Evidence map›Paper›PMID 38495754›Full record

ArticlePeerJ2024

Impact of the coronavirus disease 2019 pandemic on the diversity of notifiable infectious diseases: a case study in Shanghai, China.

Yongfang Zhang, Wenli Feng

Abstract read
In one paragraph

Article in PeerJ, 2024. 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

2 authors.

Yongfang ZhangSchool of Chemistry and Chemical Engineering, Zhoukou Normal University, Zhoukou, China.
Wenli FengSchool of Chemistry and Chemical Engineering, Zhoukou Normal University, Zhoukou, China.ORCID 0000-0003-3107-5702

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of coronavirus disease 2019 (COVID-19) has not only posed significant challenges to public health but has also impacted every aspect of society and the environment. In this study, we propose an index of notifiable disease outbreaks (NDOI) to assess the impact of COVID-19 on other notifiable diseases in Shanghai, China. Additionally, we identify the critical factors influencing these diseases using multivariate statistical analysis. We collected monthly data on 34 notifiable infectious diseases (NIDs) and corresponding environmental and socioeconomic factors (17 indicators) from January 2017 to December 2020. The results revealed that the total number of cases and NDOI of all notifiable diseases decreased by 47.1% and 52.6%, respectively, compared to the period before the COVID-19 pandemic. Moreover, the COVID-19 pandemic has led to improved air quality as well as impacted the social economy and human life. Redundancy analysis (RDA) showed that population mobility, particulate matter (PM2.5), atmospheric pressure, and temperature were the primary factors influencing the spread of notifiable diseases. The NDOI is beneficial in establishing an early warning system for infectious disease epidemics at different scales. Furthermore, our findings also provide insight into the response mechanisms of notifiable diseases influenced by social and environmental factors.

Indexed as

Communicable DiseasesCOVID-19ChinaDisease OutbreaksHumansPandemicsAir pollutantsCOVID-19EpidemiologyIndex of notifiable disease outbreaksInfluencing factorsNotifiable infectious disease

Identifiers

PMID38495754
PMCPMC10941765

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.