PurposeNoncommunicable diseases, prominently cancer, have become the second leading cause of death in the adult population of Ethiopia. A population-based cancer registry has been used in Addis Ababa (the capital city) since 2011. Availability of up-to-date estimates on cancer incidence is important in guiding the national cancer control program in Ethiopia.MethodsWe obtained primary data on 8,539 patients from the Addis Ababa population-based cancer registry and supplemented by data on 1,648 cancer cases collected from six Ethiopian regions. We estimated the number of the commonest forms of cancer diagnosed among males and females in Ethiopia and computed crude and age-standardized incidence rates.ResultsFor 2015 in Ethiopia, we estimated that 21,563 (95% CI, 17,416 to 25,660) and 42,722 (95% CI, 37,412 to 48,040) incident cancer cases were diagnosed in males and females, respectively. The most common adult cancers were: cancers of the breast and cervix, colorectal cancer, non-Hodgkin lymphoma, leukemia, and cancers of the prostate, thyroid, lung, stomach, and liver. Leukemia was the leading cancer diagnosis in the pediatric age group (age 0 to 14 years). Breast cancer was by far the commonest cancer, constituting 33% of the cancers in women and 23% of all cancers identified from the Addis Ababa cancer registry. It was also the commonest cancer in four of the six Ethiopian regions included in the analysis. Colorectal cancer and non-Hodgkin lymphoma were the commonest malignancies in men.ConclusionCancer, and more prominently breast cancer, poses a substantial public health threat in Ethiopia. The fight against cancer calls for expansion of population-based registry sites to improve quantifying the cancer burden in Ethiopia and requires both increased investment and application of existing cancer control knowledge across all segments of the Ethiopian population.

Background Despite declines in deaths from rheumatic heart disease (RHD) in Africa over the past 30 years, it remains a major cause of cardiovascular morbidity and mortality on the continent. We present an investment case for interventions to prevent and manage RHD in the African Union (AU).Methods We created a cohort state-transition model to estimate key outcomes in the disease process, including cases of pharyngitis from group A streptococcus, episodes of acute rheumatic fever (ARF), cases of RHD, heart failure, and deaths. With this model, we estimated the impact of scaling up interventions using estimates of effect sizes from published studies. We estimated the cost to scale up coverage of interventions and summarised the benefits by monetising health gains estimated in the model using a full income approach. Costs and benefits were compared using the benefit-cost ratio and the net benefits with discounted costs and benefits.Findings Operationally achievable levels of scale-up of interventions along the disease spectrum, including primary prevention, secondary prevention, platforms for management of heart failure, and heart valve surgery could avert 74 000 (UI 50 000-104 000) deaths from RHD and ARF from 2021 to 2030 in the AU, reaching a 30•7% (21•6-39•0) reduction in the age-standardised death rate from RHD in 2030, compared with no increase in coverage of interventions. The estimated benefit-cost ratio for plausible scale-up of secondary prevention and secondary and tertiary care interventions was 4•7 (2•9-6•3) with a net benefit of $2•8 billion (1•6-3•9; 2019 US$) through 2030. The estimated benefit-cost ratio for primary prevention scale-up was low to 2030 (0•2, <0•1-0•4), increasing with delayed benefits accrued to 2090. The benefit-cost dynamics of primary prevention were sensitive to the costs of different delivery approaches, uncertain epidemiological parameters regarding group A streptococcal pharyngitis and ARF, assumptions about long-term demographic and economic trends, and discounting.Interpretation Increased coverage of interventions to control and manage RHD could accelerate progress towards eradication in AU member states. Gaps in local epidemiological data and particular components of the disease process create uncertainty around the level of benefits. In the short term, costs of secondary prevention and secondary and tertiary care for RHD are lower than for primary prevention, and benefits accrue earlier.

Global health research has typically focused on single diseases, and most economic evaluation research to date has analysed technical health interventions to identify ‘best buys’. New approaches in the conduct of economic evaluations are needed to help policymakers in choosing what may be good value (ie, greater health, distribution of health, or financial risk protection) for money (ie, per budget expenditure) investments for health system strengthening (HSS) that tend to be programmatic. We posit that these economic evaluations of HSS interventions will require developing new analytic models of health systems which recognise the dynamic connections between the different components of the health system, characterise the type and interlinks of the system’s delivery platforms; and acknowledge the multiple constraints both within and outside the health sector which limit the system’s capacity to efficiently attain its objectives. We describe priority health system modelling research areas to conduct economic evaluation of HSS interventions and ultimately identify good value for money investments in HSS.

As a country with significant resource constraints, a fair and efficient health priority setting should be at the cornerstone of Ethiopia’s commitment to attain universal health coverage by 2035. This paper draws on the current national strategies including the national essential health service package to explore the criteria and processes used to set the existing national health sector priorities. Additionally, it reviews Ethiopia’s experience in comparison with the multi-criteria decision analysis proposed by Baltussen et al. Finally, the paper highlights the importance of strengthening country-led efforts and investing in human capital to shape priority setting in a developing country context.