Evidence map›Paper›PMID 37496828›Full record

ArticleInfectious Disease Modelling2023

Effects and interaction of temperature and relative humidity on the trend of influenza prevalence: A multi-central study based on 30 provinces in mainland China from 2013 to 2018.

Yi Yin, Miao Lai, Sijia Zhou, Ziying Chen, Xin Jiang, Liping Wang, Zhongjie Li, Zhihang Peng

Open access · goldAbstract read
In one paragraph

Article in Infectious Disease Modelling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 6% of its field
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Yi YinSchool of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Miao LaiSchool of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Sijia ZhouSchool of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Ziying ChenSchool of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Xin JiangSchool of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Liping WangDivision of Infectious Disease/Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhongjie LiSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zhihang PengSchool of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Nanjing Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNChinese Center For Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China. Methods: We estimated the time-varying reproduction number ( Results: Low temperature and low relative humidity contributed to influenza epidemics on the national level, while shapes of merged cumulative effect plots were different across regions. Compared to that of median temperature, the merged RR (95%CI) of low temperature in northern and southern regions were 1.40(1.24,1.45) and 1.20 (1.14,1.27), respectively, while those of high temperature were 1.10(1.03,1.17) and 1.00 (0.95,1.04), respectively. There were negative interactions between temperature and relative humidity on national (SI = 0.59, 95%CI: 0.57-0.61), southern (SI = 0.49, 95%CI: 0.17-0.80), and northern regions (SI = 0.59, 95%CI: 0.56,0.62). In general, with the increase of the change of the two meteorological factors, the ER of Conclusions: Temperature and relative humidity have an effect on the influenza epidemics in China, and there is an interaction between the two meteorological factors, but the effect of each factor is heterogeneous among regions. Meteorological factors may be considered to predict the trend of influenza epidemic.

Indexed as

DLNMInfluenzaMeteorological factorsMulti-centralMultiple random-meta analysisRt

Identifiers

PMID37496828
PMCPMC10366480
OpenAlexW4383618214

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.