Evidence map›Paper›PMID 34692616›Full record

ArticleFrontiers in public health2021

COVID-19 Pandemic & Bureaucracy: The Crisis Inside the Crisis.

Katalyn Roßmann, Heike Wegner, Hans Stark, Gerd Großmann, Andreas Jansen, Dimitrios Frangoulidis

Abstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors.

Katalyn RoßmannBundeswehr Medical Service Headquarters VI-2, Medical Intelligence & Information (MI2), Munich, Germany.
Heike WegnerBundeswehr Centre for Software Expertise (BwCSE), Euskirchen, Germany.
Hans StarkBundeswehr Centre for Software Expertise (BwCSE), Euskirchen, Germany.
Gerd GroßmannBundeswehr Medical Service Headquarters VI-2, Medical Intelligence & Information (MI2), Munich, Germany.
Andreas JansenFederal Information Centre for International Health Protection, Robert Koch-Institute, Berlin, Germany.
Dimitrios FrangoulidisBundeswehr Medical Service Headquarters VI-2, Medical Intelligence & Information (MI2), Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Medical Intelligence and Information (MI2) Unit of the German Armed Forces (Bundeswehr) is experienced in crisis support in military missions since several years. It gained additional experiences during the current coronavirus 2019 (COVID-19) pandemic on different levels of the response to crisis and was requested to share the findings and expertise with the overloaded civil public health agencies inside Germany. Since the beginning of the pandemic, the unit is constantly developing new products for crisis communication, knowledge sharing techniques in new databases, dashboards for leadership, and training for laypersons in contact tracing. Hence, trying to innovate in crisis since the first severe acute respiratory syndrome coronavirus (SARS-CoV)-2-disease wave. During the second wave, the unit was requested to evaluate the outbreak management of different national civil public health agencies in southern Germany, and to support the development of dashboards in a comprehensive public health approach as a necessary start toward digitalization.

Indexed as

COVID-19PandemicsContact TracingDisease OutbreaksHumansSARS-CoV-2BundeswehrCOVID-19crisisCynefin frameworkevaluation matrixinnovationlayperson trainingpublic health dashboard

Identifiers

PMID34692616
PMCPMC8528952

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.