Evidence map›Paper›PMID 38854464›Full record

ArticleChina CDC weekly2024

The Impact of Medical Resources and Oral Antiviral Drugs on SARS-CoV-2 Mortality - Hong Kong SAR, China, 2022.

Zhiqi Zeng, Jingyi Liang, Zhijie Lin, Wenda Guan, Wei He, Qianying Li, Lixi Liang, Weiqi Pan, Zige Liu, Guibin Lu and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in China CDC weekly, 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

14 authors.

Zhiqi ZengGuangzhou key laboratory for clinical rapid diagnosis and early warning of infectious diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Jingyi LiangMacao Institute of Systems Engineering, Macao University of Science and Technology, Macau SAR, China.
Zhijie LinRespiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications, Faculty of Innovative Engineering, Macau University of Science and Technology, Macau SAR, China.
Wenda GuanState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Wei HeMacao Institute of Systems Engineering, Macao University of Science and Technology, Macau SAR, China.
Qianying LiState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Lixi LiangState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Weiqi PanState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Zige LiuMacao Institute of Systems Engineering, Macao University of Science and Technology, Macau SAR, China.
Guibin LuMacao Institute of Systems Engineering, Macao University of Science and Technology, Macau SAR, China.
Xiaoyan DengGuangzhou key laboratory for clinical rapid diagnosis and early warning of infectious diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Eric Hy LauSchool of Public Health, The University of Hong Kong, Hong Kong SAR, China.
Chitin HonMacao Institute of Systems Engineering, Macao University of Science and Technology, Macau SAR, China.
Zifeng YangGuangzhou key laboratory for clinical rapid diagnosis and early warning of infectious diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou City, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrates increased transmissibility compared to earlier strains, contributing to a significant number of fatalities in Hong Kong Special Administrative Region (HKSAR), China. Adequate medical resources and medications are essential in mitigating these deaths. This study evaluates the effects of supplementary resources from the Chinese mainland during the fifth wave of the pandemic in HKSAR. Methods: Vector autoregression (VAR) was employed to analyze data from the Oxford coronavirus disease 2019 (COVID-19) Government Response Tracker to assess the effectiveness of control measures during five waves of the pandemic in HKSAR. Additionally, a transmission dynamics model was created to investigate the influence of supplementary medical resources from the Chinese mainland and oral medications on mortality. Results: In the initial four waves, workplace closures, restrictions on public events, international travel bans, and shielding the elderly significantly influenced pandemic management. Contrarily, during the fifth wave, these measures showed no notable effects. When comparing a situation without extra medical resources or COVID-19 oral medication, there was a 17.7% decrease in COVID-19 fatalities with mainland medical resources and an additional 10.2% reduction with oral medications. Together, they contributed to a 26.6% decline in fatalities. Discussion: With the rapid spread of the virus, regional reallocation of medical resources may reduce mortality even when the local healthcare system is overstretched.

Indexed as

efficacymedical resourcesoral medicinesSARS-CoV-2 Omicron variant

Identifiers

PMID38854464
PMCPMC11154106

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.