Background By adulthood, gender inequalities in health and wellbeing are apparent. Yet, the timing and nature of gender inequalities during childhood and adolescence are less clear. We describe the emergence of gender inequalities in health and wellbeing across the first two decades of life.Methods We focused on the 40 low-income and middle-income countries in Asia and the Pacific. A measurement framework was developed around four key domains of wellbeing across the first two decades: health, education and transition to employment, protection, and a safe environment. Specific measurement constructs were then defined by considering gender indicator frameworks, the Sustainable Development Goals, indicator frameworks for child and adolescent health and wellbeing, and key stakeholder input. Available data were then mapped to define 87 indicators, subsequently populated using databases (UN agencies and the Global Burden of Diseases, Injuries, and Risk Factors Study) and nationally representative surveys. Where possible, estimates in girls were compared with boys to report relative risks.Findings Although son preference is evident in some settings-as shown by higher than expected male-to-female sex ratios at birth in India, Vietnam, and China (all >1•10 compared with an expected ratio of 1•05) and excess mortality of girl children in some South Asian and Pacific nations-it is during early adolescence where marked gender inequalities consistently emerged. Adolescent girls face considerable disadvantage in relation to sexual and reproductive health (notably in South Asia and the Pacific), with high rates of child marriage (≥30% of women aged 20-24 years married before 18 years in Bangladesh, Nepal, and Afghanistan), fertility (≥65 livebirths per 1000 girls in Nauru,

Background: Myanmar has set national hepatitis C (HCV) targets to achieve 50% of people diagnosed and 50% treated by 2030. The WHO has additional targets of reducing incidence by 80% and mortality by 65% by 2030. We aimed to estimate the impact, cost, cost-effectiveness and net economic benefit of achieving these targets. Methods: Mathematical models of HCV transmission, disease progression and the care cascade were calibrated to 15 administrative regions of Myanmar. Cost data were collected from a community testing and treatment program in Yangon. Three scenarios were projected for 2020-2030: (1) baseline (current levels of testing/treatment); and testing/treatment scaled up sufficiently to reach (2) the national strategy targets; and (3) the WHO targets. Findings: Without treatment scale-up, 333,0 0 0 new HCV infections and 97,0 0 0 HCV-related deaths were estimated to occur in Myanmar 2020-2030, with HCV costing a total $100 million in direct costs (testing, treatment, disease management) and $10.4 billion in lost productivity. In the model, treating 55,0 0 0 people each year was sufficient to reach the national strategy targets and prevented a cumulative 40,0 0 0 new infections (12%) and 25,0 0 0 HCV-related deaths (25%) 2020-2030. This was estimated to cost a total $189 million in direct costs ($243 per DALY averted compared to no treatment scale-up), but only $9.8 billion in lost productivity, making it cost-saving from a societal perspective by 2024 with an estimated net economic benefit of $553 million by 2030. Reaching the WHO targets required further treatment scale-up and additional direct costs but resulted in greater longer-term benefits. Interpretation: Current levels of HCV testing and treatment in Myanmar are insufficient to reach the national strategy targets. Scaling up HCV testing and treatment in Myanmar to reach the national strategy targets is estimated to generate significant health and economic benefits. Funding: Gilead Sciences.

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Background and aims Although most opioid‐related mortality in Australia involves prescription opioids, most research to understand the impact of naloxone supply on opioid‐related mortality has focused upon people who inject heroin. We aimed to examine the cost and probable impact of up‐scaling naloxone supply to people who are prescribed opioids. Design Decision‐tree model. Four scenarios were compared with a baseline scenario (the current status quo): naloxone scale‐up between 2020 and 2030 to reach 30 or 90% coverage by 2030, among the subgroups of people prescribed either ≥ 50 or ≥ 100 mg of oral morphine equivalents (OME). Setting Australia. Participants People who are prescribed opioids. Measurements Possible deaths averted, costs (ambulance and naloxone distribution) and cost per life saved for different scenarios of naloxone scale‐up. Findings Maintaining the status quo, there would be an estimated 7478 [uncertainty interval (UI) = 6868–8275] prescription opioid overdose deaths between 2020 and 2030, resulting in Australian dollars (A$)51.9 million (49.4, 56.0) in ambulance costs. If naloxone were scaled‐up to 90% of people prescribed > 50 mg OME, an estimated 657 (UI = 245, 1489) deaths could be averted between 2020 and 2030 (a 20% reduction in the final year of the model compared with the no naloxone scenario), with a cost of A$43 600 (20 800–110 500) per life saved. If naloxone were scaled‐up to 30% of people prescribed > 50 mg OME an estimated 219 (82–496) deaths could be averted with the same cost per live saved. If naloxone were restricted to those prescribed > 100 mg OME, an estimated 130 (UI = 44–289) deaths would be averted if scaled‐up to 30% or 390 (UI = 131–866) deaths averted if scaled‐up to 90%, with the cost per life saved for both scenarios A$38 200 (UI = 12 400–97 400). Conclusion In Australia, scaling‐up take‐home naloxone by 2030 to reach 90% of people prescribed daily doses of ≥ 50 mg of oral morphine equivalents would be cost‐effective and save more than 650 lives.