Annual hepatitis C testing and positive tests among gay and bisexual men in Australia from 2016 to 2022: a serial cross-sectional analysis of sentinel surveillance data.

OBJECTIVE: Guidelines recommend annual hepatitis C virus (HCV) testing for gay and bisexual men (GBM) with HIV and GBM prescribed HIV pre-exposure prophylaxis (PrEP). However, there is a limited understanding of HCV testing among GBM. We aimed to examine trends in HCV testing and positivity from 2016 to 2022. METHODS: Using sentinel surveillance data, we examined the proportion of GBM with at least one test and the proportion with a positive test in each year for HCV antibody testing among GBM with no previous HCV positive test, HCV RNA testing among GBM with a positive antibody test but no previous positive RNA test (naïve RNA testing), and HCV RNA testing among people who had a previous RNA positive test and a subsequent negative test (RNA follow-up testing). Trends were examined using logistic regression from 2016 to 2019 and 2020 to 2022. RESULTS: Among GBM with HIV, from 2016 to 2019 antibody testing was stable averaging 55% tested annually. Declines were observed for both naïve HCV RNA testing (75.4%-41.4%: p<0.001) and follow-up HCV RNA testing (70.1%-44.5%: p<0.001). Test positivity declined for HCV antibody tests (2.0%-1.3%: p=0.001), HCV RNA naïve tests (75.4%-41.4%: p<0.001) and HCV RNA follow-up tests (11.3%-3.3%: p=0.001). There were minimal or no significant trends from 2020 to 2022.Among GBM prescribed PrEP, antibody testing declined from 2016 to 2019 (79.4%-69.4%: p<0.001) and was stable from 2020 to 2022. Naïve and follow-up HCV RNA testing was stable with an average of 55% and 60% tested each year, respectively. From 2016-2019, the proportion positive from HCV RNA naïve tests declined (44.1%-27.5%: p<0.046) with no significant change thereafter. Positive follow-up HCV RNA tests fluctuated with no or one new positive test among this group in most years. CONCLUSION: The proportion of GBM with positive HCV tests has declined, however a substantial proportion are not tested annually. A renewed focus on HCV testing, and treatment where required, is warranted to achieve HCV elimination among GBM in Australia.

Hepatitis C virus reinfection incidence among gay and bisexual men with HIV in Australia from 2016 to 2020.

BACKGROUND: There is some concern that hepatitis C virus (HCV) reinfection might impact HCV micro-elimination efforts among gay and bisexual men (GBM) with HIV. However, there is a limited understanding of reinfection incidence in the context of unrestricted government-funded HCV treatment. We aimed to estimate HCV reinfection incidence among GBM with HIV in Australia from 2016 to 2020. METHODS: Data were from 39 clinics participating in ACCESS, a sentinel surveillance network for blood borne viruses and sexually transmissible infections across Australia. GBM with HIV who had evidence of treatment or spontaneous clearance with at least one positive HCV RNA test, a subsequent negative HCV RNA test, and at least one additional HCV RNA test between 1st January 2016 and 31st December 2020 were eligible for inclusion. A new HCV RNA positive test and/or detectable viral load was defined as a reinfection. Generalised linear modelling was used to examine trends in reinfection. RESULTS: Among 12 213 GBM with HIV who had at least one HCV test, 540 were included in the reinfection incidence analysis, of whom 38 (7%) had evidence of reinfection during the observation period. Over 1124 person-years of follow-up, the overall rate of reinfection was 3.4/100PY (95% CI 2.5-4.6). HCV reinfection incidence declined on average 30% per calendar year (Incidence Rate Ratio 0.70, 95% CI 0.54-0.91). CONCLUSION: HCV reinfection incidence has declined among GBM with HIV in Australia since government-funded unrestricted DAAs were made available. Ongoing HCV RNA testing following cure and prompt treatment for anyone newly diagnosed is warranted to sustain this.

COVID-19 epidemic modelling for policy decision support in Victoria, Australia 2020-2021.

BACKGROUND: Policy responses to COVID-19 in Victoria, Australia over 2020-2021 have been supported by evidence generated through mathematical modelling. This study describes the design, key findings, and process for policy translation of a series of modelling studies conducted for the Victorian Department of Health COVID-19 response team during this period. METHODS: An agent-based model, Covasim, was used to simulate the impact of policy interventions on COVID-19 outbreaks and epidemic waves. The model was continually adapted to enable scenario analysis of settings or policies being considered at the time (e.g. elimination of community transmission versus disease control). Model scenarios were co-designed with government, to fill evidence gaps prior to key decisions. RESULTS: Understanding outbreak risk following incursions was critical to eliminating community COVID-19 transmission. Analyses showed risk depended on whether the first detected case was the index case, a primary contact of the index case, or a 'mystery case'. There were benefits of early lockdown on first case detection and gradual easing of restrictions to minimise resurgence risk from undetected cases. As vaccination coverage increased and the focus shifted to controlling rather than eliminating community transmission, understanding health system demand was critical. Analyses showed that vaccines alone could not protect health systems and need to be complemented with other public health measures. CONCLUSIONS: Model evidence offered the greatest value when decisions needed to be made pre-emptively, or for questions that could not be answered with empiric data and data analysis alone. Co-designing scenarios with policy-makers ensured relevance and increased policy translation.

The Incidence of Hepatitis C Among Gay, Bisexual, and Other Men Who Have Sex With Men in Australia, 2009-2019.

BACKGROUND: Hepatitis C virus (HCV) infection has been reported among gay, bisexual, and other men who have sex with men (GBM) globally including GBM with human immunodeficiency virus (HIV) and HIV-negative GBM, particularly those using HIV preexposure prophylaxis (PrEP). In Australia, HCV direct-acting antiviral treatment (DAA) was government-funded from 2016. Large implementation studies of PrEP also began in 2016. We examined HCV incidence among GBM to assess whether HCV incidence has changed since 2015. METHODS: Data were drawn from the Australian Collaboration for Coordinated Enhanced Sentinel Surveillance. We included GBM who tested HCV antibody negative at their first test and had ≥1 subsequent test. Generalized linear modeling (Poisson distribution) was used to examine HCV incidence from 2009 to 2019 stratified by HIV status, and among HIV-negative GBM prescribed PrEP from 2016 to 2019. RESULTS: Among 6744 GBM with HIV, HCV incidence was 1.03 per 100 person-years (PY). Incidence declined by 78% in 2019 compared to 2015 (incidence rate ratio [IRR], 0.22 [95% confidence interval {CI}: .09-.55]). Among 20 590 HIV-negative GBM, HCV incidence was 0.20/100 PY, with no significant change over time. Among 11 661 HIV-negative GBM prescribed PrEP, HCV incidence was 0.29/100 PY. Compared to 2016, incidence among GBM prescribed PrEP declined by 80% in 2019 (IRR, 0.20 [95% CI: .06-.64]). CONCLUSIONS: HCV incidence among GBM living with HIV declined following DAA availability. There was no observed change in HCV incidence among HIV-negative GBM overall. Among GBM prescribed PrEP, incidence declined since the early years of PrEP implementation in Australia. Australia is on track to eliminate HCV among GBM before global 2030 targets.

Mathematical Modeling for Removing Border Entry and Quarantine Requirements for COVID-19, Vanuatu.

The Pacific Island country of Vanuatu is considering strategies to remove border restrictions implemented during 2020 to prevent imported coronavirus disease. We performed mathematical modeling to estimate the number of infectious travelers who had different entry scenarios and testing strategies. Travel bubbles and testing on entry have the greatest importation risk reduction.

Impact of COVID-19 lockdown restrictions on hepatitis C testing in Australian primary care services providing care for people who inject drugs.

In 2020, the Australian state of Victoria experienced the longest COVID-19 lockdowns of any jurisdiction, with two lockdowns starting in March and July, respectively. Lockdowns may impact progress towards eliminating hepatitis C through reductions in hepatitis C testing. To examine the impact of lockdowns on hepatitis C testing in Victoria, de-identified data were extracted from a network of 11 services that specialize in the care of people who inject drugs (PWID). Interrupted time-series analyses estimated weekly changes in hepatitis C antibody and RNA testing from 1 January 2019 to 14 May 2021 and described temporal changes in testing associated with lockdowns. Interruptions were defined at the weeks corresponding to the start of the first lockdown (week 14) and the start (week 80) and end (week 95) of the second lockdown. Pre-COVID, an average of 80.6 antibody and 25.7 RNA tests were performed each week. Following the first lockdown in Victoria, there was an immediate drop of 23.2 antibody tests and 8.6 RNA tests per week (equivalent to a 31% and 46% drop, respectively). Following the second lockdown, there was an immediate drop of 17.2 antibody tests and 4.6 RNA tests per week (equivalent to a 26% and 33% drop, respectively). With testing and case finding identified as a key challenge to Australia achieving hepatitis C elimination targets, the cumulative number of testing opportunities missed during lockdowns may prolong efforts to find, diagnose and engage or reengage in care of the remaining population of PWID living with hepatitis C.

A multi-site, nurse-coordinated hepatitis C model of care in primary care and community services in Melbourne, Australia.

BACKGROUND: Hepatitis C virus (HCV) treatment through primary care and community-based services will be a critical component of HCV elimination. We evaluated a nurse-coordinated programme providing care across eight sites and analysed progression through the HCV care cascade. METHODS: People-accessing services from six primary care clinics, a homeless crisis accommodation provider and a mental health service were directly referred to nurses or engaged by nurses during regular clinic visits. Nurses supported HCV testing, treatment and follow-up. The prescription was provided by affiliated clinicians. Logistic regression was used to examine factors associated with treatment commencement and sustained virological response (SVR) testing. RESULTS: Of 640 people referred to and/or engaged by the nurses from January 2017 to July 2019, 518 had an HCV RNA test of whom 381 (74%) were HCV RNA positive. Treatment was commenced by 281 (74%) people of whom 161 had an SVR test, 157 (97.5%) were cured. Opioid agonist therapy was associated with treatment commencement (aOR 2.68, 95% CI 1.48-4.88). People who were homeless/unstably housed were less likely to commence treatment (aOR 0.45, 95% CI 0.23-0.87). Treatment prescription from a specialist (aOR 2.39, 95% CI 1.20-4.74) and recent injection drug use (<6 months) (aOR 2.15, 95% CI 1.07-4.31) was associated with SVR testing. CONCLUSION: A nurse-coordinated model of care led to high levels of HCV treatment uptake and cure amongst people attending primary care and community services. More tailored models of care may be beneficial for people who are homeless or have unstable housing. These results support primary care and community-based hepatitis C treatment.

Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases.

BACKGROUND: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. METHODS: We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. RESULTS: We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. CONCLUSIONS: Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.

Injecting network structure determines the most efficient strategy to achieve Hepatitis C elimination in people who inject drugs.

Transmission of Hepatitis C (HCV) continues via sharing of injection equipment between people who inject drugs (PWID). Network-based modelling studies have produced conflicting results about whether random treatment is preferable to targeting treatment at PWID with multiple partners. We hypothesise that differences in the modelled injecting network structure produce this heterogeneity. The study aimed to test how changing network structure affects HCV transmission and treatment effects. We created three dynamic injecting network structures connecting 689 PWID (UK-net, AUS-net and USA-net) based on published empirical data. We modelled HCV in the networks and at 5 years compared prevalence of HCV 1) with no treatment, 2) with randomly targeted treatment and 3) with treatment targeted at PWID with the most injecting partnerships (degree-based treatment). HCV prevalence at 5 years without treatment differed significantly between the three networks (UK-net (42.8%) vs. AUS-net (38.2%), p < 0.0001 and vs. USA-net (54.0%), p < 0.0001). In the treatment scenarios UK-net and AUS-net showed a benefit of degree-based treatment with a 5-year prevalence of 1.0% vs. 9.6% p < 0.0001 and 0.15% vs. 0.44%, p < 0.0001. USA-net showed no significant difference (29.3% vs. 29.2%, p = 0.0681). Degree-based treatment was optimised with low prevalence, moderate treatment coverage conditions whereas random treatment was optimised in low treatment coverage, high prevalence conditions. In conclusion, injecting network structure determines the transmission rate of HCV and the most efficient treatment strategy. In real-world injecting network structures, the benefit of targeting HCV treatment at individuals with multiple injecting partnerships may have been underestimated.

Modelling the impact of relaxing COVID-19 control measures during a period of low viral transmission.

OBJECTIVES: To assess the risks associated with relaxing coronavirus disease 2019 (COVID-19)-related physical distancing restrictions and lockdown policies during a period of low viral transmission. DESIGN: Network-based viral transmission risks in households, schools, workplaces, and a variety of community spaces and activities were simulated in an agent-based model, Covasim. SETTING: The model was calibrated for a baseline scenario reflecting the epidemiological and policy environment in Victoria during March-May 2020, a period of low community viral transmission. INTERVENTION: Policy changes for easing COVID-19-related restrictions from May 2020 were simulated in the context of interventions that included testing, contact tracing (including with a smartphone app), and quarantine. MAIN OUTCOME MEASURE: Increase in detected COVID-19 cases following relaxation of restrictions. RESULTS: Policy changes that facilitate contact of individuals with large numbers of unknown people (eg, opening bars, increased public transport use) were associated with the greatest risk of COVID-19 case numbers increasing; changes leading to smaller, structured gatherings with known contacts (eg, small social gatherings, opening schools) were associated with lower risks. In our model, the rise in case numbers following some policy changes was notable only two months after their implementation. CONCLUSIONS: Removing several COVID-19-related restrictions within a short period of time should be undertaken with care, as the consequences may not be apparent for more than two months. Our findings support continuation of work from home policies (to reduce public transport use) and strategies that mitigate the risk associated with re-opening of social venues.

Estimating the number of new hepatitis C infections in Australia in 2015, prior to the scale-up of direct-acting antiviral treatment.

BACKGROUND AND AIM: The recent downward revision of the estimated number of people living with chronic hepatitis C in Australia means that the annual number of new hepatitis C infections should also be revised. We aimed to estimate the annual number of new hepatitis C infections among people who inject drugs (PWID) in Australia in 2015, prior to the introduction of direct-acting antiviral (DAA) treatment for hepatitis C, as an updated baseline measure for assessing the impact of DAAs on hepatitis C incidence over the next 10 years. METHODS: A systematic review identified articles estimating hepatitis C incidence rates among PWID between 2002 and 2015. Reported incidence rates were adjusted to account for unrepresentative needle and syringe program (NSP) coverage among study participants compared with PWID overall. The total number of PWID in Australia and the hepatitis C RNA prevalence among PWID were taken from published estimates. The annual number of new infections was estimated by multiplying the pooled NSP coverage-adjusted incidence rate by the number of susceptible PWID in 2015. RESULTS: Five studies were included, with unadjusted incidence rates ranging from 7.6 to 12.8 per 100 person-years. The overall pooled incidence rate (after adjusting for NSP coverage) was 9.9 per 100 person-years (95% confidence interval: 8.3-11.8). This led to an estimate of 4126 (range 2499-6405) new hepatitis C infections in 2015. CONCLUSIONS: Our updated estimate provides an important baseline for evaluating the impact of hepatitis C elimination efforts and can be used to validate outcomes of future modeling studies.

Measuring hepatitis C virus elimination as a public health threat: Beyond global targets.

An increasing number of countries are committing to meet the World Health Organization (WHO) targets to eliminate hepatitis C virus (HCV) as a public health threat by 2030. These include service coverage targets (90% diagnosed and 80% of diagnosed patients treated) and impact targets (80% and 65% reductions in incidence and mortality, respectively, compared to 2015 levels). Currently, a dozen countries are on track to reach 2030 WHO HCV targets. However, while striving for the WHO targets is important, it should be recognized that progress on impact targets is derived from mathematical models projecting decreases in incidence and mortality on a global scale. Despite HCV treatment access in many counties for a number of years, limited empirical data are available to evaluate progress towards elimination. In some countries, substantial incidence and mortality reductions based on reaching the WHO service coverage targets may be unachievable. For example, in countries with ageing hepatitis C-infected populations, even if they have a quality hepatitis C response, high hepatitis C-related morbidity at baseline may not be reversible even with increased HCV treatment uptake and diagnosis. Finally, WHO targets are not necessarily easily or reliably measurable. Measuring relative impact targets requires high-quality data at baseline (ie 2015) and longitudinal data to assess temporal trends. In this commentary, we propose alternative additional measures to track progress on reducing the HCV burden, offer examples where the WHO targets may not be informative or achievable, and potential practical solutions.

Australia needs to increase testing to achieve hepatitis C elimination.

OBJECTIVES: To assess progress in Australia toward the 2030 WHO hepatitis C elimination targets two years after the introduction of highly effective direct-acting antiviral (DAA) treatments. DESIGN: Analysis of quarterly data on government-subsidised hepatitis C RNA testing and hepatitis C treatment in Australia, January 2013 - June 2018. Changes in testing and treatment levels associated with DAA availability were assessed in an autoregressive integrated moving average (ARIMA) statistical model, and the impact by 2030 of different levels of testing and treatment were estimated using a mathematical model. MAJOR OUTCOME MEASURES: Hepatitis C prevalence among people who inject drugs; annual hepatitis C incidence relative to 2015 levels; projections for the hepatitis C care cascade in 2030. RESULTS: The mean annual number of treatments initiated for people with hepatitis C increased from 6747 during 2013-2015 (before the introduction of DAAs) to 28 022 during 2016-18; the mean annual number of diagnostic RNA tests increased from 17 385 to 23 819. If current trends in testing and treatment continue (ie, 2018 testing numbers are maintained but treatment numbers decline by 50%), it is projected that by 2030 only 72% of infected people would be treated (by 2025 all people diagnosed with hepatitis C would be treated). The incidence of hepatitis C in 2030 would be 59% lower than in 2015, well short of the WHO target of an 80% reduction. The identification and testing of people exposed to hepatitis C must be increased by at least 50% for Australia to reach the WHO elimination targets. CONCLUSION: Hepatitis C elimination programs in Australia should focus on increasing testing rates and linkage with care to maintain adequate levels of treatment.

Staying hepatitis C negative: A systematic review and meta-analysis of cure and reinfection in people who inject drugs.

BACKGROUND AND AIMS: Direct-acting antivirals (DAAs) are highly effective in treating hepatitis C. However, there is concern that cure rates may be lower, and reinfection rates higher, among people who inject drugs. We conducted a systematic review of treatment outcomes achieved with DAAs in  people who inject drugs (PWID). METHODS: A search strategy was used to identify studies that reported sustained viral response (SVR), treatment discontinuation, adherence or reinfection in recent PWID and/or opioid substitution therapy (OST) recipients. Study quality was assessed using the Newcastle-Ottawa Scale. Meta-analysis of proportions was used to estimate pooled SVR and treatment discontinuation rates. The pooled relative risk of achieving SVR and pooled reinfection rate were calculated using generalized mixed effects linear models. RESULTS: The search identified 8075 references; 26 were eligible for inclusion. The pooled SVR for recent PWID was 88% (95% CI, 83%-92%) and 91% (95% CI 88%-95%) for OST recipients. The relative risk of achieving SVR for recent PWID compared to non-recent PWID was 0.99 (95% CI, 0.94-1.06). The pooled treatment discontinuation was 2% (95% CI, 1%-4%) for both recent PWID and OST recipients. Amongst recent PWID, the pooled incidence of reinfection was 1.94 per 100 person years (95% CI, 0.87-4.32). In OST recipients, the incidence of reinfection was 0.55 per 100 person years (95% CI, 0.17-1.76). CONCLUSIONS: Treatment outcomes were similar in recent PWID compared to non-PWID treated with DAAs. People who report recent injecting or OST recipients should not be excluded from hepatitis C treatment.

Injection drug network characteristics as a predictor of injection behaviour.

Social network characteristics of people who inject drugs (PWID) have previously been flagged as potential risk factors for HCV transmission such as increased injection frequency. To understand the role of the injecting network on injection frequency, we investigated how changes in an injecting network over time can modulate injecting risk behaviour. PWID were sourced from the Networks 2 Study, a longitudinal cohort study of PWID recruited from illicit drug street markets across Melbourne, Australia. Network-related correlates of injection frequency and the change in frequency over time were analysed using adjusted Cox Proportional Hazards and Generalised Estimating Equations modelling. Two-hundred and eighteen PWID followed up for a mean (s.d.) of 2.8 (1.7) years were included in the analysis. A greater number of injecting partners, network closeness centrality and eigenvector centrality over time were associated with an increased rate of infection frequency. Every additional injection drug partner was associated with an increase in monthly injection frequency. Similarly, increased network connectivity and centrality over time was also associated with an increase in injection frequency. This study observed that baseline network measures of connectivity and centrality may be associated with changes in injection frequency and, by extension, may predict subsequent HCV transmission risk. Longitudinal changes in network position were observed to correlate with changes in injection frequency, with PWID who migrate from the densely-connected network centre out to the less-connected periphery were associated with a decreased rate of injection frequency.

Eliminating hepatitis C: The importance of frequent testing of people who inject drugs in high-prevalence settings.

Modelling suggests that more frequent screening of people who inject drugs (PWID) and an improved care cascade are required to achieve the WHO hepatitis C virus (HCV) elimination target of an 80% reduction in incidence by 2030. We determined the testing frequencies (2-yearly, annually, 6-monthly and 3-monthly) and retention in care required among PWID to achieve the HCV incidence reduction target through treatment as prevention in low (25%), medium (50%) and high (75%) chronic HCV prevalence settings. Mathematical modelling of HCV transmission among PWID, capturing testing, treatment and other features of the care cascade were employed. In low-prevalence settings, 2-yearly antibody testing of PWID was estimated to reach the elimination target by 2027-2030 depending on retention in care, with annual testing reducing the time by up to 3 years. In medium-prevalence settings, if close to 90% testing coverage were achieved, then annual antibody testing of PWID would be sufficient. If testing coverage were lower (80%), 6-monthly antibody testing with at least 70% retention in care or annual HCV RNA/cAg testing would be required. In high-prevalence settings, even 3-monthly HCV RNA/cAg testing of PWID was unable to achieve the incidence reduction target. Thus, for geographical areas or subpopulations with high prevalence, WHO incidence targets are unlikely to be met without 3-monthly RNA/cAg testing accompanied by other prevention measures. Novel testing strategies, such as rapid point-of-care antibody testing or replacing antibody testing with RNA/cAg tests as a screening tool, can provide additional population-level impacts to compensate for imperfect follow-up or testing coverage.

Hepatitis C Virus Reinfection and Spontaneous Clearance of Reinfection--the InC3 Study.

BACKGROUND: We aimed to characterize the natural history of hepatitis C virus (HCV) reinfection and spontaneous clearance following reinfection (reclearance), including predictors of HCV reclearance. METHODS: Data were synthesized from the 9 prospective cohorts of the International Collaboration of Incident Human Immunodeficiency Virus and HCV in Injecting Cohorts study, which evaluated HCV infection outcomes among people who inject drugs. Participants with primary HCV infection were classified as having achieved viral suppression if they had negative results of at least 1 subsequent HCV RNA test. Those with positive results of an HCV RNA test following viral suppression were investigated for reinfection. Viral sequence analysis was used to identify reinfection (defined as detection of heterologous virus with no subsequent detection of the original viral strain). RESULTS: Among 591 participants with acute primary HCV infection, 118 were investigated for reinfection. Twenty-eight participants were reinfected (12.3 cases/100 person-years; 95% confidence interval [CI], 8.5-17.8). Peak HCV RNA level was lower during reinfection than primary infection (P = .011). The proportion of individuals with reclearance 6 months after reinfection was 52% (95% CI, 33%-73%). After adjustment for study site, females with the IFNL4 (formerly IFNL3 and IL28B) rs12979860 CC genotype detected were more likely to have reclearance (hazard ratio, 4.16; 95% CI, 1.24-13.94; P = .021). CONCLUSIONS: Sex and IFNL4 genotype are associated with spontaneous clearance after reinfection.

The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs.

UNLABELLED: With the development of new highly efficacious direct-acting antiviral (DAA) treatments for hepatitis C virus (HCV), the concept of treatment as prevention is gaining credence. To date, the majority of mathematical models assume perfect mixing, with injectors having equal contact with all other injectors. This article explores how using a networks-based approach to treat people who inject drugs (PWID) with DAAs affects HCV prevalence. Using observational data, we parameterized an exponential random graph model containing 524 nodes. We simulated transmission of HCV through this network using a discrete time, stochastic transmission model. The effect of five treatment strategies on the prevalence of HCV was investigated; two of these strategies were (1) treat randomly selected nodes and (2) "treat your friends," where an individual is chosen at random for treatment and all their infected neighbors are treated. As treatment coverage increases, HCV prevalence at 10 years reduces for both the high- and low-efficacy treatment. Within each set of parameters, the treat your friends strategy performed better than the random strategy being most marked for higher-efficacy treatment. For example, over 10 years of treating 25 per 1,000 PWID, the prevalence drops from 50% to 40% for the random strategy and to 33% for the treat your friends strategy (6.5% difference; 95% confidence interval: 5.1-8.1). CONCLUSION: Treat your friends is a feasible means of utilizing network strategies to improve treatment efficiency. In an era of highly efficacious and highly tolerable treatment, such an approach will benefit not just the individual, but also the community more broadly by reducing the prevalence of HCV among PWID.

The effects of female sex, viral genotype, and IL28B genotype on spontaneous clearance of acute hepatitis C virus infection.

UNLABELLED: Although 20%-40% of persons with acute hepatitis C virus (HCV) infection demonstrate spontaneous clearance, the time course and factors associated with clearance remain poorly understood. We investigated the time to spontaneous clearance and predictors among participants with acute HCV using Cox proportional hazards analyses. Data for this analysis were drawn from an international collaboration of nine prospective cohorts evaluating outcomes after acute HCV infection. Among 632 participants with acute HCV, 35% were female, 82% were Caucasian, 49% had interleukin-28 (IL28)B CC genotype (rs12979860), 96% had injected drugs ever, 47% were infected with HCV genotype 1, and 7% had human immunodeficiency virus (HIV) coinfection. Twenty-eight percent were HCV antibody negative/RNA positive at the time of acute HCV detection (early acute HCV). During follow-up, spontaneous clearance occurred in 173 of 632, and at 1 year after infection, 25% (95% confidence interval [CI]: 21, 29) had cleared virus. Among those with clearance, the median time to clearance was 16.5 weeks (IQR: 10.5, 33.4), with 34%, 67%, and 83% demonstrating clearance at 3, 6, and 12 months. Adjusting for age, factors independently associated with time to spontaneous clearance included female sex (adjusted hazards ratio [AHR]: 2.16; 95% CI: 1.48, 3.18), IL28B CC genotype (versus CT/TT; AHR, 2.26; 95% CI: 1.52, 3.34), and HCV genotype 1 (versus non-genotype 1; AHR: 1.56; 95% CI: 1.06, 2.30). The effect of IL28B genotype and HCV genotype on spontaneous clearance was greater among females, compared to males. CONCLUSIONS: Female sex, favorable IL28B genotype, and HCV genotype 1 are independent predictors of spontaneous clearance. Further research is required to elucidate the observed sex-based differences in HCV control.

The use of social networking platforms for sexual health promotion: identifying key strategies for successful user engagement.

BACKGROUND: Online social networking platforms such as Facebook and Twitter have grown rapidly in popularity, with opportunities for interaction enhancing their health promotion potential. Such platforms are being used for sexual health promotion but with varying success in reaching and engaging users. We aimed to identify Facebook and Twitter profiles that were able to engage large numbers of users, and to identify strategies used to successfully attract and engage users in sexual health promotion on these platforms. METHODS: We identified active Facebook (n = 60) and Twitter (n = 40) profiles undertaking sexual health promotion through a previous systematic review, and assessed profile activity over a one-month period. Quantitative measures of numbers of friends and followers (reach) and social media interactions were assessed, and composite scores used to give profiles an 'engagement success' ranking. Associations between host activity, reach and interaction metrics were explored. Content of the top ten ranked Facebook and Twitter profiles was analysed using a thematic framework and compared with five poorly performing profiles to identify strategies for successful user engagement. RESULTS: Profiles that were able to successfully engage large numbers of users were more active and had higher levels of interaction per user than lower-ranked profiles. Strategies used by the top ten ranked profiles included: making regular posts/tweets (median 46 posts or 124 tweets/month for top-ranked profiles versus six posts or six tweets for poorly-performing profiles); individualised interaction with users (85% of top-ranked profiles versus 0% for poorly-performing profiles); and encouraging interaction and conversation by posing questions (100% versus 40%). Uploading multimedia material (80% versus 30%) and highlighting celebrity involvement (70% versus 10%) were also key strategies. CONCLUSION: Successful online engagement on social networking platforms can be measured through quantitative (user numbers and interactions) and basic qualitative content analysis. We identified the amount and type of host activity as key strategies for success, and in particular, regular individualised interaction with users, encouraging conversation, uploading multimedia and relevant links, and highlighting celebrity involvement. These findings provide valuable insight for achieving a high level of online engagement through social networking platforms to support successful health promotion initiatives.