tetano
Editor, Senior Moderator
JMIR Public Health Surveill
. 2026 Jun 22:12:e86209.
doi: 10.2196/86209.
Multimodal Data Approaches for Examining the 2024-2025 Highly Pathogenic Avian Influenza Outbreak in the United States: Descriptive Study
Juliana Sopko[SUP] 1 [/SUP], Aimee R Han[SUP] 1 [/SUP], Jacqueline Powers[SUP] 1 [/SUP], Jacquelin A Sauer[SUP] 1 [/SUP], Mansi Avunoori[SUP] 1 [/SUP], Stanislaw Zakrzewski[SUP] 2 [/SUP], Allison Krugman[SUP] 3 [/SUP], Abhishek Dasgupta[SUP] 4 5 [/SUP], Kara Sewalk[SUP] 1 [/SUP], Autumn Gertz[SUP] 1 [/SUP], Benjamin Rader[SUP] 1 6 [/SUP], James Sheldon[SUP] 7 [/SUP], Brennan Klein[SUP] 8 9 [/SUP], Jessica Malaty Rivera[SUP] 1 [/SUP], Moritz U G Kraemer[SUP] 4 5 [/SUP], Samuel V Scarpino[SUP] 7 8 10 11 12 [/SUP], John S Brownstein[SUP] 1 13 [/SUP]
Affiliations
Background: Highly pathogenic avian influenza (HPAI) A(H5N1) clade 2.3.4.4b, a globally predominant strain, was introduced into poultry in the United States in 2022 via spillover from wild birds, and has since been regularly reported, posing ongoing risks to animal and human health. In 2024, the United States reported the first known HPAI A(H5N1) clade 2.3.4.4b infection in dairy cattle, rapidly evolving into a multispecies outbreak among cattle and poultry, with spillover into humans. Publicly available data remained siloed and fragmented, hindering timely response. Innovative multimodal surveillance methods can enhance situational awareness through comprehensive, standardized data collection, integration, and visualization.
Objective: This study aimed to describe observations from the application of enhanced surveillance methods that collect, integrate, and visualize multimodal data for real-time tracking of the 2024-2025 HPAI A(H5) outbreak in the United States as an innovative, transparent, repeatable, and scalable approach for open-source public health surveillance.
Methods: Global.health conducted real-time, multimodal surveillance of the United States 2024-2025 HPAI A(H5) outbreak using publicly available data for human cases (Centers for Disease Control and Prevention), animal outbreaks (United States Department of Agriculture), wastewater monitoring (WastewaterSCAN), genomic data (public genomic databases), research updates (scholarly communication), and policy changes and response measures (media and government) for the study period from February 1, 2024 through February 28, 2025. This digital data stream was used to create outbreak resources-an epidemiological linelist, event timeline, and interactive map-using a One Health framework to track emerging hotspots.
Results: Global.health curated 70 confirmed human HPAI A(H5) cases across 13 states in a linelist, with exposure for nearly all (n = 65, 92.9%) cases associated with commercial agriculture and related operations. We curated 682 timeline entries across 6 distinct categories: human, cattle, response (eg, research, policy changes, and public health guidance), birds, genome, wastewater, and mammals. The map integrated human cases (n=70) and animal outbreaks (commercial cattle: n=977 and commercial poultry: n=325) into a single view. California was identified as the outbreak epicenter with high numbers of human cases (n=38, 54.3%), commercial cattle outbreaks (n=748, 76.6%), and commercial poultry outbreaks (n=66, 20.3%) during the study period. Wastewater surveillance detected the virus in California, with an unknown source at least 81 days before the first confirmed commercial dairy cattle case.
Conclusions: Global.health's approach for integrating traditional and nontraditional public health surveillance data within a One Health framework enhanced early situational awareness during the United States 2024-2025 HPAI A(H5) outbreak, creating open access to resources that improve contextual understanding of the scope and evolution of this emerging zoonotic event. Further research should seek to understand the full potential of multimodal data in outbreak surveillance.
Keywords: avian influenza; data analysis; data curation; data visualization; digital health; one health; public health surveillance; wastewater surveillance; zoonotic infectious diseases; zoonotic spillover.
. 2026 Jun 22:12:e86209.
doi: 10.2196/86209.
Multimodal Data Approaches for Examining the 2024-2025 Highly Pathogenic Avian Influenza Outbreak in the United States: Descriptive Study
Juliana Sopko[SUP] 1 [/SUP], Aimee R Han[SUP] 1 [/SUP], Jacqueline Powers[SUP] 1 [/SUP], Jacquelin A Sauer[SUP] 1 [/SUP], Mansi Avunoori[SUP] 1 [/SUP], Stanislaw Zakrzewski[SUP] 2 [/SUP], Allison Krugman[SUP] 3 [/SUP], Abhishek Dasgupta[SUP] 4 5 [/SUP], Kara Sewalk[SUP] 1 [/SUP], Autumn Gertz[SUP] 1 [/SUP], Benjamin Rader[SUP] 1 6 [/SUP], James Sheldon[SUP] 7 [/SUP], Brennan Klein[SUP] 8 9 [/SUP], Jessica Malaty Rivera[SUP] 1 [/SUP], Moritz U G Kraemer[SUP] 4 5 [/SUP], Samuel V Scarpino[SUP] 7 8 10 11 12 [/SUP], John S Brownstein[SUP] 1 13 [/SUP]
Affiliations
- PMID: 42330167
- PMCID: PMC13286079
- DOI: 10.2196/86209
Background: Highly pathogenic avian influenza (HPAI) A(H5N1) clade 2.3.4.4b, a globally predominant strain, was introduced into poultry in the United States in 2022 via spillover from wild birds, and has since been regularly reported, posing ongoing risks to animal and human health. In 2024, the United States reported the first known HPAI A(H5N1) clade 2.3.4.4b infection in dairy cattle, rapidly evolving into a multispecies outbreak among cattle and poultry, with spillover into humans. Publicly available data remained siloed and fragmented, hindering timely response. Innovative multimodal surveillance methods can enhance situational awareness through comprehensive, standardized data collection, integration, and visualization.
Objective: This study aimed to describe observations from the application of enhanced surveillance methods that collect, integrate, and visualize multimodal data for real-time tracking of the 2024-2025 HPAI A(H5) outbreak in the United States as an innovative, transparent, repeatable, and scalable approach for open-source public health surveillance.
Methods: Global.health conducted real-time, multimodal surveillance of the United States 2024-2025 HPAI A(H5) outbreak using publicly available data for human cases (Centers for Disease Control and Prevention), animal outbreaks (United States Department of Agriculture), wastewater monitoring (WastewaterSCAN), genomic data (public genomic databases), research updates (scholarly communication), and policy changes and response measures (media and government) for the study period from February 1, 2024 through February 28, 2025. This digital data stream was used to create outbreak resources-an epidemiological linelist, event timeline, and interactive map-using a One Health framework to track emerging hotspots.
Results: Global.health curated 70 confirmed human HPAI A(H5) cases across 13 states in a linelist, with exposure for nearly all (n = 65, 92.9%) cases associated with commercial agriculture and related operations. We curated 682 timeline entries across 6 distinct categories: human, cattle, response (eg, research, policy changes, and public health guidance), birds, genome, wastewater, and mammals. The map integrated human cases (n=70) and animal outbreaks (commercial cattle: n=977 and commercial poultry: n=325) into a single view. California was identified as the outbreak epicenter with high numbers of human cases (n=38, 54.3%), commercial cattle outbreaks (n=748, 76.6%), and commercial poultry outbreaks (n=66, 20.3%) during the study period. Wastewater surveillance detected the virus in California, with an unknown source at least 81 days before the first confirmed commercial dairy cattle case.
Conclusions: Global.health's approach for integrating traditional and nontraditional public health surveillance data within a One Health framework enhanced early situational awareness during the United States 2024-2025 HPAI A(H5) outbreak, creating open access to resources that improve contextual understanding of the scope and evolution of this emerging zoonotic event. Further research should seek to understand the full potential of multimodal data in outbreak surveillance.
Keywords: avian influenza; data analysis; data curation; data visualization; digital health; one health; public health surveillance; wastewater surveillance; zoonotic infectious diseases; zoonotic spillover.