Pashu Sandesh, 22 October 2022
The association between infectious diseases and climate was known since ancient times. Hippocrates observed in the 5th century that epidemics were associated with natural phenomena rather than deities or demons. In modern times, our increasing capabilities to detect and predict climate variations joined with growing evidence for global climate change, have powered interest in understanding the impacts of climate on animal health, particularly the emergence and transmission of infectious disease agents. Simple reasoning suggests that climate can affect infectious disease patterns because the pathogens (viruses, bacteria, and parasites) and their vectors are sensitive to temperature, moisture, and other ambient environmental conditions.
India is an agriculture-based country, the livestock sector plays a vital role in contributing to the economy. A robust reporting and forewarning system enables the concerned authorities to be disease preparedness and aware of the risk associated with livestock diseases. Therefore, the economic loss due to morbidity and mortality of the animals is reduced thereby helping to increase the productivity in terms of egg, meat, and dairy products. The National Animal Disease Referral Expert System database is a weather-based forewarning system enabled by an artificial intelligence system developed by ICAR- National Institute of Veterinary Epidemiology & Disease Informatics Bengaluru, Karnataka state, India that forecast potential threats from pathogens two months in advance to provide the stakeholders with the sufficient timeline for awareness and preparedness to act.
The livestock disease forewarning for December 2022 revealed Jharkhand, Uttar Pradesh, Karnataka, Kerala Assam and West Bengal as the top states with high predicted livestock disease outbreaks.
Among the predicted diseases, control programmes are in full swing for FMD and PPR in the country and due attention is demanded by the predicted disease outbreaks of these diseases. Among the expected disease outbreaks, the predicted FMD and PPR outbreaks are high in Jharkhand, 21 and 17 respectively. Further, the co-occurrence of FMD and HS can be expected in Andhra Pradesh, Gujarat, Jharkhand, Karnataka, Kerala, Madhya Pradesh, Odisha, Rajasthan, Tamil Nadu, Tripura and West Bengal. Among the different diseases in livestock, the predicted outbreaks are expected to be high for Fasciolosis (96), Trypanosomosis (74) and Theileriosis (70).
The major challenges for the effective disease control programme are the lack of thorough understanding of the complexity of disease dynamics, the wide host range of pathogens, the widening of the niche of pathogens due to climate change etc. The effective control programme for major livestock diseases in the country can be efficiently addressed by planning and executing available control measures in high-risk areas and routine surveillance and monitoring of diseases.
output (Infectious risk prediction) values within an acceptable range. As new data fed into this Artificial Intelligence (AI) and Machine Learning (ML) models use the programmed algorithms that receive and analyse input data to predict algorithms, they learn and optimize their operations to improve performance, developing intelligence over time.
Published by: Director, ICAR- National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Yelahanka, Bengaluru-560064.