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The case for urgent investment Annex 1. Additional methodological details and tables related to Chapter 1 This Annex provides further methodological detail on three aspects included in the main report: measuring the costs of inaction (see Section 1.3.1), the extent to which the models used have been validated by external reviews (see Section 1.3.2) and the methodology for health services modelling (see Section 1.3.3). It also includes an additional Table A1.7 related to Chapter 1 of the main report. 1.
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1. The cost of inaction 1.1 Measuring the costs of inaction In this section we provide details of the methodology used to estimate the cost of inaction, which is the cost of failing to take action to address the challenges facing adolescents and to improve their well-being. There are several possible approaches to this question, which in turn provide different interpretations of the cost of inaction.
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For example, one might estimate the economic and social loss arising from any death or morbidity for adolescents over a given period (or the loss arising from of a more broadly defined set of diminutions of adolescent well-being). This approach measures, for example, the loss from any deaths or morbidity for a given group of adolescents but does not tie the estimate to any failure to take action to avert these deaths or this morbidity.
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It measures the loss from a given level of mortality or morbidity, rather than losses arising from a specific failure to act. For the present study, we take an approach that focuses squarely on the costs of inaction. We estimate the opportunity costs incurred by failing to intervene, in the ways specified in the report, to improve adolescent well-being over the period in question. The costs of inaction are those of failing to intervene and hence of failing to achieve the estimated benefits.
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1.2 Implementing an opportunity cost approach In implementing this approach, it is important to note that the period of inaction – the period during which the interventions are not undertaken – is different from that in which the costs are incurred. Because many interventions have long-term benefits, over the full working life or even over the lifetime of the individual involved, the period of implementation is conceptually quite different to that in which the costs are incurred.
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There are several complexities involved in giving effect to the opportunity cost approach. The first complexity is that there are two different types of intervention considered in the report, discrete and extended. One type of intervention (such as a health treatment or a vaccination) is implemented at a discrete time, even though its benefits may accrue well into the future.
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The second type covers interventions that take place over an extended period, such as in the case of interventions to improve school retention and the quality of learning. Such interventions may take place over a period of 5–6 years, as improved teaching in a better context takes place over the student’s years of attendance at secondary school.
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For this reason, there are two modelling variants included in the overall report, as follows: (i) In areas where there are mainly discrete interventions, the interventions are scaled up progressively from base case levels in 2023 to target levels by 2035, and then cease. These include the four sets of health interventions (health services, HPV, TB and myopia).
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(ii) For the extended intervention areas (education and learning, road safety and child marriage), the interventions are again scaled up progressively from base case levels in 2023 to target levels by 2035 but are held at that effective level through to 2050. This means that the effect of the interventions is held at their level in 2035 through to 2050. This will require continued investment to maintain them at the 2035 level but will not require further investment in incremental programs. 101 Annex 1.
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101 Annex 1. Additional methodological details and tables related to Chapter 1 The cost of inaction reported here is the gross cost of inaction. That is, it does not take account of the investment necessary to reap the benefits. In calculating benefit-cost ratios (BCRs) for each type of intervention, the full costs are included in the denominator.
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For each of the intervention areas noted below, we construct a base case (broadly the consequences of existing policy settings) and an intervention case (broadly a set of interventions that are scaled up over time to 2035 and then, for the extended interventions, maintained at that level until 2050).
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Using epidemiological or other subject-specific models to estimate the human impact of the interventions and an economic model to value those impacts, we derive an estimate of the economic and social benefits of the intervention outcomes relative to those of the base case. The costs of inaction are the economic and social costs incurred by failing to take action to implement the interventions.
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We have applied this approach to the following areas: ƒ health (adolescent health services, HPV, TB, myopia); ƒ education, training and skills; ƒ child marriage; and ƒ road safety. Insufficient information is available to extend this approach to other areas covered in the report. 1.3 Specific methods and results The key specific aspects of the methodology are as follows: ƒ We express the costs of inaction as described above as net present values, at a 3% discount rate of flows over the 27 years 2024–50.
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ƒ For interventions of the discrete type, which are only modelled to 2035, we make the minimal assumption that, if the interventions were continued at the 2035 level out to 2050, the additional benefits to new cohorts subject to the interventions will be at least equal to those received by the 2024–35 cohorts. ƒ The country coverage of the interventions varies across the seven areas shown above, but in most areas of intervention, coverage rates are at or above 80% of the global population.
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ƒ For this reason, we use as our gross domestic product (GDP) comparator the GDP of emerging market and developing economies, as defined and estimated by the World Bank. Given the much lower per capita GDP in these countries than in developed nations, the emerging market and developing countries share of global GDP is 41.7%.1 ƒ The starting figure for estimating long-run GDP is projected GDP in this region in US$s in 2024. This figure is assumed to grow by 4% in real terms per annum out to 2050.
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The resulting GDP flow is expressed as a net present value, in 2024 and at a discount rate of 3%, to give the net present value (NPV) of estimated GDP in emerging market and developing economies over the 27 years 2024–50. ƒ This total NPV is divided by 27 to get the average annual GDP of this region over 2024–50, again expressed as an NPV in 2024 US$. This figure is US$52.5 trillion.
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This figure is US$52.5 trillion. ƒ On the same basis, the estimate of the average annual cost of inaction (benefits foregone) over 2024–50 is US$4.1 trillion per annum. ƒ This gives the estimated average cost of inaction as 7.7% of GDP, as indicated in the report. 1. https://www.imf.org/external/datamapper/NGDPD@WEO/ADVEC/WEOWORLD/OEMDC 102 Adolescents in a changing world. The case for urgent investment 2.
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The case for urgent investment 2. Validation of models The full report utilizes eight models, developed by the report writers and their collaborators, to calculate impacts, costs and benefits, and hence to estimate the benefit-cost ratios for the various classes of interventions. Of these models, five are established models which have been progressively developed and improved over time, while three are newer models, which have not as yet been used in peer-reviewed journal articles.
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The status of these models is reviewed in Table A1.1. Table A1.1 Origins, development paths and validation status for eight benefit-cost models used in this report Model area Origin and development Validation by journal reviewers Established models 1. Adolescent health services model Built for Sheehan et al. (2017) and reported in Sweeny et al. (2019). For this application there has been full re-estimation of OneHealth Tool (OHT) results with updated cost and economic components.
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See Chapter 2, section 2.1. Reviewed by eight external reviewers for the two publications cited (The Lancet and the Journal of Adolescent Health). 2. Education and training Built for Sheehan et al. (2017) from earlier work by UNESCO and UNICEF; reported in Wils et al. (2019). Here the model has been re-developed, retaining the basic structure of transition through grades. Upgrades include a new meta- analysis for effect sizes and the grouping of related interventions. See Chapter 6, section 6.2.
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See Chapter 6, section 6.2. Reviewed by eight external reviewers for the two publications cited (The Lancet and the Journal of Adolescent Health). 3. Improved productivity and employment Built for Sheehan et al. (2017); reported in Sheehan and Shi (2019). Modest macroeconomic multiplier and innovation effects have been added, but otherwise the values from the 2019 paper have been used. See Chapter 6, section 6.4 and Table 6.3.
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See Chapter 6, section 6.4 and Table 6.3. Reviewed by eight external reviewers for the two publications cited (The Lancet and the Journal of Adolescent Health). 4. Prevention of child marriage Initial modelling reported in Sheehan et al. (2017) and Rasmussen, Maharaj et al. (2019 and 2021) with further development in UNFPA (2022). The model used here now includes 70 countries with updated data inputs and effect size estimates. An optimization facility is also available.
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An optimization facility is also available. This model was substantially developed beyond the initial work for Sheehan et al (2017), with revised versions subject to peer review for the 2019 and 2021 publications. But the final version used here has not been reviewed. 5. Road traffic injury prevention Initially developed for Sheehan et al. (2017); see also Symons et al. (2019). Further enhanced since then with support from the FIA Foundation (Symons et al., 2022).
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For changes see Chapter 7, section 7.4. Base model reviewed by eight external reviewers for the two publications cited (The Lancet and the Journal of Adolescent Health). New models 1. HPV While an earlier model was used for Sheehan et al. (2017), a new model was built jointly with the Daffodil Centre, University of Sydney and Sweeny, Nguyen et al. (2023). See Chapter 2, section 2.2. The new model has not yet been sent for external review. 2.
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2. TB prevention and treatment This new model estimates the BCR from implementing the WHO End TB Strategy in 50 countries (95.7% of adolescent TB deaths). See Chapter 2, section 2.3. The new model has not yet been sent for external review. 3. Myopia screening and treatment This new model uses inter alia evidence from The Lancet Global Health Commission on Global Eye Health (Burton et al., 2021). See Chapter 2, section 2.4. The new model has not yet been sent for external review. 103 Annex 1.
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103 Annex 1. Additional methodological details and tables related to Chapter 1 1. Rasmussen, B, Maharaj, N. et al. Cost of ending child marriage. In UNFPA. Costing the three transformative results. New York: United Nations Population Fund; 2020, chap. 4. (https://www.unfpa. org/featured-publication/costing-three-transformative-results, accessed 15 May 2024). 2. UNFPA, Avenir Health, Johns Hopkins University, Victoria University.
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Impact of the COVID-19 pandemic on family planning and ending gender-based violence, female genital mutilation and child marriage. Interim technical note. New York: United Nations Population Fund; 2020. (https://www.unfpa.org/resources/impact-covid-19-pandemic-family-planning-and-ending-gender- based-violence-female-genital, accessed 15 May 2024). 3. Sweeny, K, Nguyen, DTN, Simms, K, Keane, A, Bateson, D, Canfell, K. An investment case study on HPV vaccination in Viet Nam.
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Hanoi: Ministry of Health (Viet Nam) and UNFPA Hanoi; 2023. (https://vietnam.unfpa.org/en/publications/investment-case-study-hpv-vaccination-viet-nam, accessed 20 February 2024). 4. Rasmussen, B, Sheehan, P, Symons, J, Maharaj, N, Welsh, A, Kumnick, M. Syria education and development investment case: economic, social and psychological costs and risks resulting from not investing in education systems in Syria. Report to UNICEF Syria. Melbourne: Victoria University; 2022.
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Melbourne: Victoria University; 2022. (https://content.vu.edu.au/sites/default/files/adolescents-education-syria-report.pdf, accessed 20 February 2024). 5. Rasmussen, B, Sheehan, P, Sweeny, K, Symons, J, Maharaj, N, Kumnick, M, et al. Adolescent investment case Burundi: estimating the impacts of social sector investments for adolescents. Report to UNICEF Burundi. Melbourne: Victoria University; 2019. (https://vuir.vu.edu.au/40741, accessed 20 February 2024). 6.
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6. Symons, J, Sweeny, K. Development of the investment case to reduce road traffic injuries among adolescents. London: FIA Foundation; 2022. (https://www.fiafoundation.org/media/ iyjfnfaj/final-report.pdf, accessed 20 February 2024). 3. Detailed methodology for health services modelling This section describes the methodology and assumptions used in modelling a range of adolescent health interventions using the OneHealth tool (OHT).
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3.1 Introduction This section reports on the modelling of 95 adolescent health interventions using the OHT in 40 low- income countries (LICs) and middle-income countries (MICs). The countries included in the modelling, which account for more than 80% of the global adolescent burden of disease, are listed in Table A1.2, along with their current World Bank income status (World Bank, 2023a).
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The group consists of 13 Low-income countries (LICs), 17 lower middle-income countries (LMICs) and ten upper middle-income countries (UMICs). The results from the OHT modelling are then used in an economic model to undertake a return on investment (ROI) analysis. In addition to extensive review by expert reviewers for leading journals, these models have been constructed and developed in conjunction with experts in individual subject areas.
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They have also been used in studies for international agencies and other organizations, such as UNFPA (1, 2 and 3), UNICEF (4, 5) and FIA Foundation (6) (see Box A1.1). Box A1.1 VISES reports and other papers 104 Adolescents in a changing world.
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The case for urgent investment Table A1.2 Countries included in OHT modelling, income status Afghanistan Low-income Angola Lower middle-income Bangladesh Lower middle-income Brazil Upper middle-income Burkina Faso Low-income Cameroon Lower middle-income China Upper middle-income Colombia Upper middle-income Cote d’Ivoire Lower middle-income Democratic Republic of the Congo Low-income Egypt Lower middle-income Ethiopia Low-income Ghana Lower middle-income India Lower middle-income Indonesia Upper middle-income Iran (Islamic Republic of) Lower middle-income Iraq Upper middle-income Kenya Lower middle-income Madagascar Low-income Malawi Low-income Mali Low-income Mexico Upper middle-income Mozambique Low-income Myanmar Lower middle-income Nepal Lower middle-income Niger Low-income Nigeria Lower middle-income Pakistan Lower middle-income Philippines Lower middle-income Russian Federation Upper middle-income Somalia Low-income South Africa Upper middle-income Sudan Low-income Thailand Upper middle-income Türkiye Upper middle-income Uganda Low-income United Republic of Tanzania Lower middle-income Viet Nam Lower middle-income Yemen Low-income Zambia Lower middle-income 3.2 Methods The approach for this study is similar to the one used in a global study on adolescent health and well-being for UNFPA (Sheehan et al., 2017).
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It estimates both the health impact and the cost of a programme of interventions designed to reduce adolescent death and disability. The outputs from an epidemiological model are used as inputs to an economic model that estimates the economic and social benefits arising from the interventions. The OHT model (Avenir Health, 2023) is overseen by the UN Inter-Agency Working Group on Costing, which has developed and governed the tool since the first version was launched in 2012.
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It estimates the costs and benefits of interventions to address many of the major causes of the adolescent burden of disease, including sexual and reproductive health (SRH), as well as a number of communicable and non-communicable diseases (NCDs). Avenir Health undertook the OHT modelling for this project.
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Making an investment case for interventions that address adolescent health relies on the following: ƒ selecting interventions; ƒ identifying the target population to which the interventions will be delivered; ƒ specifying what proportion of the target population (population in need) will receive the intervention; ƒ calculating the cost associated with delivering the intervention; and ƒ being able to quantify the impact of the intervention on the particular aspect of adolescent health and well-being considered.
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105 Annex 1. Additional methodological details and tables related to Chapter 1 The version of OHT used in this study is Spectrum 6.3 Beta 19, which has some 390 interventions across 12 major health programmes and 70 sub-programmes. It should be noted that the epidemiological models currently available within the tool to undertake cost and health impact modelling do not cover the full set of diseases and risk factors. Future expansions of the modelling framework are planned.
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In the current version of the model, from a total of 390 there are 181 interventions for which the model also calculates health outcomes in terms of mortality, morbidity, fertility and other demographic characteristics. For the remaining interventions, the tool calculates costs only (no impact) and therefore these interventions were excluded from the modelling.
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