Evidence map›Paper›PMID 26154506›Full record

ArticlePLoS neglected tropical diseases2015

A Spatio-temporal Model of African Animal Trypanosomosis Risk.

Ahmadou H Dicko, Lassane Percoma, Adama Sow, Yahaya Adam, Charles Mahama, Issa Sidibé, Guiguigbaza-Kossigan Dayo, Sophie Thévenon, William Fonta, Safietou Sanfo and 5 more

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 32 citations in OpenAlex.

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  18. Mapping landscape friction to locate isolated tsetse populations that are candidates for elimination.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 12 institutions in 7 countries.

Ahmadou H DickoWest African Science Service on Climate Change and Adapted Land Use, Climate Change Economics Research Program, Cheikh Anta Diop University, Dakar-Fann, Sénégal.
Lassane PercomaThe Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC), Bobo-Dioulasso, Burkina Faso.
Adama SowEcole Inter Etats des Sciences et Médecine Vétérinaires de Dakar (EISMV), Dakar, Sénégal.
Yahaya AdamVeterinary Services Department of the Ministry of Food and Agriculture, Pong-Tamale, Ghana.
Charles MahamaVeterinary Services Department of the Ministry of Food and Agriculture, Pong-Tamale, Ghana.
Issa SidibéThe Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC), Bobo-Dioulasso, Burkina Faso; Centre International de Recherche-Développement sur l'Elevage en zone Subhumide (CIRDES), Bobo-Dioulasso, Burkina Faso.
Guiguigbaza-Kossigan DayoThe Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC), Bobo-Dioulasso, Burkina Faso; Centre International de Recherche-Développement sur l'Elevage en zone Subhumide (CIRDES), Bobo-Dioulasso, Burkina Faso.
Sophie ThévenonCIRAD, UMR INTERTRYP, Montpellier, France.
William FontaWest African Science Center on Climate Change and Adapted Land Use, Ouagadougou, Burkina Faso.
Safietou SanfoWest African Science Center on Climate Change and Adapted Land Use, Ouagadougou, Burkina Faso.
Aligui DjiteyeDirection Nationale des Services Vétérinaires, Pan African Tsetse and Trypanosomosis Eradication Campaign (PATTEC), Mali, Bamako, Mali.
Ernest SalouCentre International de Recherche-Développement sur l'Elevage en zone Subhumide (CIRDES), Bobo-Dioulasso, Burkina Faso; Université Polytechnique de Bobo Dioulasso (UPB), Bobo Dioulasso, Burkina Faso.
Vincent DjohanFelix Houphouet Boigny University, National Institute of Public Health, Abidjan, Côte d'Ivoire.
Giuliano CecchiFood and Agriculture Organization of the United Nations (FAO), Sub-regional Office for Eastern Africa, Addis Ababa, Ethiopia.
Jérémy BouyerCIRAD, UMR INTERTRYP, Montpellier, France; CIRAD, UMR CMAEE, Dakar-Hann, Sénégal; CIRAD, UMR CMAEE, Montpellier, France; INRA, UMR1309 CMAEE, Montpellier, France; Institut Sénégalais de Recherches Agricoles (ISRA), Laboratoire National d'Elevage et de Recherches Vétérinaires (LNERV), LNERV, Dakar-Hann, Sénégal.
Burkina Faso Ministry of the Environment, Green Economy, and Climate Change · BFCentre international de recherche-développement sur l'elevage en zone subhumide · BFMinistry of Food and Agriculture · GHCentre de Coopération Internationale en Recherche Agronomique pour le Développement · FRCheikh Anta Diop University · SNÉcole Inter-États des Sciences et Médecine Vétérinaires de Dakar · SNInstitut Sénégalais de Recherches Agricoles · SNMali-Folkecenter · MLNazi Boni University · BFPan African Tsetse and Trypanosomiasis Eradication Campaign · BFUnited Nations Economic Commission for Africa · ETUniversité Félix Houphouët-Boigny · CI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAfrican animal trypanosomosis (AAT) is a major constraint to sustainable development of cattle farming in sub-Saharan Africa. The habitat of the tsetse fly vector is increasingly fragmented owing to demographic pressure and shifts in climate, which leads to heterogeneous risk of cyclical transmission both in space and time. In Burkina Faso and Ghana, the most important vectors are riverine species, namely Glossina palpalis gambiensis and G. tachinoides, which are more resilient to human-induced changes than the savannah and forest species. Although many authors studied the distribution of AAT risk both in space and time, spatio-temporal models allowing predictions of it are lacking. METHODOLOGY/PRINCIPAL

findingsWe used datasets generated by various projects, including two baseline surveys conducted in Burkina Faso and Ghana within PATTEC (Pan African Tsetse and Trypanosomosis Eradication Campaign) national initiatives. We computed the entomological inoculation rate (EIR) or tsetse challenge using a range of environmental data. The tsetse apparent density and their infection rate were separately estimated and subsequently combined to derive the EIR using a "one layer-one model" approach. The estimated EIR was then projected into suitable habitat. This risk index was finally validated against data on bovine trypanosomosis. It allowed a good prediction of the parasitological status (r2 = 67%), showed a positive correlation but less predictive power with serological status (r2 = 22%) aggregated at the village level but was not related to the illness status (r2 = 2%). CONCLUSIONS/SIGNIFICANCE: The presented spatio-temporal model provides a fine-scale picture of the dynamics of AAT risk in sub-humid areas of West Africa. The estimated EIR was high in the proximity of rivers during the dry season and more widespread during the rainy season. The present analysis is a first step in a broader framework for an efficient risk management of climate-sensitive vector-borne diseases.

Indexed as

AfricaAnimalsCattleEcosystemInsect VectorsModels, TheoreticalRisk FactorsSeasonsTrypanosomiasis, BovineTsetse Flies

Identifiers

PMID26154506
PMCPMC4495931
OpenAlexW1747967554

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.