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Crimean-congo haemorrhagic fever virus circulates within broad ecological networks of ticks and vertebrates

  • Agustín Estrada-Peña*
  • , Oliver Carnell
  • , Sara R. Wijburg
  • , Maya Holding
  • , Hein Sprong
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

We produced spatial datasets of the known distribution of Orthonairovirus haemorrhagiae (formerly Crimean-Congo haemorrhagic fever virus, CCHFV) by compiling human cases, virus isolations, and serological data from humans and animals, spanning from Europe to southern Africa, with the aim of virus range modelling. Models based solely on climatic variables produced unrealistic and overly extensive predictions, overestimating suitability in northern Europe and confirming that climate alone poorly explains CCHFV range. Approaches using only tick species distributions underperformed in many parts of Africa, reflecting the complexity of vector-host interactions and the absence of a strict tick-virus association. The integration of human-biting tick distributions, livestock density, and chorotypes yielded the most robust results, accurately capturing over 90% of known occurrences, by identifying vertebrate assemblages most likely to amplify the virus while reducing the number of explanatory variables. Chorotypes, representing clusters of co-occurring hosts, enhanced model performance and improved the delineation of both the Palearctic and African ranges limits of the virus. Our results support a generalist epidemiological model in which multiple tick species, together with a broad range of vertebrate hosts, sustain CCHFV circulation. This ecological flexibility, rather than strict vector specificity, likely explains the CCHFV wide biogeographical range and occasional lineage expansions across continents. This study provides the most comprehensive assessment to date of the determinants of the distribution of CCHFV. Although gaps remain, this study demonstrates that coupling abiotic and biotic predictors provides a more accurate and ecologically meaningful understanding of CCHFV distribution.

Original languageEnglish
Pages (from-to)e0013783
JournalPLoS Neglected Tropical Diseases
Volume20
Issue number5
DOIs
Publication statusPublished - 1 May 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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