Evidence map›Paper›PMID 31299907›Full record

ArticleBMC infectious diseases2019

Spatial analysis of HIV-TB co-clustering in Uganda.

Augustus Aturinde, Mahdi Farnaghi, Petter Pilesjö, Ali Mansourian

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors at 1 institution in 2 countries.

Augustus AturindeGIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, SE-221 00, Lund, Sweden.
Mahdi FarnaghiGIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, SE-221 00, Lund, Sweden.
Petter PilesjöGIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, SE-221 00, Lund, Sweden.
Ali MansourianGIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, SE-221 00, Lund, Sweden. ali.mansourian@nateko.lu.se.ORCID http://orcid.org/0000-0001-6812-4307
Lund University · SE

Funding

Styrelsen för Internationellt Utvecklingssamarbete 2015-003424
6 · The paper itself

Abstract

backgroundTuberculosis (TB) is the leading cause of death for individuals infected with Human immunodeficiency virus (HIV). Conversely, HIV is the most important risk factor in the progression of TB from the latent to the active status. In order to manage this double epidemic situation, an integrated approach that includes HIV management in TB patients was proposed by the World Health Organization and was implemented in Uganda (one of the countries endemic with both diseases). To enable targeted intervention using the integrated approach, areas with high disease prevalence rates for TB and HIV need to be identified first. However, there is no such study in Uganda, addressing the joint spatial patterns of these two diseases.

methodsThis study uses global Moran's index, spatial scan statistics and bivariate global and local Moran's indices to investigate the geographical clustering patterns of both diseases, as individuals and as combined. The data used are TB and HIV case data for 2015, 2016 and 2017 obtained from the District Health Information Software 2 system, housed and maintained by the Ministry of Health, Uganda.

resultsResults from this analysis show that while TB and HIV diseases are highly correlated (55-76%), they exhibit relatively different spatial clustering patterns across Uganda. The joint TB/HIV prevalence shows consistent hotspot clusters around districts surrounding Lake Victoria as well as northern Uganda. These two clusters could be linked to the presence of high HIV prevalence among the fishing communities of Lake Victoria and the presence of refugees and internally displaced people camps, respectively. The consistent cold spot observed in eastern Uganda and around Kasese could be explained by low HIV prevalence in communities with circumcision tradition.

conclusionsThis study makes a significant contribution to TB/HIV public health bodies around Uganda by identifying areas with high joint disease burden, in the light of TB/HIV co-infection. It, thus, provides a valuable starting point for an informed and targeted intervention, as a positive step towards a TB and HIV-AIDS free community.

Indexed as

Cluster AnalysisCoinfectionHIV InfectionsHumansPrevalenceRisk FactorsSpatial AnalysisTuberculosisUgandaBivariate Moran’s IHIVMoran’s ISpatial co-clusteringSpatial scan statisticsTBTB/HIV co-infectionUganda

Identifiers

PMID31299907
PMCPMC6625059
OpenAlexW2958022795

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.