Etter, E. | Search bioRxiv

bioRxiv2025

Prevalence of Heartwater in Guadeloupe (2024): Stable endemicity and Evidence of Spread to Les Saintes

Heartwater is a tick-borne disease caused by Ehrlichia ruminantium and remains endemic in the Guadeloupe archipelago. While previous data from 1989 suggested a seroprevalence of 22% in cattle, no updated figures were available for livestock, and certain islands such as Les Saintes were considered disease-free. This study aimed to update the sero-epidemiological status of heartwater in cattle and goats across Guadeloupe in 2024. Blood samples were collected from 261 cattle and 135 goats from all islands. Serological testing using the MAP1B ELISA was performed, and true seroprevalence was estimated using a simplified stochastic model that accounts for test sensitivity, specificity, and sample uncertainty. The mean cattle seroprevalence was estimated at 28% (95% CI [22-34%]), with no significant differences between Basse-Terre, Grande-Terre, and Marie-Galante. Importantly, seropositive goats were identified on all major islands, including Les Saintes. Our findings suggest that heartwater remains endemically stable in Guadeloupe since the 1980s and reveal for the first time its serological presence in Les Saintes. These results emphasize the importance of strengthening regional surveillance systems, including veterinary reporting, serological monitoring, and coordinated efforts to prevent further spread across the Caribbean.

immunology↗

bioRxiv2025

Downscaling local distribution of cattle over Guadeloupe archipelago: an adapted method for disaggregating census data

Gridded livestock distribution datasets have been produced for several years and are used in various fields, including epidemiology, livestock impact assessment, and territory management. Those datasets are based on census conducted at national/sub-national scale which are then downscaled using machine learning algorithm and relevant spatial-explicit environmental predictors. The most known dataset of livestock disaggregated observations is the Gridded Livestock of the World (GLW), which produces global maps of livestock density at 10 km spatial resolution for several livestock species. Though this spatial resolution can be appropriate to describe livestock distribution at the global scale, it inherently leads to a coarse representation of breeding species density for smaller territories such as the Caribbean Islands. In this study, we propose an adaptation of the GLW methodology that accounts for the spatial autocorrelation in observed cattle distribution, thereby better capturing the specific characteristics of geographically limited areas such as the Guadeloupean archipelago. Cattle census data were collected for the 32 municipalities of the archipelago and associated to environmental predictors derived from remote sensing and land cover datasets. Together with the Random Forest (RF) algorithm used in the standard GLW methodology, we tested the performance of a Geographical Random Forest (GRF), a novel methodology allowing for taking into account the spatial autocorrelation of the response variable. The GRF algorithm demonstrated significantly better performance compared to the RF algorithm, albeit with longer processing times, and allowed us producing cattle distribution maps for the entire Guadeloupe archipelago at a spatial resolution of 225 m using both algorithms. The approach developed holds potential for application to other small territories, including other islands in the Caribbean.

bioinformatics↗