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Published on: August 2, 2011
Multimodal Data Approaches for Examining the 2024-2025 Highly Pathogenic Avian Influenza Outbreak in the United
Juliana Sopko1, Aimee R Han1, Jacqueline Powers1
1Computational Epidemiology Lab, Boston Children's Hospital, 401 Park Drive, 7th Floor West, Boston, MA, 02215, United States, 1 617 355 8278.
JMIR Public Health and Surveillance
|June 22, 2026
Summary
Multimodal surveillance enhanced situational awareness during the 2024-2025 highly pathogenic avian influenza (HPAI) A(H5) outbreak in the United States. This approach integrated diverse data streams for real-time tracking and open-source public health surveillance.
Area of Science:
- Public Health
- Epidemiology
- Infectious Disease Surveillance
Background:
- Highly pathogenic avian influenza (HPAI) A(H5N1) clade 2.3.4.4b poses ongoing risks to animal and human health in the US.
- The 2024 HPAI A(H5N1) outbreak in dairy cattle rapidly evolved into a multispecies event with human spillover.
- Fragmented data hindered timely response to the evolving HPAI A(H5) outbreak.
Purpose of the Study:
- To describe enhanced surveillance methods for real-time tracking of the 2024-2025 HPAI A(H5) outbreak in the US.
- To showcase an innovative, transparent, repeatable, and scalable approach for open-source public health surveillance.
- To integrate multimodal data for comprehensive situational awareness.
Main Methods:
- Conducted real-time, multimodal surveillance using publicly available data from February 2024 to February 2025.
- Integrated data from human cases (CDC), animal outbreaks (USDA), wastewater monitoring (WastewaterSCAN), and genomic databases.
- Utilized a One Health framework to create an epidemiological linelist, event timeline, and interactive map.
Main Results:
- Curated 70 confirmed human HPAI A(H5) cases across 13 states, with most exposures linked to commercial agriculture.
- Documented 682 timeline entries across human, cattle, poultry, wildlife, genomic, wastewater, and response categories.
- Identified California as the outbreak epicenter, with early wastewater detection preceding confirmed cattle cases.
Conclusions:
- The multimodal surveillance approach enhanced early situational awareness of the HPAI A(H5) outbreak.
- Open-access resources created improve contextual understanding of the zoonotic event's scope and evolution.
- Further research is needed to explore the full potential of multimodal data in outbreak surveillance.
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