ReviewCurrent epidemiology reports2026
Mapping the Surveillance Data Infrastructure in the U.S. for SARS-CoV-2, Influenza, and Respiratory Syncytial Virus.
Review in Current epidemiology reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.