In recent decades, external financing of health systems in low- and middle-income countries has helped achieve remarkable improvements across the world. However, these successes have not come without problems. There are a growing number of areas where external assistance can cause harm and even undermine the development of national health systems. Recent decades have seen a surge of knowledge on investing in health systems. We propose the setting up of investment standards for external assistance that aim to incentivize a more efficient evidence-based investment in a country’s health system, led by decision-makers in country. Using a more standardized process would lead to a better use of precious external assistance resources. The long-term goal would be fully functioning health systems with all the necessary essential public health functions in all countries.

South Africa’s effort to eliminate malaria is significantly challenged by a large number of imported malaria cases, especially from neighbouring Mozambique. The country has a funding gap to achieve its malaria elimination goals (prior to 2019) and is ineligible to receive a national allocation from the Global Fund. The findings of an IC were utilised to successfully mobilise resources for malaria elimination in South Africa in 2018. A five-step resource mobilisation strategy was implemented to highlight financing challenges and leverage the economic evidence from an IC for malaria elimination in South Africa. South Africa’s malaria programme implements control and elimination activities in three malaria-endemic provinces (KwaZulu Natal, Limpopo, and Mpumalanga). Driven by the IC findings, the South African government took an unprecedented step and increased total domestic malaria financing by approximately 36%, from the 2018/19 to the 2019/20 financial years through the creation of a new conditional grant for malaria. The IC findings predicted that malaria control in southern Mozambique is a prerequisite to eliminate malaria in South Africa. Based on this, the South African government also allocated funding towards a co-financing mechanism to support malaria control efforts in southern Mozambique. The IC findings assisted the South African National Department of Health to make a convincing case to key government decision-makers to invest in national malaria elimination and maximise economic returns in the long run. The South African government is the first in Southern Africa to mobilise a significant increase in domestic malaria financing to address the financial sustainability of both national and regional malaria elimination efforts. Continued surveillance activities will be required to prevent the re-establishment of malaria transmission even after malaria elimination is achieved in South Africa. Information sharing and close collaboration with provincial and national government officials were key to the successful outcome.

While South Africa has some experience in various forms of health technology assessment (HTA), it is currently fragmented across numerous players. Additionally, there is a lack of systematic and consistently applied HTA processes that inform priority-setting and budget allocations. To address this, the country is journeying toward more institutionalized use of HTA. This will begin with the establishment of a Ministerial Advisory Committee on HTA for National Health Insurance (NHI) and will gradually embed HTA processes in decision-making. The goal is to create an independent HTA agency. Although these reforms will be intrinsically linked to the wider health financing reforms envisaged under NHI, such as formulating the benefits package, they will also assist in strengthening South Africa's health system. As a country facing a highly constrained fiscal environment, with limited space for additional funding for the health sector, evidence-based priority-setting will be critical to ensure that value for money is achieved in the government's investments in health care services in NHI.

The COVID-19 epidemic was expected to result in shortages of public-sector critical care beds. This prompted the Western Cape Department of Health to explore ways to address the shortfall, culminating in a service-level agreement with the private sector and national level development of a system of reimbursement for critical care. This chapter describes the experience of formulating the agreement and the insights gained. Since the shift of patients between the sectors did not materialise, the most important outcome was that the parties were able to conclude this agreement, and the engagement provided insights beyond the original problem. The process revealed a lack of national leadership and co-ordination capacity; high levels of fragmentation; different visions of what care should be provided; the complexity entailed in contracting; capacity constraints in both sectors; and data constraints to inform policy choices. The most prominent lesson was that a trusting relationship was essential to the success of this initiative, built on a vision and a value system that all parties could endorse. We recommend the establishment of national-level capacity for public−private engagement, reviewing the regulations constraining contracting, fast-tracking the national data management system, enhancing in-house administrative capacity to complement the use of intermediaries, conducting a critique of this engagement, and a cost assessment of the options for expanding critical care capacity. It is premature to make a judgement on the success of the agreement. However, it provided a real-time demonstration of the complexities and constraints for such engagement within the South African context and it showed how, with trust and commitment, we can develop solutions. We should build on this experience by addressing the constraints, so that progress is made towards the more integrated health system as envisaged by National Health Insurance and required for universal health coverage.

South Africa has embarked on major health policy reform to deliver universal health coverage through the establishment of National Health Insurance (NHI). The aim is to improve access, remove financial barriers to care, and enhance care quality. Health technology assessment (HTA) is explicitly identified in the proposed NHI legislation and will have a prominent role in informing decisions about adoption and access to health interventions and technologies. The specific arrangements and approach to HTA in support of this legislation are yet to be determined. Although there is currently no formal national HTA institution in South Africa, there are several processes in both the public and private healthcare sectors that use elements of HTA to varying extents to inform access and resource allocation decisions. Institutions performing HTAs or related activities in South Africa include the National and Provincial Departments of Health, National Treasury, National Health Laboratory Service, Council for Medical Schemes, medical scheme administrators, managed care organizations, academic or research institutions, clinical societies and associations, pharmaceutical and devices companies, private consultancies, and private sector hospital groups. Existing fragmented HTA processes should coordinate and conform to a standardized, fit-for-purpose process and structure that can usefully inform priority setting under NHI and for other decision makers. This transformation will require comprehensive and inclusive planning with dedicated funding and regulation, and provision of strong oversight mechanisms and leadership.

COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and development partners. To understand the limitations of existing COVID-19 disease models (primarily from high income countries) and how they could be adequately support decision-making in LMICs, a desk review of modelling experience during the COVID-19 and past disease outbreaks, two online surveys, and regular online consultations were held among the collaborators. Three key recommendations from CMCC include: A ‘fitness-for-purpose’ flowchart, a tool that concurrently walks policymakers (or their advisors) and modellers through a model selection and development process. The flowchart is organised around the following: policy aims, modelling feasibility, model implementation, model reporting commitment. A ‘reporting standards trajectory’, which includes three gradually increasing standard of reports, ‘minimum’, ‘acceptable’, and ‘ideal’, and seeks collaboration from funders, modellers, and decision-makers to enhance the quality of reports over time and accountability of researchers. A framework for “collaborative modelling for effective policy implementation and evaluation” which extends the definition of stakeholders to funders, ground-level implementers, public, and other researchers, and outlines how each can contribute to modelling. We advocate for standardisation of modelling processes and adoption of country-owned model through iterative stakeholder participation and discuss how they can enhance trust, accountability, and public ownership to decisions.

Objective Previous research suggests a significant relationship between intimate partner violence (IPV) and HIV infection in women and that the risk of IPV is heightened in women with disabilities. Women with disabilities, particularly those residing in low-income and middle-income countries, may experience additional burdens that increase their vulnerability to IPV. We aimed to examine the association between having disability and HIV infection and the risk of IPV among women in South Africa.Design Using the 2016 South Africa Demographic and Health Survey, we calculated the prevalence of IPV and conducted modified Poisson regressions to estimate the unadjusted and adjusted risk ratios of experiencing IPV by disability and HIV status.Participants Our final analytical sample included 1269 ever-partnered women aged 18–49 years, who responded to the IPV module and received HIV testing.Results The prevalence of IPV was twice as high in women with disabilities with HIV infection compared with women without disabilities without HIV infection (21.2% vs 50.1%). Our unadjusted regression analysis showed that compared with women without disabilities without HIV infection, women with disabilities with HIV infection had almost four times higher odds (OR 3.72, 95% CI 1.27 to 10.9, p<0.05) of experiencing IPV. It appeared that women with disabilities with HIV infection experience compounded disparity. The association was compounded, with the OR for the combination of disability status and HIV status equal to or more than the sum of each of the individual ORs.Conclusions Women with disabilities and HIV infection are at exceptionally high risk of IPV in South Africa. Given that HIV infection and disability magnify each other’s risks for IPV, targeted interventions to prevent IPV and to address the complex and varied needs of doubly marginalised populations of women with disabilities with HIV infection are critical.

This chapter brings together aspects of the impact of COVID-19 on lives and livelihoods in South Africa. As at 15 August 2021, the epidemic is reported to have led to 77 141 deaths and been associated with 229 850 excess deaths. At the same time, the national economy has been severely affected with Gross Domestic Product decline of 7% in 2020/21, job losses exceeding 2 million, and sharp reductions in national revenue. The chapter takes a case study approach to provide an overview of the Government’s budgetary support to the health and income protection responses as well as the modelling that informed these. It also reviews some of the carry-through implications of the economic down-turn on public finances, including health budgets. The authors draw primarily on their experiences and subsequent reflection, with particular focus on the period 1 March 2021 to 28 February 2022. The budget provision for the health response to COVID-19 exceeded R20 billion, which was achieved through additional allocations and reprioritisation. Income protection measures exceeded R100 billion. However, suboptimal attention was given to how prolonged lockdowns would affect businesses, jobs, livelihoods and the economy over the medium and long term, with job losses initially exceeding 2.2 million and 1.4 million by the first quarter of 2021. As these effects fed through to public finances, growth and tax revenue declined substantially, resulting in reductions in virtually all government budgets. Over the 2021 Medium-term Expenditure Framework period, the economic effects of the epidemic and stringent lockdown measures have resulted in the reduction of provincial health budget projections by as much as R76 billion. The chapter emphasises the need to consider both lives and livelihoods in pandemic decision-making, ideally bringing together various dimensions of epidemiological and economic modelling in a multi-criteria decision framework.

BACKGROUND:Many countries have committed to achieving Universal Health Coverage. This paper summarizes selected health financing themes from five middle-income country case studies with incomplete progress towards UHC.METHODS:The paper focuses on key flagship UHC programs in these countries, which exist along other publicly financed health delivery systems, reviewed through the lens of key health financing functions such as revenue raising, pooling and purchasing as well as governance and institutional arrangements.RESULTS:There is variable progress across countries. Indonesia's Jaminan Kesehatan Nasional (JKN) reforms have made substantial progress in health services coverage and health financing indicators though challenges remain in its implementation. In contrast, Ghana has seen reduced funding levels for health and achieved less than 50% in the UHC service coverage index. In India, despite Ayushman Bharat (PM-JAY) reforms having provided important innovations in purchasing and public-private mix, out of pocket spending remains high and the public health financing level low. Kenya still has a challenge to use public financing to enhance coverage for the informal sector, while South Africa has made little progress in strategic purchasing.CONCLUSIONS:Despite variations across countries, therefore, important challenges include inadequate financing, sub-optimal pooling, and unmet expectations in strategic purchasing. While complex federal systems may complicate the path forward for most of these countries, evidence of strong political commitment in some of these countries bodes well for further progress.

To provide an overview of the impact of COVID-19 on lives and livelihoods in South Africa, and government’s budgetary support to the health and income protection responses; to review the epidemiological and economic modelling that informed the response and carry-through effects of the economic downturn on the economy, public finances and health budgets.

Public payers around the world are increasingly using cost-effectiveness thresholds (CETs) to assess the value-for-money of an intervention and make coverage decisions. However, there is still much confusion about the meaning and uses of the CET, how it should be calculated, and what constitutes an adequate evidence base for its formulation. One widely referenced and used threshold in the last decade has been the 1-3 GDP per capita, which is often attributed to the Commission on Macroeconomics and WHO guidelines on Choosing Interventions that are Cost Effective (WHO-CHOICE). For many reasons, however, this threshold has been widely criticised; which has led experts across the world, including the WHO, to discourage its use. This has left a vacuum for policy-makers and technical staff at a time when countries are wanting to move towards Universal Health Coverage . This article seeks to address this gap by offering five practical options for decision-makers in low- and middle-income countries that can be used instead of the 1-3 GDP rule, to combine existing evidence with fair decision-rules or develop locally relevant CETs. It builds on existing literature as well as an engagement with a group of experts and decision-makers working in low, middle and high income countries.

Public payers around the world are increasingly using cost-effectiveness thresholds (CETs) to assess the value-for-money of an intervention and make coverage decisions. However, there is still much confusion about the meaning and uses of the CET, how it should be calculated, and what constitutes an adequate evidence base for its formulation. One widely referenced and used threshold in the last decade has been the 1-3 GDP per capita, which is often attributed to the Commission on Macroeconomics and  WHO guidelines on Choosing Interventions that are Cost Effective (WHO-CHOICE). For many reasons, however, this threshold has been widely criticised; which has led experts across the world, including the WHO, to discourage its use. This has left a vacuum for policy-makers and technical staff at a time when countries are wanting to move towards Universal Health Coverage . This article seeks to address this gap by offering five practical options for decision-makers in low- and middle-income countries that can be used instead of the 1-3 GDP rule, to combine existing evidence with fair decision-rules or develop locally relevant CETs. It builds on existing literature as well as an engagement with a group of experts and decision-makers working in low, middle and high income countries.

Public payers around the world are increasingly using cost-effectiveness thresholds (CETs) to assess the value-for-money of an intervention and make coverage decisions. However, there is still much confusion about the meaning and uses of the CET, how it should be calculated, and what constitutes an adequate evidence base for its formulation. One widely referenced and used threshold in the last decade has been the 1-3 GDP per capita, which is often attributed to the Commission on Macroeconomics and WHO guidelines on Choosing Interventions that are Cost Effective (WHO-CHOICE). For many reasons, however, this threshold has been widely criticised; which has led experts across the world, including the WHO, to discourage its use. This has left a vacuum for policy-makers and technical staff at a time when countries are wanting to move towards Universal Health Coverage. This article seeks to address this gap by offering five practical options for decision-makers in low- and middle-income countries that can be used instead of the 1-3 GDP rule, to combine existing evidence with fair decision-rules or develop locally relevant CETs. It builds on existing literature as well as an engagement with a group of experts and decision-makers working in low, middle and high income countries.

Dean T. Jamison, Ala Alwan, Charles N. Mock, Rachel Nugent, David A. Watkins, Olusoji Adeyi, Shuchi Anand, Rifat Atun, Stefano Bertozzi, Zulfiqar Bhutta, Agnes Binagwaho, Robert Black, Mark Blecher, Barry R. Bloom, Elizabeth Brouwer, Donald A. P. Bundy, Dan Chisholm, Alarcos Cieza, Mark Cullen, Kristen Danforth, Nilanthi de Silva, Haile T. Debas, Peter Donkor, Tarun Dua, Kenneth A. Fleming, Mark Gallivan, Patricia García, Atul Gawande, Thomas Gaziano, Hellen Gelband, Roger Glass, Amanda Glassman, Glenda Gray, Demissie Habte, King K. Holmes, Susan Horton, Guy Hutton, Prabhat Jha, Felicia Knaul, Olive Kobusingye, Eric Krakauer, Margaret E. Kruk, Peter Lachmann, Ramanan Laxminarayan, Carol Levin, Lai Meng Looi, Nita Madhav, Adel Mahmoud, Jean-Claude Mbanya, Anthony R. Measham, María Elena Medina-Mora, Carol Medlin, Anne Mills, Jody-Anne Mills, Jaime Montoya, Ole Norheim, Zachary Olson, Folashade Omokhodion, Ben Oppenheim, Toby Ord, Vikram Patel, George C. Patton, John Peabody, Dorairaj Prabhakaran, Jinyuan Qi, Teri Reynolds, Sevket Ruacan, Rengaswamy Sankaranarayanan, Jaime Sepúlveda, Richard Skolnik, Kirk R. Smith, Agnes Soucat, Marleen Temmerman, Stephen Tollman, Stéphane Verguet, Damian Walker, Neff Walker, Yangfeng Wu y Kun Zhao Volumen 9, Capítulo 1

Conveys the main findings of Disease Control Priorities, Third Edition (DCP3), and in particular its conclusions concerning intersectoral policy priorities and essential universal health coverage (EUHC), describing the context in which DCP3's analyses have been undertaken and introducing the substantive topics addressed. DCP3 has four major objectives that go beyond previous editions: (1) to address explicitly the financial risk protection and poverty reduction objective of health systems; (2) to apply systematic attention to the intersectoral determinants of health; (3) to organize interventions into 21 essential packages (EPs); and (4) to provide estimates for low- and lower-middle-income countries of incremental and total costs in 2030 for both EUHC and highest-priority package (HPP)—and of the magnitude of their impact on mortality. In addition to these new elements, DCP3 updates the efforts of DCP1 and DCP2 to assemble and interpret the literature on economic evaluation of health interventions.