Modelling the Dynamics of Post-Vaccination Immunity Rate in a Population of Sahelian Sheep after a Vaccination Campaign against Peste des Petits Ruminants Virus

Abstract

BackgroundPeste 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.MethodsIn 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 offtake rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns.ResultsThe 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.

Ex-ante assessment of different vaccination-based control schedules against the peste des petits ruminants virus in sub-Saharan Africa

“…For simplicity, and consistency with assumptions and findings made in Hammami et al, 2016 [ 18 ], the Epi. U. were defined as isolated populations of a few thousand small ruminants with no PPRV transmission occurring during the whole study period.…”

“…346-369) [ 23 ]. The basic demographic model and the PVIR estimation method were described for one average year in Hammami et al (2016) [ 18 ]. Following the international recommendations [ 11 ], we considered (a) different four-year vaccination schedules according to the sequence of full annual campaigns (targeting all immunocompetent animals) and partial annual campaigns (only targeting immunocompetent offspring), and (b) two possible PVIR variables: i) the vaccination month and ii) the vaccination coverage in the target population.…”

“… The small-ruminant follow-up demographic surveys were located in the Ndiagne municipality (Louga region) and Kolda area. This map was adapted from Hammami et al, 2016 [ 18 ] under a CC BY license, with permission from Dianne Cartwright—PLoS ONE, original copyright 2016. It was generated using data sources from Zomer et al, 2006 [ 25 ] and Trabucco et al, 2009 [ 26 ]; spatial resolution: 10 arc minutes.…”

“…Because of the population turnover (offtake, mortality and birth), the immunized animals are progressively replaced with susceptible animals (newborn, purchased animals, loans) until the epidemic threshold has passed. Therefore, PVIR dynamics are closely related to this turnover and can be estimated using a population dynamics model [ 17 , 18 ]. In a previous study, based on a predictive model of PVIR dynamics developed in Lesnoff et al (2009) [ 17 ], the monthly PVIR dynamics was estimated for an average year following a PPR vaccination campaign in a sheep population reared in a semi-arid area [ 18 ].…”

“…Therefore, PVIR dynamics are closely related to this turnover and can be estimated using a population dynamics model [ 17 , 18 ]. In a previous study, based on a predictive model of PVIR dynamics developed in Lesnoff et al (2009) [ 17 ], the monthly PVIR dynamics was estimated for an average year following a PPR vaccination campaign in a sheep population reared in a semi-arid area [ 18 ]. In this latter study, a PVIR threshold of 70% was used: populations with a PVIR ≥ 70% were considered as protected against PPR virus transmission, according to international standards [ 11 ].…”