B’luru Institute develops software tool for zoonotic disease surveillance – The New Indian Express

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Express news service

BENGALURU: Post-Covid security infrastructure will involve strengthening scientific and technical intelligence that will aid surveillance and early warning systems for health epidemics that may impact life and the economy on a large scale in the country.

The Department of Biotechnology, as part of “Establishing a One Health Consortium to Combat Zoonotic and Transboundary Diseases in India, including the North East Region”, “approved a sampling plan and a predictive model for surveillance of infectious zoonotic diseases in humans in ICAR-NIVEDI, Bengaluru, ”said Dr KP Suresh, senior scientist at the National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI ).

“The first intelligence software tool of its kind will be based on the National Expert System of Reference in Animal Diseases-v2 (NADRES-v2), which was developed by ICAR-NIVEDI five years ago as a surveillance and warning system for livestock diseases. management. It will be used for the monitoring and forecasting of zoonotic diseases in humans such as coronaviruses, brucellosis, tuberculosis, coxiellosis, cryptosporidiosis, cysticercosis, Japanese encephalitis, leptospirosis, brush typhus and brush typhus. listeriosis, ”he said. NADRES-v2 is a software based on artificial intelligence (AI) and real-time machine learning that is used in the prediction of infectious diseases in livestock two months in advance to prepare stakeholders and educate them. help initiate preventive measures.

“The National Center for Disease Control, Department of Health and Family Welfare, had approached NIVEDI to develop a system to be used for the prediction of zoonotic diseases in humans,” said NIVEDI senior scientist, the Dr Sharangouda Patil. Suresh and Patil are involved in the development of the software application. “Operational disease alert systems using AI, machine learning and data science are more feasible and economical to mitigate the risk of epidemics, when predictions are more precise and accurate,” said Dr Suresh.


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