A Spatio-temporal Model of African Animal Trypanosomosis Risk

[b]Background[/b]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.[b]Methodology/Principal Findings[/b]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(2) = 67%), showed a positive correlation but less predictive power with serological status (r(2) = 22%) aggregated at the village level but was not related to the illness status (r(2) = 2%).[b]Conclusions/Significance[/b]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

An atlas to support the progressive control of tsetse-transmitted animal trypanosomosis in Burkina Faso

International audienceBackground African animal trypanosomosis (AAT), transmitted by tsetse flies, is arguably the main disease constraint to integrated crop-livestock agriculture in sub-Saharan Africa, and African heads of state and governments adopted a resolution to rid the continent of this scourge. In order to sustainably reduce or eliminate the burden of AAT, a progressive and evidence-based approach is needed, which must hinge on harmonized, spatially explicit information on the occurrence of AAT and its vectors. Methods A digital repository was assembled, containing tsetse and AAT data collected in Burkina Faso between 1990 and 2019. Data were collected either in the framework of control activities or for research purposes. Data were systematically verified, harmonized, georeferenced and integrated into a database (PostgreSQL). Entomological data on tsetse were mapped at the level of individual monitoring traps. When this was not possible, mapping was done at the level of site or location. Epidemiological data on AAT were mapped at the level of location or village. Results Entomological data showed the presence of four tsetse species in Burkina Faso. Glossina tachinoides , present from the eastern to the western part of the country, was the most widespread and abundant species (56.35% of the catches). Glossina palpalis gambiensis was the second most abundant species (35.56%), and it was mainly found in the west. Glossina morsitans submorsitans was found at lower densities (6.51%), with a patchy distribution in the southern parts of the country. A single cluster of G. medicorum was detected (less than 0.25%), located in the south-west. Unidentified tsetse flies accounted for 1.33%. For the AAT component, data for 54,948 animal blood samples were assembled from 218 geographic locations. The samples were tested with a variety of diagnostic methods. AAT was found in all surveyed departments, including the tsetse-free areas in the north. Trypanosoma vivax and T. congolense infections were the dominant ones, with a prevalence of 5.19 ± 18.97% and 6.11 ± 21.56%, respectively. Trypanosoma brucei infections were detected at a much lower rate (0.00 ± 0.10%). Conclusions The atlas provides a synoptic view of the available information on tsetse and AAT distribution in Burkina Faso. Data are very scanty for most of the tsetse-free areas in the northern part of the country. Despite this limitation, this study generated a robust tool for targeting future surveillance and control activities. The development of the atlas also strengthened the collaboration between the different institutions involved in tsetse and AAT research and control in Burkina Faso, which will be crucial for future updates and the sustainability of the initiative. Graphical Abstrac

Marginal effect of the entomological inoculate rate on seropositivity probability.

<p>The confidence interval is presented as a red dashed line.</p

Mean predicted habitat suitability index for both species.

<p>The index varies between 0 (less suitable, green scale) and 1 (highly suitable, red scale).</p

Logistic regression of disease metrics against EIR (entomological inoculation rate) at the cattle level.

<p>Significant codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ‘ 1</p><p>The results present the probability of an animal for being ill, having a positive parasitical status and being seropositive. The Age variable is measured in months and the Breed variable represents the breed of the animal (Taurin/Mixed/Zebu). Standard errors in brackets.</p

Predicted risk of bovine trypanosomosis for the dry and rainy season 2005.

<p>The risk indicator is the estimated Entomological Inoculate Rate (EIR). Darker areas in red are more at risk.</p

Optimal spatio-temporal lag for the regression model of serological and parasitological prevalences using AICc.

<p>The bold value presents the best model.</p

Remote sensing data from which environmental data was built.

<p>RFE (precipitation), NDVI (vegetation), MIR (vegetation), DLST (thermal), NLST (thermal) are time series of monthly raster grids from Jan. 2003 to Dec. 2013. DEM (topographic) is a static elevation model.</p

Binomial random effect models for trypanosomose infection rates in tsetse (both species).

<p>Significant codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ‘ 1</p><p>DLST (Day Land Surface Temperature), Cattle_density (FAO cattle density grid), Seasonality (sinusoidal function of month when infection status was recorded). Standard error for fixed effects in brackets.</p

Environmental data derived from remote sensing used for the analysis.

<p>Environmental data derived from remote sensing used for the analysis.</p