Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus
Background: Peste des petits ruminants (PPR) is an acute infectious viral disease affecting domestic small ruminants (sheep and goats) and some wild ruminant species in Africa, the Middle East and Asia. A global PPR control strategy based on mass vaccination—in regions where PPR is endemic—was recently designed and launched by international organizations. Sahelian Africa is one of the most challenging endemic regions for PPR control. Indeed, strong seasonal and annual variations in mating, mortality and offtake rates result in a complex population dynamics which might in turn alter the population post-vaccination immunity rate (PIR), and thus be important to consider for the implementation of vaccination campaigns. Methods: In a context of preventive vaccination in epidemiological units without PPR virus transmission, we developed a predictive, dynamic model based on a seasonal matrix population model to simulate PIR dynamics. This model was mostly calibrated with demographic and epidemiological parameters estimated from a long-term follow-up survey of small ruminant herds. We used it to simulate the PIR dynamics following a single PPR vaccination campaign in a Sahelian sheep population, and to assess the effects of (i) changes in off take rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns. Results: The persistence of PIR was not influenced by the Tabaski date. Decreasing the vaccination coverage from 100 to 80% had limited effects on PIR. However, lower vaccination coverage did not provide sufficient immunity rates (PIR < 70%). As a trade-off between model predictions and other considerations like animal physiological status, and suitability for livestock farmers, we would suggest to implement vaccination campaigns in September-October. This model is a first step towards better decision support for animal health authorities. It might be adapted to other species, livestock farming systems or diseases.
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Biblioteca del CIRAD Francia |
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L73 - Maladies des animaux U10 - Informatique, mathématiques et statistiques peste des petits ruminants virus peste petits ruminants vaccin modèle de simulation ovin dynamique des populations immunologie immunité anticorps évaluation de l'impact choix de la date variation saisonnière environnement socioculturel système d'aide à la décision modèle mathématique http://aims.fao.org/aos/agrovoc/c_16789 http://aims.fao.org/aos/agrovoc/c_16581 http://aims.fao.org/aos/agrovoc/c_8130 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_7030 http://aims.fao.org/aos/agrovoc/c_6111 http://aims.fao.org/aos/agrovoc/c_3808 http://aims.fao.org/aos/agrovoc/c_3802 http://aims.fao.org/aos/agrovoc/c_493 http://aims.fao.org/aos/agrovoc/c_37938 http://aims.fao.org/aos/agrovoc/c_7779 http://aims.fao.org/aos/agrovoc/c_24894 http://aims.fao.org/aos/agrovoc/c_24950 http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_6970 L73 - Maladies des animaux U10 - Informatique, mathématiques et statistiques peste des petits ruminants virus peste petits ruminants vaccin modèle de simulation ovin dynamique des populations immunologie immunité anticorps évaluation de l'impact choix de la date variation saisonnière environnement socioculturel système d'aide à la décision modèle mathématique http://aims.fao.org/aos/agrovoc/c_16789 http://aims.fao.org/aos/agrovoc/c_16581 http://aims.fao.org/aos/agrovoc/c_8130 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_7030 http://aims.fao.org/aos/agrovoc/c_6111 http://aims.fao.org/aos/agrovoc/c_3808 http://aims.fao.org/aos/agrovoc/c_3802 http://aims.fao.org/aos/agrovoc/c_493 http://aims.fao.org/aos/agrovoc/c_37938 http://aims.fao.org/aos/agrovoc/c_7779 http://aims.fao.org/aos/agrovoc/c_24894 http://aims.fao.org/aos/agrovoc/c_24950 http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_6970 |
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L73 - Maladies des animaux U10 - Informatique, mathématiques et statistiques peste des petits ruminants virus peste petits ruminants vaccin modèle de simulation ovin dynamique des populations immunologie immunité anticorps évaluation de l'impact choix de la date variation saisonnière environnement socioculturel système d'aide à la décision modèle mathématique http://aims.fao.org/aos/agrovoc/c_16789 http://aims.fao.org/aos/agrovoc/c_16581 http://aims.fao.org/aos/agrovoc/c_8130 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_7030 http://aims.fao.org/aos/agrovoc/c_6111 http://aims.fao.org/aos/agrovoc/c_3808 http://aims.fao.org/aos/agrovoc/c_3802 http://aims.fao.org/aos/agrovoc/c_493 http://aims.fao.org/aos/agrovoc/c_37938 http://aims.fao.org/aos/agrovoc/c_7779 http://aims.fao.org/aos/agrovoc/c_24894 http://aims.fao.org/aos/agrovoc/c_24950 http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_6970 L73 - Maladies des animaux U10 - Informatique, mathématiques et statistiques peste des petits ruminants virus peste petits ruminants vaccin modèle de simulation ovin dynamique des populations immunologie immunité anticorps évaluation de l'impact choix de la date variation saisonnière environnement socioculturel système d'aide à la décision modèle mathématique http://aims.fao.org/aos/agrovoc/c_16789 http://aims.fao.org/aos/agrovoc/c_16581 http://aims.fao.org/aos/agrovoc/c_8130 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_7030 http://aims.fao.org/aos/agrovoc/c_6111 http://aims.fao.org/aos/agrovoc/c_3808 http://aims.fao.org/aos/agrovoc/c_3802 http://aims.fao.org/aos/agrovoc/c_493 http://aims.fao.org/aos/agrovoc/c_37938 http://aims.fao.org/aos/agrovoc/c_7779 http://aims.fao.org/aos/agrovoc/c_24894 http://aims.fao.org/aos/agrovoc/c_24950 http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_6970 Hammami, Pachka Lancelot, Renaud Lesnoff, Matthieu Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus |
description |
Background: Peste des petits ruminants (PPR) is an acute infectious viral disease affecting domestic small ruminants (sheep and goats) and some wild ruminant species in Africa, the Middle East and Asia. A global PPR control strategy based on mass vaccination—in regions where PPR is endemic—was recently designed and launched by international organizations. Sahelian Africa is one of the most challenging endemic regions for PPR control. Indeed, strong seasonal and annual variations in mating, mortality and offtake rates result in a complex population dynamics which might in turn alter the population post-vaccination immunity rate (PIR), and thus be important to consider for the implementation of vaccination campaigns. Methods: In a context of preventive vaccination in epidemiological units without PPR virus transmission, we developed a predictive, dynamic model based on a seasonal matrix population model to simulate PIR dynamics. This model was mostly calibrated with demographic and epidemiological parameters estimated from a long-term follow-up survey of small ruminant herds. We used it to simulate the PIR dynamics following a single PPR vaccination campaign in a Sahelian sheep population, and to assess the effects of (i) changes in off take rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns. Results: The persistence of PIR was not influenced by the Tabaski date. Decreasing the vaccination coverage from 100 to 80% had limited effects on PIR. However, lower vaccination coverage did not provide sufficient immunity rates (PIR < 70%). As a trade-off between model predictions and other considerations like animal physiological status, and suitability for livestock farmers, we would suggest to implement vaccination campaigns in September-October. This model is a first step towards better decision support for animal health authorities. It might be adapted to other species, livestock farming systems or diseases. |
format |
article |
topic_facet |
L73 - Maladies des animaux U10 - Informatique, mathématiques et statistiques peste des petits ruminants virus peste petits ruminants vaccin modèle de simulation ovin dynamique des populations immunologie immunité anticorps évaluation de l'impact choix de la date variation saisonnière environnement socioculturel système d'aide à la décision modèle mathématique http://aims.fao.org/aos/agrovoc/c_16789 http://aims.fao.org/aos/agrovoc/c_16581 http://aims.fao.org/aos/agrovoc/c_8130 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_7030 http://aims.fao.org/aos/agrovoc/c_6111 http://aims.fao.org/aos/agrovoc/c_3808 http://aims.fao.org/aos/agrovoc/c_3802 http://aims.fao.org/aos/agrovoc/c_493 http://aims.fao.org/aos/agrovoc/c_37938 http://aims.fao.org/aos/agrovoc/c_7779 http://aims.fao.org/aos/agrovoc/c_24894 http://aims.fao.org/aos/agrovoc/c_24950 http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_6970 |
author |
Hammami, Pachka Lancelot, Renaud Lesnoff, Matthieu |
author_facet |
Hammami, Pachka Lancelot, Renaud Lesnoff, Matthieu |
author_sort |
Hammami, Pachka |
title |
Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus |
title_short |
Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus |
title_full |
Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus |
title_fullStr |
Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus |
title_full_unstemmed |
Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus |
title_sort |
modelling the dynamics of post-vaccination immunity rate in a population of sahelian sheep after a vaccination campaign against peste des petits ruminants virus |
url |
http://agritrop.cirad.fr/581619/ http://agritrop.cirad.fr/581619/1/Hammami%20et%20al%20-%202016%20-%20Modelling%20the%20Dynamics%20of%20Post%20Vaccination%20Immunity%20Rate.pdf |
work_keys_str_mv |
AT hammamipachka modellingthedynamicsofpostvaccinationimmunityrateinapopulationofsaheliansheepafteravaccinationcampaignagainstpestedespetitsruminantsvirus AT lancelotrenaud modellingthedynamicsofpostvaccinationimmunityrateinapopulationofsaheliansheepafteravaccinationcampaignagainstpestedespetitsruminantsvirus AT lesnoffmatthieu modellingthedynamicsofpostvaccinationimmunityrateinapopulationofsaheliansheepafteravaccinationcampaignagainstpestedespetitsruminantsvirus |
_version_ |
1792499110548340736 |
spelling |
dig-cirad-fr-5816192024-01-28T23:41:24Z http://agritrop.cirad.fr/581619/ http://agritrop.cirad.fr/581619/ Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus. Hammami Pachka, Lancelot Renaud, Lesnoff Matthieu. 2016. PloS One, 11 (9):e0161769, 24 p.https://doi.org/10.1371/journal.pone.0161769 <https://doi.org/10.1371/journal.pone.0161769> Modelling the dynamics of post-vaccination immunity rate in a population of Sahelian sheep after a vaccination campaign against Peste des petits ruminants virus Hammami, Pachka Lancelot, Renaud Lesnoff, Matthieu eng 2016 PloS One L73 - Maladies des animaux U10 - Informatique, mathématiques et statistiques peste des petits ruminants virus peste petits ruminants vaccin modèle de simulation ovin dynamique des populations immunologie immunité anticorps évaluation de l'impact choix de la date variation saisonnière environnement socioculturel système d'aide à la décision modèle mathématique http://aims.fao.org/aos/agrovoc/c_16789 http://aims.fao.org/aos/agrovoc/c_16581 http://aims.fao.org/aos/agrovoc/c_8130 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_7030 http://aims.fao.org/aos/agrovoc/c_6111 http://aims.fao.org/aos/agrovoc/c_3808 http://aims.fao.org/aos/agrovoc/c_3802 http://aims.fao.org/aos/agrovoc/c_493 http://aims.fao.org/aos/agrovoc/c_37938 http://aims.fao.org/aos/agrovoc/c_7779 http://aims.fao.org/aos/agrovoc/c_24894 http://aims.fao.org/aos/agrovoc/c_24950 http://aims.fao.org/aos/agrovoc/c_49868 http://aims.fao.org/aos/agrovoc/c_24199 Sahel Sénégal http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_6970 Background: Peste des petits ruminants (PPR) is an acute infectious viral disease affecting domestic small ruminants (sheep and goats) and some wild ruminant species in Africa, the Middle East and Asia. A global PPR control strategy based on mass vaccination—in regions where PPR is endemic—was recently designed and launched by international organizations. Sahelian Africa is one of the most challenging endemic regions for PPR control. Indeed, strong seasonal and annual variations in mating, mortality and offtake rates result in a complex population dynamics which might in turn alter the population post-vaccination immunity rate (PIR), and thus be important to consider for the implementation of vaccination campaigns. Methods: In a context of preventive vaccination in epidemiological units without PPR virus transmission, we developed a predictive, dynamic model based on a seasonal matrix population model to simulate PIR dynamics. This model was mostly calibrated with demographic and epidemiological parameters estimated from a long-term follow-up survey of small ruminant herds. We used it to simulate the PIR dynamics following a single PPR vaccination campaign in a Sahelian sheep population, and to assess the effects of (i) changes in off take rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns. Results: The persistence of PIR was not influenced by the Tabaski date. Decreasing the vaccination coverage from 100 to 80% had limited effects on PIR. However, lower vaccination coverage did not provide sufficient immunity rates (PIR < 70%). As a trade-off between model predictions and other considerations like animal physiological status, and suitability for livestock farmers, we would suggest to implement vaccination campaigns in September-October. This model is a first step towards better decision support for animal health authorities. It might be adapted to other species, livestock farming systems or diseases. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/581619/1/Hammami%20et%20al%20-%202016%20-%20Modelling%20the%20Dynamics%20of%20Post%20Vaccination%20Immunity%20Rate.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1371/journal.pone.0161769 10.1371/journal.pone.0161769 info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0161769 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1371/journal.pone.0161769 info:eu-repo/semantics/dataset/purl/https://figshare.com/articles/Modelling_the_Dynamics_of_Post-Vaccination_Immunity_Rate_in_a_Population_of_Sahelian_Sheep_after_a_Vaccination_Campaign_against_Peste_des_Petits_Ruminants_Virus/3812367 |