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A Spatio-temporal Model of African Animal Trypanosomosis Risk.

Dicko AH, Percoma L, Sow A, Adam Y, Mahama C, Sidibé I, Dayo GK, Thévenon S, Fonta W, Sanfo S, Djiteye A, Salou E, Djohan V, Cecchi G, Bouyer J - PLoS Negl Trop Dis (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: West African Science Service on Climate Change and Adapted Land Use, Climate Change Economics Research Program, Cheikh Anta Diop University, Dakar-Fann, Sénégal.

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 (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.

No MeSH data available.


Related in: MedlinePlus

Marginal effect of the entomological inoculate rate on seropositivity probability.The confidence interval is presented as a red dashed line.
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pntd.0003921.g005: Marginal effect of the entomological inoculate rate on seropositivity probability.The confidence interval is presented as a red dashed line.

Mentions: For the model of seropositivity, fitted at the animal level (cattle), we used the breed (zebu/taurin/cross) of the animal and its age as co-variables. EIR had an important positive impact on sero-positivity probability (OR = 1.5, CI = 1.3–1.7) with a positive marginal effect (Fig 5 and Table 5). Observed serological prevalence aggregated at the village level showed a positive correlation with the predicted sero-prevalence (Fig 6, r2 = 22%). Optimal spatio-temporal lag for the regression of parasitological prevalence against EIR was obtained for a time lag of one month but there was no difference between the three distances tested (Table 4). For homogeneity with the serological prevalence model, we kept the 5km radius model.


A Spatio-temporal Model of African Animal Trypanosomosis Risk.

Dicko AH, Percoma L, Sow A, Adam Y, Mahama C, Sidibé I, Dayo GK, Thévenon S, Fonta W, Sanfo S, Djiteye A, Salou E, Djohan V, Cecchi G, Bouyer J - PLoS Negl Trop Dis (2015)

Marginal effect of the entomological inoculate rate on seropositivity probability.The confidence interval is presented as a red dashed line.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4495931&req=5

pntd.0003921.g005: Marginal effect of the entomological inoculate rate on seropositivity probability.The confidence interval is presented as a red dashed line.
Mentions: For the model of seropositivity, fitted at the animal level (cattle), we used the breed (zebu/taurin/cross) of the animal and its age as co-variables. EIR had an important positive impact on sero-positivity probability (OR = 1.5, CI = 1.3–1.7) with a positive marginal effect (Fig 5 and Table 5). Observed serological prevalence aggregated at the village level showed a positive correlation with the predicted sero-prevalence (Fig 6, r2 = 22%). Optimal spatio-temporal lag for the regression of parasitological prevalence against EIR was obtained for a time lag of one month but there was no difference between the three distances tested (Table 4). For homogeneity with the serological prevalence model, we kept the 5km radius model.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: West African Science Service on Climate Change and Adapted Land Use, Climate Change Economics Research Program, Cheikh Anta Diop University, Dakar-Fann, Sénégal.

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 (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.

No MeSH data available.


Related in: MedlinePlus