A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission

Autores
Alarcon, Laura Romina; la Sala, Luciano Francisco; Pérez, Alejandro; Perez, Maria Sol; Cipriotti, Pablo Ariel
Año de publicación
2024
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
African swine fever (ASF) has re-emerged in the Americas and is now of global concern as a direct threat to the swine production and health. In the USA, it was estimated that ASF would cost the swine industry between US$15 and US$50 billion in lost revenues and 140,000 jobs nationwide. Moreover, 25-55% of the pig population has been culled due to ASF in China or Vietnam. Our main objective was to simulate the potential spread dynamics of ASF in the Argentinean swine industry and identify the principal pathways for transmission.A mechanistic, spatially explicit and stochastic simulation model was built/designed based on local conditions in the study region. A daily time step and a real spatial representation of entities involved in the disease spread were used: pig farms, markets, slaughterhouses, wild boar populations, landfills, ports/airports, international waste treatment plants and livestock trucks data were provided by the National Food Service and Animal Health (SENASA) based on official information for 2019. We simulated the disease spread at two hierarchical levels: at the top level, ASF spread between farms or other spatial entities through direct pathways (movement of animals and vehicles between network nodes) and indirect pathways (contacts with wild boar, contaminated fomites, or human food waste). At the bottom level, once a pig farm was infected, a SEIR model was used to simulate ASF intra-farm dynamics. Most of the model parameters were calibrated based on field data and bibliographic sources. After parameterizing the model, a sensitivity analysis was conducted to assess the role of five transmission pathways: large or small pig farms, wild boar populations, arrival of contaminated food at landfills, and contaminated trucks. Preliminary results suggested striking differences in ASF spread depending on each of the analysed pathways. During the first 50-70 days since the initial infection events, the role of small farms, trucks and waste treatment plants increased the spread and prevalence of ASF, far outweighing the other routes of transmission. Moreover, the spatial extent of potential contacts (i.e. by sharing personnel, tools, equipment) between farms at local scale (10-35 km) and the size of small farms (10-50 sows) were key parameters controlling the dynamics. In the full model including all routes, a farm-level prevalence of 61% was reached 60 days after the initial infection, whereas a reduction in indirect contact radius of 25km reduced this prevalence to 12%. However, the mean intra-farm prevalence was 24.4% (SD=31.8%), and showed considerable spatial heterogeneity depending on the type of farm. Additionally, the prevalence of wild boars populations was ca. 2%, while the percentage of contaminate trucks was ca. 4% of the fleet. This model made it possible to weigh the role of the propagation pathways in the face of a potential ASF outbreak in the Argentine swine industry. These results could guide the decision-making process for designing appropriate surveillance measures and preventive actions at both the national network and farm level. Management focused on small pig farms, wasted treatment plants, and animal transport could help reduce the consequences of epidemic.
Fil: Alarcon, Laura Romina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias; Argentina
Fil: la Sala, Luciano Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; Argentina
Fil: Pérez, Alejandro. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
Fil: Perez, Maria Sol. Ministerio de Produccion y Trabajo. Secretaria de Gobierno de Agroindustria. Servicio Nacional de Sanidad y Calidad Agroalimentaria. Direccion Nacional de Sanidad Animal.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina
Fil: Cipriotti, Pablo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
The Allen D. Leman Swine Conference
Minnesota
Estados Unidos
University of Minnesota Extension
The University of Minnesota College of Veterinary Medicine
Materia
ASF
EPIDEMICS
PIGS
TRANSBOUNDARY DISEASES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/289861
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmissionAlarcon, Laura Rominala Sala, Luciano FranciscoPérez, AlejandroPerez, Maria SolCipriotti, Pablo ArielASFEPIDEMICSPIGSTRANSBOUNDARY DISEASEShttps://purl.org/becyt/ford/4.3https://purl.org/becyt/ford/4African swine fever (ASF) has re-emerged in the Americas and is now of global concern as a direct threat to the swine production and health. In the USA, it was estimated that ASF would cost the swine industry between US$15 and US$50 billion in lost revenues and 140,000 jobs nationwide. Moreover, 25-55% of the pig population has been culled due to ASF in China or Vietnam. Our main objective was to simulate the potential spread dynamics of ASF in the Argentinean swine industry and identify the principal pathways for transmission.A mechanistic, spatially explicit and stochastic simulation model was built/designed based on local conditions in the study region. A daily time step and a real spatial representation of entities involved in the disease spread were used: pig farms, markets, slaughterhouses, wild boar populations, landfills, ports/airports, international waste treatment plants and livestock trucks data were provided by the National Food Service and Animal Health (SENASA) based on official information for 2019. We simulated the disease spread at two hierarchical levels: at the top level, ASF spread between farms or other spatial entities through direct pathways (movement of animals and vehicles between network nodes) and indirect pathways (contacts with wild boar, contaminated fomites, or human food waste). At the bottom level, once a pig farm was infected, a SEIR model was used to simulate ASF intra-farm dynamics. Most of the model parameters were calibrated based on field data and bibliographic sources. After parameterizing the model, a sensitivity analysis was conducted to assess the role of five transmission pathways: large or small pig farms, wild boar populations, arrival of contaminated food at landfills, and contaminated trucks. Preliminary results suggested striking differences in ASF spread depending on each of the analysed pathways. During the first 50-70 days since the initial infection events, the role of small farms, trucks and waste treatment plants increased the spread and prevalence of ASF, far outweighing the other routes of transmission. Moreover, the spatial extent of potential contacts (i.e. by sharing personnel, tools, equipment) between farms at local scale (10-35 km) and the size of small farms (10-50 sows) were key parameters controlling the dynamics. In the full model including all routes, a farm-level prevalence of 61% was reached 60 days after the initial infection, whereas a reduction in indirect contact radius of 25km reduced this prevalence to 12%. However, the mean intra-farm prevalence was 24.4% (SD=31.8%), and showed considerable spatial heterogeneity depending on the type of farm. Additionally, the prevalence of wild boars populations was ca. 2%, while the percentage of contaminate trucks was ca. 4% of the fleet. This model made it possible to weigh the role of the propagation pathways in the face of a potential ASF outbreak in the Argentine swine industry. These results could guide the decision-making process for designing appropriate surveillance measures and preventive actions at both the national network and farm level. Management focused on small pig farms, wasted treatment plants, and animal transport could help reduce the consequences of epidemic.Fil: Alarcon, Laura Romina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias; ArgentinaFil: la Sala, Luciano Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; ArgentinaFil: Pérez, Alejandro. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Perez, Maria Sol. Ministerio de Produccion y Trabajo. Secretaria de Gobierno de Agroindustria. Servicio Nacional de Sanidad y Calidad Agroalimentaria. Direccion Nacional de Sanidad Animal.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; ArgentinaFil: Cipriotti, Pablo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaThe Allen D. Leman Swine ConferenceMinnesotaEstados UnidosUniversity of Minnesota ExtensionThe University of Minnesota College of Veterinary MedicineUniversity of Minnesota2024info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectConferenciaBookhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/289861A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission; The Allen D. Leman Swine Conference; Minnesota; Estados Unidos; 2024; 1-1CONICET DigitalCONICETenghttps://sites.google.com/a/umn.edu/leman-swine-conference/home/2024info:eu-repo/semantics/altIdentifier/url/https://lemanconference.umn.edu/2024-conference-programinfo:eu-repo/semantics/altIdentifier/url/https://sites.google.com/a/umn.edu/leman-swine-conference/home/2024Nacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T14:42:46Zoai:ri.conicet.gov.ar:11336/289861instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 14:42:47.191CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
title A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
spellingShingle A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
Alarcon, Laura Romina
ASF
EPIDEMICS
PIGS
TRANSBOUNDARY DISEASES
title_short A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
title_full A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
title_fullStr A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
title_full_unstemmed A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
title_sort A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission
dc.creator.none.fl_str_mv Alarcon, Laura Romina
la Sala, Luciano Francisco
Pérez, Alejandro
Perez, Maria Sol
Cipriotti, Pablo Ariel
author Alarcon, Laura Romina
author_facet Alarcon, Laura Romina
la Sala, Luciano Francisco
Pérez, Alejandro
Perez, Maria Sol
Cipriotti, Pablo Ariel
author_role author
author2 la Sala, Luciano Francisco
Pérez, Alejandro
Perez, Maria Sol
Cipriotti, Pablo Ariel
author2_role author
author
author
author
dc.subject.none.fl_str_mv ASF
EPIDEMICS
PIGS
TRANSBOUNDARY DISEASES
topic ASF
EPIDEMICS
PIGS
TRANSBOUNDARY DISEASES
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.3
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv African swine fever (ASF) has re-emerged in the Americas and is now of global concern as a direct threat to the swine production and health. In the USA, it was estimated that ASF would cost the swine industry between US$15 and US$50 billion in lost revenues and 140,000 jobs nationwide. Moreover, 25-55% of the pig population has been culled due to ASF in China or Vietnam. Our main objective was to simulate the potential spread dynamics of ASF in the Argentinean swine industry and identify the principal pathways for transmission.A mechanistic, spatially explicit and stochastic simulation model was built/designed based on local conditions in the study region. A daily time step and a real spatial representation of entities involved in the disease spread were used: pig farms, markets, slaughterhouses, wild boar populations, landfills, ports/airports, international waste treatment plants and livestock trucks data were provided by the National Food Service and Animal Health (SENASA) based on official information for 2019. We simulated the disease spread at two hierarchical levels: at the top level, ASF spread between farms or other spatial entities through direct pathways (movement of animals and vehicles between network nodes) and indirect pathways (contacts with wild boar, contaminated fomites, or human food waste). At the bottom level, once a pig farm was infected, a SEIR model was used to simulate ASF intra-farm dynamics. Most of the model parameters were calibrated based on field data and bibliographic sources. After parameterizing the model, a sensitivity analysis was conducted to assess the role of five transmission pathways: large or small pig farms, wild boar populations, arrival of contaminated food at landfills, and contaminated trucks. Preliminary results suggested striking differences in ASF spread depending on each of the analysed pathways. During the first 50-70 days since the initial infection events, the role of small farms, trucks and waste treatment plants increased the spread and prevalence of ASF, far outweighing the other routes of transmission. Moreover, the spatial extent of potential contacts (i.e. by sharing personnel, tools, equipment) between farms at local scale (10-35 km) and the size of small farms (10-50 sows) were key parameters controlling the dynamics. In the full model including all routes, a farm-level prevalence of 61% was reached 60 days after the initial infection, whereas a reduction in indirect contact radius of 25km reduced this prevalence to 12%. However, the mean intra-farm prevalence was 24.4% (SD=31.8%), and showed considerable spatial heterogeneity depending on the type of farm. Additionally, the prevalence of wild boars populations was ca. 2%, while the percentage of contaminate trucks was ca. 4% of the fleet. This model made it possible to weigh the role of the propagation pathways in the face of a potential ASF outbreak in the Argentine swine industry. These results could guide the decision-making process for designing appropriate surveillance measures and preventive actions at both the national network and farm level. Management focused on small pig farms, wasted treatment plants, and animal transport could help reduce the consequences of epidemic.
Fil: Alarcon, Laura Romina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias; Argentina
Fil: la Sala, Luciano Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; Argentina
Fil: Pérez, Alejandro. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
Fil: Perez, Maria Sol. Ministerio de Produccion y Trabajo. Secretaria de Gobierno de Agroindustria. Servicio Nacional de Sanidad y Calidad Agroalimentaria. Direccion Nacional de Sanidad Animal.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina
Fil: Cipriotti, Pablo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
The Allen D. Leman Swine Conference
Minnesota
Estados Unidos
University of Minnesota Extension
The University of Minnesota College of Veterinary Medicine
description African swine fever (ASF) has re-emerged in the Americas and is now of global concern as a direct threat to the swine production and health. In the USA, it was estimated that ASF would cost the swine industry between US$15 and US$50 billion in lost revenues and 140,000 jobs nationwide. Moreover, 25-55% of the pig population has been culled due to ASF in China or Vietnam. Our main objective was to simulate the potential spread dynamics of ASF in the Argentinean swine industry and identify the principal pathways for transmission.A mechanistic, spatially explicit and stochastic simulation model was built/designed based on local conditions in the study region. A daily time step and a real spatial representation of entities involved in the disease spread were used: pig farms, markets, slaughterhouses, wild boar populations, landfills, ports/airports, international waste treatment plants and livestock trucks data were provided by the National Food Service and Animal Health (SENASA) based on official information for 2019. We simulated the disease spread at two hierarchical levels: at the top level, ASF spread between farms or other spatial entities through direct pathways (movement of animals and vehicles between network nodes) and indirect pathways (contacts with wild boar, contaminated fomites, or human food waste). At the bottom level, once a pig farm was infected, a SEIR model was used to simulate ASF intra-farm dynamics. Most of the model parameters were calibrated based on field data and bibliographic sources. After parameterizing the model, a sensitivity analysis was conducted to assess the role of five transmission pathways: large or small pig farms, wild boar populations, arrival of contaminated food at landfills, and contaminated trucks. Preliminary results suggested striking differences in ASF spread depending on each of the analysed pathways. During the first 50-70 days since the initial infection events, the role of small farms, trucks and waste treatment plants increased the spread and prevalence of ASF, far outweighing the other routes of transmission. Moreover, the spatial extent of potential contacts (i.e. by sharing personnel, tools, equipment) between farms at local scale (10-35 km) and the size of small farms (10-50 sows) were key parameters controlling the dynamics. In the full model including all routes, a farm-level prevalence of 61% was reached 60 days after the initial infection, whereas a reduction in indirect contact radius of 25km reduced this prevalence to 12%. However, the mean intra-farm prevalence was 24.4% (SD=31.8%), and showed considerable spatial heterogeneity depending on the type of farm. Additionally, the prevalence of wild boars populations was ca. 2%, while the percentage of contaminate trucks was ca. 4% of the fleet. This model made it possible to weigh the role of the propagation pathways in the face of a potential ASF outbreak in the Argentine swine industry. These results could guide the decision-making process for designing appropriate surveillance measures and preventive actions at both the national network and farm level. Management focused on small pig farms, wasted treatment plants, and animal transport could help reduce the consequences of epidemic.
publishDate 2024
dc.date.none.fl_str_mv 2024
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info:eu-repo/semantics/conferenceObject
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/289861
A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission; The Allen D. Leman Swine Conference; Minnesota; Estados Unidos; 2024; 1-1
CONICET Digital
CONICET
url http://hdl.handle.net/11336/289861
identifier_str_mv A stochastic model for the spread dynamics of African swine fever in the Argentinean swine industry: The importance of indirect pathways for transmission; The Allen D. Leman Swine Conference; Minnesota; Estados Unidos; 2024; 1-1
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/url/https://sites.google.com/a/umn.edu/leman-swine-conference/home/2024
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dc.publisher.none.fl_str_mv University of Minnesota
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