Correction: Health and economic benefits of achieving hepatitis C virus elimination in Pakistan: A modelling study and economic analysis.

[This corrects the article DOI: 10.1371/journal.pmed.1003818.].

Pathway to global elimination of hepatitis B: HBV cure is just the first step.

Hepatitis B (HBV) is a major cause of global morbidity and mortality, and the leading cause of liver cancer worldwide. Significant advances have recently been made toward the development of a finite HBV treatment that achieves permanent loss of HBsAg and HBV DNA (so-called "HBV cure"), which could provide the means to eliminate HBV as a public health threat. However, the HBV cure is just one step toward achieving WHO HBV elimination targets by 2030, and much work must be done now to prepare for the successful implementation of the HBV cure. In this review, we describe the required steps to rapidly scale-up future HBV cure equitably. We present key actions required for successful HBV cure implementation, integrated within the World Health Organization (WHO) Global Health Sector Strategy (GHSS) 2022-2030 framework. Finally, we highlight what can be done now to progress toward the 2030 HBV elimination targets using available tools to ensure that we are preparing, but not waiting, for the cure.

The cost-effectiveness of universal hepatitis B screening for reaching WHO diagnosis targets in Australia by 2030.

OBJECTIVES: To assess the impact on diagnosis targets, cost, and cost-effectiveness of universal hepatitis B screening in Australia. DESIGN: Markov model simulation of disease and care cascade progression for people with chronic hepatitis B in Australia. SETTING: Three scenarios were compared: 1. no change to current hepatitis B virus (HBV) testing practice; 2. universal screening strategy, with the aim of achieving the WHO diagnosis target by 2030 (90% of people with chronic hepatitis B diagnosed), based on opportunistic (general practitioner-initiated) screening for HBsAg; 3. universal screening strategy, and also ensuring that 50% of people with chronic hepatitis B are receiving appropriate clinical management by 2030. MAIN OUTCOME MEASURES: Projected care cascade for people with chronic hepatitis B, cumulative number of HBV-related deaths, intervention costs, and health utility (quality-adjusted life-years [QALYs] gained during 2020-2030). An incremental cost-effectiveness ratio (ICER) threshold (v scenario 1) of $50 000 per QALY gained was applied. RESULTS: Compared with scenario 1, 80 HBV-related deaths (interquartile range [IQR], 41-127 deaths) were averted during 2020-2030 in scenario 2, 315 HBV-related deaths (IQR, 211-454 deaths) in scenario 3. Scenario 2 cost $84 million (IQR, $41-106 million) more than scenario 1 during 2020-2030 (+8%), yielding an ICER of $104 921 (IQR, $49 587-107 952) per QALY gained. Scenario 3 cost $263 million (IQR, $214-316 million) more than scenario 1 during 2020-2030 (+24%), yielding an ICER of $47 341 (IQR, $32 643-58 200) per QALY gained. Scenario 3 remained cost-effective if the test positivity rate was higher than 0.35% or the additional costs per person tested did not exceed $4.02. CONCLUSIONS: Universal screening for hepatitis B will be cost-effective only if the cost of testing is kept low and people receive appropriate clinical management.

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.

Implementing the WHO Labour Care Guide to reduce the use of Caesarean section in four hospitals in India: protocol and statistical analysis plan for a pragmatic, stepped-wedge, cluster-randomized pilot trial.

BACKGROUND: The World Health Organization (WHO) Labour Care Guide (LCG) is a paper-based labour monitoring tool designed to facilitate the implementation of WHO's latest guidelines for effective, respectful care during labour and childbirth. Implementing the LCG into routine intrapartum care requires a strategy that improves healthcare provider practices during labour and childbirth. Such a strategy might optimize the use of Caesarean section (CS), along with potential benefits on the use of other obstetric interventions, maternal and perinatal health outcomes, and women's experience of care. However, the effects of a strategy to implement the LCG have not been evaluated in a randomised trial. This study aims to: (1) develop and optimise a strategy for implementing the LCG (formative phase); and (2) To evaluate the implementation of the LCG strategy compared with usual care (trial phase). METHODS: In the formative phase, we will co-design the LCG strategy with key stakeholders informed by facility assessments and provider surveys, which will be field tested in one hospital. The LCG strategy includes a LCG training program, ongoing supportive supervision from senior clinical staff, and audit and feedback using the Robson Classification. We will then conduct a stepped-wedge, cluster-randomized pilot trial in four public hospitals in India, to evaluate the effect of the LCG strategy intervention compared to usual care (simplified WHO partograph). The primary outcome is the CS rate in nulliparous women with singleton, term, cephalic pregnancies in spontaneous labour (Robson Group 1). Secondary outcomes include clinical and process of care outcomes, as well as women's experience of care outcomes. We will also conduct a process evaluation during the trial, using standardized facility assessments, in-depth interviews and surveys with providers, audits of completed LCGs, labour ward observations and document reviews. An economic evaluation will consider implementation costs and cost-effectiveness. DISCUSSION: Findings of this trial will guide clinicians, administrators and policymakers on how to effectively implement the LCG, and what (if any) effects the LCG strategy has on process of care, health and experience outcomes. The trial findings will inform the rollout of LCG internationally. TRIAL REGISTRATION: CTRI/2021/01/030695 (Protocol version 1.4, 25 April 2022).

The new WHO Labour Care Guide (LCG) is an innovative partograph that emphasises women-centred, evidence-based care during labour and childbirth. Together with clinicians working at four hospitals in India, we will develop and test a strategy to implement the LCG into routine care in labour wards of these hospitals. We will use a randomised trial design where this LCG strategy is introduced sequentially in each of the four hospitals, in a random order. We will collect data on all women giving birth and their newborns during this period and analyse whether the LCG strategy has any effects on the use of Caesarean section, women's and newborn's health outcomes, and women's experiences during labour and childbirth. While the trial is being conducted, we will also collect qualitative and quantitative data from doctors, nurses and midwives working in these hospitals, to understand their perspectives and experiences of using the LCG in their day-to-day work. In addition, we will collect economic data to understand how much the LCG strategy costs, and how much money it might save if it is effective. Through this study, our international collaboration will generate critical evidence and innovative tools to support implementation of the LCG in other countries.

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.

Controlled temperature chain for vaccination in low- and middle-income countries: a realist evidence synthesis.

Objective: To evaluate the evidence describing how the controlled temperature chain approach for vaccination could lead to improved equitable immunization coverage in low- and middle-income countries. Methods: We created a theory of change construct from the Controlled temperature chain: strategic roadmap for priority vaccines 2017-2020, containing four domains: (i) uptake and demand for the approach; (ii) compliance and safe use of the approach; (iii) programmatic efficiency gains from the approach; and (iv) improved equitable immunization coverage. To verify and improve the theory of change, we applied a realist review method to analyse published descriptions of controlled temperature chain or closely related experiences. Findings: We evaluated 34 articles, describing 22 unique controlled temperature chain or closely related experiences across four World Health Organization regions. We identified a strong demand for this approach among service delivery providers; however, generating an equal level of demand among policy-makers requires greater evidence on economic benefits and on vaccination coverage gains, and use case definitions. Consistent evidence supported safety of the approach when integrated into special vaccination programmes. Feasible training and supervision supported providers in complying with protocols. Time-savings were the main evidence for efficiency gains, while cost-saving data were minimal. Improved equitable coverage was reported where vaccine storage beyond the cold chain enabled access to hard-to-reach populations. No evidence indicated an inferior vaccine effectiveness nor increased adverse event rates for vaccines delivered under the approach. Conclusion: Synthesized evidence broadly supported the initial theory of change. Addressing evidence gaps on economic benefits and coverage gains may increase future uptake.

Covasim: An agent-based model of COVID-19 dynamics and interventions.

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.

The impact of three progressively introduced interventions on second wave daily COVID-19 case numbers in Melbourne, Australia.

BACKGROUND: The city of Melbourne, Australia experienced two waves of the COVID-19 epidemic peaking, the first in March and a more substantial wave in July 2020. During the second wave, a series of control measure were progressively introduced that initially slowed the growth of the epidemic then resulted in decreasing cases until there was no detectable local transmission. METHODS: To determine the relative efficacy of the progressively introduced intervention measures, we modelled the second wave as a series of exponential growth and decay curves. We used a linear regression of the log of daily cases vs time, using a four-segment linear spline model corresponding to implementation of the three successive major public health measures. The primary model used all reported cases between 14 June and 15 September 2020 then compared the projection of the model with observed cases predicting future case trajectory up until the 31 October 2020 to assess the use of exponential models in projecting the future course and planning future interventions. The main outcome measures were the exponential daily growth constants, analysis of residuals and estimates of the 95% confidence intervals for the expected case distributions, comparison of predicted daily cases. RESULTS: The exponential growth/decay constants in the primary analysis were: 0.122 (s.e. 0.004), 0.035 (s.e. 0.005), - 0.037 (s.e. 0.011), and - 0.069 (s.e. 0.003) for the initial growth rate, Stage 3, Stage 3 + compulsory masks and Stage 4, respectively. Extrapolation of the regression model from the 14 September to the 31 October matched the decline in observed cases over this period. CONCLUSIONS: The four-segment exponential model provided an excellent fit of the observed reported case data and predicted the day-to-day range of expected cases. The extrapolated regression accurately predicted the decline leading to epidemic control in Melbourne.

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.

Reducing malaria transmission in forest-going mobile and migrant populations in Lao PDR and Cambodia: protocol for stepped-wedge cluster-randomised controlled trial.

BACKGROUND: Countries of the Greater Mekong Sub-region aim to achieve malaria elimination by 2030. In the region, malaria is concentrated in high-risk areas and populations such as forest-going mobile and migrant populations (MMPs). However, routine protective measures such as long-lasting insecticidal nets do not prevent all infectious bites in these high-risk populations. Evidence for the effectiveness of a personal protection package tailored to forest-going MMPs which is acceptable, feasible, and cost-effective for reducing malaria transmission is required to inform the malaria elimination toolkit in the region. METHODS: A personal protection package consisting of long-lasting insecticidal hammock net, insect repellent and health communication pamphlet was developed in consultation with relevant implementing partners from Cambodia and Lao PDR. An open stepped-wedge cluster-randomised controlled trial will be conducted over a period of 12 months in a minimum of 488 villages (~ 428 in Lao PDR and ~ 60 in Cambodia) to evaluate the effectiveness of the personal protection package. Villages will be randomised into 11 blocks, with blocks transitioned in random order from control to intervention states at monthly intervals, following a 1-month baseline period. The primary outcome of the trial is the prevalence of Plasmodium spp. infection diagnosed by rapid diagnostic test. Difference in prevalence of malaria infection will be estimated across intervention and control periods using generalized linear mixed modelling. Nested within the stepped-wedge cluster-randomised controlled trial is a mixed-methods study to explore the acceptability of the personal protection package, feasibility of implementing a personal protection package as a vector control intervention, and knowledge, attitude and practice of MMPs regarding malaria prevention; and cost-analysis to determine the cost-effectiveness of implementing a personal protection package. DISCUSSION: This study, using a rigorous design and mixed-methods methodology, will evaluate whether a personal protection package can reduce residual malaria transmission among forest-going MMPs in Cambodia and Lao PDR. It will also measure implementation research outcomes such as effectiveness of the intervention package, cost-effectiveness, acceptability, and feasibility, in order to inform potential national and regional policy. Trial registration This trial was prospectively registered on ClinicalTrials.gov (NCT05117567) on 11th November 2021.

Psychiatric well-being among men leaving prison reporting a history of injecting drug use: A longitudinal analysis.

BACKGROUND: Community reintegration from prison is typically stressful, with several health and social outcomes impacting psychiatric well-being during this time, often exacerbated among individuals with histories of drug use. Longitudinal data was used to assess change in psychiatric well-being over 2 years following release from prison among men who reported a recent history of injecting drug use. METHODS: Data for this study come from the Prison and Transition Health cohort study of 400 men recruited in prison prior to release and followed up over three time points. Psychiatric well-being was assessed using the 12-item General Health Questionnaire. We calculated change in individual General Health Questionnaire scores between interviews and identified covariates associated with General Health Questionnaire score using linear mixed-effects regression. RESULTS: Data from 690 follow-up interviews among 326 participants were included in analyses. There was considerable variation in individuals' General Health Questionnaire scores. Moving accommodation frequently and frequent illicit drug injections were associated with an increase in General Health Questionnaire score (i.e. decline in psychiatric well-being). Two or more prior adult imprisonment episodes, social supports and past month primary healthcare attendance were associated with a decrease in General Health Questionnaire score. CONCLUSION: Our findings identify health, social and structural influences on psychiatric well-being after release from prison that can inform re-entry programmes to support community reintegration.

A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers.

The COVID-19 pandemic has brought the combined disciplines of public health, infectious disease and policy modelling squarely into the spotlight. Never before have decisions regarding public health measures and their impacts been such a topic of international deliberation, from the level of individuals and communities through to global leaders. Nor have models-developed at rapid pace and often in the absence of complete information-ever been so central to the decision-making process. However, after nearly 3 years of experience with modelling, policy-makers need to be more confident about which models will be most helpful to support them when taking public health decisions, and modellers need to better understand the factors that will lead to successful model adoption and utilization. We present a three-stage framework for achieving these ends.

Health and economic benefits of achieving hepatitis C virus elimination in Pakistan: A modelling study and economic analysis.

BACKGROUND: Modelling suggests that achieving the WHO incidence target for hepatitis C virus (HCV) elimination in Pakistan could cost US$3.87 billion over 2018 to 2030. However, the economic benefits from integrating services or improving productivity were not included. METHODS AND FINDINGS: We adapt a HCV transmission model for Pakistan to estimate the impact, costs, and cost-effectiveness of achieving HCV elimination (reducing annual HCV incidence by 80% by 2030) with stand-alone service delivery, or partially integrating one-third of initial HCV testing into existing healthcare services. We estimate the net economic benefits by comparing the required investment in screening, treatment, and healthcare management to the economic productivity gains from reduced HCV-attributable absenteeism, presenteeism, and premature deaths. We also calculate the incremental cost-effectiveness ratio (ICER) per disability-adjusted life year (DALY) averted for HCV elimination versus maintaining current levels of HCV treatment. This is compared to an opportunity cost-based willingness-to-pay threshold for Pakistan (US$148 to US$198/DALY). Compared to existing levels of treatment, scaling up screening and treatment to achieve HCV elimination in Pakistan averts 5.57 (95% uncertainty interval (UI) 3.80 to 8.22) million DALYs and 333,000 (219,000 to 509,000) HCV-related deaths over 2018 to 2030. If HCV testing is partially integrated, this scale-up requires an investment of US$1.45 (1.32 to 1.60) billion but will result in US$1.30 (0.94 to 1.72) billion in improved economic productivity over 2018 to 2030. This elimination strategy is highly cost-effective (ICER = US$29 per DALY averted) by 2030, with it becoming cost-saving by 2031 and having a net economic benefit of US$9.10 (95% UI 6.54 to 11.99) billion by 2050. Limitations include uncertainty around what level of integration is possible within existing primary healthcare services as well as a lack of Pakistan-specific data on disease-related healthcare management costs or productivity losses due to HCV. CONCLUSIONS: Investment in HCV elimination can bring about substantial societal health and economic benefits for Pakistan.

A global investment framework for the elimination of hepatitis B.

BACKGROUND & AIMS: More than 292 million people are living with hepatitis B worldwide and are at risk of death from cirrhosis and liver cancer. The World Health Organization (WHO) has set global targets for the elimination of viral hepatitis as a public health threat by 2030. However, current levels of global investment in viral hepatitis elimination programmes are insufficient to achieve these goals. METHODS: To catalyse political commitment and to encourage domestic and international financing, we used published modelling data and key stakeholder interviews to develop an investment framework to demonstrate the return on investment for viral hepatitis elimination. RESULTS: The framework utilises a public health approach to identify evidence-based national activities that reduce viral hepatitis-related morbidity and mortality, as well as international activities and critical enablers that allow countries to achieve maximum impact on health outcomes from their investments - in the context of the WHO's 2030 viral elimination targets. CONCLUSION: Focusing on hepatitis B, this health policy paper employs the investment framework to estimate the substantial economic benefits of investing in the elimination of hepatitis B and demonstrates how such investments could be cost saving by 2030. LAY SUMMARY: Hepatitis B infection is a major cause of death from liver disease and liver cancer globally. To reduce deaths from hepatitis B infection, we need more people to be tested and treated for hepatitis B. In this paper, we outline a framework of activities to reduce hepatitis B-related deaths and discuss ways in which governments could pay for them.

A modelling analysis of financial incentives for hepatitis C testing and treatment uptake delivered through a community-based testing campaign.

Financial incentives may reduce opportunity costs associated with people who become lost to follow-up in hepatitis C treatment programs. We estimated the impact that different financial incentive amounts would need to have on retention in care to maintain the same unit cost per (1) RNA-positive person completing testing (defined as awareness of RNA status) and (2) RNA diagnosed person initiating treatment. Costing data were obtained from a 2019 community-based testing campaign focused on engaging people who inject drugs. For different financial incentive amounts, we modelled the corresponding improvements in retention in care that would be needed to maintain the same overall (1) unit cost per testing completion and (2) unit cost per treatment initiation. In the testing campaign, the unit cost per RNA-positive person completing testing was A$3215 and the unit cost per RNA diagnosed person initiating treatment was A$1055. Modelling found that an incentive of A$500 per RNA-positive person completing testing would result in more people completing testing for the same unit cost if the percentage of attendees receiving their test results increased from 63% to 74%. An incentive of A$200 per RNA diagnosed person initiating treatment would result in more people initiating treatment for the same unit cost if the percentage initiating treatment increased from 67% to 83%. Monetary incentives for completing testing and initiating treatment may be an effective way to increase retention in care without increasing the overall unit cost of completing testing/initiating treatment.

A mobile phone application for malaria case-based reporting to advance malaria surveillance in Myanmar: a mixed methods evaluation.

BACKGROUND: To achieve malaria elimination in the Greater Mekong Subregion, including Myanmar, it is necessary to ensure all malaria cases are detected, treated, and reported in a timely manner. Mobile phone-based applications for malaria reporting, case management, and surveillance implemented at a community-level may overcome reporting limitations associated with current paper-based reporting (PBR), but their effectiveness in this context is unknown. METHODS: A mixed methods evaluation study was undertaken to determine the effectiveness of a national Malaria Case-Based Reporting (MCBR) mobile phone application in improving malaria case reporting compared to the existing PBR reporting system in Myanmar. Methods included secondary analysis of malaria case report data, questionnaires, focus group discussions and field observations of community volunteers, interviews and direct observations of malaria programme stakeholders, and cost analysis. Using a combination of these approaches the following areas were investigated: data quality and completeness, data access and usage, capacity for timely reporting, the acceptability, functionality, and ease of use of the application and facilitators and barriers to its use, and the relative cost of MCBR compared to the PBR system. RESULTS: Compared to PBR, MCBR enabled more accurate and complete data to be reported in a much timelier manner, with 63% of MCBR users reporting they transmit rapid diagnostic test outcomes within 24 h, compared to 0% of PBR users. MCBR was favoured by integrated community malaria volunteers and their supervisors because of its efficiency. However, several technical and operational challenges associated with internet coverage, data transmission, and e-literacy were identified and stakeholders reported not being confident to rely solely on MCBR data for programmatic decision-making. CONCLUSIONS: Implementation of MCBR provided timely and accurate data for malaria surveillance. Findings from this evaluation study will enable the optimization of an application-based reporting system for malaria monitoring and surveillance in the Greater Mekong Subregion and advance systems to track progress towards, and certify, the achievement of malaria elimination targets.

Real-world monitoring progress towards the elimination of hepatitis C virus in Australia using sentinel surveillance of primary care clinics; an ecological study of hepatitis C virus antibody tests from 2009 to 2019.

To achieve the elimination of the hepatitis C virus (HCV), sustained and sufficient levels of HCV testing is critical. The purpose of this study was to assess trends in testing and evaluate the effectiveness of strategies to diagnose people living with HCV. Data were from 12 primary care clinics in Victoria, Australia, that provide targeted services to people who inject drugs (PWID), alongside general health care. This ecological study spanned 2009-2019 and included analyses of trends in annual numbers of HCV antibody tests among individuals with no previous positive HCV antibody test recorded and annual test yield (positive HCV antibody tests/all HCV antibody tests). Generalised linear models estimated the association between count outcomes (HCV antibody tests and positive HCV antibody tests) and time, and χ2 test assessed the trend in test yield. A total of 44 889 HCV antibody tests were conducted 2009-2019; test numbers increased 6% annually on average [95% confidence interval (CI) 4-9]. Test yield declined from 2009 (21%) to 2019 (9%) (χ2P = <0.01). In more recent years (2013-2019) annual test yield remained relatively stable. Modest increases in HCV antibody testing and stable but high test yield within clinics delivering services to PWID highlights testing strategies are resulting in people are being diagnosed however further increases in the testing of people at risk of HCV or living with HCV may be needed to reach Australia's HCV elimination goals.

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.