Abstract
ObjectivesGini coefficients have 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 coefficients for different sexually transmitted infections (STIs), and to determine how STI control interventions might affect the Gini coefficient over time.MethodsWe 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 coefficients for 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 coefficients for different STIs. We then used a mathematical model of STI transmission to study how control interventions affect Gini coefficients.ResultsGini coefficients for CT and MG were 0.33 (95% 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 to 0.38. During the decade between Natsal-2 and Natsal-3, the Gini coefficient for CT did not change. The transmission model shows that higher STI treatment rates are expected to reduce prevalence and increase the Gini coefficient of STIs. In contrast, increased condom use reduces STI prevalence but does not affect the Gini coefficient.ConclusionsGini coefficients for 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.
Highlights
Understanding how sexually transmitted infections (STIs) are distributed among individuals is important both from a biological and from a public health perspective
This indicates that Chlamydia trachomatis (CT) and human papillomavirus (HPV)-18 in women are more strongly associated with the number of new opposite-sex partners in the last year than Mycoplasma genitalium (MG) and the other type-specific HPV
The Lorenz curves for CT for the two survey periods of Natsal-2 (1999–2001) and Natsal-3 (2010–2012) are similar (Fig. 1C) with a Gini coefficient in Natsal-2 of 0.30 and in Natsal-3 of 0.33
Summary
Understanding how sexually transmitted infections (STIs) are distributed among individuals is important both from a biological and from a public health perspective. Gini coefficients for measuring the distribution of sexually transmitted infections among individuals with different levels of sexual activity. An STI with a long infectious duration, such as human papillomavirus (HPV), will tend to be spread more evenly across a population than an STI with a short infectious duration, such as Neisseria gonorrhoeae (NG). NG is more concentrated in a small subgroup of individuals with high sexual activity. Such ideas were initiated in the late 1970s and led to the concept of the “core group” (Hethcote Herbert & Yorke, 1984). In 1990, Brunham & Plummer (1990) inferred the size of core groups for various STIs from the biological parameters that describe transmissibility and infectious duration, and discussed the implications for selecting adequate STI control strategies
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