Evidence map›Paper›PMID 42082527›Full record

ArticleNPJ systems biology and applications2026

Spatiotemporal instability of influenza seasonality during viral co-circulation.

Hong Liu, Xuanfeng Li, Ning Sun, Jingjing Tian, Ming Xu, Chitin Hon

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 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
–field-weighted citation impact
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

6 authors.

Hong Liu *Respiratory Disease AI Laboratory in Epidemic Intelligence and Applications of Medical Big Data Instruments, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau SAR, China.
Xuanfeng Li *Respiratory Disease AI Laboratory in Epidemic Intelligence and Applications of Medical Big Data Instruments, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau SAR, China.
Ning SunRespiratory Disease AI Laboratory in Epidemic Intelligence and Applications of Medical Big Data Instruments, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau SAR, China.
Jingjing TianRespiratory Disease AI Laboratory in Epidemic Intelligence and Applications of Medical Big Data Instruments, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau SAR, China.
Ming XuDepartment of Global Health, School of Public Health, Peking University, Beijing, China. xum2022@pku.edu.cn.
Chitin HonRespiratory Disease AI Laboratory in Epidemic Intelligence and Applications of Medical Big Data Instruments, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau SAR, China. cthon@must.edu.mo.

Funding

Major Project of Guangzhou National Laboratory GZNL2024A01004National Key Research and Development Program of China 2024YFE0214800Science and Technology Development Fund of Macau SAR 0002/2024/RDP
6 · The paper itself

Abstract

Co-circulation of multiple influenza subtypes poses a major challenge to global public health. However, its specific impact on non-stationary epidemic sequences and coupling relationships with environmental drivers remains poorly understood. By integrating STL, Adaptive Fourier Decomposition, Continuous Wavelet Transform, and Wavelet Coherence, we analyzed 323 weekly influenza surveillance time series from China (2011-2025). The study identifies a fundamental regime shift during co-circulation periods, transitioning from ordered single-dominant transmission to a chaotic state. This instability is characterized by significant dominant periodicity dispersion, amplified seasonality shifts, and high-intensity anomalies in residual components, with overall seasonal strength dropping by 28%. Crucially, we uncover a marked north-south mechanistic divergence: northern regions exhibited "Environmental Locking," remaining strongly constrained by climates during co-circulation; conversely, southern regions demonstrated "Environmental Decoupling" (H3N2 phase consistency with soil moisture plummeted from R=0.45 to 0.07), where viral ecological competition overshadowed environmental drivers. Influenza co-circulation acts as a systemic perturbation reshaping transmission dynamics. Our findings highlight the necessity for context-adaptive strategies: northern regions can maintain reliance on meteorological warnings, while southern regions must dynamically shift focus toward real-time virological surveillance during co-circulation to capture rapid ecological shifts.

Indexed as

Influenza, HumanChinaClimateHumansInfluenza A Virus, H3N2 SubtypeSeasonsSpatio-Temporal Analysis

Identifiers

PMID42082527
PMCPMC13346841

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.