Evidence map›Paper›PMID 39702381›Full record

ArticleBMC research notes2024

The identification and spatial distribution of hotspots of tuberculosis occurrence in South Africa.

Thandi Kapwata, Gregory Breetzke, Caradee Y Wright, Tessa S Marcus

Abstract read
In one paragraph

Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

4 authors.

Thandi KapwataEnvironment and Health Research Unit, South African Medical Research Council, Johannesburg, 2193, South Africa. Thandi.Kapwata@mrc.ac.za.
Gregory BreetzkeDepartment of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, 0002, South Africa.
Caradee Y WrightDepartment of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, 0002, South Africa.
Tessa S MarcusCOPC Research Unit, Faculty of Health Sciences, University of Pretoria, Pretoria, 0002, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePrior research has shown strong evidence of spatial clustering of tuberculosis across a range of contexts. Identifying the spatial patterning of infectious diseases such as tuberculosis is crucial as it allows for targeted intervention strategies, directing healthcare resources efficiently to areas where tuberculosis incidence is concentrated. This is especially true for low- and middle-income countries that typically experience greater resource constraints relative to their Global North counterparts. In this study, we extend existing literature by investigating the spatial patterning of tuberculosis among vulnerable communities in South Africa, notably in the relatively under-researched provinces of the North-West and Gauteng.

resultsData for this study were collected from several locations implementing community-oriented primary care in the country. Community health workers used AitaHealth™, a custom-built mobile information management application, to obtain data on tuberculosis status and environmental conditions of households. We find notable clusters of tuberculosis in these provinces which we speculate could be associated with urban formal and informal settlement densification and overcrowding, the incidence of mining activities prevalent in sampled locations and poor access to healthcare.

Indexed as

TuberculosisDisease HotspotFemaleHumansIncidenceSouth AfricaSpatial AnalysisGISInfectious diseaseSpatial scan statistics

Identifiers

PMID39702381
PMCPMC11657308

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LicenceCC BY-NC-ND
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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.