Evidence map›Paper›PMID 35898696›Full record

ArticleMedComm2022

Outbreak control management: Lessons from SARS-CoV-2 infections in 2020-2022 in Hong Kong, an international municipality with high-frequency travelers.

Yaxiu Feng, Ching Han Young, Siu Hin Lau, Ming-Liang He

Abstract read
In one paragraph

Article in MedComm, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. What we learned from lifting COVID-19 restrictions in Macao in December 2022.International journal of biological sciences · 2023
    Article
  4. Article
  5. 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

4 authors.

Yaxiu FengDepartment of Biomedical Sciences City University of Hong Kong Hong Kong China.ORCID https://orcid.org/0000-0002-9488-8404
Ching Han YoungDepartment of Biomedical Sciences City University of Hong Kong Hong Kong China.
Siu Hin LauDepartment of Biomedical Sciences City University of Hong Kong Hong Kong China.
Ming-Liang HeDepartment of Biomedical Sciences City University of Hong Kong Hong Kong China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The control management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is one of the most challenges in the 21st century. By May 8th, 2022, SARS-CoV-2 has infected over 510 million people with 6.2 million death worldwide and over 1.2 million people with 9133 deaths in the fifth wave of infection in Hong Kong. The government responded rapidly in the early days of the 2020 outbreak, and the results were encouraging to control COVID-19 outbreak unavailable of vaccine. The quick responses to the epidemic alerts, for example, public education and control policies, kept residents safe from infection in the city with such a high population density and large-scale travelers. Nevertheless, the extremely high infectivity, Omicron variant infections, and the shortcomings of transmission control measures led to uncontrollable outbreak in 2022. The weak immunity groups, elderly and children, experienced a high hospitalization rate and mortality rate because of low vaccination rate. Currently, the infection is under well controlled. This study timely summarizes the challenges, policy, and lessons of SARS-CoV-2 outbreak control from 2020 to 2022. More importantly, the lesson and policy revealed from this study may be beneficial and applied to other cities with the outbreak of highly infectious SARS-CoV-2.

Indexed as

infection controlOmicron variantoutbreak managementSARS‐CoV‐2

Identifiers

PMID35898696
PMCPMC9309738

What OpenQuestion holds

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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.