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Deciding where to launch a global health program is one of the most consequential decisions an NGO leader makes. Launch in the wrong context — insufficient digital infrastructure, hostile regulatory environment, existing well-resourced programs already serving the population — and you generate modest impact at high cost. Launch in the right context — large unmet need, viable delivery infrastructure, a regulatory environment that permits the model — and every dollar of organizational investment translates into substantially more impact.

For digital depression programs specifically, the decision involves a distinctive combination of factors that don’t apply to most other global health interventions. The technology-mediated delivery creates digital infrastructure requirements. The lay counselor model creates workforce requirements. The evidence-based content creates adaptation requirements. And the mental health context creates stigma and regulatory dimensions that don’t exist for bed net distribution or vaccination programs.

This post lays out the framework that Ambitious Impact developed for prioritizing countries for WHO Step-by-Step expansion, the ten countries that emerged from that analysis, and the practical considerations that should inform how organizations sequence geographic expansion in this space.

The Framework: What Matters for Country Prioritization

Country prioritization for digital depression programs requires assessment across five dimensions, each of which can be a constraint or an enabler depending on context.

1. Depression Burden

The most fundamental criterion is the size of the addressable problem. Countries with higher depression prevalence — whether due to conflict, poverty, displacement, or other structural factors — have more potential beneficiaries per unit of organizational investment. Depression burden is measured using Disability-Adjusted Life Years (DALYs) lost to depressive disorders, standardized by population.

High-burden contexts for depression include countries with significant conflict-affected populations (where depression rates are substantially elevated above non-conflict baselines), countries with high rates of poverty and economic precarity, and countries where structural factors — gender inequality, limited social support systems, rapid urbanization — contribute to elevated depression prevalence.

Burden alone doesn’t determine priority, but a context with low depression burden relative to other options should rarely be prioritized, regardless of how favorable other factors are. Impact per dollar is fundamentally constrained by addressable need.

2. Treatment Gap

Burden must be considered alongside existing provision. A country with high depression burden but well-developed, accessible mental health services represents a different opportunity — and a different level of additionality — than a country with comparable burden and near-zero existing provision.

The treatment gap — the proportion of people with depression who receive no treatment — provides a direct measure of unmet need. In most LMICs, the treatment gap is 75 percent or higher, but there is meaningful variation between countries. Countries where existing provision is genuinely scarce, and where a new program would be reaching populations with no current access to comparable care, represent higher-additionality opportunities than those where some provision exists, even if imperfect.

3. Digital Infrastructure

The WHO Step-by-Step model, as deployed by Kaya Guides, requires access to a smartphone and a WhatsApp account. This requirement is less restrictive than it might appear — WhatsApp penetration rates in many target countries are high, and smartphone ownership has expanded rapidly — but it is still a real constraint that varies significantly across and within countries.

Relevant metrics include: smartphone ownership rates (overall and by income quintile, gender, and urban/rural location), WhatsApp penetration and usage patterns, mobile data affordability and reliability, and electricity access for device charging. Programs that require continuous connectivity will be more constrained by infrastructure gaps than those that allow offline engagement or asynchronous delivery.

Digital infrastructure gaps are not static — they are closing rapidly in most LMICs — which means a context that is marginally below the threshold today may be viable within two to three years. Country prioritization should consider the trajectory of digital infrastructure development, not just the current state.

4. Regulatory Environment

Mental health is a regulated domain in virtually every country. The specific regulatory questions for a program like Step-by-Step include: What are the legal requirements for delivering psychological support? Can lay counselors legally conduct the support calls that are central to the guided self-help model? Are there requirements for clinical oversight or professional registration that would add cost or operational complexity? What are the data protection and privacy requirements for handling sensitive mental health information?

Regulatory environments for lay counselor delivery vary substantially. Some countries have explicit frameworks for community mental health worker roles that accommodate the Step-by-Step model. Others have no clear framework, creating legal ambiguity. A small number have restrictive requirements that would make lay counselor delivery of psychological support illegal or prohibitively complex.

Regulatory risk is not always a hard constraint — ambiguous environments can sometimes be navigated through engagement with regulatory authorities, and regulatory frameworks evolve. But organizations should enter new country contexts with a clear-eyed assessment of regulatory risk and a strategy for managing it, rather than discovering barriers after operational investment has been made.

5. Operational Feasibility

Even in contexts that score well on burden, treatment gap, digital infrastructure, and regulatory environment, operational realities can constrain program viability. Relevant factors include: the organization’s existing presence or partnerships in the country, the availability of local staff with the language skills and cultural competence to manage the program, the ability to recruit and train lay counselors from the target community, the stability of the operating environment (political, security, economic), and the availability of referral pathways for participants who need more intensive support than the program provides.

Operational feasibility considerations often argue for sequencing expansion in ways that allow organizational learning to compound. A second country that is culturally and operationally similar to the founding context is lower-risk than a second country that requires entirely new languages, counselor recruitment channels, and partnership relationships. The learning from context A reduces the cost and risk of entering context B when they share relevant features.

The Ten Priority Countries

Applying this framework, Ambitious Impact’s research identified ten countries as priority targets for WHO Step-by-Step expansion: Pakistan, China, Nigeria, Bangladesh, Indonesia, Egypt, Brazil, Tajikistan, Ethiopia, and Malaysia.

Each country has a distinctive profile that explains its ranking. A brief analysis of the key factors for each:

Pakistan scores highly on depression burden (elevated by conflict exposure, poverty, and high rates of gender-based adversity), treatment gap (mental health infrastructure is extremely limited, particularly outside major urban centers), and digital infrastructure (rapidly expanding smartphone penetration and high WhatsApp usage). The program has already been tested in a Pakistani RCT, reducing cultural adaptation requirements. Regulatory environment for lay counselors is manageable.

China presents a different profile: middle-income country with strong digital infrastructure, high WhatsApp-equivalent penetration (though regulatory complexity around foreign apps requires consideration), substantial depression burden driven by rapid urbanization and social isolation, and a significant treatment gap despite relatively better economic resources than other priority countries. A Chinese-language RCT of Step-by-Step has been completed, providing a head start on cultural adaptation.

Nigeria is the largest country in Sub-Saharan Africa by population, with a very large absolute depression burden, near-zero specialist mental health infrastructure, rapidly growing smartphone penetration, and a population that is predominantly young — a demographic that is both at elevated depression risk and particularly likely to engage with digital delivery.

Bangladesh combines high depression burden (driven by poverty, climate vulnerability, and demographic pressure), a large addressable population, growing smartphone penetration, and limited existing mental health provision. Geographic density — one of the world’s most densely populated countries — creates favorable economics for lay counselor recruitment and supervision.

Indonesia has the fourth-largest population in the world, high WhatsApp penetration, significant depression burden, and a growing digital health ecosystem that creates potential for partnership and integration with existing programs. Linguistic diversity (hundreds of regional languages) creates adaptation complexity that should be factored into sequencing decisions.

Egypt benefits from a completed Arabic-language RCT of Step-by-Step, making it one of the best-evidenced contexts for program deployment. Depression burden is significant, WhatsApp penetration is very high, and the urban population’s familiarity with digital tools supports engagement. An Egyptian-language program is effectively ready for deployment, reducing the adaptation investment required.

Brazil represents the largest opportunity in Latin America — a country with substantial depression burden, Portuguese-language adaptation requirements, high smartphone penetration, and significant geographic variation in mental health provision (urban areas have some access; rural and peri-urban areas have much less). Brazil’s regulatory environment is complex but navigable.

Tajikistan may surprise as a priority given its relatively small population, but it scores highly on the combination of very limited mental health infrastructure, high depression burden in a post-Soviet context with significant economic precarity, and a regulatory environment shaped by the Soviet healthcare legacy that includes community health worker roles compatible with lay counselor delivery.

Ethiopia has one of the largest absolute populations in Sub-Saharan Africa, very limited mental health provision, and a rapidly expanding digital infrastructure — still with significant gaps, particularly in rural areas, but improving. The Ethiopian context is higher-complexity than some other priority countries, but the scale of unmet need justifies the operational investment.

Malaysia is an upper-middle-income country with strong digital infrastructure, high WhatsApp penetration, and — despite relatively better economic development — a significant mental health treatment gap driven partly by stigma and partly by the concentration of specialist services in major urban centers. The economic profile makes Malaysia suitable for a model with slightly higher per-participant cost than the lowest-income contexts.

Sequencing Expansion: Practical Considerations

Having a list of priority countries doesn’t answer the sequencing question: which to enter first, and in what order? Several principles should guide this decision for organizations in Kaya’s position.

Sequence for learning, not just impact. Earlier expansions should be chosen partly for their learning value — what will operating in this context teach us that will make subsequent expansions more efficient? Countries that share features with later priorities (language family, regulatory framework type, digital infrastructure profile) are valuable early entries because the learning compounds.

Minimize the number of simultaneous unknowns. Every new country entry involves multiple new unknowns — counselor recruitment, cultural adaptation, regulatory navigation, partnership development. Entering a new country that differs from the founding context on all of these dimensions simultaneously creates high operational risk. Sequencing to minimize the number of new unknowns per entry — choosing contexts that share language, or regulatory framework, or partnership network — reduces risk and improves the odds of a successful first cohort.

Build the referral pathway before scaling. The absence of referral infrastructure — clear pathways for participants who need more intensive support — is a safety and quality risk. Before scaling to significant participant volumes in a new context, organizations should invest in establishing at least basic referral relationships with whatever higher-level services exist, even if imperfect.

Consider the funding implications of geographic choice. Some contexts are more legible to specific funders than others. An organization that relies heavily on funders based in the UK may find that expansion to South Asia is more fundable than expansion to Latin America, not because of any difference in impact potential but because of funder familiarity and existing portfolio logic. Geographic sequencing should account for the funding implications of each choice, particularly for early-stage organizations where funding constraints are binding.

Don’t let the priority list become a constraint. The ten-country list is a starting point derived from the best available evidence, not a fixed mandate. If a compelling partnership opportunity, regulatory opening, or funding relationship creates a strong case for entering a country not on the list, the framework should inform — not override — that decision. The goal is maximum impact, and sometimes the path to maximum impact deviates from any pre-specified plan.

The Competitive Landscape

Country prioritization decisions should also consider the competitive landscape — whether other organizations are working effectively in the same space in the target context. The goal of NGO country selection should not be to compete with existing high-quality programs, but to extend provision to populations not currently being served.

In mental health in LMICs, the competitive landscape is generally sparse — most contexts have too little provision of any kind for “competition” to be a meaningful concern. But as the field develops and more organizations scale digital mental health programs, this will change. Maintaining awareness of what is being built in target contexts, and positioning expansion to be additive rather than duplicative, will become increasingly important.

Conclusion

Country prioritization for digital depression programs is a multi-dimensional analytical exercise that rewards rigor. The combination of depression burden, treatment gap, digital infrastructure, regulatory environment, and operational feasibility creates a complex decision space — but one that can be navigated systematically using available data.

The ten countries identified in the Ambitious Impact analysis represent a strong starting point for organizations working in this space. They are not equally ready for program launch — each has a distinctive profile of opportunities and challenges — and the sequencing decision should be made with as much care as the initial selection.

The ultimate measure of a country prioritization framework is not its analytical elegance but its impact: whether the populations in the countries selected are better served as a result of the decisions made. At $97 per DALY averted, each person reached in a well-chosen, well-executed country expansion represents exceptional value. The framework exists to maximize how many of those people can be reached.

To learn more about Kaya Guides’ expansion strategy and how to support the scaling of WHO Step-by-Step globally, visit besidehealth.org.

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Related reading

• Building the World’s First Nonprofit Around WHO Step-by-Step: Lessons from Kaya Guides’ Launch Year — the operational lessons that inform country sequencing.
• The Lay Counselor Model: Delivering Evidence-Based Mental Health Care at Scale Without Psychiatrists — the delivery model that makes expansion viable.
• The Mental Health Funding Gap Is Wider Than You Think — Here’s What’s Actually Working — the funding landscape context for geographic expansion.
• What 5 Randomized Controlled Trials Tell Us About Guided Digital Self-Help for Depression in LMICs — the evidence base that validates the target contexts.

The mental health funding gap is one of the most discussed problems in global health. It appears in WHO reports, in development finance reviews, in academic papers, and in the speeches of health ministers. Everyone agrees it exists. Far fewer people have a clear picture of what it actually looks like — or what’s being done about it that deserves more support.

This post tries to give an honest accounting: how wide the gap is, why it persists, and what the most promising evidence-backed approaches are for closing it in the places where it matters most.

The Scope of the Problem

Start with the basics. Depression affects more than 300 million people worldwide. Together with anxiety disorders, depression accounts for roughly 13 percent of the global burden of disease — more than HIV/AIDS, more than tuberculosis, comparable to cardiovascular disease in its total contribution to human suffering and lost productivity.

The treatment gap — the proportion of people with a diagnosable mental health condition who receive no treatment — varies dramatically by income level. In high-income countries, the gap is approximately 50 percent. In low- and middle-income countries (LMICs), it is 75 percent or more.

That number — 75 percent — is worth sitting with. In the countries where most of the world’s population lives, three in four people with depression receive no care at all. Not inadequate care. Not care delayed by waiting lists or cost barriers. No care.

The reason is primarily workforce. High-income countries have approximately 67.2 mental health workers per 100,000 people. Low-income countries have 1.1. There simply aren’t enough trained professionals to provide care even if every other barrier — cost, distance, stigma — were removed.

How the Funding Gap Maps onto the Burden

You might expect that the funding directed at mental health would roughly correspond to the burden it represents. It doesn’t.

In 2019 — the most recent year for which comprehensive data is available — less than 2 percent of official development assistance (ODA) for health was directed to mental health. This despite mental health conditions accounting for roughly 13 percent of the global disease burden.

The ratio is roughly 6:1 in terms of underfunding relative to burden. For every dollar that should be going to mental health based on its share of global disease burden, about 16 cents is actually flowing there.

This misallocation has persisted for decades. It reflects a complex combination of historical prioritization (infectious diseases received early institutional investment that created durable funding structures), measurement challenges (mental health burden was historically harder to quantify than, say, malaria mortality), and persistent stigma that affects not just individuals seeking help but also funders evaluating cause areas.

The measurement gap has largely been closed. The methodological tools now exist to measure mental health burden rigorously, to conduct randomized controlled trials of mental health interventions, and to calculate cost-effectiveness ratios comparable to those used for any other health intervention. The evidence exists. The funding has not followed.

What’s Not Working (and Why)

Understanding what hasn’t worked is as important as identifying what has. Several approaches to closing the mental health treatment gap in LMICs have been tried and found wanting.

Specialist training pipelines. Efforts to increase the supply of psychiatrists and clinical psychologists in low-income countries face a fundamental challenge: training takes a decade, the countries most in need have the weakest training infrastructure, and even when professionals are trained, “brain drain” to higher-income settings — where salaries and working conditions are better — means that the investment often doesn’t stay where it was intended. A psychiatrist trained in Nigeria or Bangladesh is in high demand globally and faces strong incentives to practice somewhere other than a rural health center in their home country.

Hospital-based care. The traditional model of mental health care — psychiatric hospitals providing inpatient and outpatient services — is expensive, concentrated in urban centers, and inaccessible to the majority of people in low-income countries who need care. Expanding hospital infrastructure requires capital investment that most low-income governments can’t prioritize relative to infectious disease, maternal mortality, and other acute health needs.

Awareness campaigns. Raising awareness of mental health conditions is valuable, but awareness without available services doesn’t close the treatment gap. If anything, raising awareness of depression without providing accessible treatment creates a demand that existing infrastructure can’t meet — and potentially increases the psychological burden on people who now know they have a condition but can find no way to address it.

What Is Working

The clearest evidence of what works comes from the research on task-shifted, guided self-help programs. The model is straightforward: use trained community members (lay counselors) rather than specialists to provide the human support component of mental health care, and use digital tools to deliver the evidence-based therapeutic content that doesn’t require specialist training to engage with.

WHO Step-by-Step is the most rigorously evaluated program in this category. Developed by the WHO and tested in five randomized controlled trials across Lebanon, China, Pakistan, Egypt, and South Africa — involving more than 2,200 participants — it demonstrates that effective depression treatment can be delivered at scale, by non-specialists, using WhatsApp, at a cost that makes it viable in the lowest-income settings.

The effect size across the five trials is 0.78, placing it in the medium-to-large range. For comparison, in-person therapy with a trained professional has an effect size of approximately 0.99. The difference is not statistically significant — the program produces outcomes comparable to face-to-face therapy at a fraction of the cost.

Critically, the cost-effectiveness ratio — approximately $97 per DALY averted — places Step-by-Step among the most cost-effective health interventions ever evaluated, comparable to malaria bed nets and vitamin A supplementation. Using the WELLBY framework (wellbeing-adjusted life years), the figure is approximately $25 per WELLBY, which is exceptional by any benchmark in global health philanthropy.

The Role of Guided vs. Unguided Programs

One of the most important findings from the research is the difference in outcomes between guided and unguided digital mental health programs.

Unguided programs — apps and digital tools that provide mental health content without any human contact — exist in abundance. Many have been evaluated. Most show modest effects. The average effect size for unguided digital programs is around 0.3, roughly half of what guided programs produce.

The human element makes a decisive difference. It doesn’t need to be a trained therapist. It doesn’t need to be intensive — 15 minutes a week is sufficient. But the presence of a real person who checks in, notices if you’re struggling, and provides encouragement to continue is what converts digital content from something people abandon into something they complete and benefit from.

This finding has important implications for funders evaluating the digital mental health space. Not all apps and programs are equivalent. The evidence strongly supports investing in guided programs — those that combine digital content with lay counselor support — rather than purely self-directed digital tools, regardless of how sophisticated or well-designed the latter may be.

The Kaya Guides Model

Kaya Guides is the nonprofit organization currently scaling WHO Step-by-Step. Incubated by Ambitious Impact (also known as Charity Entrepreneurship), it launched in India in August 2023 and has served approximately 3,600 participants to date.

The operational model is built around the counselor-to-participant ratio that the evidence supports. One counselor, trained and supervised by Kaya, can manage approximately 400 enrolled participants per year. The weekly 15-minute check-in calls are the primary cost driver on the human side of the program — the digital content delivery is low-cost once developed.

At full scale, Kaya projects total program costs of approximately $1.3 million per year. The organization is currently in growth mode — building the systems, partnerships, and organizational capacity needed to expand to new geographies while maintaining program quality and evidence standards.

The ten priority countries identified in Ambitious Impact’s research are Pakistan, China, Nigeria, Bangladesh, Indonesia, Egypt, Brazil, Tajikistan, Ethiopia, and Malaysia. These were selected based on disease burden, digital infrastructure, regulatory environment, and the absence of existing high-quality programs serving the target population.

What Good Funding Looks Like

The mental health funding gap won’t be closed by any single organization or any single intervention. But the evidence clearly identifies where the most cost-effective opportunities lie, and it points to a set of principles that should guide funding decisions in this space.

Fund guided programs, not just digital tools. The evidence for guided self-help is substantially stronger than for unguided apps. Funding should flow to programs that include the human contact component that makes the difference in completion and outcomes.

Prioritize evidence-backed interventions. The strength of the evidence base for WHO Step-by-Step — five RCTs across multiple countries and contexts — is unusual in global mental health. Programs with this level of evidence should receive priority over those with weaker evaluation histories.

Support organizations at the growth stage. Early-stage organizations scaling evidence-backed programs represent high-leverage funding opportunities. The marginal impact of a dollar given now — when it enables geographic expansion and organizational learning — is likely higher than the same dollar given at maturity.

Think in systems. The household spillover research shows that treating one person for depression generates benefits for the people who live with them — estimated at approximately 16 percent of total program impact. Funders who think in terms of systems and spillover effects will find the case for mental health investment even stronger than the headline individual-level numbers suggest.

The Moment for Action

The mental health funding gap has persisted for decades, but the conditions for closing it have never been better. The evidence base is strong. The delivery model is validated. The organizations capable of scaling exist. The cost-effectiveness ratios are competitive with the most celebrated interventions in global health.

What’s needed is for funders — individual philanthropists, foundations, development finance institutions, and institutional global health investors — to recognize that mental health belongs in their portfolios, not as a peripheral consideration but as a core part of the evidence-based global health agenda.

The gap is wide. What’s working is clear. The moment to act is now.

To learn more about Kaya Guides and the work of scaling evidence-based mental health programs in LMICs, visit besidehealth.org.

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Related reading

• $97 Per Year of Healthy Life: Why Digital Mental Health Is One of the Most Cost-Effective Causes You’ve Never Heard Of — the headline cost-effectiveness numbers in detail.
• From 3,600 Participants to Millions: The Investment Case for Scaling Digital Depression Treatment — what scaling looks like and what it costs.
• Guided vs. Unguided: Why Human Support Makes the Difference in Digital Mental Health Programs — why guided programmes outperform apps.
• Support Beside’s work — your donation directly funds programme delivery.

Imagine you’re a 32-year-old woman living outside Lahore. You’ve been feeling flat for months — exhausted, unmotivated, unable to find pleasure in things you used to enjoy. You’re not sleeping well. You snap at your children. You find yourself thinking, more than you’d like to admit, that everyone would be better off without you.

You know something is wrong. But there is no therapist within reasonable distance. No psychiatric clinic you could afford. No employee assistance program, no insurance network, no GP who would know what to say even if you could get an appointment. There is no pathway from where you are to the help you need.

Now imagine the same scenario, but in Surrey. Or Minneapolis. Or Zurich.

The symptoms are identical. The suffering is identical. But the landscape of possibility is utterly different.

This is the reality of depression globally. The condition itself doesn’t care where you live. But the care available to you is determined almost entirely by geography — and that geography produces a gap in treatment access so vast that we have largely stopped thinking of it as a solvable problem.

It is solvable. The evidence now exists to show us how.

The Numbers Behind the Crisis

More than 300 million people worldwide live with depression. It is one of the leading causes of disability globally, contributing more to the global burden of disease than almost any other condition.

The treatment gap — the proportion of people with depression who receive no care — varies dramatically by income level. In high-income countries, it hovers around 50 percent: still far too high, but reflecting at least a functioning infrastructure of care that reaches half of those who need it. In low- and middle-income countries, the gap is 75 percent or more. Three in four people with depression receive nothing.

The reason isn’t primarily cost or political will, though both matter. It’s workforce. High-income countries have an average of 67.2 mental health workers per 100,000 people. Low-income countries have 1.1. That’s not a ratio that can be fixed by training more psychiatrists on a timescale that matters for the hundreds of millions of people suffering now.

Psychiatrists take a decade to train. Even if every low-income country dramatically expanded its medical training capacity today, the pipeline would take a generation to fill. And in the meantime, the 300 million people already living with depression — the woman outside Lahore, the man in rural Nigeria, the teenager in the outskirts of Dhaka — have nowhere to turn.

The Model That Changes the Math

The response to this workforce shortage that has the strongest evidence behind it is not building more psychiatric hospitals. It’s not training more specialists. It’s task-shifting: redesigning the delivery of mental health support so that the parts that don’t require a decade of clinical training can be delivered by people with far less training — and the parts that do require specialist involvement can be reserved for the cases that genuinely need it.

WHO Step-by-Step is built on this logic. The core therapeutic content — five structured modules based on behavioral activation and cognitive techniques — is delivered digitally, via WhatsApp. Participants work through the material themselves, at their own pace. The modules are designed to be accessible to people with limited literacy and no prior exposure to mental health concepts.

The human element is provided by lay counselors: community members who receive focused training in how to support participants through the program. They’re not therapists. They don’t provide clinical assessment or medication management. What they provide is the brief, consistent, human contact that research consistently shows is essential for people to actually complete and benefit from structured self-help programs.

One counselor, working part-time, can support approximately 400 enrolled participants per year. The 15-minute weekly check-in call doesn’t require a clinical degree. It requires the ability to listen, to encourage, to notice if someone seems to be deteriorating and needs referral to more intensive care.

This is not a second-rate solution. Five randomized controlled trials across Lebanon, China, Pakistan, Egypt, and South Africa — involving more than 2,200 participants — show that Step-by-Step produces outcomes comparable to face-to-face therapy. The effect size is 0.78, compared to 0.99 for in-person treatment. That difference is not statistically significant. The program works.

Why Geography Shouldn’t Determine Destiny

The argument for programs like Step-by-Step isn’t just utilitarian — it’s ethical. Depression is not a condition that warrants less treatment effort because it affects people in poor countries. The suffering is equivalent. The disability is equivalent. The impact on families and communities is equivalent.

What is not equivalent is the world’s response.

Global health funding has historically concentrated on infectious diseases — HIV, malaria, tuberculosis — with mental health receiving a fraction of what the burden of disease would justify. In 2019, less than 2 percent of official development assistance for health went to mental health, despite depression and anxiety accounting for a substantial share of global disease burden.

This disparity isn’t irrational from a certain perspective — infectious diseases are highly visible, easily measured, and historically responsive to interventions like vaccines and antibiotics that map neatly onto a “deliver and scale” model. Mental health has seemed harder: harder to measure, harder to deliver, harder to scale.

Digital programs like Step-by-Step challenge that assumption. They can be delivered at scale. They can be measured. They can be adapted to different cultural contexts while maintaining fidelity to the core evidence-based content. And they can be evaluated using the same metrics — DALYs, cost-effectiveness ratios — that global health funders use to prioritize other investments.

The Countries Where This Matters Most

Ambitious Impact, the charity incubator that launched Kaya Guides, has done extensive analysis of where the WHO Step-by-Step model has the greatest potential impact. Their research identified ten priority countries for expansion: Pakistan, China, Nigeria, Bangladesh, Indonesia, Egypt, Brazil, Tajikistan, Ethiopia, and Malaysia.

These countries were selected based on a combination of factors: high burden of depression, limited existing mental health infrastructure, sufficient digital connectivity (particularly WhatsApp penetration) to support app-based delivery, and relative political and regulatory stability that makes program implementation feasible.

Together, these ten countries account for an enormous share of the global depression burden. They also represent, in different ways, the challenge that makes the mental health treatment gap so persistent: large, diverse populations; limited health system capacity; cultural and social factors that affect both help-seeking and treatment acceptability; and insufficient funding from governments and international donors.

Step-by-Step has already been tested in several of these contexts. The RCTs in Lebanon, Egypt, China, and Pakistan demonstrate that the program can be culturally adapted and delivered effectively in very different settings. The challenge now is moving from rigorously evaluated pilots to programs that reach millions.

What Scale Actually Looks Like

Kaya Guides — the nonprofit scaling Step-by-Step — has served approximately 3,600 participants since launching in India in August 2023. That’s a start. But the need is orders of magnitude larger.

Scaling from thousands to millions requires more than just hiring more counselors and sending out more WhatsApp messages. It requires building the organizational infrastructure to recruit, train, supervise, and support large cohorts of lay counselors. It requires technology systems that can manage participant flows, track progress, and flag people who might be deteriorating. It requires partnerships with governments, health systems, and community organizations that can provide referral pathways for people who need more intensive support. And it requires sustained funding.

The good news is that the unit economics are compelling. At full scale, Kaya estimates a total program cost of approximately $1.3 million per year. The cost per DALY averted — the standard metric for comparing cost-effectiveness across health interventions — is approximately $97. For context: the global health community generally considers interventions costing less than $100-200 per DALY averted to be highly cost-effective. Step-by-Step, at scale, clears that bar comfortably.

For donors who care about maximizing the impact of their giving, this is a significant number. It means that each dollar directed to Kaya Guides translates to a measurable, evidence-backed improvement in human wellbeing — at a scale and efficiency that is difficult to match in global health philanthropy.

The Spillover Nobody Talks About

One of the findings from the research that often gets overlooked is the evidence on household spillover effects. Depression doesn’t just affect the person who has it — it affects everyone around them. Partners, children, parents, siblings: all are affected when someone they love is in the grip of depression.

Research on Step-by-Step found that household spillover effects account for approximately 16 percent of the program’s total impact. In other words, when you treat one person for depression, you improve the wellbeing of the people who live with them. This effect isn’t captured in the headline DALY figures, which focus on the individual participant. Accounting for spillover effects makes the program even more cost-effective than the headline numbers suggest.

This matters for how we think about the value of mental health investment. Depression is not a private condition with private consequences. It ripples outward through families and communities. Treating it effectively has public benefits that extend far beyond the individual being treated.

The Moment We’re In

We are living through a moment when the evidence base for scalable, effective, affordable mental health treatment has never been stronger. The trials have been done. The model has been validated. The cost-effectiveness analysis has been completed. The organizations capable of delivering at scale exist and are growing.

What’s missing is not evidence. It’s not innovation. It’s not even, in most cases, political will — though that helps. What’s missing is attention and resources.

The argument that depression care in low- and middle-income countries is too hard, too costly, or too uncertain to fund has been comprehensively rebutted by the evidence. The woman outside Lahore has access to the same WhatsApp that people in London and Los Angeles use every day. The content that can help her is available. The counselor model that makes it work has been developed and tested. The infrastructure to deliver it at scale is being built.

Depression doesn’t care where you live. And with programs like WHO Step-by-Step, the solution no longer has to, either.

To support the work of scaling evidence-based mental health care globally, visit besidehealth.org.

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Related reading

• You Don’t Need a Therapist to Get Better: How a WhatsApp Program Is Treating Depression in the World’s Hardest-to-Reach Places — how the Step-by-Step programme works in practice.
• $97 Per Year of Healthy Life: Why Digital Mental Health Is One of the Most Cost-Effective Causes You’ve Never Heard Of — the cost-effectiveness case for funders.
• The Lay Counselor Model: Delivering Evidence-Based Mental Health Care at Scale Without Psychiatrists — how the task-shifting model solves the workforce problem.
• The evidence behind the Beside programme