ADAFSA succeeds at first smart algorithm to control animal diseases in Abu Dhabi

UAE AGRICULTURE

ABU DHABI- The Abu Dhabi Agriculture and Food Safety Authority, ADAFSA, has succeeded, in collaboration with the United Arab Emirates University, UAEU, and Scotland’s Rural College, SRUC, in attempting the first integrated smart algorithm for identifying potential scenarios and risks for the spread of epizootic and zoonotic diseases, and its impact on animal wealth in Abu Dhabi Emirate.

The move aims at fostering a biosecurity system in Abu Dhabi and adopting the best data science initiatives, techniques and Artificial Intelligence, AI, algorithms.

The interdisciplinary (ADFASA, UAEU and SRUC) research team has held several virtual seminars from April to July 2020, to develop algorithms and run simulations to assess the spread of different epizootic and zoonotic diseases to utilise this in supporting a biosecurity system in the short and long terms.

Using the big data of livestock in the emirate, its curative and preventive history, and geographical distribution, the outcomes of these simulations systems can be utilised in defining the expected time for the beginning and end of animal disease, the expected number of holdings and animals that can be infected, and necessary costs to ensure preparedness and rapid response to control such disease.

In this regard, Rashid Mohamed Al Mansouri, Executive Director of Animal Wealth Sector, affirmed that AI algorithms significantly contribute to enhancing the biosecurity system and promoting animal and human health.

The importance of developing this algorithm lies in getting ready to combat animal-related diseases, in case they occur, by developing effective plans and strategies to control its outbreak in the emirate, thus increasing the GDP and achieving food security in the UAE, he added.

Earlier this year, ADAFSA succeeded in developing a smart algorithm, the first-of-its-kind in the Middle East, to eradicate Paste des Petits Ruminants, PPR, and boost the immune system of animals by connecting PPR vaccination data to animal identification and registration system data, to be used as a database for defining the degree of risk that animals may face.