Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model
Crimean-Congo haemorrhagic fever (CCHF) virus (CCHFV) is a tick-borne zoonotic pathogen that can cause a lethal haemorrhagic disease in humans. Although the virus appears to be endemically established in the Iberian Peninsula, CCHF is an emerging disease in Spain. Clinical signs of CCHFV infection a...
| Autores: | , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/360348 |
| Acceso en línea: | http://hdl.handle.net/10261/360348 |
| Access Level: | acceso abierto |
| Palabra clave: | Hyalomma Orthonairovirus Risk map Serosurvey Tick Zoonosis |
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Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| title |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| spellingShingle |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model Baz-Flores, Sara Hyalomma Orthonairovirus Risk map Serosurvey Tick Zoonosis |
| title_short |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| title_full |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| title_fullStr |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| title_full_unstemmed |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| title_sort |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a model |
| dc.creator.none.fl_str_mv |
Baz-Flores, Sara Herraiz, Cesar Peralbo-Moreno, Alfonso Barral, Marta Arnal, Maria Cruz Balseiro, Ana Cano-Terriza, David Castro-Scholten, Sabrina Cevidanes, Aitor Conde-Lizarralde, Alazne Cuadrado-Matías, Raúl Escribano, Fernando Fernández de Luco, Daniel Fidalgo, Luis Eusebio Hermoso-de Mendoza, Javier Fandos, Paulino Gómez-Guillamón, Félix Granados, José E. Jiménez-Martín, Débora López-Olvera, Jorge R. Martín, Inés Martínez, Remigio Mentaberre, Gregorio García-Bocanegra, Ignacio Ruiz-Fons, Francisco |
| author |
Baz-Flores, Sara |
| author_facet |
Baz-Flores, Sara Herraiz, Cesar Peralbo-Moreno, Alfonso Barral, Marta Arnal, Maria Cruz Balseiro, Ana Cano-Terriza, David Castro-Scholten, Sabrina Cevidanes, Aitor Conde-Lizarralde, Alazne Cuadrado-Matías, Raúl Escribano, Fernando Fernández de Luco, Daniel Fidalgo, Luis Eusebio Hermoso-de Mendoza, Javier Fandos, Paulino Gómez-Guillamón, Félix Granados, José E. Jiménez-Martín, Débora López-Olvera, Jorge R. Martín, Inés Martínez, Remigio Mentaberre, Gregorio García-Bocanegra, Ignacio Ruiz-Fons, Francisco |
| author_role |
author |
| author2 |
Herraiz, Cesar Peralbo-Moreno, Alfonso Barral, Marta Arnal, Maria Cruz Balseiro, Ana Cano-Terriza, David Castro-Scholten, Sabrina Cevidanes, Aitor Conde-Lizarralde, Alazne Cuadrado-Matías, Raúl Escribano, Fernando Fernández de Luco, Daniel Fidalgo, Luis Eusebio Hermoso-de Mendoza, Javier Fandos, Paulino Gómez-Guillamón, Félix Granados, José E. Jiménez-Martín, Débora López-Olvera, Jorge R. Martín, Inés Martínez, Remigio Mentaberre, Gregorio García-Bocanegra, Ignacio Ruiz-Fons, Francisco |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
Junta de Comunidades de Castilla-La Mancha European Commission Ministerio de Ciencia e Innovación (España) Agencia Estatal de Investigación (España) Ministerio de Ciencia, Innovación y Universidades (España) Instituto de Salud Carlos III Universidad de Castilla La Mancha Universidad de Córdoba (España) Universidad de Extremadura Eusko Jaurlaritza Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72] |
| dc.subject.none.fl_str_mv |
Hyalomma Orthonairovirus Risk map Serosurvey Tick Zoonosis |
| topic |
Hyalomma Orthonairovirus Risk map Serosurvey Tick Zoonosis |
| description |
Crimean-Congo haemorrhagic fever (CCHF) virus (CCHFV) is a tick-borne zoonotic pathogen that can cause a lethal haemorrhagic disease in humans. Although the virus appears to be endemically established in the Iberian Peninsula, CCHF is an emerging disease in Spain. Clinical signs of CCHFV infection are mainly manifested in humans, but the virus replicates in several animal species. Understanding the determinants of CCHFV exposure risk from animal models is essential to predicting high-risk exposure hotspots for public health action. With this objective in mind, we designed a cross-sectional study of Eurasian wild boar (Sus scrofa) in Spain and Portugal. The study analysed 5,291 sera collected between 2006 and 2022 from 90 wild boar populations with a specific double-antigen ELISA to estimate CCHFV serum prevalence and identify the main determinants of exposure probability. To do so, we statistically modelled exposure risk with host- and environment-related predictors and spatially projected it at a 10 × 10 km square resolution at the scale of the Iberian Peninsula to map foci of infection risk. Fifty-seven (63.3 %) of the 90 populations had at least one seropositive animal, with seroprevalence ranging from 0.0 to 88.2 %. Anti-CCHFV antibodies were found in 1,026 of 5,291 wild boar (19.4 %; 95 % confidence interval: 18.3–20.5 %), with highest exposure rates in southwestern Iberia. The most relevant predictors of virus exposure risk were wild boar abundance, local rainfall regime, shrub cover, winter air temperature and soil temperature variation. The spatial projection of the best-fit model identified high-risk foci as occurring in most of western and southwestern Iberia and identified recently confirmed risk foci in eastern Spain. The results of the study demonstrate that serological surveys of CCHFV vector hosts are a powerful, robust and highly informative tool for public health authorities to take action to prevent human cases of CCHF in enzootic and emergency settings. |
| publishDate |
2024 |
| dc.date.none.fl_str_mv |
2024 2024 2024 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 Publisher's version info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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http://hdl.handle.net/10261/360348 |
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http://hdl.handle.net/10261/360348 |
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Inglés |
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Inglés |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Elsevier |
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Elsevier |
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reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC instname:Consejo Superior de Investigaciones Científicas (CSIC) |
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1869419822921547776 |
| spelling |
Mapping the risk of exposure to Crimean-Congo haemorrhagic fever virus in the Iberian Peninsula using Eurasian wild boar (Sus scrofa) as a modelBaz-Flores, SaraHerraiz, CesarPeralbo-Moreno, AlfonsoBarral, MartaArnal, Maria CruzBalseiro, AnaCano-Terriza, DavidCastro-Scholten, SabrinaCevidanes, AitorConde-Lizarralde, AlazneCuadrado-Matías, RaúlEscribano, FernandoFernández de Luco, DanielFidalgo, Luis EusebioHermoso-de Mendoza, JavierFandos, PaulinoGómez-Guillamón, FélixGranados, José E.Jiménez-Martín, DéboraLópez-Olvera, Jorge R.Martín, InésMartínez, RemigioMentaberre, GregorioGarcía-Bocanegra, IgnacioRuiz-Fons, FranciscoHyalommaOrthonairovirusRisk mapSerosurveyTickZoonosisCrimean-Congo haemorrhagic fever (CCHF) virus (CCHFV) is a tick-borne zoonotic pathogen that can cause a lethal haemorrhagic disease in humans. Although the virus appears to be endemically established in the Iberian Peninsula, CCHF is an emerging disease in Spain. Clinical signs of CCHFV infection are mainly manifested in humans, but the virus replicates in several animal species. Understanding the determinants of CCHFV exposure risk from animal models is essential to predicting high-risk exposure hotspots for public health action. With this objective in mind, we designed a cross-sectional study of Eurasian wild boar (Sus scrofa) in Spain and Portugal. The study analysed 5,291 sera collected between 2006 and 2022 from 90 wild boar populations with a specific double-antigen ELISA to estimate CCHFV serum prevalence and identify the main determinants of exposure probability. To do so, we statistically modelled exposure risk with host- and environment-related predictors and spatially projected it at a 10 × 10 km square resolution at the scale of the Iberian Peninsula to map foci of infection risk. Fifty-seven (63.3 %) of the 90 populations had at least one seropositive animal, with seroprevalence ranging from 0.0 to 88.2 %. Anti-CCHFV antibodies were found in 1,026 of 5,291 wild boar (19.4 %; 95 % confidence interval: 18.3–20.5 %), with highest exposure rates in southwestern Iberia. The most relevant predictors of virus exposure risk were wild boar abundance, local rainfall regime, shrub cover, winter air temperature and soil temperature variation. The spatial projection of the best-fit model identified high-risk foci as occurring in most of western and southwestern Iberia and identified recently confirmed risk foci in eastern Spain. The results of the study demonstrate that serological surveys of CCHFV vector hosts are a powerful, robust and highly informative tool for public health authorities to take action to prevent human cases of CCHF in enzootic and emergency settings.This study was funded by the regional Government of Castilla-La Mancha (JCCM) and the EU-European Social Fund (ESF) through project SBPLY/19/180501/000321 and by MCIN/AEI/10.13039/501100011033 and the European Regional Development Fund (EU-ERDF) through project CGL2017–89866-R. We also acknowledge funding by MCIN/AEI/10.13039/501100011033 and by the European Union "Next Generation EU"/PRTR Recovery, Transformation and Resilience Plan-Next Generation EU” through the TED2021–132599B-C21/22 project, by EU-ERDF (POPE 2014–2020) project LifeWATCH INDALO-Scientific Infrastructures for Global Change Monitoring and Adaptation in Andalusia (LIFEWATCH-2019–04-AMA-01) and by “Instituto de Salud Carlos III”, MCIN/AEI/10.13039/501100011033 and EU-Next Generation EU funds through “CIBER-Consorcio Centro de Investigación Biomédica en Red (CB 2021/13/00083)”. SB-F and CH acknowledge funding by JCCM and EU-ESF contracts PREJCCM2019/11 and SUPLY/19/180501/000487, respectively. AP-M was funded by the University of Castilla-La Mancha (UCLM) and EU-ERDF through 2019-PREDUCLM-10932 contract whereas RC-M received funding from MCIN, EU-ERDF and UCLM at PRE2018–083801 contract. DJ-M holds a PhD contract granted by the Own Research Plan of the University of Cordoba and SC-S is supported by an FPU grant from the Spanish Ministry of Universities (FPU19/06,026). This study has been partially funded by the Department of Economic Development and Infrastructures of the Basque Government. AC was supported by a ‘Ramón y Cajal’ post-doctoral grant RYC2021–033084-I funded by MCIN/AEI/10.13039/501,100,011,033 and by European Union NextGenerationEU/PRTR. RM is supported by a postdoctoral contract Margarita Salas Reference MS-23 (University of Extremadura) from the Program of Requalification of the Spanish University System (Spanish Ministry of Universities) financed by the European Union-NextGenerationEU.Peer reviewedElsevierJunta de Comunidades de Castilla-La ManchaEuropean CommissionMinisterio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)Ministerio de Ciencia, Innovación y Universidades (España)Instituto de Salud Carlos IIIUniversidad de Castilla La ManchaUniversidad de Córdoba (España)Universidad de ExtremaduraEusko JaurlaritzaConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202420242024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/360348reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CGL2017-89866-Rinfo:eu-repo/grantAgreement/AEI//TED2021-132599B-C21info:eu-repo/grantAgreement/AEI//TED2021-132599B-C22info:eu-repo/grantAgreement/AEI//RYC2021-033084-IThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI 10.1016/j.ttbdis.2023.102281https://doi.org/10.1016/j.ttbdis.2023.102281Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3603482026-05-22T06:33:51Z |
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15,811543 |