Rapid technological developments in artificial intelligence (AI) have resulted in growing public attention to the potential benefits and challenges of these developments as they relate to health care. The Trump administration recently released A National Policy Framework for Artificial Intelligence (“AI Framework”), a set of legislative recommendations that could jump-start congressional activity on the application of AI across a variety of policy areas, not just health care. A core part of the AI Framework emphasizes establishing federal AI policy that preempts many state AI laws to reduce barriers for deploying AI applications. Preemption could nullify state consumer protections governing the use of AI in health coverage, such as prior authorization, and claims review and appeals. This Issue Brief discusses the types of consumer protections for use of AI in prior authorization and claims review, describes the Trump administration’s AI Framework, and highlights areas to watch as Congress considers AI legislation.

The use of AI technology has been embraced by all participants in the claims review cycle: patients, providers, and insurers. The box below describes current uses of AI technology for each party involved in prior authorization and claims review. Prior authorization and claims review are related but distinct steps in the coverage review and reimbursement process (claims review cycle) where AI might be used. Prior authorization is a managed care tool that evaluates whether an item or service is covered by a health plan prior to a patient’s receipt of the care. Claims review is often associated with a determination by an insurer after care is provided about whether and how much to pay for the item or service. Both involve similar decision-making and consumer appeal rights.

The claims review cycle includes health plan decisions made before a patient receives care (prior authorization review), after the care is received (often called retrospective or post-claim review), and while a patient is receiving the care (called concurrent review). Where the medical necessity of a service is involved, the term “utilization review” is often used to describe this process (definitions differ across state and federal requirements).

Connection to Interoperability. Developments in technologies to enhance interoperable systems (electronic data sharing among plans, providers, and patients) may make data more readily available for the application of AI technology in prior authorization and claim decision-making. Federal regulations will soon require some health plans to implement application programming interfaces (APIs) to collect and share data among patients, plans, and providers in an effort to streamline and expedite prior authorization review. While this may be helpful to patients and providers, increased data sharing could also result in data being captured inappropriately and used for purposes that might not be allowed under current interoperability agreements, for example, for commercial sale and/or to train new AI tools.

Risks to consumers include the potential for inaccurate or biased outcomes and privacy breaches. AI systems can help insurers and TPAs triage and make coverage decisions, often without any human involvement in the process. Yet the nature of much of this decision-making requires an individualized, sometimes clinical, review of a patient’s unique circumstances. The use of an AI-based algorithm to aid in these decisions may limit full review of a claim when no human judgment is applied. Many insurers made a voluntary pledge in 2025 to have medical professionals review prior authorization denials that involve clinical issues. Still, the use of AI by an insurer or TPA in claims review, even for purely administrative, nonclinical tasks, might lead to incorrect predictions and decisions if the AI model’s data input is incorrect or missing key information. In the past few years, patients have brought class action lawsuits challenging the use of specific algorithms in claims denials, arguing that their denials were improper due to a failure to perform an individual assessment and a lack of transparency about the algorithms and underlying data used to train the AI tool. These cases are still moving through the courts.

Data used in AI tools, either obtained through a patient’s electronic medical record or uploaded by the patient, could create privacy and security risks that may not be protected under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). HIPAA applies only to health plans, health care providers, and health care clearinghouses, not to the technology companies and other third-party entities that access health information. Patient information obtained through an interoperable electronic health records (EHR) system has been the topic of recent litigation, with an EHR technology company claiming that another company obtained patient data under false pretenses and sold it.

Furthermore, the reliability of an AI tool can be compromised when trained on biased data. For example, one study found that algorithms using health care costs as a proxy for health care needs greatly underestimated the needs of Black patients compared to White patients. Health care costs are often lower for Black patients because they have less access to care, not because they have less clinical need. In this case, treatment decisions based on such algorithms may exacerbate health disparities.

Promoting AI development. While the Trump administration’s AI Framework contains few details and no recommendations specific to health care or insurance claims review, it broadly recommends expanding the use of AI and imposing only limited federal restrictions through existing agency structures and “industry-led standards.” For example, the AI Framework recommends legislation that would prevent the U.S. from “coercing technology providers, including AI providers, to ban, compel or alter content based on partisan or ideological agendas.” It also recommends that Congress authorize resources to make federal datasets accessible to “industry and academia” for training AI systems.

Preempting some state law protections while keeping others. A prominent part of the AI framework is its proposal that Congress develop national standards that preempt “cumbersome” state AI laws. This would create federal legislation that aims to stop or prevent these state laws from being implemented. The Administration suggests that these state laws result in a patchwork of different requirements that could restrict U.S. competitiveness. The AI framework also says that states should not be allowed to penalize AI developers for a third party’s “unlawful conduct” involving their models.

At the same time, the Administration recommends that any legislation “respect the principles of federalism” and not preempt traditional state policy power that allows states to enforce general state laws against AI developers and users, including laws to “protect children, prevent fraud, and protect consumers.”

This framework is consistent with earlier Trump administration actions, including a December 2025 Executive Order restricting state AI regulation and establishing a Department of Justice litigation task force to challenge state AI laws that conflict with federal policy. A July 2025 AI Action Plan (stemming from another Executive Order) included a recommendation that federal agencies not allow AI-related federal funding to states with “burdensome AI regulations.” The AI Action Plan was released shortly after congressional Republicans’ unsuccessful attempt to include a 10-year ban on state regulation of AI in the 2025 budget reconciliation law.

Significantly changing the previous administration’s policies. The Trump administration’s actions mark a significant shift in priorities and approach to AI policy from those of the Biden administration, which sought to establish federal safeguards for the use of AI in health care. The Trump administration rescinded a Biden-era Executive Order that set out an agenda for the development and use of AI “to protect American consumers from fraud, discrimination, and threats to privacy” and “promote safe and responsible” use in health care.

Federal Regulation and Oversight of AI

Few federal standards apply specifically to the use of AI in the prior authorization and claims review process, but all coverage decision-making for both public and private coverage includes general standards intended to ensure reviews are fair, substantive, and timely. These standards are fragmented across federal agencies with separate oversight responsibilities for different health coverage markets.

For private employer-sponsored plans, the federal government, through the U.S. Department of Labor (DOL), oversees claims and appeals process requirements in the Employee Retirement Income Security Act (ERISA). ERISA generally exempts self-insured plans established by private employers from most state insurance laws, including claims review protections, and would likely preempt state AI laws that relate to the claims review process. Most workers with employer-sponsored insurance are in a self-funded plan, meaning that many consumers are not guaranteed state protections related to the use of AI in claims review, where they exist.

These ERISA claims and appeals rules were the basis for reforms applied across all private health coverage in the Affordable Care Act. These reforms established a federal floor of protections for the internal claims and appeals process for those with Marketplace and off-Marketplace private insurance and added an option for all consumers with private coverage to appeal denied claims through an “external review” by an entity independent of the plan.

ERISA requires all employer plan sponsors to ensure the “full and fair” review of all health claims. What “full and fair” means in the context of the use of AI tools in the claims process is yet to be interpreted through guidance or updated regulation. ERISA also contains “fiduciary” rules requiring employers and other fiduciaries to act in the best interest of plan enrollees and monitor vendors’ activities. While these standards might provide some protection to employees related to an employer plan’s use of AI, in practice, fiduciary standards have rarely been applied to employer health plans, and to date, enrollees have not been successful in advancing litigation to challenge employers for breaching their fiduciary duties related to the health plans they sponsor.

Still, one recent DOL case against a large TPA alleged a fiduciary violation and a failure to follow ERISA claims rules when the TPA automatically denied claims in bulk without making an individual medical necessity evaluation for each under the terms of the plan. While these allegations did not necessarily involve AI, the TPA allegedly used an automated process without human review to issue denials. This case was settled with the establishment of a fund to compensate enrollees for improperly denied claims.

Federal guidance specific to AI use in prior authorization and claims review in Medicare and Medicaid has been limited. Both programs have their own claims and appeal consumer protections under federal requirements (and some state standards also apply to Medicaid).

Medicare. 2023 Medicare Advantage regulations and additional 2024 guidance clarify that Medicare Advantage organizations cannot make medical necessity decisions using an algorithm or software that does not consider individual circumstances. Denials based on medical necessity must be reviewed by a health care professional. Regulations proposed in 2024 that addressed bias and discrimination in the use of AI by Medicare Advantage plans were not finalized by the Trump administration. Additionally, the federal government is testing the use of AI to make certain prior authorization decisions for specific services in traditional Medicare through its Wasteful and Inappropriate Services Reduction (WISeR) Model, contracting with AI technology companies to administer this pilot program in six states.

Medicaid. Current Medicaid regulations do not directly address the use of automation in prior authorization. Medicaid managed care regulations require that any managed care organization (MCO) decision to deny services be made by “an individual” with appropriate expertise, but do not explicitly address AI use. Through state managed care contracts (which are reviewed and approved by CMS), states can set requirements for plan performance and reporting, such as requiring plans to disclose the use of AI in prior authorization processes. The Medicaid and CHIP Payment and Access Commission (MACPAC) has recently issued draft recommendations on the use of automation in Medicaid prior authorization.

State AI Consumer Protections in Prior Authorization and Claims Review

In recent years, some states have advanced laws and regulations aimed at protecting consumers from possible harm stemming from algorithmic decision-making systems, such as privacy breaches, inaccuracies, and bias. AI-related legislation continues to be debated in almost every state legislature, with some efforts garnering bipartisan support. Some states have issued regulations and other guidance under existing laws instead of or in addition to new state laws.

State laws specify new and existing AI consumer protections. Some state laws contain wide-ranging protections meant to cut across different sectors of the economy and apply to a broad range of entities, such as developers and those who deploy or use the technology for business purposes. Other state laws are specific to industry sectors (e.g., health care), topics (e.g., employment, civil rights, education), or uses, such as utilization review in health insurance.

Broad state laws include those that prohibit unfair or deceptive acts and practices. All 50 states have broad consumer protection laws that prohibit unfair or deceptive acts or practices. These laws are enforced by state attorneys general, and sometimes also allow a consumer to sue directly for a violation of the law (a “private right of action”) instead of relying on the state alone to enforce it. Colorado and Utah are examples of states that have amended their consumer protection laws to provide for general AI consumer protections.

Depending on the specific state law, these broader consumer protection laws might be used to address consumer harm resulting from the use of AI in prior authorization and claims review. Additionally, a growing number of states have updated longstanding state health insurance standards for managed care related to utilization review to clarify how these rules apply to AI (Figure 1). Almost all of the laws are focused on the decision-making process of utilization review, sometimes defined under state rules as individualized decisions about whether a given service is medically necessary based on the patient’s individual clinical circumstances. These laws do not necessarily include administrative claim review decisions that do not involve a medical necessity determination, such as whether a claim is for care that is excluded under the plan.

Each state law related to the use of AI in prior authorization and/or claim review has its own unique requirements, but major themes include:

• Human review of claim denials required. Some state laws include a provision that only a licensed health care provider may issue adverse determinations (a denial) and that AI cannot be used as the sole decisionmaker. For example, Illinois law requires that only a “clinical peer” make an adverse determination based on medical necessity and does not allow the sole use of an “algorithmic automated process” to make these decisions.
• AI tools must take individual clinical circumstances into account. A couple of these states require that any AI tool used for utilization review bases its determination on an enrollee’s unique clinical history. Alabama, for instance, mandates that insurers who use artificial intelligence to make prior authorization determinations ensure that they base these decisions on an enrollee’s clinical history and clinical circumstances.
• Disclosure of AI use. A few of these states, such as Utah for example, require entities that use AI to conduct utilization review to disclose its use to the public, the state department of insurance, health care providers in their network, and each enrollee.
• Review of AI tool outcomes. Some state laws also require entities that perform utilization review to periodically review performance and outcomes of AI tools they use in order to check accuracy and reliability. California law requires that an AI tool be periodically assessed and revised to ensure maximum accuracy and reliability.
• Limits on the use of patient data to protect privacy. Several of these state laws include language that prohibits those conducting utilization review from using patient data beyond its intended purpose and contrary to HIPAA or state law confidentiality protections. Maryland law is one example.
• AI tools must be open to inspection, including the underlying algorithms. Some of these laws mandate that AI tools for utilization review be open to audit by regulators. In Texas, the commissioner is allowed to audit and inspect a utilization review agent’s use of an automated decision system for utilization review at any time.
• AI protections against bias and discrimination. A few state laws, such as Washington's, require that AI tools be applied “fairly and equitably” and cannot result in discrimination, either directly or indirectly, against an enrollee.

New state guidance aims to exercise state authority to regulate AI use. Some states have issued guidance to make clear how existing state legal protections apply to AI. For example, in 2024, the Massachusetts Attorney General released a public Advisory explaining how the state’s existing consumer protection, civil rights, and data privacy laws apply to developers, suppliers, and users of AI, and how they could impact consumers in Massachusetts.

Insurance regulators in some other states have taken a similar approach, issuing new guidance to clarify how existing state law applies to AI and provide more specific information to insurers about their obligations concerning the use of AI. As of early April 2026, at least 25 states have issued guidance based on a model bulletin adopted in 2023 by the National Association of Insurance Commissioners (NAIC). The model bulletin applies to all types of state-regulated insurance (not just health insurance) and addresses the use of AI across all aspects of the insurance life cycle, including claims administration and payment, fraud detection, product development, and rating and pricing. It establishes the expectation that consumer-facing decisions made or supported by AI systems comply with existing insurance laws and regulations, including protections against unfair trade practices and illegal discrimination. It also instructs insurers to adopt policies and procedures with specifics about how AI is used and to implement controls to mitigate the risk of adverse outcomes. It specifies that insurance oversight includes the ability of regulators to inquire about the development, deployment, use, and outcomes of any AI system or predictive model used by insurers or their third-party vendors, as well as request information about system validation, testing, and ongoing audits of AI systems.

Striking a balance between the advancement of technological innovation that might save time and money and preventing harm to consumers is not a new challenge. It has been at the heart of consumer protection law for decades. AI presents just the latest policy challenge that policymakers, regardless of party affiliation, are faced with. For health insurance claims review specifically, calls for additional transparency and oversight of the process are longstanding and predate the use of AI. Future congressional action on AI will likely be shaped by the following issues:

The role of state-level consumer protections. Whether the federal government can preempt the application of state consumer protection laws in this area is an open question. The Trump administration’s AI framework appears to acknowledge that certain state protections should continue to apply. A key issue in the development of any federal legislation will be deciding what state actions are consistent with states’ traditional role in overseeing health care and insurance and should be preserved, and which ones are best placed at the federal level for uniformity and consistency. Setting a clear framework for when state and federal protections can and cannot coexist will likely be part of the policy debate.

Some federal preemption provisions can create uncertainty and confusion for consumers. Ongoing legal battles, for example, about whether state pharmacy benefit laws apply to self-insured employer plans under ERISA preemption, are in the process of being clarified through court decisions. This leaves consumers in limbo about what protections they have. Given the rapid changes and risks associated with AI technologies, whether federal preemption is a workable approach for state AI laws is another open question.

Benefits and limitations of a national framework. A single federal standard that preempts most state protections could be easier to build consensus around and simpler for the public to understand, but the current deregulatory agenda for the federal government could mean lax oversight of fast-developing technology. A recent proposed interoperability regulation, for instance, would eliminate some federal certification standards for health IT developers, including those related to transparency of AI data sources and audit reporting.

On the other hand, federal agencies that have not played a role in AI and claims review in the past could increase oversight activities. For example, the Federal Trade Commission has some responsibilities for enforcing unfair and deceptive trade practices standards. Also, some have suggested that the Food and Drug Administration (FDA) should regulate the algorithms that health plans use to determine coverage in the same way the agency oversees AI used in medical devices through a premarket review and evaluation of these tools.

Evaluation of the impact of AI tools in prior authorization and claims review. Providers may use AI to enhance their billing and collection capabilities, and plans work in the opposite direction by using AI in claims review and audit to rein in spending, raising the question of how these tools impact costs to the health system overall. The challenge is to evaluate these tools in real time to determine whether the benefits of AI use in this area (and efforts to encourage its development under federal legislation) outweigh the risks. Access to information about the precise mechanisms of these tools is limited, and efforts to obtain information, for instance, about the AI tools involved in the CMS WISeR model, have resulted in litigation.

Assessment of risks to patients. The enthusiasm about AI technology that might assist consumers in navigating the complexity of insurance bills, claims, and appeals is sometimes tempered by concerns about the risks of incorrect information and claim denials, bias, and privacy and security. Privacy is a particular concern, given the limits of the federal HIPAA standards in reaching the technology companies involved in developing or implementing AI solutions. A KFF poll found that 77% of the public is concerned about the privacy of personal health information provided to AI tools.

In addition to the risk involved when a consumer enters their health information into an AI tool, improper access to this information to test or train AI is also a risk. The Trump administration’s AI framework urges Congress to provide resources to make “federal datasets” available to industry and academia. Concerns about the federal government accessing individually identifiable data from federal agencies to train AI models or for other purposes are growing, raising questions about what additional safeguards might be important in protecting consumers.

Key Takeaways

• About four in ten (41%) U.S. adults say they support the Make America Healthy Again (MAHA) movement – a group largely made up of Republicans and supporters of the Make America Great Again (MAGA) movement. Yet, many of the concerns elevated by the MAHA movement about food safety and corporate influence resonate with a larger share of the public beyond those who identify as supporters. Majorities of the public say there is not enough regulation of chemical additives in food (75%) or of pesticides used in agriculture (64%) in the U.S., and most adults express distrust in agricultural, food, and pharmaceutical companies to act in the public’s best interest. At the same time, confidence in the government agencies that are tasked with regulating these industries is low across partisans; about a third of the public express confidence in the FDA (36%) and the EPA (36%) to act independently without outside interference.
• Even as MAHA issues resonate, the cost of health care is a more prominent focus for voters than issues like food and vaccine policy. Most voters say health costs will have a “major impact” on their decision to vote (55%) and who they vote for (61%) in November, compared to about four in ten who say the same of vaccine or food policy. Even among voters who support the MAHA movement, health care costs are the dominant priority by a wide margin when compared with other areas of health. When asked to select the most important health priority for the federal government, four in ten MAHA voters (42%) choose lowering health costs, twice the share who choose restricting chemical additives in the food supply (21%) and far outranking other MAHA priorities like reevaluating vaccine safety (10%), limiting corporate influence in U.S. food policy (8%), or restricting pesticide use in agriculture (8%).
• Voters overall give the Trump administration low approval ratings on two key health areas elevated by the MAHA movement; about four in ten approve of the administration’s handling of vaccine policy (38%), and fewer than half approve of the administration’s handling of food policy (46%). The Democratic Party holds the advantage over the Republican Party in who voters trust to handle vaccine policy (41% vs. 25%) and to ensure federal health agencies act independently without corporate influence (33% vs. 24%). Voters are more evenly divided on whether they trust Democrats (31%) or Republicans (27%) to handle the safety of food additives and pesticides, or neither party (31%).

Who Are MAHA Supporters?

Make America Healthy Again (MAHA) is the political and public health movement promoted by the Trump administration and led by Health and Human Services (HHS) Secretary Robert F. Kennedy Jr. The movement has elevated issues such as vaccine safety, the role of corporate interests in federal health agencies, and the presence of chemical additives and pesticides in the food supply. KFF’s latest Health Tracking Poll shows about four in ten adults say they are supporters of the MAHA movement, but some of the concerns elevated by the MAHA movement resonate well beyond its core supporters.

Overall, about four in ten (41%) adults – and a similar share of voters (43%) – say they are supporters of the MAHA movement, with support closely tied to partisanship and support of the Make America Great Again (MAGA) movement. Two-thirds of MAHA supporters identify as Republican or Republican-leaning independents, including about half (52%) who are supporters of the MAGA movement. Far fewer MAHA supporters are Democrats or Democratic-leaning independents (21%) or independents who do not lean toward either political party (10%). Among registered voters who support MAHA, the partisan composition is similar.

Among MAHA-supporting voters, just over half say they “strongly” support the movement (55%) and 45% say they “somewhat” support it, translating to about one in four voters overall as strong MAHA supporters (24%) and one in five who “somewhat” support it (19%).

When asked specifically why they support the MAHA movement, supporters give a range of answers, with the two most common relating to generally wanting people to be healthier (19%) and removing or regulating harmful substances in food (15%). Some MAHA supporters mention improving nutritional habits for Americans (7%) or lowering obesity rates (7%). Five percent of MAHA supporters cite health care access and affordability as their reasons for supporting the movement, despite the MAHA movement’s lack of focus on these issues. Just 4% of MAHA supporters cite vaccines and medical choice as their reason for supporting the movement. Few MAHA supporters specifically express support for President Trump or HHS Secretary Robert F. Kennedy Jr. (2%) as their reasoning for supporting the movement.

Where MAHA Concerns Resonate With the Public: Food Safety, Pesticides, and Industry Influence

Among the public, there is broad, bipartisan agreement that there is not enough government regulation of chemical additives in food and pesticides in agriculture in the U.S. Three-quarters of adults say there is not enough government regulation of chemical food additives, and about two-thirds (64%) say the same about pesticides used in agriculture. Majorities across partisan lines and among both MAHA supporters and those who do not support the movement agree, suggesting this is an area where MAHA’s concerns align with broader public sentiment.

Some food industry groups and public health experts have argued that restrictions on approved food ingredients could limit access to affordable groceries for families in the U.S. When those who originally said there is “not enough regulation” of chemical additives in food or pesticides used in agriculture are presented with the caveat that increased regulation could lead to higher food prices for consumers, most still support increased regulation. But the possibility of increased costs does move some people. The share saying there is not enough regulation of food additives drops by 13 percentage points after hearing that increased regulation could increase costs (from 75% to 62%), with a similar drop in the share who maintain that there is not enough regulation of pesticides (from 64% to 52%).

The public perception that there is not enough regulation may be rooted in broader skepticism toward the industries themselves. Most U.S. adults do not trust pharmaceutical companies, food and beverage companies, or agricultural companies to act in the public’s best interest. One in four or fewer adults say they trust food and beverage companies (25%) or pharmaceutical companies (21%) “a great deal” or “a fair amount” to act in the public's best interest, while a somewhat larger share (40%) trust agricultural companies on this measure. Very small shares – fewer than 5% – trust each of these groups “a great deal” to act in the public’s best interest.

By contrast, seven in ten adults say they trust doctors and health care providers at least “a fair amount” to act in the public’s best interest.

Across partisanship, and among those who do and do not support the MAHA movement, fewer than half trust agricultural companies, food and beverage companies, or pharmaceutical companies to act in the public’s best interest. However, most Democrats (80%), independents (69%), and Republicans (67%) have a great deal or a fair amount of trust in doctors and health care providers to act in the public’s best interest.

Confidence in the government agencies with major responsibilities for food safety and public health is low across partisans. Four in ten or fewer adults say they have “a lot” or “some” confidence in the U.S. Centers for Disease Control and Prevention (CDC) (40%), U.S. Food and Drug Administration (FDA) (36%), or the U.S. Environmental Protection Agency (EPA) (36%) to act independently without interference from outside interests. Democrats are slightly more likely than Republicans or independents to express confidence in the CDC (47% vs. 37% and 38%, respectively), but partisan differences largely disappear when it comes to confidence in the FDA and EPA.

U.S. adults who support the MAHA movement and those who do not are similarly skeptical. Four in ten MAHA supporters say they are confident in each of these agencies to act independently, leaving six in ten MAHA supporters who have “a little” or “no confidence at all.”

MAHA and Other Health Care Issues in the Election

Despite the resonance of these issues elevated by the MAHA movement, health care costs overshadow these concerns for voters heading into the 2026 midterm elections. Previously released findings from the April 2026 KFF Health Tracking Poll show health care costs remain a primary economic concern for the public. Reflecting that, costs are voters’ top health concern heading into the 2026 midterm elections, outweighing policy areas elevated by the MAHA movement, such as vaccines or food safety.

More than half of voters say health care costs will have a “major impact” on their decision to vote (55%) or which party’s candidate they will support (61%). When it comes to vaccine policy and food policy, about four in ten voters say these issues will have a “major impact” on their decision to vote or which party’s candidate they will support, at least 15 percentage points lower than the share who say the same about health care costs.

While the issue of health costs is more salient for Democratic voters than for Republicans, larger shares across partisans say health costs will have a major impact on their voting decisions than say the same about vaccine policy or food safety. For example, about half of independent voters (52%) say health care costs will have a major impact on their decision to turn out in November, compared to about four in ten who say the same about vaccine policy (39%) and food safety (38%). Patterns are similar for Republican voters (48%, 30%, and 34%, respectively) and Democratic voters (64%, 52%, and 40%, respectively).

Among voters who say they support the MAHA movement – a majority (56%) of whom identify as MAGA Republicans – at least half say the cost of health care will have a major impact on their decision to vote (51%) or which party’s candidate they support (56%). Despite the MAHA movement elevating issues such as vaccine and food safety, fewer MAHA voters – about four in ten – say vaccine policy or issues of food safety will majorly impact their voting decisions.

MAHA-supporting voters express broad enthusiasm for federal action across the movement’s core agenda, but once again, health care costs remain the dominant priority. Nearly three-quarters of MAHA voters (73%) say lowering the cost of health care, including prescription drugs, should be a top priority for the federal government. This is followed by restricting the use of certain chemical additives in the food supply (68%) and limiting corporate influence on U.S. food policy (56%). Half of MAHA voters say reevaluating the safety of vaccines currently approved for use or restricting the use of pesticides in agriculture should be top priorities. Across all five items, one in ten or fewer MAHA voters say any of these efforts are “not too important” or “should not be done.”

When asked to choose the single most important health priority to them, about four in ten MAHA-supporting voters (42%) choose lowering the cost of health care, including prescription drugs—twice the share who say the same of restricting chemical additives in the food supply (21%). Fewer cite reevaluating vaccine safety (10%), limiting corporate influence in U.S. food policy (8%), or restricting pesticide use in agriculture (8%) as their single top priority.

The cost of health care tops the list of health care priorities for MAHA voters regardless of partisanship. Among voters who support the MAHA movement, six in ten Democrats (57%) and four in ten independents (43%) and Republicans (40%) say lowering the cost of health care is the most important priority. For each of these groups, health care costs rank at least 14 percentage points ahead of restricting the use of chemical additives in food, and even further ahead of issues like reevaluating vaccine safety and restricting pesticide use.

Trump Administration Approval and Party Preference on MAHA Health Issues

Voters give the Trump administration low approval ratings on two key policy areas elevated by the MAHA movement. Just under half (46%) of voters approve of the administration’s handling of food policy, and a larger share (54%) disapprove. Just a few months after the changes made to the childhood vaccine schedule by HHS, about four in ten voters approve of the administration’s handling of U.S. vaccine policy (38%) and six in ten (61%) disapprove, including about half (47%) who “strongly disapprove.”

As the head of the MAHA Commission and Secretary of Health and Human Services, Robert F. Kennedy Jr. is the spokesperson for many of the administration’s federal health policies. About four in ten voters say they approve of the way Secretary Kennedy is handling his job (39%) and six in ten disapprove, including nearly half (46%) who “strongly disapprove.”

Unsurprisingly, voters are split along partisan lines, with the Trump administration receiving high approval ratings from Republicans on food and vaccine policy as well as Secretary Kennedy’s handling of his job at HHS, and most Democrats disapproving.

Despite Secretary Kennedy’s leadership at HHS and recent changes focused on MAHA priorities, approval of the administration’s handling of issues like vaccine policy is far from unanimous among the movement’s supporters. About seven in ten MAHA voters approve of the administration’s handling of food policy (72%) and vaccine policy (67%), and Secretary Kennedy’s handling of his job as Health Secretary (69%). On each of these areas, just a third “strongly” approve of the administration and a similar share disapprove: tepid ratings for a group that aligns with Kennedy’s signature movement.

With about six months until the 2026 midterm elections, the Democratic Party has a strong edge over the Republican Party when it comes to who voters trust to address vaccine policy, and a narrower edge on ensuring federal agencies act independently. Voters are split over who they trust to do a better job ensuring food additives are safe. Democrats have a double-digit advantage over Republicans when it comes to who voters trust to handle vaccine policy (41% vs. 25%). While the Democratic Party has a smaller advantage among voters on which party they trust to ensure that federal health agencies act independently without corporate influence (33% vs. 24%), nearly four in ten (37%) say they trust “neither party.”

Similar shares of voters say they trust the Democratic Party (31%), the Republican Party (27%), or “neither party” (31%) more when it comes to doing a better job ensuring food additives and pesticides in the U.S. are safe.

This KFF Health Tracking Poll was designed and analyzed by public opinion researchers at KFF. The survey was conducted April 14 – April 19, 2026, online and by telephone among a nationally representative sample of 1,343 U.S. adults in English (n=1,251) and in Spanish (n=92). The sample includes 1,023 adults (n=81 in Spanish) reached through the SSRS Opinion Panel either online (n=999) or over the phone (n=24). The SSRS Opinion Panel is a nationally representative probability-based panel where panel members are recruited randomly in one of two ways: (a) Through invitations mailed to respondents randomly sampled from an Address-Based Sample (ABS) provided by Marketing Systems Groups (MSG) through the U.S. Postal Service’s Computerized Delivery Sequence (CDS); (b) from a dual-frame random digit dial (RDD) sample provided by MSG. For the online panel component, invitations were sent to panel members by email followed by up to three reminder emails.

Another 320 (n=11 in Spanish) adults were reached through random digit dial telephone sample of prepaid cell phone numbers obtained through MSG. Phone numbers used for the prepaid cell phone component were randomly generated from a cell phone sampling frame with disproportionate stratification aimed at reaching Hispanic and non-Hispanic Black respondents. Stratification was based on incidence of the race/ethnicity groups within each frame. Among this prepaid cell phone component, 140 were interviewed by phone and 180 were invited to the web survey via short message service (SMS).

Respondents in the prepaid cell phone sample who were interviewed by phone received a $15 incentive via a check received by mail or an electronic gift card incentive. Respondents in the prepaid cell phone sample reached via SMS received a $10 electronic gift card incentive. SSRS Opinion Panel respondents received a $5 electronic gift card incentive (some harder-to-reach groups received a $10 electronic gift card). In order to ensure data quality, cases were removed if they failed two or more quality checks: (1) attention check questions in the online version of the questionnaire, (2) had over 30% item non-response, or (3) had a length less than one quarter of the mean length by mode. Based on this criterion, no cases were removed.

The combined cell phone and panel samples were weighted to match the sample’s demographics to the national U.S. adult population using data from the Census Bureau’s 2024 Current Population Survey (CPS), September 2023 Volunteering and Civic Life Supplement data from the CPS, and the 2025 KFF Benchmarking Survey with ABS and prepaid cell phone samples. The demographic variables included in weighting for the general population sample are gender, age, education, race/ethnicity, region, civic engagement, frequency of internet use and political party identification. The weights account for differences in the probability of selection for each sample type (prepaid cell phone and panel). This includes adjustment for the sample design and geographic stratification of the cell phone sample, within household probability of selection, and the design of the panel-recruitment procedure. Initial coding for open-ended questions was done using BT Insights AI Platform and then reviewed, edited, and finalized by KFF researchers.

The margin of sampling error including the design effect for the full sample is plus or minus 3 percentage points. Numbers of respondents and margins of sampling error for key subgroups are shown in the table below. For results based on other subgroups, the margin of sampling error may be higher. Sample sizes and margins of sampling error for other subgroups are available on request. Sampling error is only one of many potential sources of error and there may be other unmeasured error in this or any other public opinion poll. KFF public opinion and survey research is a charter member of the Transparency Initiative of the American Association for Public Opinion Research.

Health coverage plays a major role in enabling people to access health care and protecting families from high medical costs. There have been longstanding racial and ethnic disparities in health coverage that contribute to disparities in health. Due to Medicaid and Affordable Care Act (ACA) cuts in the 2025 reconciliation law and the expiration of the ACA’s enhanced premium tax credits, the number of uninsured is expected to increase by more than 14 million by 2034, potentially exacerbating racial disparities in coverage. This brief examines trends in health coverage by race and ethnicity from 2010 through 2024 and discusses the implications for health disparities. It is based on KFF analysis of American Community Survey (ACS) data for people under age 65. All noted differences between groups and years described in the text are statistically significant at the p<0.05 level. Key takeaways include:

Since 2010, there have been large gains in health coverage across racial and ethnic groups but racial and ethnic disparities in coverage persisted. The largest gains occurred after implementation of the ACA coverage expansions in 2014, with increases continuing until 2016. Hispanic people under age 65 had the largest percentage point increase in coverage, with their uninsured rate falling from 32.6% in 2014 to 19.1% as of 2016. Black, Asian, and American Indian or Alaska Native (AIAN) people also had larger percentage point increases in coverage compared to White people over that period. Despite these larger gains, Hispanic, Black, AIAN, and Native Hawaiian or Pacific Islander (NHPI) people under age 65 remained more likely than their White counterparts to be uninsured as of 2016. Beginning in 2017, coverage gains began reversing, and the overall number of uninsured increased for three consecutive years, coinciding with the first Trump administration. Pandemic-era policies drove broad coverage gains and reduced uninsured rates across most racial and ethnic groups between 2019 and 2023.

In 2024, the overall uninsured rate increased for the first time since 2019 as pandemic-era continuous enrollment in Medicaid came to an end, with significant increases among Hispanic, Black, and White people under age 65. Asian, AIAN and NHPI people did not have statistically significant changes in coverage over this period. As of 2024,AIAN and Hispanic people under age 65 had the highest uninsured rates at 18.9% and 18.4%, respectively. Uninsured rates for NHPI (12.3%) and Black people (10.1%) under age 65 also were higher than the rate for their White counterparts (6.8%). Asian people had the lowest uninsured rate at 5.7%.

Coverage disparities have persisted over time and, in some cases, widened despite earlier gains under the ACA. For example, between 2010 and 2024, the uninsured rate for AIAN people grew from 2.4 to 2.8 times higher than the uninsured rate for White people, the Hispanic uninsured rate grew from 2.5 to 2.7 times higher than the rate for White people, and Black people remained 1.5 times more likely to be uninsured than White people.

Recent policy changes are projected to lead to increased coverage losses in coming years, which will likely widen racial and ethnic coverage disparities. The 2025 reconciliation law makes significant changes to Medicaid and the ACA Marketplaces, which are projected to lead to large coverage losses. It also further restricts access to health coverage for lawfully present immigrants across public health insurance programs. Additionally, the expiration of enhanced premium tax credits for ACA Marketplace enrollees has led to substantial out-of-pocket premium increases and further growth in the uninsured population. The Congressional Budget Office estimates that the combined impact of the reconciliation law with the expiration of the ACA’s enhanced premium tax credits will increase the number of uninsured by more than 14 million in 2034. Medicaid and ACA Marketplace coverage losses will likely widen racial disparities in coverage given that disproportionately large shares of Hispanic, Black, AIAN, and NHPI people are covered through these sources. Coverage losses, in turn, would likely contribute to widening disparities in health.

Prior to the enactment of the ACA in 2010, Hispanic, Black, Asian, AIAN, and NHPI people under age 65 were more likely to be uninsured compared to their White counterparts, with Hispanic and AIAN people at the highest risk of lacking coverage (Figure 1). Their higher uninsured rates reflected more limited access to affordable health coverage options. Although the majority of individuals have at least one full-time worker in the family across racial and ethnic groups, there are ongoing racial disparities in employment and income that result in some groups having more limited access to coverage offered by an employer or having greater difficulty affording private coverage when it is available. While Medicaid helps fill some of these gaps in private coverage, prior to the ACA, Medicaid eligibility for parents in most states was limited to those with very low incomes (often below 50% of the poverty level), and adults without dependent children—regardless of how poor—were ineligible under federal rules.

Between 2010 and 2016, there were large gains in coverage across racial and ethnic groups under the ACA, but racial and ethnic disparities in coverage persisted. The ACA created new coverage options for low- and moderate-income individuals. These included provisions to extend dependent coverage in the private market up to age 26 and prevent insurers from denying people coverage or charging them more due to health status. Further, beginning in 2014, the ACA expanded Medicaid coverage to nearly all adults with incomes at or below 138% of poverty in states that adopted the expansion and made tax credits available to people with incomes up to 400% of poverty to purchase coverage through a health insurance Marketplace. Following the ACA’s enactment in 2010 through 2016, coverage increased across all racial and ethnic groups, with the largest increases occurring after implementation of the Medicaid and Marketplace coverage expansions in 2014. Hispanic people under age 65 had the largest percentage point increase in coverage, with their uninsured rate falling from 24.8% to 19.1% between 2014 and 2016. Black, Asian, and AIAN people also had larger percentage point increases in coverage compared to White people over that period. Despite these larger gains, Hispanic, Black, AIAN, and NHPI people under age 65 remained more likely than their White counterparts to be uninsured as of 2016.

Beginning in 2017, coverage gains began reversing, and the number of uninsured increased for three consecutive years. The uninsured rate for the total population under age 65 increased from 10.0% in 2016 to 10.9% in 2019. Hispanic people had the largest statistically significant increase in their uninsured rate over this period (from 19.1% to 20.0%) although the absolute change was small. There were also small but statistically significant increases in the uninsured rates among White and Black people under age 65, which rose from 7.1% to 7.8% and 10.7% to 11.4%, respectively, between 2016 and 2019. Rates for AIAN, NHPI, and Asian people under age 65 did not have a significant change. These coverage losses likely reflected policy changes made by the first Trump administration after taking office in 2017. These changes included decreased funds for outreach and enrollment assistance, guidance encouraging states to seek waivers to add new eligibility requirements for Medicaid coverage as well as to increase the frequency of eligibility verifications, and changes to public charge immigration policy that made some immigrant families more reluctant to participate in Medicaid and the Children’s Health Insurance Program (CHIP) (which were later reversed by the Biden administration).

Pandemic-era policies drove broad coverage gains and reduced uninsured rates across most racial and ethnic groups between 2019 and 2023. After rising in the years before the pandemic, uninsured rates declined between 2019 and 2023, with 3.6 million more people under age 65 gaining coverage as the uninsured rate fell from 10.9% to 9.5%. Declines occurred across most racial and ethnic groups, with the largest drop among AIAN people (21.7% to 18.7%), alongside smaller but significant declines among Hispanic (20.0% to 17.9%), Black (11.4% to 9.7%), Asian (7.2% to 5.8%), and White people (7.8% to 6.5%), while changes for NHPI people were not statistically significant. These gains were driven largely by increased Medicaid coverage, which offset declines in employer-sponsored insurance, and reflected pandemic-era policies that stabilized and expanded coverage. These policies included the Families First Coronavirus Response Act’s continuous enrollment provision for Medicaid, which required states to pause disenrollments from Medicaid during the COVID pandemic in exchange for increased federal funding to states, enhanced ACA Marketplace subsidies under the American Rescue Plan Act and Inflation Reduction Act, increased outreach and enrollment efforts, and low Marketplace attrition.

After years of decline, the overall uninsured rate among people under age 65 increased in 2024, with significant increases among Hispanic, Black, and White people. The total number of people under age 65 without health coverage increased by more than 1.3 million to 26.7 million in 2024, and the uninsured rate for the population under age 65 increased from 9.5% to 9.8%.Hispanic people experienced the largest increase in uninsured rates between 2023 and 2024 (17.9% to 18.4%), followed by Black (9.7% to 10.1%) and White people (6.5% to 6.8%).Asian, AIAN andNHPI people did not have statistically significant changes in coverage over this period.

Coverage disparities have persisted, and in some cases widened, over time even with recent gains and the large earlier gains in coverage under the ACA. For example, in 2010, the uninsured rate for AIAN people was 2.4 times higher than the uninsured rate for White people; however, in 2024, the gap had increased to 2.9 times higher than the rate for White people. Similarly, the Hispanic uninsured rate grew from 2.5 to 2.8 times higher than the rate for White people from 2010 to 2024, while Black people remained 1.5 times more likely to be uninsured than White people.

Hispanic, Black, AIAN, and NHPI people under age 65 were more likely than their White counterparts to be uninsured as of 2024(Figure 2). AIAN and Hispanic people had the highest uninsured rates at 18.9% and 18.4%, respectively, as of 2024. Uninsured rates for NHPI (12.3%) and Black people (10.1%) also were higher than the rate for their White counterparts (6.8%). Asian people had the lowest uninsured rate at 5.7%, although uninsured rates vary among subgroups of the Asian population. The higher uninsured rates among some groups are driven by lower rates of private coverage. Medicaid coverage helps to narrow these differences but does not fully offset them.

Medicaid and CHIP coverage help fill gaps in private coverage and reduce coverage disparities for children, but some disparities in children’s coverage remain (Figure 2). Medicaid and CHIP cover larger shares of children than adults, reflecting more expansive eligibility levels for children. This coverage helps fill gaps in private coverage, with over half of Hispanic, Black, AIAN, and NHPI children covered by Medicaid and CHIP. However, there remain some disparities in children’s coverage. For example, AIAN children are about three times as likely as their White counterparts to lack coverage (13.6% vs. 4.4%). Moreover, Hispanic children are more than twice as likely as White children to be uninsured (9.8% vs. 4.4%).

Among people under age 65, uninsured rates in states that have not expanded Medicaid are higher than rates in expansion states across most racial and ethnic groups as of 2024 (Figure 3). While uninsured rates for children are lower than for adults across groups, these differences between expansion and non-expansion states persist among children. For example, 16.0% of Hispanic children in non-expansion states are uninsured compared to 6.7% of Hispanic children in expansion states. The differences in coverage rates between Black and Hispanic people compared with White people are larger in non-expansion states compared with expansion states. However, the relative risk of being uninsured for Black, Hispanic, Asian and NHPI people compared with White people is similar in expansion and non-expansion states. For example, Hispanic people under the age of 65 years old are roughly 2.6 times as likely as their White counterparts to lack coverage in both expansion and non-expansion states. Uninsured rates for AIAN people are similar in expansion and non-expansion states.

Overall, about half of uninsured people are eligible for Medicaid or Marketplace coverage, but eligibility varies across racial and ethnic groups, with smaller shares of Hispanic and Asian uninsured people eligible for assistance due to these groups having larger shares of ineligible noncitizen immigrants. Overall, over half (52.2%) of people who were uninsured in 2024 were eligible for financial assistance either through Medicaid or through subsidized Marketplace coverage, while the remaining half (47.8%) were not eligible because they fell in the Medicaid coverage gap in states that have not expanded Medicaid, had income too high to qualify for Marketplace premium tax credits, , were eligible for employer coverage, or had an ineligible immigration status. However, the share of the remaining uninsured eligible for assistance varied by race and ethnicity. For example, uninsured Black people under age 65 were more likely than their uninsured White counterparts to fall in the Medicaid coverage gap, reflecting that most of the 10 states that have not expanded Medicaid, are in the South where a higher share of the Black population resides. Uninsured Hispanic and Asian people under age 65 were also less likely than White people to be eligible for coverage options, in part, due to higher shares of noncitizens who face immigrant eligibility restrictions including eligibility restrictions for lawfully present immigrants and ineligibility for undocumented immigrants. (Figure 4).

• Gavi, the Vaccine Alliance (Gavi) is an independent public-private partnership and multilateral funding mechanism that aims to expand global access to and use of vaccines, particularly among vulnerable children.
• Since its launch in 2000, Gavi has provided approximately $29 billion to support immunization efforts in low- and middle-income countries, not including funding for COVAX.
• The U.S. government (U.S.) has supported Gavi since its creation through direct financial contributions, participation in Gavi’s governance as a member of the Board, and technical assistance; it had been its third largest contributor in recent years, providing 13% of its funding since its inception (not including funding for COVAX, the global COVID-19 pandemic vaccine response), reaching $300 million in FY 2024. In addition, the Biden administration had pledged that the U.S. would provide approximately $1.6 billion to Gavi over its 2026-2030 funding period.
• While Congress again appropriated $300 million for Gavi in both FY 2025 and FY 2026, the Trump administration has not provided this funding to the organization, citing concerns about vaccine safety despite Gavi following globally recognized scientific standards and evidence.
• Gavi’s latest replenishment summit secured pledges of more than $9 billion, towards a target of $11.9 billion, for the 2026-2030 period, as well as additional financing from development finance institutions and manufacturers to support country recipients. Still, the loss of U.S. funding in the context of a constrained financing environment globally presents new challenges for reaching children in low- and middle- income countries with life-saving vaccines.

Created in 1999 and formally launched in January 2000, Gavi, the Vaccine Alliance (Gavi) is an independent public-private partnership and multilateral funding mechanism that “aims to save lives and protect people’s health by increasing coverage and equitable and sustainable use of vaccines.” Gavi’s main activities include supporting low- and middle-income countries’ access to new and underused vaccines for vulnerable children through financial support, technical expertise, and market-shaping efforts, such as negotiating with manufacturers, to help lower the cost of procuring vaccines. Gavi operates in five-year funding cycles, with a revised strategy and goals for each cycle. Each five-year strategy is accompanied by a vaccine investment strategy, which determines which vaccines will be made available to countries.

Gavi’s current five-year strategy, for the 2026-2030 period, which is its sixth strategy, includes four core goals:

1. introduce and scale-up vaccines,
2. strengthen health systems to increase equity in immunization,
3. improve sustainability of immunization programs, and
4. ensure healthy markets for vaccines and related products.

The current strategy emphasizes reducing the number of ‘zero-dose’ children with the goal of reaching no zero-dose children by 2030, in alignment with Immunization Agenda 2030; prioritizing programmatic and financial sustainability of country immunization programs; supporting targeted countries that have phased out of Gavi support or have never been eligible for Gavi support to maintain immunization progress; and providing more tailored approaches for Gavi countries to reach under-vaccinated populations, such as those living in remote or conflict settings, by encouraging countries to adopt strategies that reduce potential barriers to vaccination.

In addition to Gavi’s role in routine childhood immunizations, Gavi was one of the organizations leading COVAX, a multilateral effort that supported the equitable development, procurement, and delivery of COVID-19 vaccines globally that began in 2020 and ended in 2023. Gavi’s role in COVAX was to facilitate the procurement and delivery of COVID-19 vaccines, with particular emphasis on low- and middle-income countries. Provision of COVID-19 vaccines and funding support to countries was integrated into Gavi’s regular programming from 2024-2025 (COVID-19 vaccine support has been discontinued).

Organization

Gavi’s Secretariat, with its main headquarters in Geneva and an office in Washington, D.C., carries out the day-to-day operations of the partnership. Gavi does not have program offices or staff based in recipient countries but rather relies on country health ministries and World Health Organization (WHO) regional offices to implement programs. Gavi is led by a Chief Executive Officer (CEO), currently Sania Nishtar.

The 28-member Gavi Board sets Gavi’s funding policies and strategic direction, and monitors program implementation. It includes 18 “representative” seats, nine seats for independent individuals, and one ex-officio non-voting seat for Gavi’s CEO. The 18 representative seats, as specified in Gavi’s statutes, are as follows: donor country governments (5), implementing country governments (5), the WHO, the United Nations Children’s Fund (UNICEF), the World Bank, and the Gates Foundation, and one seat each for civil society groups, the vaccine industry in industrialized countries, the vaccine industry in developing countries, and technical health/research institutes. Additionally, several Board committees guide and advise the Board and the CEO on Gavi activities under their purview. The U.S. government was represented on Gavi’s Board as the Board member for the donor country government constituency until the end of 2025. With the suspension of U.S. support, the U.S. lost eligibility to hold a seat on the Gavi Board.

Funding

Since its 2000 launch, Gavi has received approximately $30 billion in financing, not including funding for COVAX (see Table 1).¹ Approximately four-fifths (80%) of Gavi’s funding came from contributions provided by donor governments and private organizations and individuals. The top three government donors were the United Kingdom, the U.S. and Norway, while the largest private donor was the Gates Foundation.

Donors support Gavi through direct contributions as well as funding commitments to innovative financing mechanisms, the proceeds of which help support Gavi’s overall financing. These innovative financing mechanisms include the International Finance Facility-Immunisation (IFFIm) and the Pneumococcal Conjugate Vaccine (PCV) Advance Market Commitment (AMC). The IFFIm was created in 2006 and uses donor funding commitments to back the issuance of special bonds in capital markets, essentially providing “up-front” financing to Gavi. The PCV AMC began in 2010, and though it ended in 2020, it supported accelerated access to pneumococcal vaccines through up-front funding commitments from donors and continues to do so through contracts with manufacturers that extend until 2029. The U.S. does not provide support to either of these mechanisms.² 

In addition to financing Gavi’s regular activities, donors pledged additional resources to support the Gavi COVAX Advance Market Commitment (COVAX AMC), a financial mechanism within COVAX that supported low- and middle-income countries through procurement and distribution of COVID-19 vaccines; through 2024, Gavi received $12.6 billion from donor governments, private philanthropy, and innovative financing mechanisms for the COVAX AMC for vaccine procurement, delivery, and logistics.³

Eligibility

Only low- and middle-income countries with a Gross National Income (GNI) per capita below or equal to $1,820⁴ are eligible for Gavi support. In 2025, 54 countries were eligible for Gavi support.

Recipient countries’ governments are expected to share responsibility for funding their national immunization efforts through Gavi’s co-financing requirements (introduced in 2008), determined according to country income level and transition status. As countries develop economically, they are expected to contribute a greater share of the funding required for immunization programs. Countries classified as low-income by the World Bank are initial self-financing countries, while countries between the low-income threshold and Gavi eligibility threshold ($1,820 GNI per capita) are in preparatory transition. Initial self-financing countries are responsible for co-financing the equivalent of $0.20 per dose each year. Countries in preparatory transition gradually increase their co-financing contribution each year.⁵ When a country’s income rises above the GNI per capita threshold, it moves into an eight-year “accelerated transition” period of increasing domestic financing share, after which the country is expected to fully fund its own immunization programs.⁶ As of 2025, 19 countries have transitioned out of Gavi financial support.

Additionally, Gavi offers limited support for countries that have transitioned out of Gavi eligibility and for middle-income countries that have never been eligible for Gavi support.⁷ Recognizing that many formerly and never Gavi-eligible countries experience low coverage rates and have yet to make key vaccine introductions, eligible countries can apply for “catalytic” funding to support the introduction of key missing vaccines (HPV, PCV, or rotavirus) or mitigation of backsliding.⁸

Country Support

Gavi provides grant financing to country programs in the following two support types:

• Vaccine support, including for vaccine introduction, targeted and routine campaigns, and
• Health systems and immunization strengthening (HSIS) support,⁹ to improve country data systems and to support cold chain equipment, health workforce, and community engagement.

Country allocation formulas for HSIS support are based on the following metrics: number of zero-dose children, coverage of essential vaccines,¹⁰ GNI per capita, and if a country is considered fragile or conflict-affected.¹¹ For vaccines, all countries are required to pay a share of the cost of their Gavi-supported vaccines.

Additionally, Gavi has provided country support through emergency response funding, including for Ebola vaccination during Ebola outbreaks¹² and for COVID-19, allowing for up to $200 million in reprogrammed Gavi support for the COVID-19 response in Gavi-eligible countries, and other support  for the COVID-19 response including through the creation of COVAX (which helped expand access to COVID-19 vaccines in lower-income countries) and the COVID-19 Vaccine Delivery Partnership (CoVDP, which aimed to improve COVID-19 vaccine coverage in certain COVAX countries, with a particular emphasis on countries that were below 10% coverage in January 2022).¹³ In 2022, Gavi supported 50 outbreak response vaccination campaigns. Gavi currently funds several emergency vaccine stockpiles, allowing for rapid deployment of vaccines during outbreaks, including for cholera, Ebola, meningitis, mpox,¹⁴ and yellow fever. In 2024, Gavi deployed vaccines from these emergency stockpiles to 20 countries.¹⁵

Since its launch in 2000, Gavi has provided approximately $29 billion to support country immunization programs (not including funding for COVAX).¹⁶ Over the past three years, 2023-2026, more than $8.1 billion has been disbursed, most of which has been for vaccine support (62%), followed by health systems strengthening (23%) (see Table 2).

Results

Gavi reports it has helped to immunize more than 1.2 billion children in supported countries, including more than 72 million in 2024 alone, and supported 58 different vaccine introductions and preventive campaigns and 50 outbreak response campaigns in 2024. Additionally, Gavi support has helped avert more than 20.6 million deaths and contributed to more than $280 billion in economic benefits, since its launch in 2000. Additionally, according to Gavi, its support has led to improved child health and immunization indicators across its supported countries. For example, the average vaccine coverage across multiple key Gavi-supported vaccines –  including the human papillomavirus (HPV) vaccine, inactivated polio vaccine, and pentavalent vaccine (the vaccine providing protection against diphtheria, tetanus, pertussis, hepatitis B, and Hib),¹⁷ among others –  was 63% in Gavi-supported countries in 2024, up from 48% in 2019.¹⁸ Lastly, Gavi’s work has contributed to vaccine market-shaping; for example, Gavi reports that its influence has helped lower the cost of the HPV vaccine from a price per dose of $4.50 in 2015 to $2.90 in 2022.¹⁹

The U.S. government has supported Gavi since its creation. President Clinton made the initial U.S. pledge to the newly formed partnership in 2000, and the U.S. provided its first contribution in 2001. Prior to the second Trump administration, the U.S. supported Gavi through financial contributions, participation in Gavi’s governance, and by providing technical assistance, but the current administration has not provided funding to the organization (see below).

Additionally, the U.S. had supported other global immunization activities that complemented Gavi’s  efforts, providing bilateral (country-to-country) support for immunization through USAID (before its dissolution), CDC, and other agencies, focusing on strengthening routine immunization systems to deliver vaccines. However, the U.S. government is currently reorganizing how it supports global health programs, including immunization activities, under its “America First Global Health Strategy” which includes the development of bilateral agreements with countries. Given that Gavi was the mechanism through which the U.S. supported vaccine procurement, it is not yet clear how these agreements will support procurement going forward. See also the KFF fact sheet on the Trump administration’s foreign aid review and the proposed reorganization of U.S. global health programs.

Financial Support 

The U.S. supported Gavi with direct contributions starting in 2001, with funding reaching $300 million in FY 2024, its highest level. Additionally, in response to the COVID-19 pandemic, the U.S. provided $4 billion in FY 2021 emergency funding to Gavi for COVID-19 vaccine procurement and delivery support under COVAX, making the U.S. the largest donor to COVAX (32% of $12.6 billion received overall).²⁰In addition to its financial support for COVAX, the U.S. donated the largest number of COVID-19 vaccines to other countries. While Congress appropriated $300 million for U.S. contributions to Gavi in FY 2025 and FY 2026 (see Figure 1), the current administration has not provided funding to Gavi after citing concerns about vaccine safety despite Gavi following globally recognized scientific standards and evidence.²¹ See the KFF budget tracker and the KFF fact sheet on the U.S. Global Health Budget: Maternal & Child Health (MCH) for details on historical appropriations for Gavi, and also the KFF fact sheet on the Trump administration’s foreign aid review and the status of U.S. support for Gavi.

Governance Activities

The U.S. had historically played a role in Gavi’s governance, including as a Board and committee member, but with the suspension of U.S. funding by the Trump administration, the U.S. is no longer eligible to hold a Board seat.  

Technical Support

The U.S. had historically provided Gavi with technical support and expertise in the design, implementation, and evaluation of its programs in the field through partnerships with several U.S. agencies. For example, Gavi’s accelerated vaccine introduction programs had been conducted with technical support from the Centers for Disease Control and Prevention (CDC) and the now-dissolved U.S Agency for International Development (USAID), along with other partners.

1. This amount includes proceeds for 2000-2024 and pledges for 2025. ↩︎
2. For further information about restrictions on U.S. support for these innovative financing mechanisms, see KFF, Innovative Financing Mechanisms for Global Health: Overview and Considerations for U.S. Government Participation, Sept. 2011. ↩︎
3. KFF analysis of Gavi cash receipts data. Gavi, “Cash Receipts 31 December 2024,” https://www.gavi.org/news-resources/document-library/cash-receipts. ↩︎
4. For countries to be eligible for Gavi support, their most recent GNI per capita must be at or below $1,820, or the country’s average GNI per capita over the last three years must be at or below $1,820. ↩︎
5. Countries in the first year of the preparatory transition phase co-finance the equivalent of $0.20 per dose, the same as initial self-financing countries. For each subsequent year, countries in preparatory transition co-finance a 15% increase of the total fraction paid in the prior year. Gavi, “Co-financing policy,” https://www.gavi.org/sites/default/files/programmes-impact/our-impact/01_Gavi-Alliance-Co-financing-Policy-60.pdf. ↩︎
6. Countries in the first year of the accelerated transition phase co-finance the equivalent of the prior year’s total fraction plus 15%, the same as countries in preparatory transition. For each year after, the amount per dose increases linearly until the country is fully financing each vaccine after the eighth year and end of Gavi support. Gavi, “Co-financing policy,” https://www.gavi.org/sites/default/files/programmes-impact/our-impact/01_Gavi-Alliance-Co-financing-Policy-60.pdf. ↩︎
7. Countries eligible for this limited funding include those above the Gavi eligibility threshold ($1,820 GNI per capita) but below the World Bank lower-middle income threshold ($4,495 GNI per capita) or those that are eligible to borrow from the International Development Association. Gavi, “Annex D: Report to the Board, July 24-25 2025,” https://www.gavi.org/sites/default/files/%20/board/minutes/2025/24-25-july06%20-%20Annex%20D%20-%20Framework%20for%20Gavi%20Funding%20to%20Countries.pdf. ↩︎
8. Support for backsliding mitigation is only available to former Gavi-eligible countries. Gavi, “Annex D: Report to the Board, July 24-25 2025,” https://www.gavi.org/sites/default/files/%20/board/minutes/2025/24-25-july06%20-%20Annex%20D%20-%20Framework%20for%20Gavi%20Funding%20to%20Countries.pdf. ↩︎
9. HSIS support only available for Gavi-eligible countries. Gavi, “Annex D: Report to the Board, July 24-25 2025,” https://www.gavi.org/sites/default/files/%20/board/minutes/2025/24-25-july06%20-%20Annex%20D%20-%20Framework%20for%20Gavi%20Funding%20to%20Countries.pdf. ↩︎
10. Includes coverage of first-dose diphtheria, tetanus, and pertussis containing vaccine (DPT1), coverage of DTP3, and coverage of second-dose measles containing vaccine (MCV2). Gavi, “Annex D: Report to the Board, July 24-25 2025,” https://www.gavi.org/sites/default/files/%20/board/minutes/2025/24-25-july06%20-%20Annex%20D%20-%20Framework%20for%20Gavi%20Funding%20to%20Countries.pdf.    ↩︎
11. Gavi, “Annex D: Report to the Board, July 24-25 2025,” https://www.gavi.org/sites/default/files/%20/board/minutes/2025/24-25-july06%20-%20Annex%20D%20-%20Framework%20for%20Gavi%20Funding%20to%20Countries.pdf.    ↩︎
12. Gavi, “500,000 doses of Ebola vaccine to be made available to countries for outbreak response,” webpage, https://www.gavi.org/news/media-room/500000-doses-ebola-vaccine-be-made-available-countries-outbreak-response. ↩︎
13. CoVDP phased out its operations in June 2023 as the partnership was not set up to be a permanent structure. WHO, “COVID-19 Vaccine Delivery Partnership,” webpage, https://www.who.int/emergencies/diseases/novel-coronavirus-2019/covid-19-vaccines/covid-19-vaccine-delivery-partnership; Devex, “Exclusive: A COVID-19 initiative for vaccine delivery is winding down,” 11 January 2023, https://www.devex.com/news/exclusive-a-covid-19-initiative-for-vaccine-delivery-is-winding-down-104724. ↩︎
14. Gavi, “Gavi 6.0 Funding Guidelines,” https://www.gavi.org/sites/default/files/support/guidelines-2026/gavi-60-funding-guidelines-annexes.pdf#page=43 ↩︎
15. Gavi, “Vaccine stockpiles,” https://www.gavi.org/vaccineswork/vaccine-stockpiles-guide. ↩︎
16. KFF analysis of data provided by Gavi on disbursements by program area and year. KFF personal communications with Gavi, March 19, 2026. ↩︎
17. The vaccines included in Gavi’s breadth of protection measure include: the third dose of the pentavalent vaccine, third dose of the pneumococcal conjugate vaccine, first dose of the rubella-containing vaccine, last dose of the rotavirus vaccine, second dose of the measles-containing vaccine, yellow fever, meningococcal A, Japanese encephalitis, and last dose of the HPV vaccine. Gavi, “Gavi 2024 Annual Progress Report,” https://www.gavi.org/sites/default/files/programmes-impact/our-impact/apr/Gavi-2024-Annual-Progress-Report.pdf#page=17.    ↩︎
18. Gavi, “Gavi 2024 Annual Progress Report,” https://www.gavi.org/sites/default/files/programmes-impact/our-impact/apr/Gavi-2024-Annual-Progress-Report.pdf#page=17. ↩︎
19. As another example of Gavi’s market-shaping influence, Gavi and UNICEF recently announced an agreement to make R21/Matrix-M malaria vaccines more affordable for Gavi countries through the IFFIm mechanism. UNICEF, “Gavi and UNICEF announce equitable pricing deal for malaria vaccine to protect 7 million more children by end of decade,” https://www.unicef.org/press-releases/gavi-and-unicef-announce-equitable-pricing-deal-malaria-vaccine-protect-7-million. ↩︎
20. The U.S. announced it would donate 500 million Pfizer doses to COVAX at the G7 Summit in June 2021. However, a portion of these doses were purchased using funds appropriated to Gavi ($2 billion for 300 million Pfizer doses), while the remaining 200 million doses were purchased using $1.5 billion in other emergency funds from the American Rescue Plan Act. To avoid double-counting, Gavi counts the U.S. funding that was contributed to Gavi under its COVAX funding contributions, with only 200 million of the doses – those purchased directly by the U.S. – counted as COVAX vaccine dose donations. KFF personal communication with Gavi, Nov. 12, 2021; White House, “FACT SHEET: President Biden Announces Historic Vaccine Donation: Half a Billion Pfizer Vaccines to the World’s Lowest-Income Nations,” June 10, 2021; Gavi, “COVAX AMC Donors Table,” Apr. 7, 2022, https://www.gavi.org/sites/default/files/covid/covax/COVAX-AMC-Donors-Table.pdf; Gavi, “Cash Receipts 31 December 2024,” https://www.gavi.org/news-resources/document-library/cash-receipts. ↩︎
21. Secretary Robert F. Kennedy Jr. (@SecKennedy), https://x.com/SecKennedy/status/1937986463510982869 [X post], June 25, 2025; Gavi, “Statement,” https://www.gavi.org/news/media-room/statement-response-25-june-2025; Reuters, “Exclusive: US conditions funding to global vaccine group on dropping mercury-based preservative from shots,” https://www.reuters.com/business/healthcare-pharmaceuticals/us-conditions-funding-global-vaccine-group-dropping-mercury-based-preservative-2026-01-28/. ↩︎