Evidence map›Paper›PMID 34941551›Full record

ArticleJMIR public health and surveillance2021

Availability and Suitability of Digital Health Tools in Africa for Pandemic Control: Scoping Review and Cluster Analysis.

Bernard C Silenou, John L Z Nyirenda, Ahmed Zaghloul, Berit Lange, Juliane Doerrbecker, Karl Schenkel, Gérard Krause

Abstract readScoping Review
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
–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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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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

7 authors.

Bernard C SilenouDepartment of Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany.ORCID 0000-0002-4826-0042
John L Z NyirendaDepartment of Infectious Diseases, University Hospital Freiburg, Medical Faculty, University of Freiburg, Freiburg, Germany.ORCID 0000-0003-0851-712X
Ahmed ZaghloulAfrica Centres for Disease Control and Prevention, Addis Ababa, Ethiopia.ORCID 0000-0001-7220-0798
Berit LangeDepartment of Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany.ORCID 0000-0002-9325-9307
Juliane DoerrbeckerDepartment of Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany.ORCID 0000-0002-5668-7433
Karl SchenkelWorld Health Organization, Geneva, Switzerland.ORCID 0000-0001-5444-9143
Gérard KrauseDepartment of Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany.ORCID 0000-0003-3328-8808

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundGaining oversight into the rapidly growing number of mobile health tools for surveillance or outbreak management in Africa has become a challenge.

objectiveThe aim of this study is to map the functional portfolio of mobile health tools used for surveillance or outbreak management of communicable diseases in Africa.

methodsWe conducted a scoping review by combining data from a systematic review of the literature and a telephone survey of experts. We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines by searching for articles published between January 2010 and December 2020. In addition, we used the respondent-driven sampling method and conducted a telephone survey from October 2019 to February 2020 among representatives from national public health institutes from all African countries. We combined the findings and used a hierarchical clustering method to group the tools based on their functionalities (attributes).

resultsWe identified 30 tools from 1914 publications and 45 responses from 52% (28/54) of African countries. Approximately 13% of the tools (4/30; Surveillance Outbreak Response Management and Analysis System, Go.Data, CommCare, and District Health Information Software 2) covered 93% (14/15) of the identified attributes. Of the 30 tools, 17 (59%) tools managed health event data, 20 (67%) managed case-based data, and 28 (97%) offered a dashboard. Clustering identified 2 exceptional attributes for outbreak management, namely contact follow-up (offered by 8/30, 27%, of the tools) and transmission network visualization (offered by Surveillance Outbreak Response Management and Analysis System and Go.Data).

conclusionsThere is a large range of tools in use; however, most of them do not offer a comprehensive set of attributes, resulting in the need for public health workers having to use multiple tools in parallel. Only 13% (4/30) of the tools cover most of the attributes, including those most relevant for response to the COVID-19 pandemic, such as laboratory interface, contact follow-up, and transmission network visualization.

Indexed as

COVID-19PandemicsAfricaCluster AnalysisHumansSARS-CoV-2communicable diseasesepidemiological surveillancehealth information managementmHealthmobile applicationsoutbreak responsepublic healthreviewtransmission network

Identifiers

PMID34941551
PMCPMC8738990

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.