Updated Health Opportunity Cost Estimates for 92 Low- and Middle-Income Countries: Implications for Global Health Financing and Donor Allocation

This paper presents updated marginal cost estimates per disability-adjusted life year (DALY) averted for 92 low- and middle-income countries using recent data and previously established elasticities, demonstrating that aligning domestic health spending with the Abuja Declaration and reallocating development assistance based on these opportunity costs could significantly maximize global health gains.

The Gist

Imagine the global health system as a massive, crowded kitchen where 92 different families (countries) are trying to cook the best possible meals for their people. The ingredients are money, and the meal is health.

This paper is like a new, updated recipe book that tells us exactly how much "health" we get for every extra dollar spent in each of these kitchens. The author, Jessica Ochalek, has refreshed an old recipe book from 2018 because the world has changed: prices have gone up, people are living longer, and the amount of money available has shifted.

Here is the breakdown of the paper using simple analogies:

1. The Core Problem: The "Opportunity Cost" of a Dollar

Every time a government spends a dollar on a new medicine or a hospital bed, that dollar cannot be used for something else. Maybe it could have bought vaccines, or paid for a nurse's salary.

• The Analogy: Think of your health budget as a pizza. If you add a slice of pepperoni (a new drug), you have to take a slice of cheese away (an existing service).
• The Question: Is the pepperoni slice worth more than the cheese slice?
• The Paper's Job: It calculates the "price tag" of that trade-off. It tells us: "In Country A, spending $100 saves 10 people from getting sick. In Country B, spending that same $100 only saves 1 person."

2. The Big Update: Prices Have Changed

The old recipe book (from 2018) is outdated.

• What happened: In many countries, governments have spent more money on health recently.
• The Result: Just like buying more of a product makes the next unit slightly less valuable (diminishing returns), spending more money means the next dollar doesn't save as many lives as the previous one did.
• The Finding: For most countries, the "cost" to save one year of healthy life (called a DALY) has gone up. It's harder to get a big health bang for your buck now than it was a decade ago because the "low-hanging fruit" has already been picked.

3. The Two Big Scenarios Tested

The author ran two "what-if" simulations to see how we could get the most health out of the money we have.

Scenario A: The "Abuja Promise" (Domestic Spending)

In 2001, many African countries promised to spend 15% of their total government budget on health. Most haven't kept that promise yet.

• The Simulation: What if every country finally kept that promise?
• The Cost: It would cost the world an extra $563 billion.
• The Gain: It would save 234 million years of healthy life.
• The Catch: That's a huge amount of money. It's like asking everyone to buy a second car. It's a great idea, but it's very expensive.

Scenario B: The "Global Potluck" (Donor Aid)

Rich countries and charities give about $39 billion a year to help poorer countries with health. Currently, this money is often sent to specific diseases (like just malaria) or specific countries based on old habits, not necessarily where it does the most good.

• The Simulation: What if we took that entire $39 billion pot and moved it around like a smart potluck? Instead of everyone bringing a dish to their own table, we put all the food in the middle and serve it to the people who are hungriest.
• The Result: By moving the money to the countries where it saves the most lives per dollar, we could save 133 million years of healthy life.
• The Comparison: If we just kept the money where it is now, we'd only save about 45 million years.
• The Lesson: Simply rearranging the money we already have could triple the number of lives saved, without asking for a single extra cent.

4. Why This Matters (The "New Compact")

The paper suggests a new way of doing things called the "New Compact."

• Old Way: Donors say, "Here is $1 million for malaria in Country X."
• New Way: Donors say, "Country X, you know your budget best. Here is the data showing where your money is most effective. We will help you fill the gaps there."

This approach treats the money from donors and the money from the country's own taxes as the same thing. It asks: "Where does this dollar do the most good right now?"

5. The Bottom Line

• For Countries: You need to know your own "price tag" for health. If you spend money on a treatment that costs more to save a life than your current budget allows, you are actually making your population less healthy by taking money away from better treatments.
• For Donors: Stop sending money based on tradition or politics. Send it to where the "health return on investment" is highest.
• The Takeaway: We are in a time where money is tight. To get the most out of every dollar, we need to stop guessing and start using these updated "price tags" to make smart, data-driven decisions.

In short: This paper is a map. It tells us that if we stop throwing money at the wrong places and start moving it to the places where it works best, we can save millions more lives without spending a penny more.

Technical Summary

1. Problem Statement

Low- and middle-income countries (LMICs) face severe resource constraints, necessitating difficult trade-offs in healthcare financing. To maximize population health, decision-makers require empirical evidence on the marginal cost per disability-adjusted life year (DALY) averted from government health expenditure (GHE). This metric serves as a cost-effectiveness threshold, indicating the health gains generated (or lost) by a marginal change in spending.

However, existing cross-country estimates (e.g., Ochalek et al., 2018) rely on data over a decade old. Since then, the global health landscape has shifted significantly due to:

• Changes in health expenditure patterns and disease burdens.
• Demographic shifts (aging populations).
• A 21% decline in Development Assistance for Health (DAH) between 2024 and 2025, projected to fall further.
• The need to operationalize the "New Compact" for global health, which prioritizes domestic resource mobilization and evidence-based donor alignment.

The paper addresses the critical gap in up-to-date, country-specific opportunity cost estimates required to inform both domestic priority setting and the efficient allocation of shrinking donor funds.

2. Methodology

The study updates estimates for 92 LMICs using the health opportunity cost framework established by Ochalek et al. (2018).

• Core Approach: Rather than re-estimating the elasticity of health outcomes with respect to GHE, the authors retained the previously estimated central elasticity parameters. They applied these to updated country-level inputs (mortality, morbidity, population structure, and GHE data) to reflect current realities.
• DALY Measures: Four alternative DALY-based measures were constructed to ensure consistency with the underlying elasticities:
  1. Elasticity of mortality.
  2. Elasticity of survival (Years of Life Lost - YLLs).
  3. Combined elasticity of survival and morbidity (Years Lived with Disability - YLDs).
  4. Elasticity estimated directly for DALYs.
  • Note: The analysis primarily presents results based on DALY 4 (direct DALY elasticity) as it is broadly representative and tractable for scenario modeling.
• Data Sources:
  • Health Outcomes: Global Burden of Disease (GBD) 2026 release (via GHDx).
  • Expenditure: World Bank National Health Accounts (GHE includes government schemes and compulsory insurance, excluding out-of-pocket payments).
  • Macro Data: World Bank GDP per capita and general government expenditure (GGE) data.
• Scenario Analysis:
  1. Abuja Declaration Scenario: Modeled the health impact if countries increased GHE to meet the target of 15% of General Government Expenditure (GGE). This involved calculating the additional funding required and the resulting DALYs averted using a power function of health production.
  2. Optimal Donor Allocation: Modeled the reallocation of the total 2025 DAH envelope ($39.1 billion) across countries to maximize global health gains. This involved iteratively shifting funds from countries with higher marginal costs per DALY to those with lower costs until an equilibrium was reached.

3. Key Contributions

• Updated Empirical Baseline: Provides the first comprehensive, updated estimates of marginal cost per DALY averted for 92 LMICs, replacing data that was over a decade old.
• Policy-Relevant Scenarios: Quantifies the health implications of two major policy shifts:
  • Achieving the Abuja Declaration target (15% of GGE).
  • Realigning donor funding based on the "New Compact" principles (shifting from earmarked disease-specific aid to supporting marginal expansions of national service packages).
• Refutation of Static Thresholds: Demonstrates that opportunity costs are dynamic and vary significantly across countries, challenging the use of static, universal cost-effectiveness thresholds (e.g., 1x or 3x GDP per capita) which may lead to inefficient resource allocation.
• Operationalizing the "New Compact": Offers the empirical foundation required to implement donor strategies that support domestic-first financing and consolidated supplementary aid.

4. Key Results

• Cost Estimates:
  • Updated marginal costs per DALY averted range from $78 to $15,789 (2026 USD) across countries.
  • 72% of countries show higher costs than in the 2018 analysis, largely driven by increases in GHE (diminishing marginal returns).
  • Most estimates (85 out of 91) remain below 1x GDP per capita, suggesting that using GDP-based thresholds risks underfunding cost-effective interventions.
• Abuja Declaration Scenario:
  • If all countries allocated 15% of GGE to health, an additional $563 billion would be required.
  • This investment would avert 234 million DALYs.
  • A more modest target of 10% GGE (requiring $91 billion) would avert 112 million DALYs.
• Donor Reallocation Scenario:
  • Current on-budget aid allocation averts 45.3 million DALYs.
  • Optimally reallocating existing on-budget support ($12.3 billion) could avert 71.1 million DALYs.
  • Optimally allocating the total DAH envelope ($39.1 billion) across 38 countries (moving funds from upper-middle-income and some lower-middle-income countries to the poorest nations) would avert 133.6 million DALYs.
  • This reallocation would reduce the global marginal cost per DALY averted to a minimum of $599.

5. Significance and Implications

• For Domestic Policy: Governments can use these estimates to design health benefits packages and set cost-effectiveness thresholds that reflect actual opportunity costs, ensuring that new interventions displace less efficient services.
• For Donor Strategy: The study provides a quantitative argument for the "New Compact." It demonstrates that ignoring cross-country variation in health productivity leads to massive losses in potential health gains. Aligning donor funding with country-specific opportunity costs can significantly increase global health impact without increasing total spending.
• For Global Health Financing: As external aid declines, the paper underscores the urgency for LMICs to mobilize domestic resources. However, it also highlights that efficiency is paramount; both domestic and external funds must be directed to settings where they generate the highest marginal health returns.
• Limitations: The study assumes the elasticity of health outcomes to expenditure remains stable over time and relies on national-level aggregates, potentially masking within-country heterogeneity. It also treats donor and domestic funds as interchangeable in terms of productivity, a simplification that future research should refine.

In conclusion, the paper argues that in an era of fiscal constraint and declining aid, dynamic, country-specific opportunity cost estimates are essential for maximizing the health impact of every dollar spent, whether by national governments or international donors.