Evidence map›Paper›PMID 34308213›Full record

ArticleThe East African health research journal2020

From Preparedness to Recovery: Learning Lessons Of COVID-19 Outbreak from China.

Charles Nsanzabera, Leonard Ndayisenga, Jean Damascene Kabakambira, Felix Hagenimana

Open access · diamondAbstract read
In one paragraph

Article in The East African health research journal, 2020. 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, top 95% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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 at 3 institutions in 3 countries.

Charles NsanzaberaDepartment of health science, School of Public Health, Jomo Kenyatta University of Agriculture and Technology, Kenya.
Leonard NdayisengaProject Medical Referent, Abdurafi Neglected Diseases and Outbreak response Project, Amhara regional state of Ethiopia, MSF Holland, Ethiopia Mission.
Jean Damascene KabakambiraDepartment of Internal Medicine University Teaching Hospital of Kigali, Rwanda.
Felix HagenimanaDepartment of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Kenya.
Jomo Kenyatta University of Agriculture and Technology · KECentre Hospitalier Universitaire de Kigali · RWGovernment of Ethiopia · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At the end of December 2019, the Chinese public health authorities reported several cases of acute respiratory syndrome in Wuhan City, Hubei province, China. Chinese scientists soon identified a novel coronavirus as the main causative agent. The disease is now referred to as coronavirus disease 2019 (COVID-19), and the causative virus is called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 outbreak was declared a pandemic by the World Health Organization on March 12th, 2020. COVID-19 propagates quickly and threatens the population at large; around 20% of affected populations have presented severe forms of the diseases. In China approximately ~5% cases became critical patients in need of admission to intensive-care units. The need for intensive care has led to unprecedented overcrowding in hospitals, with catastrophic situations witnessed in Italy and other countries. The highest mortality rates have been witnessed amongst the elderly with several comorbidities. In this viewpoint we draw lessons from the implementation of population containment measures, vulnerable people protection and relevant public health pillars in China. We then discuss how these lessons can or cannot be applied to other settings.

Identifiers

PMID34308213
PMCPMC8279207
OpenAlexW3042645668

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.