Host availability modifies climate-based predictions of Hyalomma rufipes distribution with geographically variable effects of livestock mobility.
7 affiliations
- 1International Centre of Insect Physiology and Ecology (icipe), PO Box 30772, Nairobi, 00100, Kenya.
- 2Laboratoire de Recherche en Science et Technologie (LARSI), Département de Génie Informatique (GI), École Polytechnique de Lomé (EPL), Université de Lomé, Lomé, Togo.
- 3Department of Zoology and Entomology, University of Pretoria, Private Bag X20, Hatfield, 0028, South Africa.
- 4Department of Medical Entomology, Faculty of Public & Environmental Health, University of Kordofan, Sudan.
- 5School of Agriculture and Science, University of KwaZulu-Natal, Pietermaritzburg, 3209, South Africa.
- 6CIRAD, UMR INTERTRYP, Nairobi, Kenya.
- 7INTERTRYP, Univ Montpellier, Cirad, IRD, Montpellier, France.
Abstract
Hyalomma rufipes is an important African tick vector whose distribution is strongly influenced by climate, but host availability and host-mediated dispersal may modify the spatial expression of climatic suitability. We evaluated these contributions using 1410 unique African occurrence localities and three nested species distribution models: climate only (M1), climate plus host availability (M2), and climate plus host availability and livestock-mobility conductance (M3). Ensemble models were evaluated using 300-km spatial block cross-validation and leave-East-Africa-out geographical transfer, with alternative background designs assessed as a sensitivity analysis. Under spatial validation, M1 showed the highest discrimination (AUC = 0.979; TSS = 0.859), followed by M2 (AUC = 0.975; TSS = 0.833) and M3 (AUC = 0.951; TSS = 0.802). Geographical transferability was substantially weaker, although M3 showed the highest relative transfer AUC (0.659) and the only positive, albeit near-zero, TSS (0.021). Controlled common-sample comparisons showed that host availability substantially modified climate-derived suitability, while livestock mobility produced an additional geographically variable effect, particularly in Kenya. Results were stable across conductance uncertainty scenarios. Overall, climate provided the strongest broad-scale predictive signal, whereas host availability and livestock mobility modified the geography of predicted suitability without improving conventional discrimination metrics. These findings highlight the complementary value of ecological information for interpreting distributions of host-dependent vectors beyond predictive performance alone.
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BibTeX
@article{agboka2026host,
title = {{Host availability modifies climate-based predictions of Hyalomma rufipes distribution with geographically variable effects of livestock mobility.}},
author = {Komi Mensah Agboka and Simon Mumo and Quinto Juma Meltus and Steve B S Baleba and Iman Brema Hassaballa and Tobias Landmann and Elfatih M Abdel-Rahman and Antoine Barreaux and Souleymane Diallo},
journal = {Current research in parasitology \& vector-borne diseases},
year = {2026},
month = oct,
doi = {10.1016/j.crpvbd.2026.100444},
url = {https://europepmc.org/article/MED/42926892},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Host availability modifies climate-based predictions of Hyalomma rufipes distribution with geographically variable effects of livestock mobility.
AU - Komi Mensah Agboka
AU - Simon Mumo
AU - Quinto Juma Meltus
AU - Steve B S Baleba
AU - Iman Brema Hassaballa
AU - Tobias Landmann
AU - Elfatih M Abdel-Rahman
AU - Antoine Barreaux
AU - Souleymane Diallo
PY - 2026
DA - 2026/10/06
JO - Current research in parasitology & vector-borne diseases
DO - 10.1016/j.crpvbd.2026.100444
UR - https://europepmc.org/article/MED/42926892
AB - Hyalomma rufipes is an important African tick vector whose distribution is strongly influenced by climate, but host availability and host-mediated dispersal may modify the spatial expression of climatic suitability. We evaluated these contributions using 1410 unique African occurrence localities and three nested species distribution models: climate only (M1), climate plus host availability (M2), and climate plus host availability and livestock-mobility conductance (M3). Ensemble models were evaluated using 300-km spatial block cross-validation and leave-East-Africa-out geographical transfer, with alternative background designs assessed as a sensitivity analysis. Under spatial validation, M1 showed the highest discrimination (AUC = 0.979; TSS = 0.859), followed by M2 (AUC = 0.975; TSS = 0.833) and M3 (AUC = 0.951; TSS = 0.802). Geographical transferability was substantially weaker, although M3 showed the highest relative transfer AUC (0.659) and the only positive, albeit near-zero, TSS (0.021). Controlled common-sample comparisons showed that host availability substantially modified climate-derived suitability, while livestock mobility produced an additional geographically variable effect, particularly in Kenya. Results were stable across conductance uncertainty scenarios. Overall, climate provided the strongest broad-scale predictive signal, whereas host availability and livestock mobility modified the geography of predicted suitability without improving conventional discrimination metrics. These findings highlight the complementary value of ecological information for interpreting distributions of host-dependent vectors beyond predictive performance alone.
SN - 2667-114X
ER -