Evidence map›Paper›PMID 34749835›Full record

ReviewOne health outlook2021

Twenty years of integrated disease surveillance and response in Sub-Saharan Africa: challenges and opportunities for effective management of infectious disease epidemics.

Irene R Mremi, Janeth George, Susan F Rumisha, Calvin Sindato, Sharadhuli I Kimera, Leonard E G Mboera

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in One health outlook, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

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

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2 more citing papers are in PubMed but not listed here.

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.

Irene R MremiDepartment of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania. irene.mremi@sacids.org.ORCID http://orcid.org/0000-0003-2578-7500
Janeth GeorgeDepartment of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania.ORCID http://orcid.org/0000-0002-4111-8748
Susan F RumishaNational Institute for Medical Research, Dar es Salaam, Tanzania.ORCID http://orcid.org/0000-0001-7058-488X
Calvin SindatoSACIDS Foundation for One Health, Sokoine University of Agriculture, Morogoro, Tanzania.ORCID http://orcid.org/0000-0003-3040-165X
Sharadhuli I KimeraDepartment of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania.ORCID http://orcid.org/0000-0002-2295-0643
Leonard E G MboeraSACIDS Foundation for One Health, Sokoine University of Agriculture, Morogoro, Tanzania.ORCID http://orcid.org/0000-0001-5746-3776

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis systematic review aimed to analyse the performance of the Integrated Disease Surveillance and Response (IDSR) strategy in Sub-Saharan Africa (SSA) and how its implementation has embraced advancement in information technology, big data analytics techniques and wealth of data sources.

methodsHINARI, PubMed, and advanced Google Scholar databases were searched for eligible articles. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols.

resultsA total of 1,809 articles were identified and screened at two stages. Forty-five studies met the inclusion criteria, of which 35 were country-specific, seven covered the SSA region, and three covered 3-4 countries. Twenty-six studies assessed the IDSR core functions, 43 the support functions, while 24 addressed both functions. Most of the studies involved Tanzania (9), Ghana (6) and Uganda (5). The routine Health Management Information System (HMIS), which collects data from health care facilities, has remained the primary source of IDSR data. However, the system is characterised by inadequate data completeness, timeliness, quality, analysis and utilisation, and lack of integration of data from other sources. Under-use of advanced and big data analytical technologies in performing disease surveillance and relating multiple indicators minimises the optimisation of clinical and practice evidence-based decision-making.

conclusionsThis review indicates that most countries in SSA rely mainly on traditional indicator-based disease surveillance utilising data from healthcare facilities with limited use of data from other sources. It is high time that SSA countries consider and adopt multi-sectoral, multi-disease and multi-indicator platforms that integrate other sources of health information to provide support to effective detection and prompt response to public health threats.

Indexed as

Big dataData sourceDisease surveillanceOne HealthPerformanceSub-Saharan Africa

Identifiers

PMID34749835
PMCPMC8575546

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.