Work

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

Year: 2026

Type: article

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. Supplementary Information: The online version contains supplementary material available at 10.1007/s40471-026-00405-w.

Source: Current Epidemiology Reports

DOI: 10.1007/s40471-026-00405-w

Authors: Akshay Deverakonda, Emily E. Ricotta, John T. Kubale

Institutions: Emory University, Uniformed Services University of the Health Sciences, University of Michigan, Institute for Social Research

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,090