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A Spatio-temporal Model of African Animal Trypanosomosis Risk.

Authors :
Dicko, Ahmadou H.
Percoma, Lassane
Sow, Adama
Adam, Yahaya
Mahama, Charles
Sidibé, Issa
Dayo, Guiguigbaza-Kossigan
Thévenon, Sophie
Fonta, William
Sanfo, Safietou
Djiteye, Aligui
Salou, Ernest
Djohan, Vincent
Cecchi, Giuliano
Bouyer, Jérémy
Source :
PLoS Neglected Tropical Diseases; 7/8/2015, Vol. 9 Issue 7, p1-20, 20p
Publication Year :
2015

Abstract

Background: African 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 Findings: We 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 (r<superscript>2</superscript> = 67%), showed a positive correlation but less predictive power with serological status (r<superscript>2</superscript> = 22%) aggregated at the village level but was not related to the illness status (r<superscript>2</superscript> = 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19352727
Volume :
9
Issue :
7
Database :
Complementary Index
Journal :
PLoS Neglected Tropical Diseases
Publication Type :
Academic Journal
Accession number :
108634649
Full Text :
https://doi.org/10.1371/journal.pntd.0003921