Gini coefficients for measuring the distribution of sexually transmitted infections among individuals with different levels of sexual activity

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

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.

Quantifying heterogeneity in sexual behaviour and distribution of STIs before and after pre-exposure prophylaxis among men who have sex with men

Objectives: Pre-exposure prophylaxis (PrEP) use may influence sexual behaviour and transmission of STIs among men who have sex with men (MSM). We aimed to quantify the distribution of STI diagnoses among MSM in the Netherlands based on their sexual behaviour before and after the introduction of PrEP.Methods: HIV-negative MSM participating in a prospective cohort study (Amsterdam Cohort Studies) completed questionnaires about sexual behaviour and were tested for STI/HIV during biannual visits (2009-2019). We developed a sexual behaviour risk score predictive of STI diagnosis and used it to calculate Gini coefficients for gonorrhoea, chlamydia and syphilis diagnoses in the period before (2009 to mid-2015) and after PrEP (mid-2015 to 2019). Gini coefficients close to zero indicate that STI diagnoses are homogeneously distributed over the population, and close to one indicate that STI diagnoses are concentrated in individuals with a higher risk score.Results: The sexual behaviour risk score (n=630, n visits=10 677) ranged between 0.00 (low risk) and 3.61 (high risk), and the mean risk score increased from 0.70 (SD=0.66) before to 0.93 (SD=0.80) after PrEP. Positivity rates for chlamydia (4%) and syphilis (1%) remained relatively stable, but the positivity rate for gonorrhoea increased from 4% before to 6% after PrEP. Gini coefficients increased from 0.37 (95% CI 0.30 to 0.43) to 0.43 (95% CI 0.36 to 0.49) for chlamydia, and from 0.37 (95% CI 0.19 to 0.52) to 0.50 (95% CI 0.32 to 0.66) for syphilis comparing before to after PrEP. The Gini coefficient for gonorrhoea remained stable at 0.46 (95% CI 0.40 to 0.52) before and after PrEP.Conclusions: MSM engaged in more high-risk sexual behaviour and gonorrhoea diagnoses increased after PrEP was introduced. Chlamydia and syphilis diagnoses have become more concentrated in a high-risk subgroup. Monitoring the impact of increasing PrEP coverage on sexual behaviour and STI incidence is important. Improved STI prevention is needed, especially for high-risk MSM.

Inequality indices to monitor geographic differences in incidence, mortality and fatality rates over time during the COVID-19 pandemic

BACKGROUND

It is of interest to explore the variability in how the COVID-19 pandemic evolved geographically during the first twelve months. To this end, we apply inequality indices over regions to incidences, infection related mortality, and infection fatality rates. If avoiding of inequality in health is an important political goal, a metric must be implemented to track geographical inequality over time.

METHODS

The relative and absolute Gini index as well as the Theil index are used to quantify inequality. Data are taken from international data bases. Absolute counts are transformed to rates adjusted for population size.

RESULTS

Comparing continents, the absolute Gini index shows an unfavorable development in four continents since February 2020. In contrast, the relative Gini as well as the Theil index support the interpretation of less inequality between European countries compared to other continents. Infection fatality rates within the EU as well as within the U.S. express comparable improvement towards more equality (as measured by both Gini indices).

CONCLUSIONS

The use of inequality indices to monitor changes in geographic inequality over time for key health indicators is a valuable tool to inform public health policies. The absolute and relative Gini index behave complementary and should be reported simultaneously in order to gain a meta-perspective on very complex dynamics.