Mapping the Surveillance Data Infrastructure in the U.S. for SARS-CoV-2, Influenza, and Respiratory Syncytial Virus

Abstract Purpose of Review Infectious disease surveillance forms the epidemiological bedrock of public health, supporting the continuous and systematic collection, and analysis of health data. However, these data are collected by a fragmented network of systems and entities which complicate their accessibility and efficient use. This review describes the key surveillance systems tracking three important respiratory viruses: influenza, respiratory syncytial virus (RSV), and SARS-CoV-2; highlights these systems’ limitations; and identifies opportunities for improvement. Recent Findings High quality surveillance data are vital for effective public health interventions. The decentralized nature of the U.S. public health infrastructure and the subsequent patchwork of surveillance networks create a formidable challenge for epidemiologists seeking to mobilize these data for outbreak response, policy evaluation, or population-based research. Greater clarity on these key surveillance systems, the data they collect, and the populations they represent could support their more effective use to support public health research and emergency response. Summary We identified thirteen surveillance data sources monitoring influenza, RSV, and SARS-CoV-2 in the U.S; all but one were governmental. Most (9) were case-based systems, 2 were syndromic surveillance systems (that monitor for increases in illness-associated symptoms in a population rather than the disease itself), and 2 were classified as “non-traditional” sources like wastewater surveillance systems. We also assessed the relative accessibility of data from these systems and of data from state and local entities which often feed into these systems, and collated this information to improve its findability and accessibility.

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Publication Details

Journal
Current Epidemiology Reports
Published
2026-08-21
DOI
https://doi.org/10.1007/s40471-026-00405-w
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
0.00

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article

Mapping the Surveillance Data Infrastructure in the U.S. for SARS-CoV-2, Influenza, and Respiratory Syncytial Virus

Emily Ricotta, John Kubale, Akshay Deverakonda
Current Epidemiology Reports
Data-Driven Disease Surveillance
article

Mapping the Surveillance Data Infrastructure in the U.S. for SARS-CoV-2, Influenza, and Respiratory Syncytial Virus

Emily Ricotta, John Kubale, Akshay Deverakonda
article en

Abstract

Abstract Purpose of Review Infectious disease surveillance forms the epidemiological bedrock of public health, supporting the continuous and systematic collection, and analysis of health data. However, these data are collected by a fragmented network of systems and entities which complicate their accessibility and efficient use. This review describes the key surveillance systems tracking three important respiratory viruses: influenza, respiratory syncytial virus (RSV), and SARS-CoV-2; highlights these systems’ limitations; and identifies opportunities for improvement. Recent Findings High quality surveillance data are vital for effective public health interventions. The decentralized nature of the U.S. public health infrastructure and the subsequent patchwork of surveillance networks create a formidable challenge for epidemiologists seeking to mobilize these data for outbreak response, policy evaluation, or population-based research. Greater clarity on these key surveillance systems, the data they collect, and the populations they represent could support their more effective use to support public health research and emergency response. Summary We identified thirteen surveillance data sources monitoring influenza, RSV, and SARS-CoV-2 in the U.S; all but one were governmental. Most (9) were case-based systems, 2 were syndromic surveillance systems (that monitor for increases in illness-associated symptoms in a population rather than the disease itself), and 2 were classified as “non-traditional” sources like wastewater surveillance systems. We also assessed the relative accessibility of data from these systems and of data from state and local entities which often feed into these systems, and collated this information to improve its findability and accessibility.

Current Epidemiology ReportsVol. 13(1)
Uniformed Services University of the Health Sciences (US), Emory University (US), Institute for Social Research (NO)
National Institutes of Health, Uniformed Services University of the Health Sciences
Openalex Percentile: Top 9%
Data-Driven Disease Surveillance
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