Beyond survival: Shifting patterns of disease and disability in the Americas

In contrast to Chapter 1, which grouped the countries of the Americas by SDI scores, countries are grouped in this chapter using PAHO's Sustainable Health Index (SHIx) framework (Table 1). The SDI groupings in Chapter 1 placed countries within a broad development context based on fertility, education, and income to examine how this context relates to general health outcomes such as HALE. In this chapter, the SHIx framework is used instead to align with the chapter's focus on differences in disease burden, potentially avertable DALYs, and improvement potential across country groupings. In addition to socioeconomic conditions, SHIx incorporates health status, service coverage, inequality, and environmental determinants, providing a broader framework for examining between-country gradients relevant to disease burden and health equity. The groups of countries in this chapter are referred to as Clusters 1–⁠6 to differentiate them from the SDI groups of countries in Chapter 1 (Groups A–E). It is important to note that, although substantial inequalities may also exist within each country, grouping countries using the SHIx framework allows comparison only across clusters defined by specified SHIx score ranges.

For additional methodological details underlying this chapter, see Appendix II.

Is the Region of the Americas becoming healthier?

Health loss trends across regions of the world

In 2000 the Region of the Americas had the lowest health loss rate among WHO regions, at 32 916 per 100 000 population (Figure 13). However, the Region subsequently experienced a slower decline in this rate than all other WHO regions. Between 2000 and 2019, the age-standardized DALY rate in the Americas declined by 14%, compared with 26% in the European Region and 35% in the Western Pacific Region. The COVID-19 pandemic reversed these gains, especially in the Americas where the age-standardized DALY rate increased by 17% between 2019 and 2021, compared with 11% in the European Region and 5% in the Western Pacific Region. By 2023 the age-standardized DALY rate in the Americas remained above its 2019 level, and the Americas continued to have higher rates than both aforementioned regions. This pattern suggests that the slowdown in the Americas began before the pandemic.

The crude DALY trend adds a different dimension to the analysis. Although the crude DALY rates in the Americas follow a similar pattern to the Region's age-standardized rates, the crude rates retain the effect of the population's changing age structure and therefore provide a complementary indication of population-level service pressure associated with demographic change. Between 2000 and 2009, crude DALY rates in the Americas declined from 31 766 per 100 000 population to 30 186 and then spiked briefly in 2010, largely due to the earthquake in Haiti (Figure 14). After fluctuating in the early 2010s, the rates began a sustained increase around 2013–⁠2014, reaching 31 306 in 2019 before rising sharply again during the COVID-19 pandemic. Since 2020 crude DALY rates have declined, but by 2023 the rate remained elevated at 33 291. This indicates that even though age-standardized trends suggest some long-term improvement, population-level burden and associated service pressure have increased, especially since the mid-2010s. The longer-term trend of rising healthcare demand driven by aging populations and chronic conditions, together with violence and injuries, warrants particular attention, as these shifts may not be fully captured by age-standardized trends alone.

Magnitude and composition of health loss in the Americas over time

It is also useful to examine age-standardized DALY rates in the Americas in more detail to assess the magnitude and composition of health loss over time. In Figure 15, Panel (a) shows that most of the long-term decline in age-standardized DALY rates occurred before the early 2010s, falling from 32 916 per 100 000 population in 2000 to 29 619 in 2009. Between 2011 and 2019, they declined only slightly, again suggesting that progress had slowed before the pandemic. Panel (a) also shows that short-term spikes in the DALY burden were driven mainly by premature mortality, with spikes in YLL in 2010 (Haiti earthquake) and 2020–⁠2021 (COVID-19).

Panel (b) shows an important compositional shift: the disability component of DALYs (YLDs) has been increasing over time – from 38% in 2000 to 44% in 2023. This pattern indicates that the Region's disease burden profile is gradually shifting toward chronic diseases and disability, even as premature mortality remains important. The post-pandemic pattern reinforces this shift. Compared with 2019, YLD rates in 2023 were 714 per 100 000 higher, whereas YLL rates were 271 per 100 000 higher. The larger gap for YLD rates than YLL rates between the two time periods suggests that the post-pandemic burden profile reflects not only higher mortality but also higher levels of chronic morbidity and disability.

Health loss patterns across country clusters in the Americas

The regional DALY average masks substantial differences across SHIx clusters. Between 2000 and 2023, a clear equity gradient between clusters persisted, with Cluster 1 having the highest age-standardized DALY rate every year (Figure 16). In 2023 Cluster 1 recorded 38 932 DALYs per 100 000 population, compared with 27 120 DALYs in Cluster 6 – a difference of about 44%.

Progress before the pandemic was also uneven. Between 2000 and 2019, age-standardized DALY rates fell in five of the six clusters, with the largest reductions in Cluster 1 (20%) and Cluster 3 (18%). Cluster 2 was the exception, with rates increasing (5%) over the same period. DALY rates then climbed in all clusters due to the pandemic, temporarily widening gaps. The largest increases (>20%) occurred in Clusters 1 and 3 between 2019 and 2021. Recovery was incomplete by 2023: Cluster 1 had returned close to its 2019 level, but Clusters 2–⁠6 remained above their pre-pandemic rates. These differences show that inequities are not limited to the magnitude of burden; they also involve the pace of improvement, the intensity of shocks, and the extent of recovery.

Health loss patterns across the life course

Understanding where health loss concentrates across the life-span is essential for planning health services. Figure 17 explores how DALY rates vary across age groups and by sex, showing where health systems face the greatest volume of demand.

In both 2000 and 2023, DALY rates were highest at both ends of the life-span – among children under 5 years and among adults aged 70 years and older. Rates were lowest among children aged 5–⁠14 years, while working-age and older adults showed progressively higher levels of burden. Between 2000 and 2023, the most substantial improvements in DALY rates were among children under 5 years, among whom the rates fell sharply for both females and males. Across age groups, DALY rates were generally higher for males than females in both years.

So, is the Region of the Americas becoming healthier? The answer is complicated. Progress has occurred, but slowly and unevenly. Health emergencies, including the 2010 Haiti earthquake and the COVID-19 pandemic caused major setbacks. However, momentum had already been lost by the 2010s. By 2023 most country clusters still had not recovered to pre-pandemic levels. Meanwhile, health loss is shifting over the longer term from premature death toward chronic illness and disability. The crude disease burden also remains elevated, indicating that aging populations and chronic conditions are likely increasing the population-level service pressure for health systems, even when age-standardized trends suggest modest improvement. The age–sex pattern of health loss further shows that this service need is distributed unevenly across the life course: improvements in health loss among young children contrast with stubborn burden among working-age adults and rising demand from older populations. The equity lens adds another layer of complexity. Persistent differences across SHIx country clusters further show that regional averages can mask substantial inequities, not only in burden levels but also in improvement trajectories and post-pandemic recovery. These patterns point to a dual imperative in the Region: strengthen resilience to acute health emergencies while adapting health systems toward prevention, chronic and disability care, and continuity, with priorities and approaches tailored to the different needs and constraints of individual countries.

What are the leading causes of health loss in the Region of the Americas?

Knowing which conditions cause the greatest health loss is critical for smarter priority-setting. But rankings alone do not tell the full story. Some causes have been rising in prominence over time while others have remained persistently at the top despite intervention efforts. It is also important to understand similarities and differences between country clusters to combine regional priority-setting with context-specific adaptations where needed.

This section identifies the leading causes of health loss in the Region of the Americas and how the profile has changed over time. The GBD classifies these causes hierarchically, moving from broad Level 1 groups to progressively more specific Level 2, Level 3, and Level 4 causes. This chapter uses Level 2 causes, which group related diseases and conditions together to support consistent regional and cross-country comparisons across heterogeneous country settings. For example:

• The category “cardiovascular diseases” includes ischemic heart disease, stroke, hypertensive heart disease, cardiomyopathy and myocarditis, rheumatic heart disease, and other cardiovascular conditions.
• “Diabetes and kidney diseases” includes diabetes mellitus, acute glomerulonephritis, and chronic kidney disease, with chronic kidney disease further disaggregated by etiology.
• “Other NCDs” comprises congenital birth defects, urinary diseases and male infertility, gynecological diseases, hemoglobinopathies and hemolytic anemias, oral disorders, and endocrine, metabolic, blood, and immune disorders.

Level 3 and Level 4 analyses provide greater disease specificity but may be more sensitive to sparse data and wider uncertainty, particularly in countries with small populations. They are therefore more appropriate for detailed country-level priority-setting and intervention design using local data and context. Rankings are based on age-standardized DALY rates, with complementary attention to causes primarily associated with premature mortality (YLLs) vs. nonfatal disability (YLDs). This distinction is important because DALYs combine both fatal and nonfatal health loss, and shifts in DALY rankings can therefore reflect changes in mortality, survival with chronic disease, disability, or some combination of these.

Leading causes of health loss over time

The analysis shows that health loss in the Region of the Americas has remained concentrated in a relatively stable set of leading causes, even as the order of some causes has changed over time (Figure 18). Cardiovascular diseases and neoplasms (which include DALYs for both malignant cancers and benign/in situ neoplasms) remained the two leading causes throughout the period, illustrating that chronic diseases are the Region's core health challenge. Musculoskeletal disorders also remained near the top of the burden profile throughout most of the period.

Nine causes remained in the top 10 every year, suggesting that the Region's main burden agenda has been relatively persistent over time. Within this stable group, however, some shifts are policy relevant:

• Diabetes and kidney diseases rose from 9th to 5th, reflecting the growing importance of metabolic disease and its complications.
• Substance use disorders moved from 16th to 11th and approached the top 10 by 2023 – one of the largest upward movements across all causes.
• Maternal and neonatal disorders declined substantially, moving from 6th to 12th.
• Unintentional injuries also became less prominent in the regional ranking, moving from 4th to 7th.

The COVID-19 pandemic produced a major but partly temporary disruption in this otherwise stable pattern: respiratory infections moved from outside the top 10 prior to 2020 to the highest-ranked cause in 2020–⁠2021, before falling to 5th in 2022 and 10th in 2023. This pattern illustrates the scale of the COVID-era mortality shock and also shows that the underlying regional burden profile remained dominated by NCDs once the acute phase of the pandemic receded.

Mortality and disability burdens by the leading causes of health loss

DALYs combine two different types of health loss: years of life lost and years lived with disability. Understanding the mortality and disability components of the leading causes of health loss is critical for health systems to identify the appropriate balance between prevention and acute care on the one hand and long-term management, rehabilitation, and mental health needs on the other hand.

Premature mortality, or years of life lost, is dominated by cardiovascular diseases, neoplasms, violence, diabetes and kidney diseases, maternal and neonatal disorders, and respiratory infections and tuberculosis (Figure 19). These causes define the mortality-reduction agenda for the Region and point to the continued importance of health promotion, prevention, timely diagnosis, acute care, and effective management of life-threatening complications. The persistence of cardiovascular diseases and neoplasms near the top also reinforces the importance of primary prevention, such as policies to promote healthy eating, physical activity, healthy weights, and tobacco and alcohol reduction. It also requires long-term risk management, early detection, and continuous disease management – not only acute treatment.

The years lived with disability side of Figure 19 presents a different burden profile. Nonfatal disability is more strongly shaped by mental disorders, musculoskeletal disorders, sequelae of injuries, neurological disorders, diabetes and kidney diseases, and other chronic conditions that require continuous, person-centered care over time, as well as strengthened emergency and critical care response in the case of injuries. These causes do not always dominate mortality rankings, but they account for a large and growing share of lived health loss. Their prominence helps explain why the shift in the disease burden toward disability has important implications for service delivery. Health systems must prevent deaths and disabilities while also managing chronic morbidity, functional limitations, pain, mental health needs, and rehabilitation requirements.

Differences in leading causes of health loss by country clusters

The leading causes of health loss are broadly convergent across SHIx clusters, but they are not identical (Figure 20). Across all six clusters, the top causes are dominated by NCDs, especially cardiovascular diseases, neoplasms, diabetes and kidney diseases, mental disorders, and musculoskeletal disorders. This convergence supports the case for a shared regional agenda to address chronic disease prevention, cardiometabolic care, cancer control, mental health, and management of long-term disability. These priorities should be addressed through PHC-oriented integrated health service delivery networks, with referral-linked specialized and hospital care where required.

At the same time, there are meaningful differences across country clusters. Lower-SHIx clusters retain greater prominence of conditions such as maternal and neonatal disorders and respiratory infections and tuberculosis, while higher-SHIx clusters show a stronger profile of chronic conditions and mental disorders. Cluster 6 stands out as the only cluster with substance use disorders emerging prominently, while Cluster 2 is distinctive for the relative prominence of self-harm and interpersonal violence.

The figure therefore adds an important equity and prioritization lens to the regional rankings: the cluster-level patterns indicate that, despite a shared NCD-dominant burden profile, the relative prominence of leading causes differs across SHIx clusters. These differences are consistent with variation in development context, epidemiological transition, exposure patterns, and recovery from shocks, meaning that regional priorities should not be interpreted as a uniform package applied identically across all countries. Instead, they should provide a common starting point that is adapted to cluster-specific burden profiles and implementation needs. For cluster-specific rank trajectories for the leading causes of health loss, see Appendix III.

In summary, the answer to which conditions drive the Region's disease burden is both concentrated and differentiated. It is concentrated because a stable set of leading causes, dominated by NCDs, accounts for the main share of health loss across the Region. Cardiovascular diseases, neoplasms, diabetes and kidney diseases, musculoskeletal disorders, and mental disorders together define much of the long-term priority agenda. It is differentiated because the balance between mortality-driven and disability-driven causes varies, and because SHIx clusters differ in the causes that remain most prominent at the margin. The policy implication is that regional priority-setting can anchor around a shared core of high-burden conditions, especially cardiometabolic and chronic disabling conditions, but delivery strategies should be adapted to the specific cause mix, equity profile, and implementation needs of each country.

Which risk factors drive the leading causes of health loss in the Americas?

Prevention of disease works best when it targets the right risks. Identifying upstream risks and pathways – like high blood pressure and drug use – can inform a more efficient path to prevention, service delivery, and priority-setting than considering each condition separately.

This section ranks the leading modifiable and biological risk factors that shaped DALY burden in the Region of the Americas in 2000, 2015, and 2023, and identifies the specific risk–cause pairings that accounted for the greatest burden in 2023. (See Appendix II for methodological details.)

The findings reveal two critical patterns. First, health loss is concentrated in a small set of modifiable risks, with cardiometabolic and behavioral risks especially prominent. These risks include high body mass index, high fasting plasma glucose, high systolic blood pressure, dietary risks, tobacco, kidney dysfunction, and drug and alcohol use, alongside historically important risks such as child and maternal malnutrition and air pollution (Figure 21). Second, the risk profile is evolving: while some long-standing risks like tobacco use and child and maternal malnutrition have declined, metabolic risks including high body mass index and high fasting plasma glucose, along with substance use risks, have become more prominent. In policy terms, the risk profile supports a stronger focus on primary and secondary prevention for cardiometabolic conditions while also recognizing the growing importance of behavioral and substance use risks.

It is important to emphasize that these risk factors reflect more than individual behaviors or clinical traits. Their distribution follows social patterns, shaped by the conditions in which people live and work. Evidence shows that socioeconomic position contributes to premature mortality independently of conventional behavioral and metabolic risks (25).

Figure 22 identifies the specific Level 2 risk–cause pairings that accounted for the largest attributable DALY burden in the Region of the Americas in 2023. The leading pairings are heavily concentrated around cardiometabolic conditions:

• For cardiovascular diseases, the major attributable pathways are strongly shaped by modifiable risks related to blood pressure, diet, and lipid control.
• Diabetes and kidney diseases form the second major cardiometabolic pathway for which high fasting plasma glucose and high body mass index appear among their leading pairings, indicating that hyperglycemia and obesity-related risks are central contributors to this rising burden.

Together, the cardiovascular and diabetes–kidney pairings show that the cardiometabolic agenda is not confined to one disease category. It cuts across several high-burden outcomes and requires integrated prevention, risk detection, and long-term management.

Other leading pairings point to additional priorities:

• Child and maternal malnutrition remain linked to maternal and neonatal disorders.
• Drug use linked to substance use disorders appears among the leading pairings in 2023.

These pairings suggest that the prevention agenda should remain anchored in cardiometabolic risk reduction while also addressing persistent maternal and neonatal risks and emerging substance use-related burden. Furthermore, reducing future DALY burden will require population-level policies that make healthy choices easier, with sustained primary and secondary prevention.

How much of the Region's health loss remains above best-performance levels?

Some countries around the world have achieved substantially lower burden for the same diseases and conditions that still affect other countries. This raises a critical policy question: how large is the gap between the Region's current burden and comparatively strong performance already observed elsewhere? This section answers that question by comparing the Region to a global best-performance benchmark.

For each Level 2 cause of health loss, the benchmark represents the 10th percentile of 2023 age-standardized DALY rates across 204 countries and territories worldwide. In practical terms, the defined benchmark represents a comparatively strong performance level that has already been observed globally for the same cause while avoiding the instability of using the single lowest observed country rate. The difference between a country's observed burden and this benchmark provides a measure of improvement potential and is referred to here as “potentially avertable DALYs.”

The measure should be interpreted as a relative, benchmark-defined performance or improvement gap – not as burden proven to be causally, immediately, or fully preventable, and not as an operational target that countries are expected to close in full. The gap may reflect a combination of healthcare access and quality, risk exposure, social determinants of health, epidemiological differences not removed by age standardization, policy context, and uncertainty or assumptions in GBD estimates. Because the aggregate measure combines gaps across 22 cause-specific benchmarks, a single country may not realistically be able to achieve all thresholds simultaneously, and closing the aggregate gap may not be epidemiologically, operationally, or financially feasible. The potentially avertable DALYs measure is therefore most useful as a screening and comparative tool for identifying where more detailed cause-specific analysis, priority-setting, and equity-focused planning may be warranted. A related limitation is that low current burden or a small benchmark-defined gap may reflect the continuous effect of successful vaccination, vector control, treatment, surveillance, or other programs rather than low underlying need. Because the benchmark does not capture the maintenance value of these programs or the risk of resurgence if they weaken, a small gap should not be interpreted as evidence that investment can be reduced safely.

When the improvement gap is larger in some countries or SHIx clusters than others, it points to avoidable inequity in relation to better performance observed globally. However, the pathways and extent of improvement will differ by context, risk profile, resources, and capacity. (See Appendix II for further methodological details.)

Patterns in potentially avertable DALYs across countries of the Americas

The findings show substantial variation across countries of the Americas in the share of 2023 total DALYs estimated to be potentially avertable (Figure 23). The regional average was 39%, but country values varied widely around this average, from a low of 21% in Canada to a high of 84% in Haiti.

This measure adds information that is not captured by total DALY burden alone and serves an important screening function to assess a country's performance against a global benchmark. Two countries may have similar overall DALY levels but different avertable shares if one is closer to the benchmark across more causes. Conversely, a country with high total burden may have a moderate avertable share if its dominant causes are already closer to the benchmark.

The policy implication is that countries with a higher-than-average avertable share warrant a more detailed cause-level analysis. A high avertable share does not by itself identify which interventions should be prioritized, but it signals that a larger proportion of current health loss is above levels already achieved elsewhere.

Patterns in potentially avertable DALYs across SHIx clusters

Some variation in avertable burden across countries might be expected – but it is useful to explore how much of that variation follows predictable equity patterns. Analysis of the potentially avertable burden by SHIx clusters reveals a strong overall inverse pattern: lower-SHIx clusters have substantially larger shares of their total DALY burden estimated to be potentially avertable, while higher-SHIx clusters generally have smaller benchmark-defined gaps (Figure 24). This pattern reinforces the equity interpretation of the measure. The gap is not distributed randomly across the Region; it is larger in country groupings with greater inequality and less favorable health status, service coverage, and socioeconomic and environmental conditions.

These differences reflect patterns between countries, not within-country inequality. These patterns show that the remaining improvement potential in the Region is closely related to broader development and health system conditions. Lower-SHIx clusters not only experience higher burden in many areas but also remain farther from better levels of performance observed in other countries globally. In that sense, the potentially avertable DALY gap provides a quantitative expression of avoidable inequity across country groupings.

The SHIx pattern also has practical implications for priority-setting. A higher avertable share indicates greater scope for improvement, but the causes driving that gap differ across clusters. Cluster-specific cause-mix analyses are presented in Appendix IV, which shows how the benchmark-defined gap differs not only in magnitude but also in composition across SHIx clusters.

Patterns in potentially avertable DALYs across causes

The next question is which conditions or causes account most for the potentially avertable gap? Figure 25 compares each cause's share of total DALYs with its share of potentially avertable DALYs. This comparison is important because high burden and high benchmark-defined improvement potential are related but not identical. The findings show that some causes, such as neoplasms, contribute substantially to total DALYs but account for a smaller share of the benchmark-defined gap, suggesting that the Region's burden for those causes is relatively closer to the best-performance benchmark. Cardiovascular diseases remain central because of their large contribution to both total and potentially avertable DALYs. Other causes are overrepresented in the avertable gap, indicating larger shortfalls in the Region's burden relative to the global benchmark. The causes of health loss in this category include diabetes and kidney disease, self-harm and interpersonal violence, substance use disorders, maternal and neonatal disorders, respiratory infections and tuberculosis, transport injuries, and digestive diseases.

This distinction helps sharpen priority-setting: a cause with high total burden may justify continued investment because of scale, even where its benchmark-defined gap is relatively small or where currently available interventions have limited potential to reduce it further. Conversely, a cause with a high avertable share may indicate an especially important opportunity for further analysis, equity gains, or delivery reform, particularly when better outcomes have already been achieved elsewhere. Cause-specific gaps should therefore be interpreted alongside their mortality and disability composition, risk attribution, social determinants, feasibility, and available interventions, because different patterns may call for different combinations of preventive, clinical, rehabilitative, public health, and broader policy responses.

Mortality vs. disability component of the potentially avertable DALY gap

Understanding whether gaps in potentially avertable DALYs are mainly mortality-driven or disability-driven helps health authorities determine the best strategies needed to close the avertable gap. Figure 26 (a) compares the YLL (premature mortality) and YLD (disability) composition of potentially avertable DALYs in 2000, 2015, and 2023. Across the selected years, YLLs accounted for the larger share of potentially avertable DALYs, indicating that closing the benchmark-defined gap still requires substantial progress in preventing premature deaths. The rising YLD share in Panel (a) also shows that the disability component of the gap has become more important over time, consistent with the broader shift identified earlier in the chapter: the burden profile for the Region of the Americas is moving toward a greater share of lived health loss, even as premature mortality remains central.

Panel (b) adds the cause-specific interpretation for 2023. It shows that the YLL–YLD composition of potentially avertable DALYs varied sharply by Level 2 cause. For some causes, like cardiovascular diseases and maternal and neonatal disorders, the benchmark-defined gap is primarily mortality-driven. For others, such as mental disorders and musculoskeletal disorders, it is predominantly disability-driven. This means that closing the avertable DALY gap will require different delivery strategies across causes. Mortality-heavy gaps require prevention, early detection, acute care, and referral readiness. Disability-heavy gaps require continuity of care, rehabilitation, mental health services, functional support, and long-term management.

Returning to the main question of how much of the Region's health loss could be potentially averted, the benchmark analysis presented here suggests considerable room for improvement: nearly 40% of the Region's 2023 health loss remained above cause-specific levels already achieved by better-performing countries globally. This estimate represents a relative, benchmark-defined improvement gap, not a prediction that the burden can be immediately or fully prevented and not an operational target that countries are expected to close in full. The headline figure also conceals important variation across countries, causes, and the mortality and disability components of the gap.

Further analysis reveals a strong overall inverse pattern across SHIx clusters, with lower-SHIx clusters facing a higher intensity of potentially avertable burden. The cause analysis also shows that the causes contributing the most to total DALYs are not always the same ones that are overrepresented in the potentially avertable gap. Cardiovascular diseases and diabetes and kidney diseases remain central because they combine high burden with substantial potential for improvement. Other conditions appear more prominent through the avertable lens than through total burden. These include maternal and neonatal disorders, self-harm and interpersonal violence, substance use disorders, transport injuries, respiratory infections and tuberculosis, and selected disability-related conditions. The policy implication is that priority-setting should distinguish between causes that are large in total burden and causes that account for the largest benchmark-defined improvement gaps.

...

The evidence presented in this chapter shows that health loss in the Region of the Americas is changing not only in magnitude but also in composition, distribution, and avertability. Burden is increasingly concentrated in a set of chronic, cardiometabolic, disabling, injury-related, and equity-sensitive conditions; a small set of modifiable and biological risks connects several of these causes; and the benchmark-defined gap shows where improvement potential and avoidable inequity remain greatest. Regional and SHIx-cluster findings provide a starting point rather than a uniform package for countries. Health authorities must validate these signals against more granular national and subnational burden and equity evidence, disaggregated by locally relevant population groups. They should identify which causes and populations are driving priority gaps and assess intervention effectiveness, feasibility, affordability, and delivery capacity before selecting priorities and designing context-appropriate priority service bundles. Chapter 3 turns to this country-led process and to the policy, financing, regulatory, and delivery arrangements required to translate priorities into measurable health and equity gains.