Evidence map›Paper›PMID 32997641›Full record

ArticleJMIR public health and surveillance2020

Novel Approach to Support Rapid Data Collection, Management, and Visualization During the COVID-19 Outbreak Response in the World Health Organization African Region: Development of a Data Summarization and Visualization Tool.

Kamran Ahmed, Muhammad Arish Bukhari, Tamayi Mlanda, Jean Paul Kimenyi, Polly Wallace, Charles Okot Lukoya, Esther L Hamblion, Benido Impouma

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Lessons Learned from the Lessons Learned in Public Health during the First Years of COVID-19 Pandemic.International journal of environmental research and public health · 2023
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Managing Pandemics with Health Informatics.Yearbook of medical informatics · 2021
    Review
  10. 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

8 authors.

Kamran AhmedRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0003-2473-1492
Muhammad Arish BukhariRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0001-6224-8667
Tamayi MlandaRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0001-9767-2898
Jean Paul KimenyiRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0003-0582-4036
Polly WallaceAustralian National University, Canberra, Australia.ORCID 0000-0002-3979-9281
Charles Okot LukoyaRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0001-7313-207X
Esther L HamblionRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0003-4250-3696
Benido ImpoumaRegional Office for Africa, World Health Organization, Brazzaville, Congo.ORCID 0000-0001-6363-7146

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has created unprecedented challenges to the systematic and timely sharing of COVID-19 field data collection and management. The World Health Organization (WHO) is working with health partners on the rollout and implementation of a robust electronic field data collection platform. The delay in the deployment and rollout of this electronic platform in the WHO African Region, as a consequence of the application of large-scale public health and social measures including movement restrictions and geographical area quarantine, left a gap between data collection and management. This lead to the need to develop interim data management solutions to accurately monitor the evolution of the pandemic and support the deployment of appropriate public health interventions.

objectiveThe aim of this study is to review the design, development, and implementation of the COVID-19 Data Summarization and Visualization (DSV) tool as a rapidly deployable solution to fill this critical data collection gap as an interim solution.

methodsThis paper reviews the processes undertaken to research and develop a tool to bridge the data collection gap between the onset of a COVID-19 outbreak and the start of data collection using a prioritized electronic platform such as Go.Data in the WHO African Region.

resultsIn anticipation of the implementation of a prioritized tool for field data collection, the DSV tool was deployed in 18 member states for COVID-19 outbreak data management. We highlight preliminary findings and lessons learned from the DSV tool deployment in the WHO African Region.

conclusionsWe developed a rapidly deployable tool for COVID-19 data collection and visualization in the WHO African Region. The lessons drawn on this experience offer an opportunity to learn and apply these to improve future similar public health informatics initiatives in an outbreak or similar humanitarian setting, particularly in low- and middle-income countries.

Indexed as

SoftwareAfricaCoronavirus InfectionsCOVID-19Data CollectionData ManagementData VisualizationDisease OutbreaksHumansPandemicsPneumonia, ViralWorld Health OrganizationCOVID-19data collectionEWARSGo.Datahealth emergencieshealth information managementoutbreakpandemicvisualizationWHO African region

Identifiers

PMID32997641
PMCPMC7593858

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.