Pig herd management and infection transmission dynamics: a challenge for modellers

The control of epidemics requires a thorough understanding of the complex interactions between pathogen transmission, disease impact, and population dynamics and management. Mechanistic epidemiological modelling is an effective way to address this issue, but handling highly structured and dynamic sy...

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Main Authors: Sicard, Vianney, Picault, Sébastien, Andraud, Mathieu
Format: Article
Language:English
Published: Peer Community In 2024-05-01
Series:Peer Community Journal
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Online Access:https://peercommunityjournal.org/articles/10.24072/pcjournal.403/
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author Sicard, Vianney
Picault, Sébastien
Andraud, Mathieu
author_facet Sicard, Vianney
Picault, Sébastien
Andraud, Mathieu
author_sort Sicard, Vianney
collection DOAJ
description The control of epidemics requires a thorough understanding of the complex interactions between pathogen transmission, disease impact, and population dynamics and management. Mechanistic epidemiological modelling is an effective way to address this issue, but handling highly structured and dynamic systems, remains challenging. We therefore developed a novel approach that combines Multi-Level Agent-Based Systems (MLABS) with spatial and temporal organization, allowing for a tuned representation of the transmission processes amongst the host population. We applied this method to model the spread of a PRRSv-like virus in pig farms, integrating the clinical consequences (conception and reproduction failures), in terms of animal husbandry practices. Results highlighted the importance to account for spatial and temporal structuring and herd management policies in epidemiological models. Indeed, disease-related abortions, inducing reassignments of sows in different batches, was shown to enhance the transmission process, favouring the persistence of the virus at the herd level. Supported by a declarative Domain-Specific Language (DSL), our approach provides flexible and powerful solutions to address the issues of on-farm epidemics and broader public health concerns. The present application, based on a simple Susceptible-Exposed-Infected-Recovered (SEIR) model, opens the way to the representation of more complex epidemiological systems, including more specific features such as maternally derived antibodies, vaccination, or dual infections, along with their respective clinical consequences on the management practices.
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institution Kabale University
issn 2804-3871
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publishDate 2024-05-01
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series Peer Community Journal
spelling doaj-art-ec4313c6a4b6471e82c6a404621477e42025-02-07T10:17:18ZengPeer Community InPeer Community Journal2804-38712024-05-01410.24072/pcjournal.40310.24072/pcjournal.403Pig herd management and infection transmission dynamics: a challenge for modellers Sicard, Vianney0https://orcid.org/0000-0002-4909-5544Picault, Sébastien1https://orcid.org/0000-0001-9029-0555Andraud, Mathieu2https://orcid.org/0000-0003-2891-2901Oniris, INRAE, BIOEPAR, 44300, Nantes, FranceOniris, INRAE, BIOEPAR, 44300, Nantes, FranceAnses, Ploufragan-Plouzané-Niort Laboratory, EPISABE Unit, Ploufragan, FranceThe control of epidemics requires a thorough understanding of the complex interactions between pathogen transmission, disease impact, and population dynamics and management. Mechanistic epidemiological modelling is an effective way to address this issue, but handling highly structured and dynamic systems, remains challenging. We therefore developed a novel approach that combines Multi-Level Agent-Based Systems (MLABS) with spatial and temporal organization, allowing for a tuned representation of the transmission processes amongst the host population. We applied this method to model the spread of a PRRSv-like virus in pig farms, integrating the clinical consequences (conception and reproduction failures), in terms of animal husbandry practices. Results highlighted the importance to account for spatial and temporal structuring and herd management policies in epidemiological models. Indeed, disease-related abortions, inducing reassignments of sows in different batches, was shown to enhance the transmission process, favouring the persistence of the virus at the herd level. Supported by a declarative Domain-Specific Language (DSL), our approach provides flexible and powerful solutions to address the issues of on-farm epidemics and broader public health concerns. The present application, based on a simple Susceptible-Exposed-Infected-Recovered (SEIR) model, opens the way to the representation of more complex epidemiological systems, including more specific features such as maternally derived antibodies, vaccination, or dual infections, along with their respective clinical consequences on the management practices.https://peercommunityjournal.org/articles/10.24072/pcjournal.403/Epidemiological Modelling; Agent-based Simulation; Animal diseases; swine influenza virus; modelling language; herd management
spellingShingle Sicard, Vianney
Picault, Sébastien
Andraud, Mathieu
Pig herd management and infection transmission dynamics: a challenge for modellers
Peer Community Journal
Epidemiological Modelling; Agent-based Simulation; Animal diseases; swine influenza virus; modelling language; herd management
title Pig herd management and infection transmission dynamics: a challenge for modellers
title_full Pig herd management and infection transmission dynamics: a challenge for modellers
title_fullStr Pig herd management and infection transmission dynamics: a challenge for modellers
title_full_unstemmed Pig herd management and infection transmission dynamics: a challenge for modellers
title_short Pig herd management and infection transmission dynamics: a challenge for modellers
title_sort pig herd management and infection transmission dynamics a challenge for modellers
topic Epidemiological Modelling; Agent-based Simulation; Animal diseases; swine influenza virus; modelling language; herd management
url https://peercommunityjournal.org/articles/10.24072/pcjournal.403/
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