Gsteiger Sandro, Low Nicola, Sonnenberg Pam, Mercer Catherine H, Althaus Christian L
Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
Institute for Global Health, University College London, London, UK.
PeerJ. 2020 Jan 20;8:e8434. doi: 10.7717/peerj.8434. eCollection 2020.
Gini coefficients have been used to describe the distribution of (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.
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, (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.
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.
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.
基尼系数已被用于描述不同性活动水平个体中沙眼衣原体（CT）感染的分布情况。本研究的目的是调查不同性传播感染（STI）的基尼系数，并确定性传播感染控制干预措施如何随时间影响基尼系数。
我们使用了来自两项英国全国性性态度和生活方式调查（Natsal - 2：1999 - 2001；Natsal - 3：2010 - 2012）的有性经历女性的基于人群的数据，来计算CT、生殖支原体（MG）以及人乳头瘤病毒（HPV）6、11、16和18型的基尼系数。我们应用自助法来评估不确定性，并比较不同性传播感染的基尼系数。然后，我们使用性传播感染传播的数学模型来研究控制干预措施如何影响基尼系数。
CT和MG的基尼系数分别为0.33（95%置信区间[0.18 - 0.49]）和0.16（95%置信区间[0.02 - 0.36]）。MG相对较小的系数表明其感染持续时间比CT长。HPV 6、11、16和18型的系数范围为0.15至0.38。在Natsal - 2和Natsal - 3之间的十年中，CT的基尼系数没有变化。传播模型表明，较高的性传播感染治疗率预计会降低患病率并增加性传播感染的基尼系数。相比之下，增加避孕套的使用会降低性传播感染患病率，但不影响基尼系数。
性传播感染的基尼系数可以帮助我们根据性活动水平了解性传播感染在人群中的分布情况，并可用于为性传播感染的预防和治疗策略提供信息。
