Author
Listed:
- O’Neill, Xander
- White, Andy
- Gortázar, Christian
- Ruiz-Fons, Francisco
Abstract
Crimean-Congo haemorrhagic fever virus (CCHFV) is an emerging tick-borne zoonotic disease with a wide geographical distribution and high case mortality in humans. The emerging nature of the pathogen means there is limited understanding of the epidemiological drivers of infection prevalence and regional variation in the risk of pathogen spillover. In this study we develop a mathematical model of CCHFV transmission between ticks and their different hosts to understand how changes in tick birth and tick survival will interact with host density and host composition to determine the incidence of infection in ticks and their varied hosts. A key result shows that CCHFV antibody prevalence in ungulate hosts is sensitive to variation in tick demographic parameters where a 50% variation in tick birth or death rates can lead to ranges of 0–90% seroprevalence in ungulates. Therefore, environmentally derived changes in tick life history parameters could explain the variation in CCHFV transmission to ungulates observed in the Iberian Peninsula. The model indicates that CCHFV transmission is sensitive to changes in the level of vertical or co-feeding transmission and calls for further studies to determine the importance of these transmission routes. We find that the risk of pathogen spillover to human populations due to an increased density of infected questing ticks is greatest in regions where ungulate seroprevalence is high. Therefore, monitoring wildlife disease status can inform on infection risk to humans and highlights the need for one health policies to manage pathogens that can infect multiple species.
Suggested Citation
O’Neill, Xander & White, Andy & Gortázar, Christian & Ruiz-Fons, Francisco, 2025.
"Environmental driven changes in tick life history can explain the variation in CCHFV prevalence in the Iberian Peninsula,"
Ecological Modelling, Elsevier, vol. 509(C).
Handle:
RePEc:eee:ecomod:v:509:y:2025:i:c:s0304380025002534
DOI: 10.1016/j.ecolmodel.2025.111267
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