Modeling for Smart Vaccination against Peste des Petits Ruminants (PPR) in the Emirate of Abu Dhabi, United Arab Emirates

Author:

Eltahir Yassir M.1ORCID,Aburizq Wael2,Bensalah Oum Keltoum1ORCID,Mohamed Meera S.1,Al Shamisi Aysha2,AbdElkader Ayman I.3,Al-Majali Ahmad45

Affiliation:

1. Animals Health and Extension Division, Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), Abu Dhabi 52150, United Arab Emirates

2. Data and Artificial Intelligence Division, Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), Abu Dhabi 52150, United Arab Emirates

3. Policy and Regulatory Affairs, Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), Abu Dhabi 52150, United Arab Emirates

4. Subregional Office for the Gulf Cooperation Council States and Yemen, Food and Agriculture Organization of the United Nations (FAO), Abu Dhabi 62072, United Arab Emirates

5. Department of Veterinary Clinical Sciences, Faculty of Veterinary Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan

Abstract

Peste des petits ruminants (PPR) is a contagious and economically important transboundary viral disease of small ruminants. The United Arab Emirates (UAE) national animal health plan aimed to control and eradicate PPR from the country by following the global PPR control and eradication strategy which adopts small ruminants’ mass vaccination to eradicate the disease from the globe by 2030. A smart vaccination approach, which is less expensive and has longer-term sustainable benefits, is needed to accelerate the eradication of PPR. In this study, a mathematical algorithm was developed based on animals’ identification and registration data, belonging to the Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), and other different parameters related to PPR risk occurrence. The latter included animal holding vaccination history, the number of animals per holding, forecasting of the number of animals and newborns per holding, the proximity of an animal holding to a PPR outbreak and the historical animal holding owner vaccination rejection attitude. The developed algorithm successfully prioritized animal holdings at risk of PPR infection within Abu Dhabi Emirate to be targeted by vaccination. This in turn facilitated the mobilization of field vaccination teams to target specific sheep and goat holdings to ensure the generation of immunity against the disease on a risk-based approach. The vaccination coverage of the targeted livestock population was increased to 86% and the vaccination rejection attitude was reduced by 35%. The duration of the vaccination campaign was reduced to 30 compared to 70 working days and hence can alleviate the depletion of human and logistic resources commonly used in classical mass vaccination campaigns. The results obtained from implementing the algorithm-based PPR vaccination campaign will reduce the negative impact of PPR on the UAE livestock sector and accelerate the achievement of the national PPR eradication plan requirements.

Publisher

MDPI AG

Subject

General Veterinary,Animal Science and Zoology

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