Heterogeneity of the COVID-19 epidemic: what can we learn from it?

Qiuli Chen, Yibeltal Assefa, Peter Wang, Guifen Li

Abstract readReview

In one paragraph

Review in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Qiuli ChenDepartment of Research and Development, Zhejiang Zhongwei Medical Research Center Hangzhou 310018, Zhejiang, China.

Yibeltal AssefaSchool of Public Health, The University of Queensland Brisbane, Australia.

Peter WangDepartment of Research and Development, Zhejiang Zhongwei Medical Research Center Hangzhou 310018, Zhejiang, China.

Guifen LiThe First People's Hospital of Fuyang Hangzhou 311400, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe goal of this article is to evaluate and explain the heterogeneity of the Coronavirus disease 2019 (COVID-19) epidemic in Australia, to offer advice for stopping the current outbreak and preparing for a suitable response to epidemics in the future.

methodsWe conducted a review to analyze the epidemic and explain its variable manifestation across states in Australia. Most COVID-19 cases and deaths were in the states of Victoria and New South Wales due to differences in the governance of the epidemic and public health responses (quarantine and contact tracing) among states.

resultsCountries could learn from Australia's overall successful response not only through good governance, effective community participation, adequate public health, adequate health system capacity and multisectoral actions but also from the heterogeneity of the epidemic among states.

conclusionsA successful response to epidemics in countries with a decentralized administration requires multilevel governance with alignment and harmonization of the response.

Indexed as

COVID-19epidemicgovernancehealth responsesSARS-CoV-2

Identifiers

PMID36398230

PMCPMC9641441

What OpenQuestion holds

Textmetadata

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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.