Evidence map›Paper›PMID 36052353›Full record

ArticleJournal of environmental and public health2022

Based on Contaminated Water and Human Health to Change of China's International Image Under Mainstream Media Reports During the COVID-19 Pandemic.

Kaixi Ji, Mengqian Zhou, Zitong Yang, Haiyong Zong

Open access · hybridAbstract read
In one paragraph

Article in Journal of environmental and public health, 2022. 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, top 91% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

4 authors at 1 institution in 1 country.

Kaixi JiSchool of Liberal Arts, Nantong University, Nantong 226000, China.ORCID 0000-0003-2048-6258
Mengqian ZhouSchool of Liberal Arts, Nantong University, Nantong 226000, China.
Zitong YangSchool of Liberal Arts, Nantong University, Nantong 226000, China.
Haiyong ZongSchool of Marxism, Nantong University, Nantong 226000, China.ORCID 0000-0002-0634-5021
Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As water quality can be an indicator of public health, it cannot be ignored. We can regard the international image of a country as a kind of soft national power, which embodies the comprehensive strength of the country and plays a very important role in safeguarding the interests of a country. This article aims to study the changes in China's international image under mainstream media reports during the COVID-19 pandemic. This article is based on contaminated water and human health to study the concept of the international image, the optimization path of China's international image, and the SEIR model. The SEIR model is one of the classic infectious disease models. Because the virus infection rate in this model is constant, it is difficult to accurately determine the spread of new coronary pneumonia. To model and complete the pandemic trend prediction and other issues, this article proposes a virus infection rate prediction method based on the long short-term memory network (LSTM), and combines it with the SEIR model to establish a new crown pneumonia pandemic trend prediction model (LS-Net). The conclusion of this article shows that in the fight against the novel coronavirus infectious pneumonia pandemic, the Chinese people have demonstrated the style of a big country. I have unreservedly passed on my own experience in pandemic prevention and control to countries around the world, and dispatched medical teams to provide the world with Chinese "prescriptions." Chinese diagnosis and treatment programs are the crystallization of common wisdom of Chinese medicine and Western medicine to support the world. All countries fight the pandemic together. In this analysis, Pakistan, Kenya, and Nigeria hold 84%, 85%, and 75% of China's positive views, respectively, 61% of Russians also have a positive attitude toward China.

Indexed as

COVID-19PandemicsChinaHumansPublic HealthSARS-CoV-2

Identifiers

PMID36052353
PMCPMC9427284
OpenAlexW4292787575

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.