A model of lineage-1 and lineage-2 rinderpest virus transmission in pastoral areas of East Africa

Mariner, Jeffrey C.; McDermott, John J.; Heesterbeek, J.A.P.; Catley, Andy; Roeder, P. L.

doi:10.1016/j.prevetmed.2005.02.001

Cited by 43 publications

(30 citation statements)

References 22 publications

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“…In the best cases, the strategies are based on the results of disease surveillance and other epidemiological studies [73, 74], disease transmission models [21, 75], and economic studies [2, 76, 77]. Post-vaccination evaluation of vaccination campaigns use similar tools and methods [7, 78, 79].…”

Section: Discussionmentioning

confidence: 99%

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

2016

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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.

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Section: Discussionmentioning

confidence: 99%

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

2016

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“…Information on herd composition—age and sex structure—was crucial to the definition of the basic reproductive number (R 0 ), while participatory mapping and seasonal calendars helped in defining contact rates between communities and herds across seasons. This assisted in the design of the final surveillance programme of the disease in one of its final refuges [71]. …”

Section: Modelling Zoonosesmentioning

confidence: 99%

Integrative modelling for One Health: pattern, process and participation

Scoones

Jones

Iacono

et al. 2017

Phil. Trans. R. Soc. B

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This paper argues for an integrative modelling approach for understanding zoonoses disease dynamics, combining process, pattern and participatory models. Each type of modelling provides important insights, but all are limited. Combining these in a ‘3P’ approach offers the opportunity for a productive conversation between modelling efforts, contributing to a ‘One Health’ agenda. The aim is not to come up with a composite model, but seek synergies between perspectives, encouraging cross-disciplinary interactions. We illustrate our argument with cases from Africa, and in particular from our work on Ebola virus and Lassa fever virus. Combining process-based compartmental models with macroecological data offers a spatial perspective on potential disease impacts. However, without insights from the ground, the ‘black box’ of transmission dynamics, so crucial to model assumptions, may not be fully understood. We show how participatory modelling and ethnographic research of Ebola and Lassa fever can reveal social roles, unsafe practices, mobility and movement and temporal changes in livelihoods. Together with longer-term dynamics of change in societies and ecologies, all can be important in explaining disease transmission, and provide important complementary insights to other modelling efforts. An integrative modelling approach therefore can offer help to improve disease control efforts and public health responses.This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’.

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“…However, basic knowledge of disease behavior and immune responses in populations and experience in other disease eradication programs, especially RP during the GREP, has taught us that there should be far more to disease control and eradication than institutionalized, pulsed vaccination. It was demonstrated very clearly during GREP that inefficient vaccination in the face of endemic disease frequently did not induce immunity that reached the virus elimination threshold, aiding long-term virus persistence in some extensive populations (39) and resulting in the disease being difficult to detect. It is clear that to be optimally effective in achieving elimination of the PPR virus from an infected population, smart vaccination has to be applied within a systematic and adaptively managed program.…”

Section: A Guiding Strategy For Ppr Eradicationmentioning

confidence: 99%

The Opportunity To Eradicate Peste des Petits Ruminants

Mariner

Jones

Rich

et al. 2016

The Journal of Immunology

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Peste des petits ruminants (PPR) is a highly infectious disease of sheep and goats that is caused by PPR virus, a member of the genus Morbillivirus that includes the viruses that cause rinderpest (RP) in cattle. RP was the first animal disease to be globally eradicated in 2011 and is only the second disease, after smallpox, to have ever been eradicated. PPR is one of the principal constraints to small ruminant production in Africa, Asia, and the Middle East. The epidemiology of PPR and RP as well as the technologies available for their diagnosis and control are similar. The conditions that favored the eradication of RP are also largely present for PPR. In this work, we outline the evolving strategy for eradication in light of current opportunities and challenges, as well as the lessons from other eradication programs in animal and human health. The global PPR situation and technology for its control are summarized. A strategy based on the lessons from previous eradication efforts that integrate epidemiology, social science, and economics as tools to target and motivate vaccination is summarized. Major aspects of the cost and benefit-cost analysis of the indicated program are presented. The overall undiscounted cost of eradication was estimated as $3.1 billion, and the benefit-cost ratio for the most likely scenario was estimated at 33.8. We close with a discussion of the possible next steps.

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A model of lineage-1 and lineage-2 rinderpest virus transmission in pastoral areas of East Africa

Cited by 43 publications

References 22 publications

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

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

Integrative modelling for One Health: pattern, process and participation

The Opportunity To Eradicate Peste des Petits Ruminants

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