Impact of Hepatitis C Treatment as Prevention for People Who Inject Drugs is sensitive to contact network structure

Treatment as Prevention (TasP) using directly-acting antivirals has been advocated for Hepatitis C Virus (HCV) in people who inject drugs (PWID), but treatment is expensive and TasP’s effectiveness is uncertain. Previous modelling has assumed a homogeneously-mixed population or a static network lacking turnover in the population and injecting partnerships. We developed a transmission-dynamic model on a dynamic network of injecting partnerships using data from survey of injecting behaviour carried out in London, UK. We studied transmission on a novel exponential-clustered network, as well as on two simpler networks for comparison, an exponential unclustered and a random network, and found that TasP’s effectiveness differs markedly. With respect to an exponential-clustered network, the random network (and homogeneously-mixed population) overestimate TasP’s effectiveness, whereas the exponential-unclustered network underestimates it. For all network types TasP’s effectiveness depends on whether treated patients change risk behaviour, and on treatment coverage: higher coverage requires fewer total treatments for the same health gain. Whilst TasP can greatly reduce HCV prevalence, incidence of infection, and incidence of reinfection in PWID, assessment of TasP’s effectiveness needs to take account of the injecting-partnership network structure and post-treatment behaviour change, and further empirical study is required

Impact of baseline Diabetic Retinopathy Severity Scale scores on visual outcomes in the VIVID-DME and VISTA-DME studies

BACKGROUND/AIMS: To evaluate intravitreal aflibercept versus laser in subgroups of patients with baseline Diabetic Retinopathy Severity Scale (DRSS) scores 6443, 47, and 6553 in VIVID-DME and VISTA-DME. METHODS: Patients with diabetic macular oedema were randomised to receive intravitreal aflibercept 2\u2009mg every 4 weeks (2q4), intravitreal aflibercept 2\u2009mg every 8 weeks after five initial monthly doses (2q8), or macular laser photocoagulation at baseline with sham injections at every visit. These post hoc analyses evaluate outcomes based on baseline DRSS scores in patients in the integrated dataset. The 2q4 and 2q8 treatment groups were also pooled. RESULTS: 748 patients had a baseline DRSS score based on fundus photographs ( 6443, n=301; 47, n=153; 6553, n=294). At week 100, the least squares mean difference between treatment groups (effect of intravitreal aflibercept above that of laser, adjusting for baseline best-corrected visual acuity) was 8.9 (95% CI 5.99 to 11.81), 9.7 (95% CI 5.54 to 13.91), and 11.0 (95%\u2009CI 7.96 to 14.1) letters in those with baseline DRSS scores 6443, 47, and 6553, respectively. The proportions of patients with 652\u2009step DRSS score improvement were greater in the intravitreal aflibercept group versus laser, respectively, for those with baseline DRSS scores of 6443 (13% vs 5.9%), 47 (25.8% vs 4.5%), and 6553 (64.5% vs 28.4%). CONCLUSIONS: Regardless of baseline DRSS score, functional outcomes were superior in intravitreal aflibercept-treated patients, demonstrating consistent treatment benefit across various baseline levels of retinopathy

A maximum entropy method for the prediction of size distributions

We propose a method to derive the stationary size distributions of a system, and the degree distributions of networks, using maximisation of the Gibbs-Shannon entropy. We apply this to a preferential attachment-type algorithm for systems of constant size, which contains exit of balls and urns (or nodes and edges for the network case). Knowing mean size (degree) and turnover rate, the power law exponent and exponential cutoff can be derived. Our results are confirmed by simulations and by computation of exact probabilities. We also apply this entropy method to reproduce existing results like the Maxwell-Boltzmann distribution for the velocity of gas particles, the Barabasi-Albert model and multiplicative noise systems

Impact of Hepatitis C treatment as prevention for people who inject drugs is sensitive to contact network

Treatment as Prevention (TasP) using directly-acting antivirals has been advocated for Hepatitis C Virus (HCV) in people who inject drugs (PWID), but treatment is expensive and TasP’s effectiveness is uncertain. Previous modelling has assumed a homogeneously-mixed population or a static network lacking turnover in the population and injecting partnerships. We developed a transmission-dynamic model on a dynamic network of injecting partnerships using data from survey of injecting behaviour carried out in London, UK. We studied transmission on a novel exponential-clustered network, as well as on two simpler networks for comparison, an exponential unclustered and a random network, and found that TasP’s effectiveness differs markedly. With respect to an exponential-clustered network, the random network (and homogeneously-mixed population) overestimate TasP’s effectiveness, whereas the exponential-unclustered network underestimates it. For all network types TasP’s effectiveness depends on whether treated patients change risk behaviour, and on treatment coverage: higher coverage requires fewer total treatments for the same health gain. Whilst TasP can greatly reduce HCV prevalence, incidence of infection, and incidence of reinfection in PWID, assessment of TasP’s effectiveness needs to take account of the injecting-partnership network structure and post-treatment behaviour change, and further empirical study is required

Assessing uncertainty in the burden of Hepatitis C Virus: comparison of estimated disease burden and treatment costs in the UK

Hepatitis C virus (HCV) is a major and growing public health concern. We need to know the expected health burden and treatment cost, and understand uncertainty in those estimates, to inform policymaking and future research. Two models that have been important in informing treatment guidelines and assessments of HCV burden were compared by simulating cohorts of individuals with chronic HCV infection initially aged 20, 35 and 50 years. One model predicts that health losses (measured in quality‐adjusted life‐years [QALYs]) and treatment costs decrease with increasing initial age of the patients, whilst the other model predicts that below 40 years, costs increase and QALY losses change little with age, and above 40 years, they decline with increasing age. Average per‐patient costs differ between the models by up to 38%, depending on the patients' initial age. One model predicts double the total number, and triple the peak annual incidence, of liver transplants compared to the other model. One model predicts 55%‐314% more deaths than the other, depending on the patients' initial age. The main sources of difference between the models are estimated progression rates between disease states and rates of health service utilization associated with different disease states and, in particular, the age dependency of these parameters. We conclude that decision‐makers need to be aware that uncertainties in the health burden and economic cost of HCV disease have important consequences for predictions of future need for care and cost‐effectiveness of interventions to avert HCV transmission, and further quantification is required to inform decisions