Evidence map›Paper›PMID 41853162›Full record

ArticleFrontiers in public health2026

Divergent surveillance needs and resource allocation for COVID-19 and influenza: insights from a community-based syndromic surveillance study in Shanghai (2024-2025).

Xiao Yu, Shiying Yuan, Huanyu Wu, Shenghua Mao, Sheng Lin, Xianjin Jiang, Xiaohuan Gong, Chenyan Jiang, Yaxu Zheng, Jian Chen

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PubMed Full text at PMC Publisher
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers 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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xiao Yu *Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Shiying Yuan *Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Huanyu Wu *Institute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Shenghua MaoInstitute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Sheng LinInstitute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Xianjin JiangInstitute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Xiaohuan GongInstitute for Surveillance and Early Warning, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medical Sciences), Shanghai, China.
Chenyan JiangInstitute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.
Yaxu ZhengInstitute for Surveillance and Early Warning, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medical Sciences), Shanghai, China.
Jian ChenInstitute for Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention (Shanghai Academy of Preventive Medicine), Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 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.

Indexed as

COVID-19Influenza, HumanPopulation SurveillanceResource AllocationAdultChinaFemaleHumansMaleMiddle AgedSARS-CoV-2community-based syndromic surveillanceCOVID-19healthcare-seekingILIinfluenzasymptom profiles

Identifiers

PMID41853162
PMCPMC12992253

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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 OpenQuestion graph.