Crimean–Congo Haemorrhagic Fever Virus Circulates within Broad Ecological Networks of Ticks and Vertebrates

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 on 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 dimensionality. Chorotypes, representing clusters of co-occurring hosts, enhanced model performance and improved the delineation of both the northern 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 abiotic and biotic 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.

Author Summary

Crimean–Congo haemorrhagic fever virus (CCHFV) is a tick-borne pathogen causing severe disease in humans across Africa, Asia and Europe. Understanding where the virus may circulate is crucial for anticipating outbreaks and guiding surveillance. Previous studies have mostly relied on climate-based models, assuming that temperature and humidity determine where infected ticks can prevail. However, such models often overestimate risk, predicting virus presence in regions where no cases or vectors exist.

In this study, we combined climatic data with ecological information on ticks, livestock, and wildlife to create a more realistic prediction of CCHFV distribution. By incorporating host–vector interactions and vertebrate communities, our models accurately captured most known occurrences and revealed the ecological patterns underlying virus transmission. Our results suggest that CCHFV persists within broad networks of tick and vertebrate species rather than a single vector. This integrated approach offers a powerful framework to identify emerging risk areas and forms a good starting point to further improve our understanding of the ecological drivers of tickborne viral diseases.