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

Gsteiger, Sandro; Low, Nicola; Sonnenberg, Pam; Mercer, Catherine H; Althaus, Christian L (2020). Gini coefficients for measuring the distribution of sexually transmitted infections among individuals with different levels of sexual activity. PeerJ, 8, e8434. PeerJ, Ltd 10.7717/peerj.8434

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Objectives Gini 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. Methods 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 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. Results Gini 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. Conclusions Gini 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.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)

UniBE Contributor:

Gsteiger, Sandro; Low, Nicola and Althaus, Christian

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

2167-8359

Publisher:

PeerJ, Ltd

Funders:

[4] Swiss National Science Foundation

Language:

English

Submitter:

Andrea Flükiger-Flückiger

Date Deposited:

13 Feb 2020 16:11

Last Modified:

20 Feb 2020 14:47

Publisher DOI:

10.7717/peerj.8434

PubMed ID:

31998566

Uncontrolled Keywords:

Chlamydia trachomatis Gini coefficient HPV Lorenz curve Mathematical model Mycoplasma genitalium Sexual behavior Transmission model

BORIS DOI:

10.7892/boris.139932

URI:

https://boris.unibe.ch/id/eprint/139932

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