Evidence map›Paper›PMID 40017849›Full record

ArticleBMJ public health2023

Assessing disparity in the distribution of HIV and sexually transmitted infections in Australia: a retrospective cross-sectional study using Gini coefficients.

Phyu Mon Latt, Nyi Nyi Soe, Xianglong Xu, Rashidur Rahman, Eric P F Chow, Jason J Ong, Christopher Fairley, Lei Zhang

Abstract read
In one paragraph

Article in BMJ public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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.

Phyu Mon LattCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.ORCID 0000-0001-5880-5731
Nyi Nyi SoeCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.
Xianglong XuArtificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Carlton, Victoria, Australia.
Rashidur RahmanMelbourne Sexual Health Centre, Alfred Health, Carlton, Victoria, Australia.
Eric P F ChowCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.ORCID 0000-0003-1766-0657
Jason J OngCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.ORCID 0000-0001-5784-7403
Christopher FairleyCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.
Lei ZhangCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.ORCID 0000-0003-2343-084X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The risk of HIV and sexually transmitted infections (STIs) varies substantially across population groups in Australia. We examined this disparity in HIV/STI distribution using Gini coefficients, where scores closer to one indicate greater disparity. Methods: We used demographic and sexual behaviour data from the Melbourne Sexual Health Centre, between 2015 and 2018. We examined 88 642 HIV consultations, 92 291 syphilis consultations, 97 473 gonorrhoea consultations and 115 845 chlamydia consultations. We applied a machine learning-based risk assessment tool, MySTIRisk, to determine the risk scores. Based on individuals' risk scores and HIV/STIs diagnoses, we calculated the Gini coefficients for these infections for different subgroups. Results: Overall, Gini coefficients were highest for syphilis (0.60, 95% CI 0.57 to 0.64) followed by HIV (0.57, 95% CI 0.52 to 0.62), gonorrhoea (0.38, 95% CI 0.36 to 0.42) and chlamydia (0.31, 95% CI 0.28 to 0.35). Gay, bisexual and other men who have sex with men (GBMSM) had lower Gini coefficients compared with heterosexual men or women; HIV (0.54 vs 0.94 vs 0.96), syphilis (0.50 vs 0.86 vs 0.93), gonorrhoea (0.24 vs 0.57 vs 0.57) and chlamydia (0.23 vs 0.42 vs 0.40), respectively. The Gini coefficient was lower among 25-34 years than in other age groups for HIV (0.66 vs 0.83-0.90) and gonorrhoea (0.38 vs 0.43-0.47). For syphilis, the oldest age group (≥45 years) had a lower Gini coefficient than 18-24 years (0.61 vs 0.70). Conclusions: Our study demonstrated that HIV/STIs are more evenly distributed among GBMSM, suggesting widely disseminated interventions for GBMSM communities. In contrast, interventions for heterosexual men and women should be more targeted at individuals with higher risk scores.

Indexed as

Communicable Disease ControlDisease Transmission, InfectiousPublic HealthRisk Assessment

Identifiers

PMID40017849
PMCPMC11812685

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.