Evidence map›Paper›PMID 40304027›Full record

ArticleJournal of biomedical research2025

The association between weekly mean temperature and the epidemic of influenza across 122 countries/regions, 2014-2019.

Xiaoxiao Cao, Wenhao Zhu, Zhenghan Luo, Ran He, Yihao Li, Shirong Hui, Sheng Yang, Rongbin Yu, Peng Huang

Abstract read
In one paragraph

Article in Journal of biomedical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Xiaoxiao CaoDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Wenhao ZhuDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Zhenghan LuoDepartment of Infectious Disease Prevention and Control I, Center for Disease Control and Prevention, Eastern Theater of Operations, Nanjing, Jiangsu 210002, China.
Ran HeDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Yihao LiDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Shirong HuiDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Sheng YangDepartment of Biostatistics, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Rongbin YuDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
Peng HuangDepartment of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study examined the association between weekly mean temperature and influenza cases across 122 countries/regions (2014-2019) using a distributed lag non-linear model (DLNM). We analyzed 3145206 cases of overall influenza (Flu-All), with influenza A (Flu-A) and influenza B (Flu-B) accounting for 73.49% and 26.51%, respectively. Within a lag of 2 weeks, Flu-All incidence demonstrated a bimodal temperature relationship, with peak relative risks (RR) of 6.02 (95% CI: 1.92-20.77) at -8 ℃ and 3.08 (95% CI: 1.27-7.49) at 22 ℃. Flu-A exhibited a similar bimodal pattern, with RRs of 3.76 (95% CI: 2.39-5.91) at -8 ℃ and 2.08 (95% CI: 1.55-2.80) at 22 ℃. Flu-B demonstrated a single risk peak at 1 ℃ (RR = 4.48, 95% CI: 1.74-11.55). Subgroup analyses of climate zones revealed variations: tropical zones peaked at 12 ℃ (RR = 1.37, 95% CI: 1.08-1.74), while dry and temperate zones exhibited the highest risk at -5 ℃, with RRs of 4.49 (95% CI: 2.46-7.15) and 5.23 (95% CI: 3.17-8.64), respectively. Cold zones peaked at 1 ℃ (RR = 5.96, 95% CI: 3.76-9.43). Subgroup analyses of influenza transmission zones (ITZs) revealed variations: Africa showed higher risk between 6 ℃-14 ℃, Asia showed higher risk below 3 ℃, and Europe exhibited distinct risks of influenza peaks at -1 ℃ (Eastern), 1 ℃ (Southwest), and -20 ℃ (Northern). Elevated risks above 11 ℃ were identified in the Americas and Oceania. These findings establish a predictive framework for influenza outbreak preparedness by integrating regional temperature patterns with global climate variability.

Indexed as

climatic zonesinfluenzainfluenza subtypeinfluenza transmission zonestemperature

Identifiers

PMID40304027
PMCPMC12683506

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Registered trials

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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.