Evidence map›Paper›PMID 42812401›Full record

ArticleFrontiers in public health2026

Temporal association between influenza A and B positivity and fever-clinic visit burden in Shanghai, China, 2022-2025: a retrospective time-series study.

Shan Yu, Tongtong Xu, Cunzheng Song, Xiaosong Chen, Yueqiu Gao

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shan YuShanghai University of Traditional Chinese Medicine, Shanghai, China.
Tongtong XuRenji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Cunzheng SongRenji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaosong ChenRenji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yueqiu GaoShanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Temporal changes in respiratory virus circulation after the COVID-19 pandemic have created new challenges for fever-clinic preparedness. Outpatient influenza laboratory activity may provide useful operational information, but its type-specific temporal relationship with subsequent fever-clinic burden has not been well characterized. Methods: We conducted a retrospective time-series study using aggregated fever-clinic visit records and outpatient influenza testing data from Renji Hospital, Shanghai, China, from 2022 to 2025. Lead-lag correlations were evaluated over a primary -28 to +28-day window using 7-day centered moving averages, with trailing moving averages and an extended -56 to +56-day window as sensitivity analyses. High-burden days were defined as days with visits at or above the 90th percentile. Adjusted quasi-Poisson models accounted for day of week, calendar month, calendar year, and testing volume. Additional analyses excluded 2022, evaluated adjacent 0-21-day influenza A leads, and used Newey-West autocorrelation-robust inference. Results: We included 254,346 fever-clinic visits and 303,597 outpatient influenza testing episodes. Overall influenza positivity was 33.96%, with 84,819 influenza A-positive and 18,504 influenza B-positive episodes. Influenza A was the main contributor to increased overall activity, particularly in 2023 and 2025. Peak correlations occurred at -12 days for overall influenza positivity and -15 days for influenza A positivity, whereas influenza B peaked at the positive boundary of the primary window. In the extended analysis, the influenza B peak shifted to +50 days, indicating no stable leading relationship. High-burden days were preceded by higher overall influenza and influenza A positivity than reference days. In the conventional testing-volume-adjusted model, influenza A positivity at a 15-day lead was associated with daily fever-clinic visits, but this association was attenuated after exclusion of 2022 and was no longer statistically significant with Newey-West inference. Adjacent-lag analyses did not identify a robust positive day-specific association after false discovery rate correction. Conclusion: Outpatient influenza A positivity showed clearer temporal alignment with subsequent fever-clinic burden than influenza B. Although the fixed 15-day estimate was sensitive to period restriction and residual serial correlation, influenza A positivity may still serve as a complementary hospital-level surveillance indicator rather than a stand-alone forecasting tool.

Indexed as

FeverInfluenza A virusInfluenza B virusInfluenza, HumanChinaCOVID-19HumansRetrospective StudiesTime Factorsfever clinichealthcare utilizationhospital preparednessinfluenza Ainfluenza Brespiratory virus surveillance

Identifiers

PMID42812401
PMCPMC13619934

What Socratic holds

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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 Socratic graph.