Evidence map›Paper›PMID 42359003›Full record

ArticleFrontiers in cellular and infection microbiology2026

Three-stage interpretability analysis of influenza virus and meteorological correlation in Jiuquan City, 2016-2025: SARIMAX + TreeSHAP.

Biao Wang, Xia Han, Maoxing Dong, Hui Zhang, Hong Shi, Huan Wei, Miao Wang, Xiaoshu Zhang, Shu Liang, Congshan Xu

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 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

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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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0 citing papers in PubMed.

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4 · The record

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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.

Biao WangGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Xia HanJiuquan Center for Disease Control and Prevention, Jiuquan, China.
Maoxing DongGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Hui ZhangGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Hong ShiLanzhou Center for Disease Control and Prevention, Lanzhou, China.
Huan WeiGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Miao WangGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Xiaoshu ZhangGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Shu LiangGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Congshan XuGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The COVID-19 pandemic has profoundly altered global influenza circulation. This study aimed to investigate the impact of meteorological factors on influenza transmission in Jiuquan, China, during three distinct phases: before, during, and after the COVID-19 pandemic. Methods: Weekly influenza surveillance and concurrent weather data were modeled using seasonally adjusted SARIMAX to capture temporal and seasonal structures. An XGBoost surrogate was trained to emulate the SARIMAX outputs, and TreeSHAP was applied to decompose and quantify the relative contributions of the environmental variables. Results: 2016-2019: Influenza followed the northern hemisphere winter-spring pattern, with A/H3N2 being predominant. 2020: COVID-19 non-pharmaceutical interventions suppressed transmission; positivity rates decreased sharply, and a 78-week "low circulation" persisted. Post-mitigation relaxation: 2023-24 winter resurgence. Weeks with positivity >10% increased from approximately seven pre-pandemic to approximately 11 post-pandemic. Overall positivity differed across phases (pre:25.29%; pandemic:12.07%; post:12.42%; P<0.001). SARIMAX explained moderate variance pre-COVID (R Conclusion: During COVID-19, NPIs drastically suppressed influenza transmission in Jiuquan, disrupting its winter-spring cycle and causing prolonged "low circulation". Following relaxation, immunity debt fueled stronger and longer seasonal resurgences, with subtype niche shifts; influenza rebounded but not to pre-pandemic levels after relaxation. Stable temperature effects and shifting roles of wind, pressure, and thermal gradients may reflect environmental-behavioral transmission restructuring, highlighting region-specific, immunity- and seasonality-informed control strategies.

Indexed as

COVID-19Influenza, HumanMeteorological ConceptsChinaHumansInfluenza A Virus, H3N2 SubtypeOrthomyxoviridaePandemicsSARS-CoV-2SeasonsTemperatureWeatherCOVID-19 pandemicinfluenzameteorological factorsnon-pharmaceutical interventionstime-series dynamics

Identifiers

PMID42359003
PMCPMC13290768

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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.