SynthesisJournal of global health2025
Characteristics of influenza, SARS-CoV-2, and RSV surveillance systems that utilise ICD-coded data: a systematic review.
Synthesis in Journal of global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Incidence of respiratory syncytial virus and influenza: A Danish nationwide cohort study.Human vaccines & immunotherapeutics · 2026Article
- How Pandemics Have Reshaped the Respiratory Virus Data Landscape in Europe: Scoping Review.Journal of medical Internet research · 2026Article
- Strengthening Respiratory Virus Surveillance in Sub-Saharan Africa: Integrated Epidemiological and Genomic Monitoring in Côte d'Ivoire.Influenza and other respiratory viruses · 2026Article
- Reconstructing severe acute respiratory infection dynamics from ICD-10 hospital discharge data: a 10-year analysis of 11.2 million discharges in Ecuador, 2014-2023.Frontiers in public health · 2026Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Some surveillance systems for influenza, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and respiratory syncytial virus (RSV) utilise International Classification of Diseases (ICD)-coded data and are useful for analysing trends and enhancing quick, evidence-based decisions against the epidemic potential that threatens global health security. With variations in the design of systems globally, the World Health Organization requested a systematic review to identify key characteristics of influenza, SARS-CoV-2, and RSV surveillance systems that utilise ICD-coded data, and to assess their performance. Methods: We searched EMBASE, MEDLINE, and Global Health to identify relevant studies reporting on influenza, SARS-CoV-2, and RSV surveillance systems that use ICD-coded data. We independently assessed studies for the ICD codes used, their statistical estimates and limitations. We appraised included studies using Joana Briggs Institute's critical appraisal tools and synthesised using narrative synthesis. Results: We identified 77 studies, reporting on 71 surveillance systems - 33 systems recorded surveillance data only, 15 systems recorded burden of disease data only, and 23 systems recorded both surveillance and burden of disease data. Surveillance systems utilised ICD-10 codes (75%), ICD-9 codes (22%), or both (3%). ICD-10 codes J09 and J10 were frequently used for influenza, U07.1 for COVID-19, and B97.4, J12.1, J20.5, and J21.0 for RSV. ICD-9 codes 487 and 488 were mostly used for influenza, and codes 466.11 and 480.1 for RSV. ICD-10 codes had low-to-moderate sensitivity (6.60-79.87%) and high specificity (97.40-99.72%) for influenza, low-to-high sensitivity (30.00-98.4%) and specificity (39.50-99.80%) for COVID-19, and low-to-high sensitivity (6.00-99.80%) and specificity (12.10-100.00%) for RSV. ICD-9 codes had low sensitivity (45.60%) and high specificity (97.90%) for influenza. Underestimation of infections or mortality attributable to influenza, SARS-CoV-2, or RSV is a major limitation to using ICD-coded data across surveillance systems. Conclusions: The performance of ICD codes for syndromic- or disease-specific surveillance remains inconclusive, although using only ICD-coded data within these systems may underestimate influenza, SARS-CoV-2, or RSV-attributable morbidity and mortality. Future studies should assess the accuracy of ICD code combinations for surveillance of influenza, SARS-CoV-2, and RSV.
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