Double trouble: modelling the impact of low risk perception and high-risk sexual behaviour on chlamydia transmission

Longitudinal Patterns of Sexually Transmitted Infection Risk Based on Psychological Characteristics and Sexual Behavior in Heterosexual Sexually Transmitted Infection Clinic Visitors

We identified longitudinal patterns of STI risk based on psychological and behavioral characteristics, and these characteristics did not change over time in most participants, irrespective of sexually transmitted infection test results.

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Background

Great heterogeneity in sexually transmitted infections (STI) risk exists, and investigating individual-level characteristics related to changes in STI risk over time might facilitate the development and implementation of effective evidence-based behavior change interventions. The aim of this study was to identify longitudinal patterns of STI risk based on psychological and behavioral characteristics.

Methods

A longitudinal study was conducted among heterosexual STI clinic visitors aged 18 to 24 years. Latent classes based on behavioral and psychological characteristics at baseline, and transitions from 1 latent class to another at 3-week, 6-month, and 1-year follow-up, were identified using latent transition analysis.

Results

Four latent classes were identified that could be differentiated by psychological and behavioral characteristics and STI risk: overall low-risk (10%), insecure high-risk (21%), condom-users (38%), and confident high-risk (31%). Although the majority of the total study population did not move to another latent class over time, the size of the overall low-risk group increased from 10% at baseline to 30% after 1 year. This was mainly due to transitions from the insecure high-risk, condom-users, and confident high-risk class at 3-week follow-up to the overall low-risk class at 6-month follow-up.

Conclusions

Distinct subgroups among heterosexual STI clinic visitors can be differentiated from each other by multiple psychological and behavioral characteristics, and these characteristics reflecting the risk of acquiring STI are consistent over the course of 1 year in most individuals. An integral approach, adapting behavioral interventions to match multiple psychological and behavioral characteristics of high-risk subgroups, might be more effective in controlling STI transmission.

Modelling the impact of tailored behavioural interventions on chlamydia transmission

Behavioural interventions tailored to psychological characteristics of an individual can effectively achieve risk-reducing behaviour. The impact of tailored interventions on population-level chlamydia prevalence is unknown. We aimed to assess the impact on overall chlamydia prevalence five years after the introduction of an intervention aimed at increasing self-efficacy, social norms, attitudes and intentions towards condom use (i.e., condom intervention), and an intervention aimed at increasing health goals and decreasing impulsiveness (i.e., impulsiveness intervention). A pair model, informed by longitudinal psychological and behavioural data of young heterosexuals visiting sexual health centers, with susceptible-infected-susceptible structure was developed. The intervention effect was defined as an increased proportion of each subgroup moving to the desired subgroup (i.e., lower risk subgroup). Interventions tailored to subgroup-specific characteristics, assuming differential intervention effects in each subgroup, more effectively reduced overall chlamydia prevalence compared to non-tailored interventions. The most effective intervention was the tailored condom intervention, which was assumed to result in a relative reduction in chlamydia prevalence of 18% versus 12% in the non-tailored scenario. Thus, it is important to assess multiple psychological and behavioural characteristics of individuals. Tailored interventions may be more successful in achieving risk-reducing behaviour, and consequently, reduce chlamydia prevalence more effectively.

Introducing pre-exposure prophylaxis to prevent HIV acquisition among men who have sex with men in Sweden: insights from a mathematical pair formation model

OBJECTIVES

Since 2017, the Public Health Agency of Sweden recommends that pre-exposure prophylaxis (PrEP) for HIV should be offered to high-risk individuals, in particular to men who have sex with men (MSM). The objective of this study is to develop a mathematical model investigating the effect of introducing PrEP to MSM in Sweden.

DESIGN

A pair formation model, including steady and casual sex partners, is developed to study the impact of introducing PrEP. Two groups are included in the model: sexually high active MSM and sexually low active MSM. Three mixing assumptions between the groups are considered.

SETTING

A gay-friendly MSM HIV/sexually transmitted infection testing clinic in Stockholm, Sweden. This clinic started offering PrEP to MSM in October 2018.

PARTICIPANTS

The model is calibrated according to detailed sexual behaviour data gathered in 2015 among 403 MSM.

RESULTS

By targeting sexually high active MSM, a PrEP coverage of 3.5% of the MSM population (10% of all high actives) would result in the long-term HIV prevalence to drop considerably (close to 0%). While targeting only low actives would require a PrEP coverage of 35% for a similar reduction. The main effect of PrEP is the reduced susceptibility, whereas the increased HIV testing rate (every third month) among PrEP users plays a lesser role.

CONCLUSIONS

To create a multifaceted picture of the effects of interventions against HIV, we need models that include the different stages of HIV infection and real-world data on detailed sexual behaviour to calibrate the mathematical models. Our findings conclude that targeting HIV high-risk individuals, within HIV risk populations such as MSM, with PrEP programmes could greatly decrease the long-term HIV prevalence in Sweden. Therefore, risk stratification of individuals is of importance in PrEP implementation programmes, to ensure optimising the effect and cost-effectiveness of such programmes.

A Multidimensional Approach to Assessing Infectious Disease Risk: Identifying Risk Classes Based on Psychological Characteristics

Prevention of infectious diseases depends on health-related behavior, which is often influenced by psychological characteristics. However, few studies assessing health-related behavior have examined psychological characteristics to identify risk groups, and this multidimensional approach might improve disease risk assessment. We aimed to characterize subgroups based on psychological characteristics and examine their influence on behavior and disease risk, using chlamydia as a case study. Selected participants (heterosexuals aged 18–24 years and females aged 18–24 years who had sex with both men and women) in a Dutch longitudinal cohort study (the Mathematical Models Incorporating Psychological Determinants: Control of Chlamydia Transmission (iMPaCT) Study) filled out a questionnaire and were tested for chlamydia (2016–2017). Latent class analysis was performed to identify risk classes using psychological predictors of chlamydia diagnosis. Two classes were identified: class 1 (n = 488; 9% chlamydia diagnosis) and class 2 (n = 325; 13% chlamydia diagnosis). The proportion of participants with high shame, high impulsiveness, and lower perceived importance of health was higher in class 2 than in class 1. Furthermore, persons in class 2 were more likely to be male and to report condomless sex compared with class 1, but the number of recent partners was comparable. Thus, risk classes might be distinguished from each other by psychological characteristics beyond sexual behavior. Therefore, the impact of the same intervention could differ, and tailoring interventions based on psychological characteristics might be necessary to reduce chlamydia prevalence most effectively.

Who drops out and when? Predictors of non-response and loss to follow-up in a longitudinal cohort study among STI clinic visitors

Introduction

Response rates in health research are declining, and low response rates could result in biased outcomes when population characteristics of participants systematically differ from the non-respondents. Few studies have examined key factors of non-response beyond demographic characteristics, such as behavioral and psychological factors. The aim of the current study was to identify predictors of non-response and loss to follow-up in a longitudinal sexual health study.

Materials and methods

A longitudinal cohort study (iMPaCT) was conducted from November 2016 to July 2018 among heterosexual STI clinic visitors aged 18–24 years. At four different time points in one year, data was collected on sexual behavior, psychological determinants and chlamydia infections. The national STI surveillance database provided data on demographic, behavioral and sexual health-related characteristics for non-respondents. Predictors of non-response at baseline and of loss to follow-up were identified using multivariable logistic regression analyses.

Results

In total, 13,658 STI clinic visitors were eligible to participate, of which 1,063 (8%) participated. Male gender, low/medium education level, young age (≤ 20 years) and having a non-Dutch migration background were significant predictors of non-response at baseline. Furthermore, non-respondents at baseline were more likely to report STI-related symptoms, to have been notified by a partner, to have had condomless sex, and to have had ≤ 2 partners in the past six months, compared to participants. Psychological predictors of loss to follow-up differed between STI clinic regions, but low perceived importance of health at baseline was associated with loss to follow-up in all regions. The baseline chlamydia positivity rate was significantly higher in the non-respondents (17%) compared to the participants (14%), but was not a predictor of loss to follow-up.

Discussion

Targeted recruitment aimed at underrepresented groups in the population based on demographic, behavioral and psychological characteristics, might be necessary to decrease loss to follow-up, and to prevent non-response bias in health research.