Evidence map›Paper›PMID 36575769›Full record

ArticleScience China. Earth sciences2023

Correlation analysis between the occurrence of epidemic in ancient China and solar activity.

Si Chen, Yong Wei, Xin'an Yue, Kaihua Xu, Mingkun Li, Wei Lin

Abstract read
In one paragraph

Article in Science China. Earth sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Si ChenKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 China.
Yong WeiKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 China.
Xin'an YueKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 China.
Kaihua XuKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 China.
Mingkun LiBeijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing, 100101 China.
Wei LinKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the globe has witnessed the pandemic, epidemic diseases exert a strong impact on human beings and ecosystems. Since the Sun is the primary energy source of the Earth, some scientific pioneers attempted to search for the discernible relation between solar activity and the incidence of epidemics. In this study, the periodic changes and trends of ancient Chinese epidemic data were analyzed in comparison with those of sunspot numbers, a solar activity proxy. The results show that the epidemic and solar activity changes are in good agreement to a certain extent, especially during the Gleissberg and the de Vries cycles. The wavelet coherence shows that the frequency of the epidemic data and sunspot numbers are highly associated. In addition, results from the ensemble empirical mode decomposition illustrate consistent variations in low-frequency decompositions. This study has important implications for further understanding of the potential impact of solar activity on Earth's biosphere, the underlying mechanism of which needs further exploration.

Indexed as

Ancient ChinaEpidemicSolar activitySpectrum analysis

Identifiers

PMID36575769
PMCPMC9782271

What OpenQuestion holds

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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.