Mapping the Surveillance Data Infrastructure in the U.S. for SARS-CoV-2, Influenza, and Respiratory Syncytial Virus
Current Epidemiology Reports·
- DOI
- 10.1007/s40471-026-00405-w
- PMID
- —
- PMCID
- —
- OpenAlex
- —
- Study type
- Journal article
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Why this research matters now
Clarifying the scope and availability of these monitoring frameworks may streamline epidemiological investigations and support more effective emergency management strategies.
Structured evidence summary
Research question
How can investigators efficiently locate and apply existing public health monitoring frameworks for major respiratory pathogens across the United States?
Study design
A narrative review characterizing the organizational structure and operational features of national infectious disease tracking networks.
Population and setting
Federal, state, and local public health monitoring networks operating within the United States to track influenza, respiratory syncytial virus, and SARS-CoV-2.
Main findings
The authors cataloged thirteen primary data sources, predominantly government-operated. The majority utilize individual case reporting, while a minority employ symptom-based tracking or environmental sampling. The manuscript evaluates how readily these datasets can be accessed and organized for external analytical use.
Public-health relevance
Clarifying the scope and availability of these monitoring frameworks may streamline epidemiological investigations and support more effective emergency management strategies.
Important limitations
The decentralized architecture of domestic public health operations produces a fragmented collection landscape that impedes rapid data mobilization for research and crisis response.
GIDS interpretation
This publication offers a contextual inventory of established tracking architectures and evaluates how easily their outputs can be discovered and incorporated into broader analytical workflows.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 12 auditable classifier relationships to diseases, places, topics, and study design.