Evidence map›Paper›PMID 41736010›Full record

ArticleBMC public health2026

Long-term trends of influenza-like illness and severe acute respiratory infection across pandemic phases: an interrupted time-series study.

Ying Guo, Ning Ma, Huimin Xu, Fangyi Zhu, Wanyu Qiao, Ye Yao, Weibing Wang

Abstract read
In one paragraph

Article in BMC 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

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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ying GuoShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.
Ning MaZhongshan Hospital Wusong Branch, Fudan University, Shanghai, China.
Huimin XuZhongshan Hospital Wusong Branch, Fudan University, Shanghai, China.
Fangyi ZhuSchool of Public Health, Nanchang University, Nanchang, Jiangxi Province, China.
Wanyu QiaoSchool of Public Health, Fudan University, Shanghai, China.
Ye YaoShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China. yyao@fudan.edu.cn.
Weibing WangShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China. wwb@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInfluenza-like illness (ILI) and severe acute respiratory infection (SARI) remain significant public health burdens, particularly among older adults and in resource-limited settings. However, long-term epidemiologic trends across different pandemic phases remain poorly understood, especially for vulnerable populations.

methodsSurveillance and hospital records collected between 2017 and 2024 from two sentinel hospitals in Shanghai, China, were analyzed. Interrupted time-series (ITS) models were used to evaluate temporal changes in ILI and SARI incidence. Large-scale data processing techniques were applied to extract structured information from unstructured medical records, enabling comprehensive analysis of clinical characteristics and outcomes.

resultsBoth ILI and SARI cases declined sharply during the COVID-19 pandemic but rebounded thereafter. Older adults (≥60 years) experienced disproportionately greater increases in these cases, along with higher risks of ILI-to-SARI progression and ICU admission. Although clinical recovery rates improved in the post-pandemic period, the demand for oxygen therapy and hospital-based care remained elevated.

conclusionThese findings highlight the long-term impact of the COVID-19 pandemic on respiratory infection dynamics and underscore the need for targeted interventions for older adults. Despite highest susceptibility and baseline risk for severe illness, older adults demonstrated improved post-pandemic clinical outcomes due to enhanced clinical prioritization. Strengthening vaccination programs, improving health education, and enhancing resource preparedness are crucial to reduce the post-pandemic disease burden, particularly in settings with limited healthcare capacity. These findings provide important evidence to strengthen post-pandemic respiratory surveillance and improve protection strategies for older adults in China.

Indexed as

COVID-19Influenza, HumanPandemicsRespiratory Tract InfectionsSevere Acute Respiratory SyndromeAdolescentAdultAgedChinaFemaleHumansIncidenceInterrupted Time Series AnalysisMaleMiddle AgedYoung AdultCOVID-19Influenza-like IllnessSevere Acute Respiratory Infection

Identifiers

PMID41736010
PMCPMC13037121

What OpenQuestion holds

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LicenceCC BY-NC-ND
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None linked

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.