Evidence map›Paper›PMID 35847656›Full record

ArticleJournal of biosafety and biosecurity2022

2021-2022 monitoring, early warning, and forecasting of global infectious diseases.

Jie Luan, Jianbo Ba, Bin Liu, Xiongli Xu, Dong Shu

Open access · goldAbstract read
In one paragraph

Article in Journal of biosafety and biosecurity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
0.8field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. 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

5 authors at 2 institutions in 1 country.

Jie LuanNaval Medical Center of PLA, 880 Xiangyin Road, Yangpu District, Shanghai, China.
Jianbo BaNaval Medical Center of PLA, 880 Xiangyin Road, Yangpu District, Shanghai, China.
Bin LiuNaval Medical Center of PLA, 880 Xiangyin Road, Yangpu District, Shanghai, China.
Xiongli XuNaval Medical Center of PLA, 880 Xiangyin Road, Yangpu District, Shanghai, China.
Dong ShuNaval Medical Center of PLA, 880 Xiangyin Road, Yangpu District, Shanghai, China.
Second Military Medical University · CNPLA Navy General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has had a considerable impact on society since 2019, and the disease has high mortality and infection rates. There has been a particular focus on how to best manage COVID-19 and how to analyze and predict the epidemic status of infectious diseases in general. Methods The present study analyzed the COVID-19 epidemic patterns and made predictions of future trends based on the statistics obtained from a global infectious disease network data monitoring and early warning system (OBN, http://27.115.41.130:8888/OBN/). The development trends of other major infectious diseases were also examined. Results The global COVID-19 pandemic showed periodic increases throughout 2021. At present, there is a high incidence in European countries, especially in Eastern Europe, followed by in Africa. The risk of contracting COVID-19 was divided into high, medium-high, medium, medium-low, and low grades depending on the stage of the epidemic in each examined region over the current period. The occurrence and prevalence of major infectious diseases throughout the world did not significantly change in 2021. Conclusions The COVID-19 pandemic has strongly impacted people's lives and the economy. The effects of global infectious diseases can be ameliorated by strengthening monitoring and early warning systems and by facilitating the international exchange of information.

Indexed as

COVID-19EpidemicPredictStatus and development trend

Identifiers

PMID35847656
PMCPMC9270068
OpenAlexW4284965868

What OpenQuestion holds

Textmetadata
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.