Descriptive Analysis of Strains of Avian Influenza in India, 2016-2024 Using EPIWATCH®

Authors

  • Aung Zayar Paing Biosecurity program, The Kirby Institute, University of New South Wales.
  • Ashley Quigley Biosecurity program, The Kirby Institute, University of New South Wales
  • Samsung Lim School of Civil and Environmental Engineering, University of New South Wales
  • Haley Stone Biosecurity program, The Kirby Institute, University of New South Wales
  • Aye Moa
  • C. Raina Macintyre Biosecurity program, The Kirby Institute, University of New South Wales

DOI:

https://doi.org/10.31646/gbio.347

Keywords:

Avian Influenza, Epidemiology, EPIWATCH, India, descriptive analysis

Abstract

Background: Avian influenza viruses pose a significant threat to animal and human health, food security and the economy. India has reported animal outbreaks and human cases of avian influenza in increasing frequency since 2006. Open-source intelligence (OSINT) on outbreak data can provide valuable early warning signals.

 

Aim: To analyse the temporal trend of various avian influenza strains in animal and human hosts in India using open-source intelligence data from EPIWATCH®, an Artificial Intelligence (AI)-driven early warning system for epidemics, and to access the timeliness of its reports.

 

Methods: Animal and human outbreak data of avian influenza strains in India were extracted from EPIWATCH® from 1st January 2016 to 31st July 2024. A time series analysis of EPIWATCH® reports was conducted to investigate the temporal trend of avian influenza in India. To investigate usefulness of EPIWATCH®, reports from EPIWATCH® were also compared with the animal outbreak data from EMPRES-i+. Geospatial analysis was performed to visualise the temporal trend of hotspots of infection.

 

Results: EPIWATCH® reports on avian influenza outbreaks in animals were found to be highly concentrated in winter months from December to early April, closely aligned with the trend of animal outbreak data from EMPRES-i+. The findings of Kerala and Maharashtra, identified as hotspots of avian influenza in EPIWATCH® between 2021 and 2024, were consistent with findings reported elsewhere. Statistical analysis of report dates of EMPRES-i+ showed a median delay of 73.5 days [IQR: 22.3 – 221.8]. These highlight the OSINT’s ability to capture far earlier signals of avian influenza outbreaks compared to formal reporting.

 

Conclusion: EPIWATCH® reports on avian influenza in both animals and humans closely match official data sources while offering early warning signals of outbreaks. As such, use of OSINT as an adjunct surveillance system could inform timely outbreak responses, reducing public health risks and socio-economic impacts.

Author Biographies

Ashley Quigley, Biosecurity program, The Kirby Institute, University of New South Wales

Senior Research Associate

Biosecurity Program

Kirby Institute

University of New South Wales, Sydney

Samsung Lim, School of Civil and Environmental Engineering, University of New South Wales

Associate Professor

School of Civil and Environmental Engineering

University of New South Wales, Sydney

Aye Moa

Postdoctoral Research Fellow

Biosecurity Program

Kirby Institute

University of New South Wales, Sydney

C. Raina Macintyre, Biosecurity program, The Kirby Institute, University of New South Wales

Professor of Global Biosecurity

Biosecurity Program

Kirby Institute

University of New South Wales, Sydney

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Published

2026-03-27

How to Cite

Aung Zayar Paing, Quigley, A., Lim, S., Stone, H., Moa, A., & Macintyre, C. R. (2026). Descriptive Analysis of Strains of Avian Influenza in India, 2016-2024 Using EPIWATCH®. Global Biosecurity, 8(88). https://doi.org/10.31646/gbio.347

Issue

Vol. 8 (2026)

Section

Research Articles

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Copyright (c) 2026 The Author(s)

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Received 2025-12-11
Accepted 2026-02-16
Published 2026-03-27