Targeting core groups for gonorrhoea control: feasibility and impact

Giguère, Katia; Alary, Michel

doi:10.1136/sextrans-2014-051732

Cited by 6 publications

(8 citation statements)

References 25 publications

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“…28 Studies of gonorrhoea have also shown localised clustering of cases, and the impact of geotargeted interventions to these areas. 6 However, empirical and modelling studies of other infectious diseases identified several factors affecting the potential effects of targeting hotspots, including the connectivity between hotspots and other areas, the reproductive numbers of infections in each location, and the timing of interventions. 1,3 HIV spreads between geographical areas through two mechanisms: when infection is spread between sexual partners from different communities of residence, and when infection is spread by migration of people infected with HIV.…”

Section: Discussionmentioning

confidence: 99%

“…1 Targeting core groups has been used in the control of sexually transmitted infections for decades, 5 for example gonorrhoea, in which geo-targeted approaches to high-burden areas have proved effective. 6 With respect to HIV, the President's Emergency Plan for AIDS Relief, the Global Fund, WHO, and UNAIDS among others have advocated geographical targeting of HIV control interventions to hotspots. 7,8 These recommendations include calls for HIV elimination in the USA, based on targeting of geo graphical hotspots to "disrupt the kinetics of HIV spread".…”

Section: Introductionmentioning

confidence: 99%

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Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

et al. 2020

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Background International and global organisations advocate targeting interventions to areas of high HIV prevalence (ie, hotspots). To better understand the potential benefits of geo-targeted control, we assessed the extent to which HIV hotspots along Lake Victoria sustain transmission in neighbouring populations in south-central Uganda. Methods We did a population-based survey in Rakai, Uganda, using data from the Rakai Community Cohort Study. The study surveyed all individuals aged 15-49 years in four high-prevalence Lake Victoria fishing communities and 36 neighbouring inland communities. Viral RNA was deep sequenced from participants infected with HIV who were antiretroviral therapy-naive during the observation period. Phylogenetic analysis was used to infer partial HIV transmission networks, including direction of transmission. Reconstructed networks were interpreted through data for current residence and migration history. HIV transmission flows within and between high-prevalence and low-prevalence areas were quantified adjusting for incomplete sampling of the population. Findings Between Aug 10, 2011, and Jan 30, 2015, data were collected for the Rakai Community Cohort Study. 25 882 individuals participated, including an estimated 75•7% of the lakeside population and 16•2% of the inland population in the Rakai region of Uganda. 5142 participants were HIV-positive (2703 [13•7%] in inland and 2439 [40•1%] in fishing communities). 3878 (75•4%) people who were HIV-positive did not report antiretroviral therapy use, of whom 2652 (68•4%) had virus deep-sequenced at sufficient quality for phylogenetic analysis. 446 transmission networks were reconstructed, including 293 linked pairs with inferred direction of transmission. Adjusting for incomplete sampling, an estimated 5•7% (95% credibility interval 4•4-7•3) of transmissions occurred within lakeside areas, 89•2% (86•0-91•8) within inland areas, 1•3% (0•6-2•6) from lakeside to inland areas, and 3•7% (2•3-5•8) from inland to lakeside areas. Interpretation Cross-community HIV transmissions between Lake Victoria hotspots and surrounding inland populations are infrequent and when they occur, virus more commonly flows into rather than out of hotspots. This result suggests that targeted interventions to these hotspots will not alone control the epidemic in inland populations, where most transmissions occur. Thus, geographical targeting of high prevalence areas might not be effective for broader epidemic control depending on underlying epidemic dynamics.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

et al. 2020

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“…Accordingly, the observed variation could impact the ideal combination of local HIV interventions (Nosyk et al, 2020). These findings also suggest that efforts to target high-risk individuals to prevent STIs (Giguère & Alary, 2015) may not yield the expected prevention benefits if these individuals do not maintain a consistent level of risk. However, to the extent that these temporary periods of high-risk can be understood and predicted, tailored interventions could be implemented for individuals during these periods.…”

Section: Discussionmentioning

confidence: 99%

Temporal variation in one-time partnership rates among young men who have sex with men and transgender women

Janulis¹,

Goodreau

Birkett³

et al. 2020

Preprint

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Background: Volatility in sexual contact rates has been recognized as an important factor influencing HIV transmission dynamics. One-time partnerships may be particularly important given the potential to quickly accumulate large number of contacts. Yet, empirical data documenting individual variation in contact rates remains rare. This study provides much needed data on temporal variation in one-time partners to better understand behavioral dynamics and improve the accuracy of transmission models. Methods: Data for this study from a longitudinal cohort study of young men who have sex with men (MSM) and transgender women in Chicago. Participants provided sexual network data every 6-months for 2 years. A series of random effects models examined variation in one-time partnership rates and disaggregated within and between associations of exposure variables. Exposure variables included prior number of one-time partners, number of casual partners, and having a main partner. Results: Results indicated substantial between and within person variation in one-time partners. Casual partnerships were positively associated and main partnerships negatively association with one-time partnership rates. There remained a small positive association between prior one-time partnerships and the current number of one-time partnerships. Conclusions: Despite the preponderance of a low number of one-time partners, substantial variation in one-time partnership rates exists among young MSM and transgender women. Accordingly, focusing on high contact rate individuals alone may be insufficient to identify periods of highest risk. Future studies should utilize these estimates to more accurately model how volatility impacts HIV transmission and better understand how this variation influences intervention effectiveness.

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“…21 Accordingly, the observed variation could impact the ideal combination of local HIV interventions. 45 These findings also suggest efforts to target high-risk individuals to prevent STIs 46 may not yield the expected prevention benefits if these individuals do not maintain consistent levels of risk. However, to the extent that these temporary periods of high-risk can be understood and predicted, tailored interventions could be implemented during these periods.…”

Section: Discussionmentioning

confidence: 99%

Temporal Variation in One-Time Partnership Rates Among Young Men Who Have Sex With Men and Transgender Women

Janulis

Goodreau²,

Birkett

et al. 2021

JAIDS Journal of Acquired Immune Deficiency Syndromes

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Targeting core groups for gonorrhoea control: feasibility and impact

Cited by 6 publications

References 25 publications

Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

Temporal variation in one-time partnership rates among young men who have sex with men and transgender women

Temporal Variation in One-Time Partnership Rates Among Young Men Who Have Sex With Men and Transgender Women

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