The Atlas of human African trypanosomiasis: a contribution to global mapping of neglected tropical diseases

Simarro, Pere P.; Cecchi, Giuliano; Paone, Massimo; Franco, José R.; Diarra, Abdoulaye; Ruiz, José Arturo; Fèvre, Eric M.; Courtin, Fabrice; Mattioli, Raffaele C.; Jannin, J.

doi:10.1186/1476-072x-9-57

Cited by 343 publications

(380 citation statements)

References 42 publications

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“…Untreated patients become progressively less responsive before coma and death supervene. [80][81][82][83] While children with Nodding Syndrome may exhibit blank, staring facies perhaps attributable to absence seizures, the overall clinical pattern of the syndrome is distinct from African trypanosomiasis. Additionally, infection with T. brucei gambiense among cases and controls was similar.…”

Section: Parasitesmentioning

confidence: 99%

Nodding syndrome in Mundri county, South Sudan: Environmental, nutritional and infectious factors

Spencer¹,

Vandemaele

Richer³

et al. 2013

Afr H. Sci.

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Background: Nodding Syndrome is a seizure disorder of children in Mundri County, Western Equatoria, South Sudan. The disorder is reported to be spreading in South Sudan and northern Uganda. Results: Nodding Syndrome was associated with Onchocerca volvulus and Mansonella perstans infections, with food use of a variety of sorghum (serena) introduced as part of an emergency relief program, and was inversely associated with a history of measles infection. There was no evidence to suggest exposure to a manmade neurotoxic pollutant or chemical agent, other than chemically dressed seed intended for planting but used for food. Food use of cyanogenic plants was documented, and exposure to fungal contaminants could not be excluded. Conclusion: Nodding Syndrome in South Sudan has an unknown etiology. Further research is recommended on the association of Nodding Syndrome with onchocerciasis/mansonelliasis and neurotoxins in plant materials used for food.

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Section: Parasitesmentioning

confidence: 99%

Nodding syndrome in Mundri county, South Sudan: Environmental, nutritional and infectious factors

Spencer¹,

Vandemaele

Richer³

et al. 2013

Afr H. Sci.

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“…Over the last two decades, advances in remote sensing, geographical information systems (GIS) and spatial statistics have triggered the development of modelling approaches to tsetse distribution mapping (Rogers and Randolph, 1993;Robinson et al, 1997;Rogers and Robinson, 2004). Turning to the disease, the human form (sleeping sickness) is characterized by a pronounced focal nature, with the distribution of endemic foci remaining remarkably stable over the last century (Simarro et al, 2010) with a few notable exceptions (e.g. Fèvre et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…Fèvre et al, 2001). Recently, systematic data collation and mapping have made it possible to represent the current distribution of human African trypanosomosis with high accuracy (Cecchi et al, 2009;Simarro et al, 2010) and to assess the population at risk (Simarro et al, 2012). In domestic animals, although the prevalence of the disease varies between populations and localities, trypanosomosis generally presents as an endemic disease, with a widespread presence in livestock populations across the tsetse-infested area of sub-Saharan Africa.…”

Section: Introductionmentioning

confidence: 99%

Mapping the benefit-cost ratios of interventions against bovine trypanosomosis in Eastern Africa

Shaw

Wint

Cecchi³

et al. 2015

Preventive Veterinary Medicine

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This study builds upon earlier work mapping the potential benefits from bovine trypanosomosis control and analysing the costs of different approaches. Updated costs were derived for five intervention techniques: trypanocides, targets, insecticide-treated cattle, aerial spraying and the release of sterile males. Two strategies were considered: continuous control and elimination. For mapping the costs, cattle densities, environmental constraints, and the presence of savannah or riverine tsetse species were taken into account. These were combined with maps of potential benefits to produce maps of benefit-cost ratios. The results illustrate a diverse picture, and they clearly indicate that no single technique or strategy is universally profitable. For control using trypanocide prophylaxis, returns are modest, even without accounting for the risk of drug resistance but, in areas of low cattle densities, this is the only approach that yields a positive return. Where cattle densities are sufficient to support it, the use of insecticidetreated cattle stands out as the most consistently profitable technique, widely achieving benefit-cost ratios above 5. In parts of the high-potential areas such as the mixed farming, high-oxen-use zones of western Ethiopia, the fertile crescent north of Lake Victoria and the dairy production areas in western and central Kenya, all tsetse control strategies achieve benefit-cost ratios from 2 to over 15, and for elimination strategies, ratios from 5 to over 20. By contrast, in some areas, notably where cattle densities are below 20 per km 2 , the costs of interventions against tsetse match or even outweigh the benefits, especially for control scenarios using aerial spraying or the deployment of targets where both savannah and riverine flies are present. If the burden of human African trypanosomosis were factored in, the benefit-cost ratios of some of the low-return areas would be considerably increased. Comparatively, elimination strategies give rise to higher benefit-cost ratios than do those for continuous control. However, the costs calculated for elimination assume problem-free, large scale operations, and they rest on the outputs of entomological models that are difficult to validate in the field. Experience indicates that the conditions underlying successful and sustained elimination campaigns are seldom met. By choosing the most appropriate thresholds for benefit-cost ratios, decision-makers and planners can use the maps to define strategies, assist in prioritising areas for intervention, and help choose among intervention techniques and approaches. The methodology would have wider applicability in analysing other disease constraints with a strong spatial component.

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“…Detailed information on the spatial distribution of diseases also provides significant benefits for disease control programmes, particularly for spatially heterogeneous disease distributions (Snow et al, 1996;Simarro et al, 2010). However, just as in the mapping of biodiversity, obtaining comprehensive spatial coverage of a disease within a region of interest is not always possible using disease surveillance data (particularly not in developing countries where the infrastructure is often poor).…”

Section: Introductionmentioning

confidence: 99%

Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

et al. 2014

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Abstract. The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps). These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread) can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

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The Atlas of human African trypanosomiasis: a contribution to global mapping of neglected tropical diseases

Cited by 343 publications

References 42 publications

Nodding syndrome in Mundri county, South Sudan: Environmental, nutritional and infectious factors

Nodding syndrome in Mundri county, South Sudan: Environmental, nutritional and infectious factors

Mapping the benefit-cost ratios of interventions against bovine trypanosomosis in Eastern Africa

Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

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