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

Gini coefficientshave been used to describe the distribution of Chlamydia trachomatis (CT) infections among individuals with different levels of sexual activity. The objectives of this study were to investigate Gini coefficientsfor different sexually transmitted infections (STIs), and to determine how STI control interventions might affect the Gini coefficientover time. We used population-based data for sexually experienced women from two British National Surveys of Sexual Attitudes and Lifestyles (Natsal-2: 1999-2001; Natsal-3: 2010-2012) to calculate Gini coefficientsfor CT, Mycoplasma genitalium(MG), and human papillomavirus (HPV) types 6, 11, 16 and 18. We applied bootstrap methods to assess uncertainty and to compare Gini coefficientsfor different STIs. We then used a mathematical model of STI transmission to study how control interventions affect Gini coefficients. Gini coefficientsfor CT and MG were 0.33 (95% confidence interval (CI): 0.18-0.49) and 0.16 (95% CI: 0.02-0.36), respectively. The relatively small coefficient for MG suggests a longer infectious duration compared with CT. The coefficients for HPV types 6, 11, 16 and 18 ranged from 0.15-0.38. During the decade between Natsal-2 and Natsal-3, the Gini coefficientfor CT did not change. The transmission model shows that higher STI treatment rates are expected to reduce prevalence and increase the Gini coefficientof STIs. In contrast, increased condom use reduces STI prevalence but does not affect the Gini coefficient. Gini coefficientsfor STIs can help us to understand the distribution of STIs in the population, according to level of sexual activity, and could be used to inform STI prevention and treatment strategies.