Evidence map›Paper›PMID 32521811›Full record

ArticleInternational journal of environmental research and public health2020

Preparing for the Next Wave of COVID-19: Resilience in the Face of a Spreading Pandemic.

Gerald Steiner, Lukas Zenk, Eva Schernhammer

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-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, 13 citations in OpenAlex.

  1. Article
  2. Fast Response to Superspreading: Uncertainty and Complexity in the Context of COVID-19.International journal of environmental research and public health · 2020
    Article
  3. Review
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.

Gerald SteinerDepartment of Knowledge and Communication Management, Faculty of Business and Globalization, Danube University Krems, 3500 Krems an der Donau, Austria.ORCID 0000-0003-3340-3941
Lukas ZenkDepartment of Knowledge and Communication Management, Faculty of Business and Globalization, Danube University Krems, 3500 Krems an der Donau, Austria.
Eva SchernhammerComplexity Science Hub Vienna, 1090 Vienna, Austria.ORCID 0000-0002-4337-9415
Universität für Weiterbildung Krems · ATHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 painfully demonstrates how little resilience our societies have to novel viruses. Societies, decision makers, and scientists lack (1) a comprehensive understanding of the complexity of viral outbreaks and their impact on society; (2) intervention portfolios; and (3) a global crisis and resilience policy, all of which are required to develop appropriate measures and to improve societal resilience. We highlight COVID-19 immunity as one key benchmark in preparation for the next wave of the pandemic. Specifically, using network scenarios, we demonstrate the substantial advantage of reintegrating health care workers with acquired COVID-19 immunity in epidemic hotspots, which would not only enable their safe contribution to the health care system but also drastically contain further spread.

Indexed as

BenchmarkingBetacoronavirusCommunicable Disease ControlCoronavirus InfectionsCOVID-19Health Services Needs and DemandHumansInfectious Disease MedicinePandemicsPneumonia, ViralSARS-CoV-2COVID-19healthcare workersnetwork scenariospandemic spread

Identifiers

PMID32521811
PMCPMC7312045
OpenAlexW3033583368

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.