Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Divergent surveillance needs and resource allocation for Covid-19 and influenza

Insights from a community-based syndromic surveillance study in Shanghai (2024–2025)

Bibliographic Data

ID22072606
AuthorsXiao Yu (0000-0002-0964-756X, Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine)), Shiying Yuan (0000-0002-6415-1604, Shanghai Municipal Center For Disease Control Prevention), Huanyu Wu (0000-0002-1274-0271, Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine)), H y Wu (0000-0001-5928-195X, Shanghai Municipal Center For Disease Control Prevention), Shenghua Mao (Shanghai Municipal Center For Disease Control Prevention), Sheng Lin (0000-0001-8812-9842, Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine)), Xianjin JIANG (Shanghai Municipal Center For Disease Control Prevention), Xiaohuan Gong (0000-0001-6494-0534, Shanghai Municipal Center For Disease Control Prevention), Chenyan Jiang (0000-0003-1649-5901, Shanghai Municipal Center For Disease Control Prevention), Yaxu Zheng (0009-0004-6977-6074, Shanghai Municipal Center For Disease Control Prevention, corresponding author), Jian Chen (0000-0002-9033-4033, Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine))
Year2026
Volume14
Pages1777017-1777017
Publication date2026-03-03
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1777017
PMID41853162
OpenAlexW7133345622
LanguageEN
References cited21

Introduction The rapid evolution and symptom overlap of Coronavirus disease 2019 (COVID-19) and influenza challenge the effectiveness of current surveillance and healthcare resource planning. However, comparative evidence regarding their surveillance sensitivity and healthcare burden remains limited, particularly within concurrent community populations that capture the full spectrum of disease severity. Methods To address this gap, data were derived from a community-based syndromic surveillance cohort in Shanghai, followed weekly between May 2024 and August 2025. We analyzed symptom profiles and illness duration, assessed the sensitivity of Influenza-Like Illness (ILI) definitions, and evaluated healthcare-seeking behaviors across both acute (0–14 days) and post-acute (>14 days) phases. Results From May 2024 to August 2025, 382 COVID-19 and 175 influenza cases were identified. Compared with influenza, COVID-19 cases presented distinctively with upper respiratory symptoms (sore throat: 72.88% vs. 58.29%, runny or stuffy nose: 46.58% vs. 33.71%, loss of taste or smell: 3.84% vs. 0.57%; all p < 0.05), rather than fever (61.64% vs. 74.86%, p = 0.003). Consequently, standard ILI definitions failed to detect a significantly larger proportion of COVID-19 cases compared to influenza (China CDC criteria: 35.89% vs. 50.86%, p = 0.001; WHO criteria: 27.12% vs. 44.00%, p < 0.001). While illness duration was shorter for COVID-19 (6.66 ± 4.35 days vs. 8.25 ± 4.34 days, p < 0.05), influenza imposed a heavier healthcare burden, characterized by a two-fold increase in outpatient visits during the acute phase (OR = 2.12, 95% CI: 1.52–2.95) and sustained demand in the first 90 days of the post-acute phase (HR = 1.29, 95% CI: 1.03–1.61). Conclusion COVID-19’s symptom profile limits ILI surveillance sensitivity, whereas influenza imposes a higher burden extending into the post-acute phase. These differences call for adapting surveillance strategies and healthcare resource allocation to these distinct pathogen profiles

Cohort · Cohort study · Disease · Disease burden · Health care · Influenza-like illness · Public health · Respiratory illness · Respiratory tract infections · Data-Driven Disease Surveillance · Influenza Virus Research Studies · Respiratory viral infections research

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae