Evidence map›Paper›PMID 35989440›Full record

ArticleEpidemiology and infection2022

Assessing government policies' impact on the COVID-19 pandemic and elderly deaths in East Asia.

Cathy W S Chen, Mike K P So, Feng-Chi Liu

Open access · goldAbstract read
In one paragraph

Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.5field-weighted citation impact, top 4% 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

7 citing papers in PubMed, 32 citations in OpenAlex.

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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

3 authors at 2 institutions in 2 countries.

Cathy W S ChenDepartment of Statistics, Feng Chia University, Taiwan.ORCID 0000-0001-8727-8168
Mike K P SoDepartment of Information Systems, Business Statistics and Operations Management, Hong Kong University of Science and Technology, Hong Kong.ORCID 0000-0003-0781-8166
Feng-Chi LiuDepartment of Statistics, Feng Chia University, Taiwan.ORCID 0000-0002-0385-9836
Feng Chia University · TWHong Kong University of Science and Technology · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study assesses governments' long-term non-pharmaceutical interventions upon the coronavirus disease 2019 (COVID-19) pandemic in East Asia. It advances the literature towards a better understanding of when and which control measures are effective. We (1) provide time-varying case fatality ratios and focus on the elderly's mortality and case fatality ratios, (2) measure the correlations between daily new cases (daily new deaths) and each index based on multiple domestic pandemic waves and (3) examine the lead-lag relationship between daily new cases (daily new deaths) and each index via the cross-correlation functions on the pre-whitened series. Our results show that the interventions reduce COVID-19 infections for some periods before the period of the Omicron variant. Moreover, there is no COVID-19 policy lag in Taiwan between daily new confirmed cases and each index. As of March 2022, the case fatality ratios of the elderly group in Japan, Hong Kong and South Korea are 4.69%, 4.72% and 1.48%, respectively, while the case fatality ratio of the elderly group in Taiwan is 25.01%. A government's COVID-19 vaccination distribution and prioritisation policies are pivotal for the elderly group to reduce the number of deaths. Immunising this specific group as best as possible should undoubtedly be a top priority.

Indexed as

COVID-19PandemicsAgedAsia, EasternCOVID-19 VaccinesGovernmentHumansPolicySARS-CoV-2COVID-19 VaccinesCase fatality ratioCOVID-19elderly groupnon-pharmaceutical interventionsSpearman's rank correlation

Identifiers

PMID35989440
PMCPMC9472036
OpenAlexW4292567136

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.