Reducing regional health inequality: a sub-national distributional cost-effectiveness analysis of community-based treatment of childhood pneumonia in Ethiopia

Background

Increasing the coverage of community-based treatment of childhood pneumonia (CCM) is part of the strategy to improve child survival, increase life-expectancy at birth and promote equity in Ethiopia. However, full coverage of CCM has not been reached in any regions of the country. There are no sub-national cost-effectiveness analyses available to inform decision makers on the most equitable scale up strategy.

Objectives

Our first objective is to estimate the sub-national cost-effectiveness and the interindividual inequality impacts of scaling up CCM coverages to 90% in each region. Our second objective is to explore the costs, health effects, and geographical inequality impacts associated with three scale-up scenarios promoting different policy-aims: maximizing health, reducing geographical inequalities, and achieving 90% universal coverage.

Methods

We used Markov modelling to estimate the sub-national cost-effectiveness of CCM in each region. All data were collected through literature review and adjusted to the region-specific proportions of the rural population. Health effects were modeled as life years gained and under-five deaths averted. Interindividual and geographical inequality impacts were measured by the GINI index applied to health. In scenario analysis we explored three different scale-up strategies: 1) maximizing health by prioritizing the regions where the intervention was the most cost-effective, 2) reducing geographical inequalities by prioritizing the regions with high baseline under-five mortality rate (U5MR), and 3) universal upscaling to 90% coverage in all the regions.

Results

The regional incremental-cost effectiveness ratio (ICER) of scaling up the intervention coverage varied from 26 USD per life year gained in Addis to 199 USD per life year gained in the Southern Nations, Nationalities, and Peoples’ region. Universal upscaling of CCM in all regions would cost about 1.3 billion USD and prevent about 90,000 under-five deaths. This is less than 15,000 USD per life saved and translates to an increase in life expectancy at birth of 1.6 years across Ethiopia. In scenario analysis, we found that prioritizing regions with high U5MR is effective in reducing geographical inequalities, although at the cost of fewer lives saved as compared to the health maximizing strategy.

Conclusions

Our model results illustrate a trade-off between maximizing health and reducing health inequalities, two common policy-aims in low-income settings.

Inequality of health stock and the relation to national wealth

BACKGROUND

The decline in global and between-country health inequality is a major challenge to overcome. However, few studies have systematically investigated the relationship between inequality of health stock and national wealth. From an economic perspective, health can be viewed as a durable capital stock that produces an output of healthy time. Therefore, in this paper, we focused on health capital to investigate the relationship between inequalities of national health and national wealth.

METHODS

Based on health stock data from 1990 to 2015 for 140 countries, we estimated Gini coefficients of health stock to investigate associations with a well-known economic flow indicator, Gross Domestic Product (GDP), stock-based national wealth indicator, Inclusive Wealth Index (IWI), and firm-level net income.

RESULTS

The estimated Gini coefficient of global health stock shows that health stock has experienced a global decline. The Gini coefficient for low-income countries (LICs) showed the fastest decline in health stock, dropping from 0.69 to 0.66 in 25 years. Next, rapid population growth and the rise in the youth share of the working-age population in LICs were most likely contributing factors to the decline in inequality. Most countries that experienced positive health stock growth also indicated a strong positive relationship with GDP and IWI. However, some countries showed a negative relationship with natural capital, which is a part of IWI. In addition, firm-level net income showed no obvious associations with health stock, GDP and IWI.

CONCLUSIONS

We argue that a negative relationship between health stock and natural capital is a sign of unstable development because sustainable development involves maintaining not only GDP but also IWI, as it is a collective set of assets or wealth comprising human, produced and natural capital. Moreover, in our analysis of firm-level income data, we also discuss that income will be influenced by other factors, such as innovations, human resources, organization culture and strategy. Therefore, the paper concludes that health stock is a vital component in measuring health inequality and health-related Sustainable Development Goals (SDGs). Thus, IWI is more comprehensive in measuring national wealth and can complement GDP in measuring progress toward sustainable development.