Epidemic Signals of Mycoplasma Pneumonia outbreaks in 2023 and early 2024 using Artificial Intelligence System (EPIWATCH®)

Authors

  • Tsai-Yun Lu UNSW
  • Moa Aye
  • Ashley Quigley

DOI:

https://doi.org/10.31646/gbio.278

Keywords:

EPIWATCH®, Syndromic Surveillance, Mycoplasma pneumonia

Abstract

Background: Mycoplasma pneumonia is a significant respiratory infection that primarily affects children and young adults and is responsible for 10 to 40% of community-acquired pneumonia cases. Transmission occurs through close contact, complicating infection control in schools, families, and institute settings. The incidence rate of Mycoplasma pneumonia dropped during COVID-19; however, concerning trends emerged in mid-October 2023. This study aims to identify and summarise the timelines of AI intelligence-EPIWATCH signals for enhanced surveillance of Mycoplasma pneumonia in 2023 and early 2024.

Methods: EPIWATCH® database was utilized to retrieve syndromic surveillance reports between January 1, 2023, and February 13, 2024, using syndromic keywords such as influenza-like illness, febrile syndromes, pneumonia of unknown origin, and the disease keyword Mycoplasma pneumonia. Study findings were grouped according to geographical locations, and a descriptive epidemiologic analysis of the outbreak was conducted. The top 5 countries were selected for further analysis to show the trends and patterns over the study period.

Results: The syndromic surveillance included a total of 1943 reports, including 26 reports of confirmed Mycoplasma pneumonia outbreaks. China, India, Russia, the USA, and Pakistan were included in the descriptive analysis. The trend in the EPIWATCH® syndromic surveillance data between January 1, 2023, and February 11, 2024, across these 5 countries revealed increases in reporting of influenza-like illness and pneumonia of unknown origin starting around August or September 2023, with notable spikes occurring in November or December 2023.

Conclusion: This study demonstrates the effectiveness of using EPIWATCH® as a syndromic surveillance tool in providing timely early signals of outbreaks compared to traditional surveillance methods. This proactive approach helps in understanding and managing emerging infectious diseases, facilitating effective control measures to mitigate the impact of future Mycoplasma pneumonia outbreaks.

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Published

2025-03-21

How to Cite

Lu, T.-Y., Aye, M., & Quigley, A. (2025). Epidemic Signals of Mycoplasma Pneumonia outbreaks in 2023 and early 2024 using Artificial Intelligence System (EPIWATCH®). Global Biosecurity, 7(1). https://doi.org/10.31646/gbio.278

Issue

Vol. 7 (2025)

Section

Research Articles

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Copyright (c) 2025 The Author(s)

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Received 2024-05-21
Accepted 2024-12-10
Published 2025-03-21