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<p>Heartwater is a tick-borne disease affecting livestock in Africa and the Caribbean, including Guadeloupe, where it threatens animal health and productivity. While <i>Amblyomma variegatum</i> has long been recognized as the primary vector, recent studies suggest <i>Rhipicephalus microplus</i> may also transmit <i>Ehrlichia ruminantium</i>, the causative agent. This study presents a spatial modelling framework to assess heartwater risk across Guadeloupe. Tick presence data collected during livestock inspections were combined with environmental variables derived from satellite imagery and other geospatial sources. Ecological Niche Factor Analysis identified key environmental predictors, which were then used to build MaxEnt models and generate suitability maps for both tick species. These maps revealed distinct ecological preferences and were integrated with cattle density data using a Multi-Criteria Decision Analysis approach, with expert-derived weighting, to produce a composite risk index. The resulting maps provide the first spatially explicit assessment of heartwater risk in Guadeloupe. This approach offers a reproducible method for mapping tick-borne disease risk in data-limited tropical regions and can guide targeted surveillance and control strategies.</p>

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Mapping heartwater risk in Guadeloupe using a combination of spatial modelling approaches

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月1日

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  • Victor Dufleit,
  • Eric Etter,
  • Laure Guerrini

摘要

Heartwater is a tick-borne disease affecting livestock in Africa and the Caribbean, including Guadeloupe, where it threatens animal health and productivity. While Amblyomma variegatum has long been recognized as the primary vector, recent studies suggest Rhipicephalus microplus may also transmit Ehrlichia ruminantium, the causative agent. This study presents a spatial modelling framework to assess heartwater risk across Guadeloupe. Tick presence data collected during livestock inspections were combined with environmental variables derived from satellite imagery and other geospatial sources. Ecological Niche Factor Analysis identified key environmental predictors, which were then used to build MaxEnt models and generate suitability maps for both tick species. These maps revealed distinct ecological preferences and were integrated with cattle density data using a Multi-Criteria Decision Analysis approach, with expert-derived weighting, to produce a composite risk index. The resulting maps provide the first spatially explicit assessment of heartwater risk in Guadeloupe. This approach offers a reproducible method for mapping tick-borne disease risk in data-limited tropical regions and can guide targeted surveillance and control strategies.