalence and under-detection of gambiense human African trypanosomiasis during mass screening sessions in Uganda and Sudan.

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    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
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