There is currently no published data on the effectiveness of DAA treatment for elimination of HCV... more There is currently no published data on the effectiveness of DAA treatment for elimination of HCV infection in HIV-infected populations at a population level. However, a number of relevant studies and initiatives are emerging. This research aims to report cascade of care data for emerging HCV elimination initiatives and studies that are currently being evaluated in HIV/HCV co-infected populations in the context of implementation science theory. HCV elimination initiatives and studies in HIV co-infected populations that are currently underway were identified. Context, intervention characteristics and cascade of care data were synthesized in the context of implementation science frameworks. Seven HCV elimination initiatives and studies were identified in HIV co-infected populations, mainly operating in high-income countries. Four were focused mainly on HCV elimination in HIV-infected gay and bisexual men (GBM), and three included a combination of people who inject drugs (PWID), GBM an...
The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is d... more The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is driven by people who inject drugs (PWID). Injecting networks powerfully influence HCV transmission. In this paper we provide an overview of 10 years of research into injecting networks and HCV, culminating in a network-based approach to provision of direct-acting antiviral therapy. Between 2005 and 2010 we followed a cohort of 413 PWID, measuring HCV incidence, prevalence and injecting risk, including network-related factors. We developed an individual-based HCV transmission model, using it to simulate the spread of HCV through the empirical social network of PWID. In addition, we created an empirically grounded network model of injecting relationships using exponential random graph models (ERGMs), allowing simulation of realistic networks for investigating HCV treatment and intervention strategies. Our empirical work and modelling underpins the TAP Study, which is examining the feasibility of community-based treatment of PWID with DAAs. We observed incidence rates of HCV primary infection and reinfection of 12.8 per 100 person-years (PY) (95%CI: 7.7-20.0) and 28.8 per 100 PY (95%CI: 15.0-55.4), respectively, and determined that HCV transmission clusters correlated with reported injecting relationships. Transmission modelling showed that the empirical network provided some protective effect, slowing HCV transmission compared to a fully connected, homogenous PWID population. Our ERGMs revealed that treating PWID and all their contacts was the most effective strategy and targeting treatment to infected PWID with the most contacts the least effective. Networks-based approaches greatly increase understanding of HCV transmission and will inform the implementation of treatment as prevention using DAAs.
Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 ... more Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 estimated deaths attributed yearly to HCV-related liver diseases. It disproportionally affects people who inject drugs (PWID). Currently there is no preventative vaccine and interventions feature long treatment durations with severe side-effects. Upcoming treatments will improve this situation, making possible large-scale treatment interventions. How these strategies should target HCVinfected PWID remains an important unanswered question. Previous models of HCV have lacked empirically grounded contact models of PWID. Here we report results on HCV transmission and treatment using simulated contact networks generated from an empirically grounded network model using recently developed statistical approaches in social network analysis. Our HCV transmission model is a detailed, stochastic, individual-based model including spontaneously clearing nodes. On transmission we investigate the role of number of contacts and injecting frequency on time to primary infection and the role of spontaneously clearing nodes on incidence rates. On treatment we investigate the effect of nine networkbased treatment strategies on chronic prevalence and incidence rates of primary infection and re-infection. Both numbers of contacts and injecting frequency play key roles in reducing time to primary infection. The change from ''less-'' to ''morefrequent'' injector is roughly similar to having one additional network contact. Nodes that spontaneously clear their HCV infection have a local effect on infection risk and the total number of such nodes (but not their locations) has a network wide effect on the incidence of both primary and re-infection with HCV. Re-infection plays a large role in the effectiveness of treatment interventions. Strategies that choose PWID and treat all their contacts (analogous to ring vaccination) are most effective in reducing the incidence rates of re-infection and combined infection. A strategy targeting infected PWID with the most contacts (analogous to targeted vaccination) is the least effective.
ABSTRACT This study uses social network analysis to model a contact network of people who inject ... more ABSTRACT This study uses social network analysis to model a contact network of people who inject drugs (PWID) relevant for investigating the spread of an infectious disease (hepatitis C). Using snowball sample data, parameters for an exponential random graph model (ERGM) including social circuit dependence and four attributes (location, age, injecting frequency, gender) are estimated using a conditional estimation approach that respects the structure of snowball sample designs. Those network parameter estimates are then used to create a novel, model-dependent estimate of network size. Simulated PWID contact networks are created and compared with Bernoulli graphs. Location, age and injecting frequency are shown to be statistically significant attribute parameters in the ERGM. Simulated ERGM networks are shown to fit the collected data very well across a number of metrics. In comparison with Bernoulli graphs, simulated networks are shown to have longer paths and more clustering. Results from this study make possible simulation of realistic networks for investigating treatment and intervention strategies for reducing hepatitis C prevalence.
Journal of the Royal Society, Interface / the Royal Society, Jan 6, 2015
Hepatitis C virus (HCV) reinfection rates are probably underestimated due to reinfection episodes... more Hepatitis C virus (HCV) reinfection rates are probably underestimated due to reinfection episodes occurring between study visits. A Markov model of HCV reinfection and spontaneous clearance was fitted to empirical data. Bayesian post-estimation was used to project reinfection rates, reinfection spontaneous clearance probability and duration of reinfection. Uniform prior probability distributions were assumed for reinfection rate (more than 0), spontaneous clearance probability (0-1) and duration (0.25-6.00 months). Model estimates were 104 per 100 person-years (95% CrI: 21-344), 0.84 (95% CrI: 0.59-0.98) and 1.3 months (95% CrI: 0.3-4.1) for reinfection rate, spontaneous clearance probability and duration, respectively. Simulation studies were used to assess model validity, demonstrating that the Bayesian model estimates provided useful information about the possible sources and magnitude of bias in epidemiological estimates of reinfection rates, probability of reinfection clearance...
Findings of large proportions of hepatitis C
virus (HCV) anti-HCV negative injecting drug users ... more Findings of large proportions of hepatitis C
virus (HCV) anti-HCV negative injecting drug users (IDUs) with
detectable HCV-specific cellular immune responses raise the
question of whether some people have immunity to HCV infection.
We conducted a longitudinal study to determine whether anti-
HCV negative IDUs with detectable HCV-specific cellular immune
responses were more or less likely than other anti-HCV negative
participants to develop persistent HCV infection.
Methods: Cohort study participants who were anti-
This study uses social network analysis to model a contact network of people who inject drugs (PW... more This study uses social network analysis to model a contact network of people who inject drugs (PWID) relevant for investigating the spread of an infectious disease (hepatitis C). Using snowball sample data, parameters for an exponential random graph model (ERGM) including social circuit dependence and four attributes (location, age, injecting frequency, gender) are estimated using a conditional estimation approach that respects the structure of snowball sample designs. Those network parameter estimates are then used to create a novel, model-dependent estimate of network size. Simulated PWID contact networks are created and compared with Bernoulli graphs. Location, age and injecting frequency are shown to be statistically significant attribute parameters in the ERGM. Simulated ERGM networks are shown to fit the collected data very well across a number of metrics. In comparison with Bernoulli graphs, simulated networks are shown to have longer paths and more clustering. Results from t...
We aimed to characterize the natural history of hepatitis C virus (HCV) reinfection and spontaneo... more We aimed to characterize the natural history of hepatitis C virus (HCV) reinfection and spontaneous clearance following reinfection (reclearance), including predictors of HCV reclearance.
Online social networking platforms such as Facebook and Twitter have grown rapidly in popularity,... more 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. 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 ...
Understanding the patterns of HCV RNA levels during acute hepatitis C virus (HCV) infection provi... more Understanding the patterns of HCV RNA levels during acute hepatitis C virus (HCV) infection provides insights into immunopathogenesis and is important for vaccine design. This study evaluated patterns of HCV RNA levels and associated factors among individuals with acute infection. Data were from an international collaboration of nine prospective cohorts of acute HCV (InC3 Study). Participants with well-characterized acute HCV infection (detected within three months post-infection and interval between the peak and subsequent HCV RNA levels≤120 days) were categorised by a priori-defined patterns of HCV RNA levels: i) spontaneous clearance, ii) partial viral control with persistence (≥1 log IU/mL decline in HCV RNA levels following peak) and iii) viral plateau with persistence (increase or <1 log IU/mL decline in HCV RNA levels following peak). Factors associated with HCV RNA patterns were assessed using multinomial logistic regression. Among 643 individuals with acute HCV, 162 with...
Social media are growing in popularity and will play a key role in future sexual health promotion... more Social media are growing in popularity and will play a key role in future sexual health promotion initiatives. We asked 620 survey participants aged 16 to 29 years about their time spent using social media and their comfort in receiving information about sexual health via different channels. Median hours per day spent using social network sites was two; 36% spent more than 2 hours per day using social network sites. In multivariable logistic regression, being aged less than 20 years and living in a major city (compared to rural/regional Australia) were associated with use of social media more than 2 hours per day. Most participants reported being comfortable or very comfortable accessing sexual health information from websites (85%), followed by a doctor (81%), school (73%), and the mainstream media (67%). Fewer reported being comfortable getting information from social media; Facebook (52%), apps (51%), SMS (44%), and Twitter (36%). Several health promotion programmes via social me...
Background: Online social networking platforms such as Facebook and Twitter have grown rapidly in... more 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.
With the development of new highly efficacious direct-acting antiviral (DAA) treatments for hepat... more 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 networksbased 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. (HEPATOLOGY 2014;60:1861-1870 Abbreviations: DAA, direct-acting antiviral; ERGM, exponential random graph model; HCV, hepatitis C virus; HIV, human immunodeficiency virus; MCMC, Markov chain Monte Carlo; Peg-IFN, pegylated interferon; PWID, people who inject drugs; RBV, ribavirin.
People who inject drugs (PWID) are at risk of hepatitis C virus (HCV). It is plausible that PWID ... more People who inject drugs (PWID) are at risk of hepatitis C virus (HCV). It is plausible that PWID who receive a diagnosis of HCV will reduce their injecting risk out of concern for their injecting partners, although evidence for this is currently limited. The aim of this study was to investigate whether informing PWID of their HCV diagnosis was associated with a change in injecting behaviour. Prospective, longitudinal study of PWID recruited from street drug markets across Melbourne, Australia. Interviews and HCV testing were conducted at 3-monthly intervals. The association between receiving a diagnosis of HCV and (i) injecting frequency and (ii) injecting equipment borrowing, was examined using generalized estimating equations (GEE) analysis. Thirty-five individuals received a diagnosis of HCV during the study period. Receiving a diagnosis of HCV was associated with a decrease of 0.35 injections per month (p=0.046) but there was no change in injecting equipment borrowing (p=0.750)....
Background and objectives: Hepatitis C virus (HCV) RNA level in acute HCV infection is predictive... more Background and objectives: Hepatitis C virus (HCV) RNA level in acute HCV infection is predictive of spontaneous clearance. This study assessed factors associated with HCV RNA levels during early acute infection among people who inject drugs with well-defined acute HCV infection. Study design: Data were from International Collaboration of Incident HIV and Hepatitis C in Injecting Cohorts (InC 3 ) Study, an international collaboration of nine prospective cohorts studying acute HCV infection. Individuals with available HCV RNA levels during early acute infection (first two months following infection) were included. The distribution of HCV RNA levels during early acute infection were compared by selected host and virological factors. Results: A total of 195 individuals were included. Median HCV RNA levels were significantly higher among individuals with interferon lambda 3 (IFNL3, formerly called IL28B) CC genotype compared to those with TT/CT genotype (6.28 vs. 5.39 log IU/mL, respectively; P = 0.01). IFNL3 CC genotype was also associated with top tertile HCV RNA levels (≥6.3 IU/mL; vs. TT/CT genotype; adjusted Odds Ratio: 4.28; 95%CI: 2.01, 9.10; P < 0.01).
Background: Detectable HCV-specific cellular immune responses in HCV antibody and RNA negative pe... more Background: Detectable HCV-specific cellular immune responses in HCV antibody and RNA negative people who inject drugs (PWID) raise the question of whether some are resistant to HCV infection. Immune responses from people who have been exposed to hepatitis C virus (HCV) and remain anti-HCV negative are of interest for HCV vaccine development; however, limited research addresses this area. Objectives: In a cohort of HCV antibody and RNA negative PWID, we assessed whether the presence of HCV-specific IFN-γ responses or genetic associations provide any evidence of protection from HCV infection. Patients and Methods: One hundred and ninety-eight participants were examined longitudinally for clinical, behavioral, social, environmental and genetic characteristics (IFNL3 genotype [formally IL-28B] and HLA type). Sixty-one of the 198 participants were HCV antibody and RNA negative, with 53 able to be examined longitudinally for HCV-specific IFN-γ ELISpot T cell responses. Results: Ten of the 53 HCV antibody and RNA negative participants had detectable HCV-specific IFN-γ responses at baseline (18%). The magnitude of IFN-γ responses averaged 131 +/-96 SFC/10 6 PBMC and the breadth was mean 1 +/-1 pool positive. The specificity of responses were mainly directed to E2, NS4b and NS5b. Participants with (10) and without (43) HCV-specific IFN-γ responses did not differ in behavioral, clinical or genetic characteristics (P > 0.05). There was a larger proportion sharing needles (with 70%, without 49%, P = 0.320) and a higher incidence of HCV (with 35.1 per 100 py, 95% CI 14.6, 84.4, without 16.0 per 100 py, 95% CI 7.2, 35.6, P = 0.212) in those with IFN-γ responses, although not statistically significant. Half the participants with baseline IFN-γ responses became HCV RNA positive (5/10), with one of these participants spontaneously clearing HCV. The spontaneous clearer had high magnitude and broad Th1 responses, favorable IFNL3 genotype and favorable HLA types. Conclusions: This study demonstrated the detection of HCV-specific IFN-γ responses in HCV antibody and RNA negative individuals, with a tendency for HCV-specific IFN-γ responses to be associated with HCV exposure. The potential role of HCV-specific IFN-γ responses in those who remained HCV RNA negative is of value for the development of novel HCV therapeutics.
It is hypothesized that social networks facilitate transmission of the hepatitis C virus (HCV). W... more It is hypothesized that social networks facilitate transmission of the hepatitis C virus (HCV). We tested for association between HCV phylogeny and reported injecting relationships using longitudinal data from a social network design study. People who inject drugs were recruited from street drug markets in Melbourne, Australia. Interviews and blood tests took place three monthly (during 2005-2008), with participants asked to nominate up to five injecting partners at each interview. The HCV core region of individual isolates was then sequenced and phylogenetic trees were constructed. Genetic clusters were identified using bootstrapping (cut-off: 70%). An adjusted Jaccard similarity coefficient was used to measure the association between the reported injecting relationships and relationships defined by clustering in the phylogenetic analysis (statistical significance assessed using the quadratic assignment procedure). 402 participants consented to participate; 244 HCV infections were observed in 238 individuals. 26 genetic clusters were identified, with 2-7 infections per cluster. Newly acquired infection (AOR = 2.03, 95% CI: 1.04-3.96, p = 0.037, and HCV genotype 3 (vs. genotype 1, AOR = 2.72, 95% CI: 1.48-4.99) were independent predictors of being in a cluster. 54% of participants whose infections were part of a cluster in the phylogenetic analysis reported injecting with at least one other participant in that cluster during the study. Overall, 16% of participants who were infected at study entry and 40% of participants with newly acquired infections had molecular evidence of related infections with at least one injecting partner. Likely transmission clusters identified in phylogenetic analysis correlated with reported injecting relationships (adjusted Jaccard coefficient: 0.300; p,0.001). This is the first study to show that HCV phylogeny is associated with the injecting network, highlighting the importance of the injecting network in HCV transmission.
Hepatitis C virus reinfection and spontaneous clearance of reinfection were examined in a highly ... more Hepatitis C virus reinfection and spontaneous clearance of reinfection were examined in a highly characterised cohort of 188 people who inject drugs over a five-year period. Nine confirmed reinfections and 17 possible reinfections were identified (confirmed reinfections were those genetically distinct from the previous infection and possible reinfections were used to define instances where genetic differences between infections could not be assessed due to lack of availability of hepatitis C virus sequence data). The incidence of confirmed reinfection was 28.8 per 100 person-years (PY), 95%CI: 15.0-55.4; the combined incidence of confirmed and possible reinfection was 24.6 per 100 PY (95%CI: 16.8-36.1). The hazard of hepatitis C reinfection was approximately double that of primary hepatitis C infection; it did not reach statistical significance in confirmed reinfections alone (hazard ratio [HR]: 2.45, 95%CI: 0.87-6.86, p=0.089), but did in confirmed and possible hepatitis C reinfections combined (HR: 1.93, 95%CI: 1.01-3.69, p=0.047) and after adjustment for the number of recent injecting partners and duration of injecting. In multivariable analysis, shorter duration of injection (HR: 0.91; 95%CI: 0.83-0.98; p=0.019) and multiple recent injecting partners (HR: 3.12; 95%CI: 1.08-9.00, p=0.035) were independent predictors of possible and confirmed reinfection. Time to spontaneous clearance was shorter in confirmed reinfection (HR: 5.34, 95%CI: 1.67-17.03, p=0.005) and confirmed and possible reinfection (HR: 3.10, 95%CI: 1.10-8.76, p-value=0.033) than primary infection. Nonetheless, 50% of confirmed reinfections and 41% of confirmed or possible reinfections did not spontaneously clear.
There is currently no published data on the effectiveness of DAA treatment for elimination of HCV... more There is currently no published data on the effectiveness of DAA treatment for elimination of HCV infection in HIV-infected populations at a population level. However, a number of relevant studies and initiatives are emerging. This research aims to report cascade of care data for emerging HCV elimination initiatives and studies that are currently being evaluated in HIV/HCV co-infected populations in the context of implementation science theory. HCV elimination initiatives and studies in HIV co-infected populations that are currently underway were identified. Context, intervention characteristics and cascade of care data were synthesized in the context of implementation science frameworks. Seven HCV elimination initiatives and studies were identified in HIV co-infected populations, mainly operating in high-income countries. Four were focused mainly on HCV elimination in HIV-infected gay and bisexual men (GBM), and three included a combination of people who inject drugs (PWID), GBM an...
The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is d... more The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is driven by people who inject drugs (PWID). Injecting networks powerfully influence HCV transmission. In this paper we provide an overview of 10 years of research into injecting networks and HCV, culminating in a network-based approach to provision of direct-acting antiviral therapy. Between 2005 and 2010 we followed a cohort of 413 PWID, measuring HCV incidence, prevalence and injecting risk, including network-related factors. We developed an individual-based HCV transmission model, using it to simulate the spread of HCV through the empirical social network of PWID. In addition, we created an empirically grounded network model of injecting relationships using exponential random graph models (ERGMs), allowing simulation of realistic networks for investigating HCV treatment and intervention strategies. Our empirical work and modelling underpins the TAP Study, which is examining the feasibility of community-based treatment of PWID with DAAs. We observed incidence rates of HCV primary infection and reinfection of 12.8 per 100 person-years (PY) (95%CI: 7.7-20.0) and 28.8 per 100 PY (95%CI: 15.0-55.4), respectively, and determined that HCV transmission clusters correlated with reported injecting relationships. Transmission modelling showed that the empirical network provided some protective effect, slowing HCV transmission compared to a fully connected, homogenous PWID population. Our ERGMs revealed that treating PWID and all their contacts was the most effective strategy and targeting treatment to infected PWID with the most contacts the least effective. Networks-based approaches greatly increase understanding of HCV transmission and will inform the implementation of treatment as prevention using DAAs.
Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 ... more Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 estimated deaths attributed yearly to HCV-related liver diseases. It disproportionally affects people who inject drugs (PWID). Currently there is no preventative vaccine and interventions feature long treatment durations with severe side-effects. Upcoming treatments will improve this situation, making possible large-scale treatment interventions. How these strategies should target HCVinfected PWID remains an important unanswered question. Previous models of HCV have lacked empirically grounded contact models of PWID. Here we report results on HCV transmission and treatment using simulated contact networks generated from an empirically grounded network model using recently developed statistical approaches in social network analysis. Our HCV transmission model is a detailed, stochastic, individual-based model including spontaneously clearing nodes. On transmission we investigate the role of number of contacts and injecting frequency on time to primary infection and the role of spontaneously clearing nodes on incidence rates. On treatment we investigate the effect of nine networkbased treatment strategies on chronic prevalence and incidence rates of primary infection and re-infection. Both numbers of contacts and injecting frequency play key roles in reducing time to primary infection. The change from ''less-'' to ''morefrequent'' injector is roughly similar to having one additional network contact. Nodes that spontaneously clear their HCV infection have a local effect on infection risk and the total number of such nodes (but not their locations) has a network wide effect on the incidence of both primary and re-infection with HCV. Re-infection plays a large role in the effectiveness of treatment interventions. Strategies that choose PWID and treat all their contacts (analogous to ring vaccination) are most effective in reducing the incidence rates of re-infection and combined infection. A strategy targeting infected PWID with the most contacts (analogous to targeted vaccination) is the least effective.
ABSTRACT This study uses social network analysis to model a contact network of people who inject ... more ABSTRACT This study uses social network analysis to model a contact network of people who inject drugs (PWID) relevant for investigating the spread of an infectious disease (hepatitis C). Using snowball sample data, parameters for an exponential random graph model (ERGM) including social circuit dependence and four attributes (location, age, injecting frequency, gender) are estimated using a conditional estimation approach that respects the structure of snowball sample designs. Those network parameter estimates are then used to create a novel, model-dependent estimate of network size. Simulated PWID contact networks are created and compared with Bernoulli graphs. Location, age and injecting frequency are shown to be statistically significant attribute parameters in the ERGM. Simulated ERGM networks are shown to fit the collected data very well across a number of metrics. In comparison with Bernoulli graphs, simulated networks are shown to have longer paths and more clustering. Results from this study make possible simulation of realistic networks for investigating treatment and intervention strategies for reducing hepatitis C prevalence.
Journal of the Royal Society, Interface / the Royal Society, Jan 6, 2015
Hepatitis C virus (HCV) reinfection rates are probably underestimated due to reinfection episodes... more Hepatitis C virus (HCV) reinfection rates are probably underestimated due to reinfection episodes occurring between study visits. A Markov model of HCV reinfection and spontaneous clearance was fitted to empirical data. Bayesian post-estimation was used to project reinfection rates, reinfection spontaneous clearance probability and duration of reinfection. Uniform prior probability distributions were assumed for reinfection rate (more than 0), spontaneous clearance probability (0-1) and duration (0.25-6.00 months). Model estimates were 104 per 100 person-years (95% CrI: 21-344), 0.84 (95% CrI: 0.59-0.98) and 1.3 months (95% CrI: 0.3-4.1) for reinfection rate, spontaneous clearance probability and duration, respectively. Simulation studies were used to assess model validity, demonstrating that the Bayesian model estimates provided useful information about the possible sources and magnitude of bias in epidemiological estimates of reinfection rates, probability of reinfection clearance...
Findings of large proportions of hepatitis C
virus (HCV) anti-HCV negative injecting drug users ... more Findings of large proportions of hepatitis C
virus (HCV) anti-HCV negative injecting drug users (IDUs) with
detectable HCV-specific cellular immune responses raise the
question of whether some people have immunity to HCV infection.
We conducted a longitudinal study to determine whether anti-
HCV negative IDUs with detectable HCV-specific cellular immune
responses were more or less likely than other anti-HCV negative
participants to develop persistent HCV infection.
Methods: Cohort study participants who were anti-
This study uses social network analysis to model a contact network of people who inject drugs (PW... more This study uses social network analysis to model a contact network of people who inject drugs (PWID) relevant for investigating the spread of an infectious disease (hepatitis C). Using snowball sample data, parameters for an exponential random graph model (ERGM) including social circuit dependence and four attributes (location, age, injecting frequency, gender) are estimated using a conditional estimation approach that respects the structure of snowball sample designs. Those network parameter estimates are then used to create a novel, model-dependent estimate of network size. Simulated PWID contact networks are created and compared with Bernoulli graphs. Location, age and injecting frequency are shown to be statistically significant attribute parameters in the ERGM. Simulated ERGM networks are shown to fit the collected data very well across a number of metrics. In comparison with Bernoulli graphs, simulated networks are shown to have longer paths and more clustering. Results from t...
We aimed to characterize the natural history of hepatitis C virus (HCV) reinfection and spontaneo... more We aimed to characterize the natural history of hepatitis C virus (HCV) reinfection and spontaneous clearance following reinfection (reclearance), including predictors of HCV reclearance.
Online social networking platforms such as Facebook and Twitter have grown rapidly in popularity,... more 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. 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 ...
Understanding the patterns of HCV RNA levels during acute hepatitis C virus (HCV) infection provi... more Understanding the patterns of HCV RNA levels during acute hepatitis C virus (HCV) infection provides insights into immunopathogenesis and is important for vaccine design. This study evaluated patterns of HCV RNA levels and associated factors among individuals with acute infection. Data were from an international collaboration of nine prospective cohorts of acute HCV (InC3 Study). Participants with well-characterized acute HCV infection (detected within three months post-infection and interval between the peak and subsequent HCV RNA levels≤120 days) were categorised by a priori-defined patterns of HCV RNA levels: i) spontaneous clearance, ii) partial viral control with persistence (≥1 log IU/mL decline in HCV RNA levels following peak) and iii) viral plateau with persistence (increase or <1 log IU/mL decline in HCV RNA levels following peak). Factors associated with HCV RNA patterns were assessed using multinomial logistic regression. Among 643 individuals with acute HCV, 162 with...
Social media are growing in popularity and will play a key role in future sexual health promotion... more Social media are growing in popularity and will play a key role in future sexual health promotion initiatives. We asked 620 survey participants aged 16 to 29 years about their time spent using social media and their comfort in receiving information about sexual health via different channels. Median hours per day spent using social network sites was two; 36% spent more than 2 hours per day using social network sites. In multivariable logistic regression, being aged less than 20 years and living in a major city (compared to rural/regional Australia) were associated with use of social media more than 2 hours per day. Most participants reported being comfortable or very comfortable accessing sexual health information from websites (85%), followed by a doctor (81%), school (73%), and the mainstream media (67%). Fewer reported being comfortable getting information from social media; Facebook (52%), apps (51%), SMS (44%), and Twitter (36%). Several health promotion programmes via social me...
Background: Online social networking platforms such as Facebook and Twitter have grown rapidly in... more 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.
With the development of new highly efficacious direct-acting antiviral (DAA) treatments for hepat... more 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 networksbased 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. (HEPATOLOGY 2014;60:1861-1870 Abbreviations: DAA, direct-acting antiviral; ERGM, exponential random graph model; HCV, hepatitis C virus; HIV, human immunodeficiency virus; MCMC, Markov chain Monte Carlo; Peg-IFN, pegylated interferon; PWID, people who inject drugs; RBV, ribavirin.
People who inject drugs (PWID) are at risk of hepatitis C virus (HCV). It is plausible that PWID ... more People who inject drugs (PWID) are at risk of hepatitis C virus (HCV). It is plausible that PWID who receive a diagnosis of HCV will reduce their injecting risk out of concern for their injecting partners, although evidence for this is currently limited. The aim of this study was to investigate whether informing PWID of their HCV diagnosis was associated with a change in injecting behaviour. Prospective, longitudinal study of PWID recruited from street drug markets across Melbourne, Australia. Interviews and HCV testing were conducted at 3-monthly intervals. The association between receiving a diagnosis of HCV and (i) injecting frequency and (ii) injecting equipment borrowing, was examined using generalized estimating equations (GEE) analysis. Thirty-five individuals received a diagnosis of HCV during the study period. Receiving a diagnosis of HCV was associated with a decrease of 0.35 injections per month (p=0.046) but there was no change in injecting equipment borrowing (p=0.750)....
Background and objectives: Hepatitis C virus (HCV) RNA level in acute HCV infection is predictive... more Background and objectives: Hepatitis C virus (HCV) RNA level in acute HCV infection is predictive of spontaneous clearance. This study assessed factors associated with HCV RNA levels during early acute infection among people who inject drugs with well-defined acute HCV infection. Study design: Data were from International Collaboration of Incident HIV and Hepatitis C in Injecting Cohorts (InC 3 ) Study, an international collaboration of nine prospective cohorts studying acute HCV infection. Individuals with available HCV RNA levels during early acute infection (first two months following infection) were included. The distribution of HCV RNA levels during early acute infection were compared by selected host and virological factors. Results: A total of 195 individuals were included. Median HCV RNA levels were significantly higher among individuals with interferon lambda 3 (IFNL3, formerly called IL28B) CC genotype compared to those with TT/CT genotype (6.28 vs. 5.39 log IU/mL, respectively; P = 0.01). IFNL3 CC genotype was also associated with top tertile HCV RNA levels (≥6.3 IU/mL; vs. TT/CT genotype; adjusted Odds Ratio: 4.28; 95%CI: 2.01, 9.10; P < 0.01).
Background: Detectable HCV-specific cellular immune responses in HCV antibody and RNA negative pe... more Background: Detectable HCV-specific cellular immune responses in HCV antibody and RNA negative people who inject drugs (PWID) raise the question of whether some are resistant to HCV infection. Immune responses from people who have been exposed to hepatitis C virus (HCV) and remain anti-HCV negative are of interest for HCV vaccine development; however, limited research addresses this area. Objectives: In a cohort of HCV antibody and RNA negative PWID, we assessed whether the presence of HCV-specific IFN-γ responses or genetic associations provide any evidence of protection from HCV infection. Patients and Methods: One hundred and ninety-eight participants were examined longitudinally for clinical, behavioral, social, environmental and genetic characteristics (IFNL3 genotype [formally IL-28B] and HLA type). Sixty-one of the 198 participants were HCV antibody and RNA negative, with 53 able to be examined longitudinally for HCV-specific IFN-γ ELISpot T cell responses. Results: Ten of the 53 HCV antibody and RNA negative participants had detectable HCV-specific IFN-γ responses at baseline (18%). The magnitude of IFN-γ responses averaged 131 +/-96 SFC/10 6 PBMC and the breadth was mean 1 +/-1 pool positive. The specificity of responses were mainly directed to E2, NS4b and NS5b. Participants with (10) and without (43) HCV-specific IFN-γ responses did not differ in behavioral, clinical or genetic characteristics (P > 0.05). There was a larger proportion sharing needles (with 70%, without 49%, P = 0.320) and a higher incidence of HCV (with 35.1 per 100 py, 95% CI 14.6, 84.4, without 16.0 per 100 py, 95% CI 7.2, 35.6, P = 0.212) in those with IFN-γ responses, although not statistically significant. Half the participants with baseline IFN-γ responses became HCV RNA positive (5/10), with one of these participants spontaneously clearing HCV. The spontaneous clearer had high magnitude and broad Th1 responses, favorable IFNL3 genotype and favorable HLA types. Conclusions: This study demonstrated the detection of HCV-specific IFN-γ responses in HCV antibody and RNA negative individuals, with a tendency for HCV-specific IFN-γ responses to be associated with HCV exposure. The potential role of HCV-specific IFN-γ responses in those who remained HCV RNA negative is of value for the development of novel HCV therapeutics.
It is hypothesized that social networks facilitate transmission of the hepatitis C virus (HCV). W... more It is hypothesized that social networks facilitate transmission of the hepatitis C virus (HCV). We tested for association between HCV phylogeny and reported injecting relationships using longitudinal data from a social network design study. People who inject drugs were recruited from street drug markets in Melbourne, Australia. Interviews and blood tests took place three monthly (during 2005-2008), with participants asked to nominate up to five injecting partners at each interview. The HCV core region of individual isolates was then sequenced and phylogenetic trees were constructed. Genetic clusters were identified using bootstrapping (cut-off: 70%). An adjusted Jaccard similarity coefficient was used to measure the association between the reported injecting relationships and relationships defined by clustering in the phylogenetic analysis (statistical significance assessed using the quadratic assignment procedure). 402 participants consented to participate; 244 HCV infections were observed in 238 individuals. 26 genetic clusters were identified, with 2-7 infections per cluster. Newly acquired infection (AOR = 2.03, 95% CI: 1.04-3.96, p = 0.037, and HCV genotype 3 (vs. genotype 1, AOR = 2.72, 95% CI: 1.48-4.99) were independent predictors of being in a cluster. 54% of participants whose infections were part of a cluster in the phylogenetic analysis reported injecting with at least one other participant in that cluster during the study. Overall, 16% of participants who were infected at study entry and 40% of participants with newly acquired infections had molecular evidence of related infections with at least one injecting partner. Likely transmission clusters identified in phylogenetic analysis correlated with reported injecting relationships (adjusted Jaccard coefficient: 0.300; p,0.001). This is the first study to show that HCV phylogeny is associated with the injecting network, highlighting the importance of the injecting network in HCV transmission.
Hepatitis C virus reinfection and spontaneous clearance of reinfection were examined in a highly ... more Hepatitis C virus reinfection and spontaneous clearance of reinfection were examined in a highly characterised cohort of 188 people who inject drugs over a five-year period. Nine confirmed reinfections and 17 possible reinfections were identified (confirmed reinfections were those genetically distinct from the previous infection and possible reinfections were used to define instances where genetic differences between infections could not be assessed due to lack of availability of hepatitis C virus sequence data). The incidence of confirmed reinfection was 28.8 per 100 person-years (PY), 95%CI: 15.0-55.4; the combined incidence of confirmed and possible reinfection was 24.6 per 100 PY (95%CI: 16.8-36.1). The hazard of hepatitis C reinfection was approximately double that of primary hepatitis C infection; it did not reach statistical significance in confirmed reinfections alone (hazard ratio [HR]: 2.45, 95%CI: 0.87-6.86, p=0.089), but did in confirmed and possible hepatitis C reinfections combined (HR: 1.93, 95%CI: 1.01-3.69, p=0.047) and after adjustment for the number of recent injecting partners and duration of injecting. In multivariable analysis, shorter duration of injection (HR: 0.91; 95%CI: 0.83-0.98; p=0.019) and multiple recent injecting partners (HR: 3.12; 95%CI: 1.08-9.00, p=0.035) were independent predictors of possible and confirmed reinfection. Time to spontaneous clearance was shorter in confirmed reinfection (HR: 5.34, 95%CI: 1.67-17.03, p=0.005) and confirmed and possible reinfection (HR: 3.10, 95%CI: 1.10-8.76, p-value=0.033) than primary infection. Nonetheless, 50% of confirmed reinfections and 41% of confirmed or possible reinfections did not spontaneously clear.
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Papers by Rachel Sacks-davis
virus (HCV) anti-HCV negative injecting drug users (IDUs) with
detectable HCV-specific cellular immune responses raise the
question of whether some people have immunity to HCV infection.
We conducted a longitudinal study to determine whether anti-
HCV negative IDUs with detectable HCV-specific cellular immune
responses were more or less likely than other anti-HCV negative
participants to develop persistent HCV infection.
Methods: Cohort study participants who were anti-
virus (HCV) anti-HCV negative injecting drug users (IDUs) with
detectable HCV-specific cellular immune responses raise the
question of whether some people have immunity to HCV infection.
We conducted a longitudinal study to determine whether anti-
HCV negative IDUs with detectable HCV-specific cellular immune
responses were more or less likely than other anti-HCV negative
participants to develop persistent HCV infection.
Methods: Cohort study participants who were anti-