A bill passed by the state legislature in March then signed into law by Democratic Gov. Jared Polis allows Colorado to further uncouple itself from federal guidance.

The law allows health officials to follow the recommendations of national medical groups when making decisions such as purchasing bulk vaccines for the Medicaid program.

“We are insulating our state from the dysfunction coming out of Washington,” said Democratic state Sen. Kyle Mullica, a co-sponsor of the bill and a registered nurse. “We’re going to rely on science.”

“From fighting during the pandemic for Coloradans to get vaccines as quickly as possible to combating the Trump Administration’s barriers to getting vaccinated, we have expanded access to vaccines for Coloradans who want them,” Polis said in a statement when he signed the law.

Colorado is one of at least 29 states that, along with Washington, D.C., have taken steps to bypass the new federal recommendations amid worries that the changes could chip away at public trust in vaccines and erode broad vaccine coverage.

Previously, Colorado, like most states, had followed federal guidance set by the Centers for Disease Control and Prevention. In January, CDC advisory panelists, selected by Health and Human Services Secretary Robert F. Kennedy Jr., removed six pediatric immunizations from the agency’s universal recommendation list.

Last year, doctors, scientists, local leaders, and other supporters came together to form an outreach and advocacy coalition called Colorado Chooses Vaccines.

The group aims to offer a clear, unified voice on the proven benefits of vaccines and reassure residents confused by the many federal changes.

Carol Boigon, a former Denver City Council member, joined the group because she wants more people to hear her own chilling story about vaccine-preventable illness.

“Every summer everybody got sick,” Boigon said, recounting her childhood in 1950s Detroit.

The illness was polio, a highly contagious viral disease that attacks the nervous system, sometimes causing partial or full paralysis.

During the summer of 1953, “the whole block was sick and some of us got crippled, and that was just the way it was,” she said.

New Group Steps Up

Boigon’s personal history will be part of the coalition’s work to educate new generations about the dangers of infectious diseases that were once common in the U.S. but are now relatively rare.

The group, which formed last September, will also compile vaccine information from medical groups and the state health department and advocate for policy proposals with the state government.

“It was in direct response to the federal threats,” said another coalition member, former state lawmaker Susan Lontine. She leads the nonprofit Immunize Colorado.

Another member, public relations specialist Elizabet Garcia, wants more outreach to Hispanics, whose vaccination rates lag behind other groups’.

“A lot of time it’s this fear that they’re going to have to pay out-of-pocket, that their insurance doesn’t cover it, that they might not even have insurance in general,” Garcia said.

Boigon was 5 when she got sick and was hospitalized for six weeks with a fever. The virus attacked her spine.

“None of my limbs worked immediately afterwards,” Boigon said.

Although she regained function in her other limbs, her right arm never fully recovered. She had to adapt, relearning everyday tasks such as reaching out to shake hands with people with her left hand.

In 1955, not long after she got sick, the new polio vaccine became more widely available to the public. As vaccinations took off, U.S. cases of polio, once one of the nation’s most feared diseases, dropped by an estimated 85%-90%.

Increasing Public Trust

State leaders have taken other steps to promote public health. After the Trump administration pulled the U.S. out of the World Health Organization, several states, including Colorado, decided to join the WHO’s Global Outbreak Alert and Response Network on their own.

Colorado also joined a multistate lawsuit challenging the Trump administration’s changes to the childhood vaccine schedule.

And the new state law has provisions besides allowing the state to diverge from federal recommendations. It codifies pharmacists’ ability to prescribe and give vaccines themselves. It also increases legal protections for healthcare workers who give vaccines.

“This law will provide more clarity to guide all Coloradans, including providers who administer vaccines,” Lontine said.

But the legislation has opponents who say it would interfere with parental choice and claim vaccines might be unsafe or ineffective.

“I just want to make sure we’re not just getting into a big political dispute between the federal recommendations — the CDC and so forth — and different political views in Colorado here,” said Republican state Sen. John Carson, who voted against the vaccine bill.

NPR contacted the U.S. Department of Health and Human Services about Colorado’s new law. Spokesperson Emily Hilliard answered in an email: “The updated CDC childhood schedule continues to protect children against serious diseases.”

Preventable Illnesses Surge

The flurry of statewide activity comes as Colorado and the nation have seen surges in illnesses such as flu and measles.

As of mid-May, Colorado had recorded 22 measles cases this year. In 2025, it registered 36 cases, according to the state health department, far surpassing totals from previous years.

Across Colorado, kindergarten vaccination rates for measles were 88% last school year — with only a few counties achieving rates of 95%, the level needed for herd immunity, according to data published by The Washington Post in December.

This has also been Colorado’s worst flu season in recent years.

Vaccination rates for both flu and covid-19 have dropped slightly in Colorado, according to the state health department.

Eight children in Colorado have died this season from flu; one from covid; and one from RSV, or respiratory syncytial virus. Vaccines for all three are available for children and recommended by the state’s health department.

Kennedy, a longtime anti-vaccine activist, has defended his decisions to overhaul the recommended schedule for childhood vaccinations.

In March, a federal judge put on hold many of the changes.

“We’re not taking vaccines away from anybody. If you want to get the vaccine, you could get it. It’s going to be fully covered by insurance just like it was before,” Kennedy told CBS News in January.

When a reporter suggested the new changes could result in fewer people getting a flu vaccine, Kennedy said: “Well, that may be, and maybe that’s a better thing.”

Boigon is sometimes incredulous at everything that has happened.

“It’s like we’re going backwards,” she said. “It’s like we have decided we don’t want a modern life; we want to be back in the 1950s, where children are sick and dying.”

This article is from a partnership with Colorado Public Radio and NPR.

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I believe in making it very difficult for people to refuse vaccines. There’s enough of the libertarian about me that I wouldn’t actually strap them down and inject them, but I’m fine with school districts making parents write out their conscientious objections to children being immunised or with sports clubs requiring adult proof of immunisation before people can join. What I or you think is, though, beside the point. Much of the US is walking away from cajoling and compulsion and there’s great pressure in Europe for similar change. We can either go on moaning about how we wish the world hadn’t changed or we can respond effectively.

Before the current US Administration began rewriting vaccine recommendations, one in six US parents wasn’t following them. We used to joke that vaccine-preventable diseases in the West had become diseases of children of the over-educated middle classes who shopped at Whole Foods and did naked yoga classes; vaccine refusers now are still more likely to be white, but they skew to being conservative, very religious, and young. Recommendations actually reduced uptake in this group because most have a deep distrust of the Federal Government and its agencies.

Formal vaccine refusals in Poland more than doubled from 2017 to 2022 and reached over 87,000 in 2023, a 1685% increase since 2003; measles cases surged 10x in early 2024 due to falling rates. Ireland, where I live, has the third-lowest childhood vaccine coverage rate in the OECD.

There are bright spots too, Italy for example, and the battle is far from lost. But the mistrust now endemic to the United States is coming to Europe.

High-handed US and European experts

You can understand confusion, if not mistrust. About half of parents in the USA did not vaccinate their children for flu in the past year, compared with 41 percent who said they had done so, a Washington Post / Kaiser Family Fund poll found. Coverage started declining after 2019. In 2016, the US CDC said that the nasal flu vaccine used in children provided “no measurable benefit” (injectable vaccines for adults were, as usual, highly effective). In the same year, Public Health England said that the same vaccine (produced by a British company in a British factory) was 58 percent effective. Canada followed the UK, saying that its population was very different to the USA! It’s very unlikely that both the Americans and the Canadians were right — despite those obvious population differences…. Few journalists covered the story — I suspect because no-one wanted to be accused of promoting vaccine scepticism. The vaccine is now recommended again in the USA.

Few American paediatricians and even fewer nurses would have been able to explain this to parents because no-one ever bothered to give the professionals an explanation. What do we think doctors told parents who asked why a vaccination was recommended then was not and then was again? British parents who did a web search (this was pre-Chat GPT, remember) might have asked why their children were getting an apparently ineffective vaccine and would have met equally bemused stares from their health providers. Did anyone brief social media influencers or health journalists? Of course not, who do they think they are? What impudence…

I know some of those involved and I’m sure that there was no subterfuge and nothing sinister going on; the answer is likely to be dull and involve methodology and surveillance systems.

This is the way we all used to approach treatment discussions 40 years ago — the doctor told you what to do, you thanked him (it was nearly always a him) and you did it. Questions were a sign of disrespect, of even psychological illness. I was recently treated by a Russian dentist, now practising in Ireland, who was shocked and outraged when I questioned his recommendation to use antibiotics prophylactically; if he had been Irish, he would have been completely used to it.

Nonsensical recommendations in developing countries

Vaccine hesitancy looks a bit different in France. Those least likely to have their children vaccinated tend to be more educated, high users of the internet for information and to have lower trust in health authorities. Those who refuse vaccines for themselves tend to be at the lower end of the social hierarchy with less education and fewer financial resources. Many are ​immigrants and descendants of immigrants, and residents of French overseas departments. Both are probably likely to know about the vaccines which Western experts recommend for children in the developing world, including in Francophone countries.

I remember doing a policy interview with the health minister of a large Indian state. I was trying to find out what he might pay for an effective TB vaccine. “But”, he said, “we already have a TB vaccine. Why do I need a new one?” His top civil servant was sitting behind him and frantically gesticulating to me to try to stop me explaining that the BCG vaccine, given to almost every Indian newborn, may do nothing to prevent TB infections and, at best, may make the disease less severe in some of the children who contract it. It is, though, very good at causing severe side effects. No developed economy uses it; almost every poor one does.

I’m ashamed to say that I did not explain BCG as clearly as I should have to the minister. He was the norm, not the exception, in that series of policymaker interviews: few of those making decisions about TB vaccine policy had ever been given a thorough, honest briefing about the limitations of the vaccines their expert advisers recommended. None of the parents, of course, were ever told about any of these reservations.

There might also be a case for the current practice of giving many children in Africa and Asia a vaccine that sometimes causes polio, instead of preventing it, although I doubt it. The risks of a child contracting polio from the live-attenuated oral vaccine are probably underestimated when they’re presented to politicians and policy influencers. Hardly any parents who bring their children forward for these vaccines are told about the risk or the rationale for continuing to use them, rather than the perfectly safe inactivated vaccine used throughout the rich world.

Is it any wonder that those with insight into the developing world are sceptical? The real wonder is that vaccine confidence is still so high in Africa and Asia. That probably comes from everyday encounters with the tragic consequences of infection by vaccine-preventable illnesses, an experience blessedly denied to most Americans and Europeans.

What we need to do now

The road ahead has been cleared for us. Thirty years ago, I went out with a trainee doctor at the Royal College of Surgeons in Ireland. He was upset one evening because he had been berated by his tutor for telling an older patient that she had cancer — it had been agreed with the family that she would be told that she had a “growth” to avoid upsetting her. At least she found out: King George VI of the United Kingdom sent his daughter, Princess Elizabeth, on a world tour in 1952 because neither he nor she had been told that he had lung cancer and that it was terminal. He never saw her again. These stories shock us now because honesty, realism and communication are taken for granted in what we tell patients who are ill. These principles need to be the new basis for what we tell people who are healthy and want to stay that way.

First we need a change in attitude. Whether to be immunised or not is a decision that people will take — actually, a series of decisions. We don’t need to think about whether we like the concept or not, it is the way things increasingly are. We have to get ordinary people used to making good decisions, just as they do about other life issues such as house buying or insurance or continuing education. Ordinary people are not property experts or risk analysts or trained evaluators of course offerings, but they mostly make reasonable choices. They can do the same thing with vaccines.

Then, we need to communicate much more. Vaccine producers are free to talk to the public about recommended vaccines in many countries; where they are not, they need to be allowed to. Then they need to accept their responsibility to speak often, clearly and loudly. They are the experts on the vaccines they produce and they must tell potential recipients or the parents of recipients about the benefits and disadvantages. Of course, they need to do it in an honest and balanced way. They will be more successful if they communicate in partnership with professional organisations, charities and respected consumer groups. They can be transparent: they have a commercial interest in getting people to accept vaccines but a legal responsibility to set out all the factors in deciding whether to or not. It’s like banks selling mortgages and car dealerships selling warranties.

Researchers and healthcare providers need training in communication and answering questions. They need to be much better at helping policy makers to make decisions about vaccines. Today, too few vaccines are reimbursed and many are offered only to some of those who would benefit from them. In many countries, it is still too hard to get vaccinated and even where rules have changed, practices have not — look at Poland, for example. Politicians and public officials can unleash vaccines so that they can do even more to boost productivity, growth and wealth in society.

Those same scientific and medical experts need to be much better at talking to people who are making decisions about immunisation. Research tells us clearly what helps the right decision, but too few professionals follow the evidence. The most powerful prompt to action is a trusted health professional saying, “I would like you to do this”. Setting a good example works wonders too, but too few health professionals have had all of the vaccines recommended for them.Communication can change all of this.

The vast majority of social media influencers want to give good advice and powerful motivation but no-one talks to them — after all, we want people to follow the guidelines, not think, don’t we? For example, have you seen Dr Mike Varshavski take on 20 vaccine sceptics at once? Thirty million people probably have over various platforms and he’s brilliant. Industry and professionals need to work with influencers who specialise in women’s issues, childhood, workplace effectiveness and, of course, health. Look at this from Dr Ahmed Ezzat — his videos on RSV reduced calls to the emergency services by 25% — and just think what he can do for vaccines.

Journalists are discouraged from writing pieces about vaccine decisions — “just tell people to follow expert recommendations”. Many, consequently, avoid writing about vaccines. We need to treat these journalists as powerful allies in helping lay people to make important decisions with lifelong implications for their risk of developing chronic illnesses. It’s the way that property developers treat journalists who write about houses,

Honestly, I still think it would be simpler and still ethically correct to just nudge almost everyone into getting immunised but that is not an option in many places now and, given the global market in ideas, won’t be one anywhere soon.

Parents get things right

Asia should encourage us. Many parents save and spend to get their children the best vaccines. The state often provides old tech or nothing, so middle-class parents take their children to private clinics for the best protection and pay full price for it. Of course, it’s not fair to poorer children and it is crazy public policy given that population sizes will plunge across Asia over the next 30 years so every child, whether middle class or not, is a precious national resource. Still, it shows that individual families can and do make better decisions than health policy makers when the routes of communication are open and used well.

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Conflicts compound these inequities. Fragile and conflict-afflicted countries account for just a quarter of the world’s infants, yet they harbour half of all zero-dose children, whose numbers have increased from 3.6 million in 2019 to 5.4 million in 2024. In Sudan, vaccination coverage collapsed — from 85% pre-war to as low as 8% in conflict zones — while Yemen’s zero-dose figures climbed significantly, driven by instability, health service disruptions, and misinformation.

Conversely, Gavi-supported, low-income countries saw marked improvements, reducing un- and under-vaccinated cohorts by around 650,000 in 2024. Yet even high- and upper-middle-income economies are experiencing slippage, with measles coverage hovering at 84% (first dose) and 76% (second), below the 95% threshold needed for herd immunity. Consequently, measles outbreaks surged, with 60 countries reporting significant incidents in 2024, doubling since 2022.

Country case snapshots powerfully illustrate these trends. In Bosnia and Herzegovina, measles vaccination rates are at just 55%, compared to Croatia’s 90%, contributing to over 7,000 cases and two adolescent deaths, prompting WHO and UNICEF to urge intensified immunisation campaigns. In Pakistan, polio resurgence has occurred amid militant threats and disrupted campaigns, with over one million children missing doses in 2024. The government’s response includes large-scale vaccination drives and policy enforcement, such as arrest warrants, signalling both the challenge and political recognition of routine immunisation’s fragility. Meanwhile, Bangladesh has steadily expanded its vaccine schedule — adding Hib, rubella, PCV, IPV and MR2 — achieving DTP3 coverage around 93% and fully vaccinated rates near 84% by 2019.

These illustrations reveal both progress and vulnerability. Countries with strong political will, robust systems, and community trust — like Bangladesh — are managing gains. Others, like Pakistan and Bosnia, highlight how instability, mistrust, and misinformation can swiftly unravel public health gains.

The 2024 immunisation data reiterates an urgent message. Global coverage has stabilised and broadened, but millions of children remain vulnerable in conflict zones and complacent high-income settings. Measles outbreaks, polio flare-ups, diphtheria spikes, and new threats like RSV underscore that the progress we’ve made is neither permanent nor evenly shared. Unless we decisively fill funding gaps, fortify health delivery in emergencies, ensure vaccine equity, and strengthen trust, these vulnerabilities will deepen — and outbreaks will follow.

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Conflicts compound these inequities. Fragile and conflict-afflicted countries account for just a quarter of the world’s infants, yet they harbour half of all zero-dose children, whose numbers have increased from 3.6 million in 2019 to 5.4 million in 2024. In Sudan, vaccination coverage collapsed — from 85% pre-war to as low as 8% in conflict zones — while Yemen’s zero-dose figures climbed significantly, driven by instability, health service disruptions, and misinformation.

Conversely, Gavi-supported, low-income countries saw marked improvements, reducing un- and under-vaccinated cohorts by around 650,000 in 2024. Yet even high- and upper-middle-income economies are experiencing slippage, with measles coverage hovering at 84% (first dose) and 76% (second), below the 95% threshold needed for herd immunity. Consequently, measles outbreaks surged, with 60 countries reporting significant incidents in 2024, doubling since 2022.

Country case snapshots powerfully illustrate these trends. In Bosnia and Herzegovina, measles vaccination rates are at just 55%, compared to Croatia’s 90%, contributing to over 7,000 cases and two adolescent deaths, prompting WHO and UNICEF to urge intensified immunisation campaigns. In Pakistan, polio resurgence has occurred amid militant threats and disrupted campaigns, with over one million children missing doses in 2024. The government’s response includes large-scale vaccination drives and policy enforcement, such as arrest warrants, signalling both the challenge and political recognition of routine immunisation’s fragility. Meanwhile, Bangladesh has steadily expanded its vaccine schedule — adding Hib, rubella, PCV, IPV and MR2 — achieving DTP3 coverage around 93% and fully vaccinated rates near 84% by 2019.

These illustrations reveal both progress and vulnerability. Countries with strong political will, robust systems, and community trust — like Bangladesh — are managing gains. Others, like Pakistan and Bosnia, highlight how instability, mistrust, and misinformation can swiftly unravel public health gains.

The 2024 immunisation data reiterates an urgent message. Global coverage has stabilised and broadened, but millions of children remain vulnerable in conflict zones and complacent high-income settings. Measles outbreaks, polio flare-ups, diphtheria spikes, and new threats like RSV underscore that the progress we’ve made is neither permanent nor evenly shared. Unless we decisively fill funding gaps, fortify health delivery in emergencies, ensure vaccine equity, and strengthen trust, these vulnerabilities will deepen — and outbreaks will follow.

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Artificial Intelligence (AI) is rapidly reshaping public health — from enhancing disease surveillance and diagnostics to easing workforce burdens — but it also raises complex risks and ethical questions. In Europe and globally, public health leaders are grappling with how best to harness AI’s revolutionary potential while managing its pitfalls. After decades of experience, many recognise that AI is not a magic fix for health challenges; its value depends on thoughtful integration into health systems. This article provides an in-depth review of the current relationship between AI and public health. It examines the opportunities it offers, real-world innovations already underway, practical implementation challenges, and the risks and governance frameworks that must guide responsible use. All discussions equally consider European contexts (including emerging EU regulations) and broader global health perspectives.

TL;DR Summary

• AI’s growing role in health: Artificial intelligence is increasingly used to augment public health efforts — from automating administrative tasks to advanced disease surveillance and diagnostics — offering new ways to improve efficiency and reach.
• Tangible benefits observed: Early deployments show promising results. AI tools have reduced clinicians’ paperwork burden, flagged outbreaks days before traditional systems, and enhanced diagnosis in low-resource settings (e.g. catching 15% more TB cases via X-ray analysis).
• Innovations across sectors: NGOs, governments, and companies are all investing in AI for health. For example, PATH and others use AI in field programmes, the NHS has dozens of AI pilots improving care delivery, and pharma companies leverage AI to speed up drug and vaccine development.
• Practical hurdles remain: Successful implementation requires robust data infrastructure, interoperability, and high-quality data. Many health systems must modernise IT systems and address data silos and quality issues before AI can perform optimally.
• Human factors are critical: Integrating AI into workflows and gaining staff acceptance are significant challenges. Training health workers, providing explainable outputs, and maintaining human oversight are essential to building trust in AI-assisted care.
• Key risks to manage: AI in public health brings serious risks — privacy breaches, algorithmic bias harming disadvantaged groups, opaque “black box” decisions undermining trust, and AI-generated misinformation spreading false health advice. Over-reliance on AI without safeguards can also be dangerous.
• Ethics and governance frameworks: Clear principles and regulations are emerging to guide responsible AI use. WHO’s six ethical principles (e.g. transparency, equity, accountability) set value-based guardrails, while the EU’s AI Act will enforce strict requirements on high-risk health AI (mandating transparency, risk management, and human oversight).
• Collaboration and capacity-building: Effectively advancing AI in public health will require interdisciplinary collaboration (health experts with technologists), investment in workforce AI literacy, and inclusive approaches that involve LMICs and marginalised groups so benefits are shared widely.
• Continuous evaluation and adaptation: To ensure AI delivers on its promise, public health authorities must continually monitor outcomes, audit algorithms for bias or errors, and be ready to adjust or suspend systems if problems arise. Adaptive governance and ongoing community feedback are vital for safe, effective AI integration.
• Seizing the opportunity responsibly: When guided by ethical principles and strong oversight, AI can greatly strengthen public health, easing workforce burdens, expanding outreach, and providing data-driven insights. The next few years are crucial for implementing the policies, education, and trust-building measures that will allow AI to be a force for health equity and innovation rather than a source of new disparities or dangers.

Opportunities: Transforming Public Health with AI

AI is being deployed to alleviate several longstanding public health challenges. One significant opportunity is reducing clinician burnout and workforce shortages by automating routine tasks. For example, a 2024 survey found that 57% of physicians believe automating administrative burdens is the top opportunity for AI to ease workloads amid staff shortages. Machine learning systems can transcribe medical notes, pull up patient records, and handle scheduling or prescription refills — freeing clinicians to spend more time on patient care. Many doctors see such automation as a key to improving work efficiency and reducing stress, suggesting AI could help mitigate the healthcare burnout epidemic.

AI also offers powerful tools for disease surveillance and epidemic intelligence. Algorithms can continuously scan vast data sources — news reports, social media, travel data — to spot early signs of outbreaks far faster than traditional methods. Notably, the HealthMap and BlueDot platforms (which use natural language processing and machine learning) flagged the COVID-19 outbreak days before official alerts. By sifting through informal signals and anomalies, AI-driven systems can provide precious early warnings of emerging health threats. BlueDot’s AI surveillance tools have dramatically sped up outbreak detection, reducing manual scanning time by nearly 90% in some cases. Such early alerts enable public health agencies to mobilise quicker responses and potentially contain outbreaks before they spread.

Another area of opportunity is improving diagnostics and clinical decision support, especially in resource-constrained settings. AI image recognition has shown great promise in interpreting medical images like X-rays and retinal scans. For example, AI-based chest X-ray tools for tuberculosis (TB) are being used to help screen patients in low-resource areas that lack radiologists. A recent programme in India led by PATH found that an AI tool (qXR) boosted TB case detection by ~15.8% — identifying cases that human readers missed. Many countries are now utilising AI-assisted chest X-ray screening for TB, which can lead to earlier diagnosis and treatment in underserved communities. Beyond imaging, AI-powered diagnostic apps and chatbots can guide patients through symptom checks or flag high-risk cases for follow-up, expanding access to essential healthcare advice where clinicians are scarce.

Crucially, AI is also being enlisted to address climate-related health threats and environmental impacts on health. Public health researchers increasingly pair AI with climate data to predict disease patterns under changing environmental conditions. For instance, machine learning models can correlate weather patterns (temperature, rainfall) and even animal health data with disease outbreaks to anticipate risks in specific locations. By analysing such data, AI-driven predictive analytics can serve as early warning systems — forecasting surges in vector-borne diseases like malaria following heavy rains or heat-related illness during extreme heatwaves. This capability is ever more critical as climate change intensifies health hazards. AI can help public health officials prepare for climate-sensitive disease outbreaks, allocate resources proactively, and develop adaptation strategies to protect vulnerable populations.

Real-world Applications and Innovations

AI in public health is not just theoretical — numerous real-world initiatives by NGOs, governments, and private companies have already demonstrated its potential. Global health nonprofits and international agencies have been early adopters of AI to support their missions. For example, the Bill & Melinda Gates Foundation has invested heavily in AI-driven global health projects. In 2023, it awarded grants to nearly 50 pilot projects exploring AI solutions for health and development challenges — these range from AI-augmented diagnostic tools to data systems for disease surveillance in low-income settings.

One Gates-backed innovation is AI-assisted ultrasound: in 2020, a $44 million grant was given to develop an AI-guided portable ultrasound to improve lung disease diagnosis in low-resource countries (e.g. detecting pneumonia). Likewise, PATH and other NGOs are integrating AI into field programmes — as seen in the TB screening project, where an AI tool significantly increased case finding while illuminating practical deployment hurdles. These efforts by NGOs underscore AI’s promise to close gaps in healthcare access and quality for underserved populations.

Governments and public health agencies are also launching AI initiatives. In Europe, national health systems pilot AI to improve services and efficiency. For instance, the UK’s National Health Service (NHS) created an NHS AI Lab to fund and evaluate AI innovations in care delivery. By 2025, the NHS had over 80 AI projects live, targeting everything from optimising nurse rostering and predicting hospital bed occupancy to speeding up radiology workflows.

One NHS program provided £100+ million in awards to develop AI for earlier cancer detection, resource management, and patient safety improvements. The NHS AI Lab’s “Skunkworks” team has run short-term projects that yielded practical tools — e.g. an algorithm to streamline the placement of nurses across wards and a natural language processing engine to search health records more efficiently. Meanwhile, European public health agencies are leveraging AI for epidemiology; the European Centre for Disease Prevention and Control (ECDC) has incorporated systems like BlueDot’s AI to enhance epidemic intelligence, including monitoring outbreaks during events such as the 2020 Olympics. These government-led efforts illustrate growing public sector commitment to deploying AI for health system strengthening and emergency preparedness.

The private sector, particularly in healthcare and pharmaceuticals, is likewise driving innovation at the intersection of AI and public health. Pharmaceutical companies now routinely use AI in drug discovery and development. For example, Novartis recently struck a wide-ranging partnership (worth up to $1 billion) to use a generative AI platform for designing new protein-based therapies — aiming to accelerate the search for novel disease treatments. GSK has also embraced AI to speed up R&D: its CEO noted that AI modelling helped cut two years off an RSV vaccine trial by predicting where outbreaks would occur and optimising trial site selection. This led to the faster development of the world’s first RSV vaccine, an essential public health breakthrough.

Beyond pharma, medical technology firms are integrating AI into devices, from smart wearables that flag irregular heart rhythms to imaging systems where AI assists in analysing scans for early signs of cancer. Startups and tech companies are introducing AI-driven health apps and chatbots (such as symptom checkers and mental health conversational agents), which some health services in Europe are trialling for patient triage and support. These real-world examples underscore that AI is already deeply enmeshed in the health ecosystem — from global disease surveillance networks to hospital wards and R&D labs — delivering innovations that could improve population health outcomes.

Practicalities and Implementation Challenges

While the potential is immense, implementing AI in public health is a pragmatic challenge. Infrastructure and data interoperability are foundational hurdles. Effective AI requires robust digital infrastructure — high-quality data streams, electronic health records, and cloud computing capacity — which many health systems lack, especially in low-resource settings. Data needed for public health AI often reside in silos or incompatible formats across hospitals, labs, and agencies. Poor interoperability means AI tools struggle to aggregate and interpret information from disparate sources. Bridging these gaps will require significant investment in health information systems, common data standards, and connectivity. Encouragingly, current AI technology can assist in standardising and mapping messy health datasets to make them more usable. Nonetheless, without reliable infrastructure and data-sharing frameworks, even the best AI algorithms cannot deliver consistent results across a public health network.

A related challenge is data quality and representativeness. AI models are only as good as the data they learn from, and health data can be incomplete, biased, or unrepresentative of specific populations. Studies highlight issues like variability in how data are recorded, large amounts of unstructured text, missing information, and coverage bias (e.g. most training data coming from high-income populations).

These factors can undermine an AI system’s accuracy and value to end users. Developing good AI for health requires carefully cleaning and curating data to reflect clinical reality. For instance, algorithms trained only on European hospital data may perform poorly in rural African communities. Implementers must thus invest effort in data preparation and continuously monitor model outputs for anomalies. Establishing metadata standards, common terminologies, and data quality metrics can facilitate better AI development. Additionally, clarity on data ownership and governance is needed: questions about who “owns” health data (patients, providers, governments?) affect how data can be integrated for AI. Resolving these issues through policies and trust frameworks is key to unlocking data for public health AI while respecting privacy and rights.

Another practical consideration is integrating AI tools into healthcare workflows and gaining workforce acceptance. Introducing AI decision-support systems or automation in clinics requires adapting processes and training staff. Health workers may be understandably cautious — some lack familiarity with AI, worry about accuracy, or fear being displaced. Clear protocols are needed if an AI system’s recommendation conflicts with clinical judgment. Early experience shows that human-AI collaboration works best when AI is framed as an assistive tool rather than a professional replacement. Building trust among the workforce involves providing explainable outputs and demonstrating reliability in pilot phases. It also means training clinicians in basic AI concepts and ensuring they feel confident interpreting AI outputs.

Successful deployments (like the PATH TB screening program) emphasise that significant workflow integration and training efforts are required. In that program, implementers had to solve issues of installing the software in clinics, securing internet connectivity for the AI, and ensuring staff could effectively use the AI results within their screening workflow. Without such groundwork, even a high-performing algorithm might sit on the shelf unused. Thus, the human element is crucial: public health organisations must engage and educate their workforce, adjusting roles and processes so that AI enhances rather than disrupts care delivery. Over time, as clinicians see AI reducing drudgery (e.g. auto-filling forms) and improving outcomes, their acceptance tends to grow. Indeed, physician enthusiasm for health AI has been rising year-on-year. Patience and iterative refinement are needed to blend AI smoothly into the complex fabric of health systems.

Risks and Concerns of AI in Public Health

Despite the optimism, it is vital to acknowledge the risks and potential harms associated with AI in public health. Data privacy and security tops the list of concerns. AI systems often require large datasets of patient information, raising the stakes for protecting sensitive personal health data. Any breach or misuse of such data can erode public trust and violate individuals’ rights. There is also the risk of “function creep”, where data collected for health purposes might be used in other ways (for example, a COVID-19 contact tracing app’s data later being used for law enforcement — a scenario that drew criticism in some countries). Moreover, complex AI models could inadvertently leak private details — for instance, a model might be reverse-engineered to reveal records it was trained on. Ensuring robust cybersecurity and strict data governance is therefore paramount. Many call for comprehensive privacy safeguards and compliance with regulations like Europe’s GDPR whenever AI handles health data. Techniques such as anonymisation or synthetic data can help, but they are not foolproof (even de-identified data can sometimes be unidentified).

The bottom line: without public confidence that AI will maintain confidentiality and data security, its benefits will be lost. Public health agencies must be transparent about what data are used and how to obtain informed consent where appropriate and implement state-of-the-art security measures to prevent breaches. Privacy isn’t just a legal box to tick — it’s fundamental to preserving the trust on which public health interventions depend.

Another significant risk is algorithmic bias and the exacerbation of health inequalities. AI systems can unintentionally perpetuate or even worsen disparities if their design is not carefully managed. This was starkly illustrated by a widely used healthcare risk algorithm in the United States that was found to be racially biased. The algorithm helped determine access to extra care programs and used healthcare cost as a proxy for need. This choice systematically underestimated the needs of Black patients (who often had lower healthcare expenditures due to access barriers). As a result, many high-risk Black patients were less likely to be flagged for additional care, denying them the resources they needed. This example shows how bias in data or design can translate into inequitable outcomes: the AI effectively discriminates against a vulnerable group. Similar issues could arise in public health if an AI model is trained on predominantly male patients under-detect conditions in women or if disease surveillance AI better covers wealthier communities with more data. AI could widen gaps if not addressed, with marginalised populations benefiting the least or even being harmed.

Equity must be a central design principle to counter this: datasets should be diverse and inclusive, algorithms should be tested for bias, and bias mitigation strategies (like reweighing data or algorithmic fairness adjustments) should be applied. The WHO explicitly highlights inclusiveness and equity as core ethical principles for AI, ensuring that AI tools work for all segments of society regardless of race, gender, income, or other characteristics. Ultimately, careful governance and auditing of AI systems are needed to avoid encoding systemic biases into digital form and instead use AI to reduce health inequities (for example, by targeting interventions to underserved areas).

A further concern is the lack of transparency (“black box” issue) and its impact on trust and safety. Many AI models, especially deep learning networks, operate as complex black boxes — they do not explain their reasoning in human-understandable terms. In healthcare, this opacity is problematic. Clinicians and public health decision-makers are wary of acting based on a recommendation they don’t understand, particularly if an AI’s advice contradicts intuition or standard practice. Unexplainable AI can also undermine accountability: if an AI makes a harmful mistake, it may be unclear why it happened or who is responsible. This lack of transparency feeds directly into trust issues among professionals and the public. If people perceive AI as a mysterious, untrustworthy “magic wand” imposed on health decisions, they may reject its use. There have been cautionary tales: an AI system deployed in hospitals to predict which COVID-19 patients would need ICU care was later found to underperform because it hadn’t been adequately validated. Clinicians grew sceptical of its risk scores.

To prevent such scenarios, experts call for explainable and interpretable AI in health — algorithms that can provide reasons for their predictions or use transparent, logical rules where possible. At a minimum, users should have access to information about how an AI was developed and its known limitations. Regulatory frameworks like the EU AI Act are likely to mandate a degree of transparency for high-risk AI (including many medical applications) precisely to bolster trust and enable oversight. Building more explainability into AI models remains a technical challenge, but one that is essential for aligning with the principles of transparency and accountability in healthcare.

In the age of ChatGPT and generative AI, misinformation and “AI hallucinations” have emerged as new public health risks. Advanced chatbots can produce remarkably human-like answers to questions — but they do not guarantee factual accuracy. They can hallucinate false information, confidently output incorrect medical advice, nonexistent statistics, or even fake health news. The potential for harm is considerable if the public uses such tools for health information. There is concern that AI chatbots could magnify the health misinformation problem exponentially — for instance, by generating convincing anti-vaccine narratives or spurious cures, which then spread on social media.

In recent years, public health agencies have struggled to combat misinformation (for example, false claims about vaccines or COVID-19 treatments that undermine uptake). The rise of AI-driven content generators and deepfakes only fuels this fire. Misinformation undermines public trust and can lead people to reject proven interventions in favour of dangerous alternatives. Tackling this will require new strategies — such as watermarking AI-generated content, strengthening content moderation, and improving digital health literacy so the public can better discern credible information. On the flip side, public health communicators might also leverage AI to fight misinformation (for example, using AI to detect false rumours early or personalise accurate health messages). Regardless, the advent of easy, AI-generated disinformation is a serious risk factor that the global health community cannot ignore.

Finally, there is the risk of over-reliance and systemic dependency on AI. If health systems come to depend on AI for critical functions without adequate safeguards, any failures in the technology could have severe consequences. For example, an AI model might perform well in normal conditions but fail to generalise during an unexpected scenario. If everyone has come to rely on its output, they may miss the warning signs until too late. Moreover, heavy reliance on automation might erode human skills over time (a phenomenon observed in other industries). In healthcare, this raises concerns about “deskilling” — clinicians might lose practice in specific tasks (like reading x-rays or making complex diagnoses) if those are always handled by AI, leaving them less prepared to step in when needed.

Over-reliance can also dull vigilance: users might stop double-checking results if an algorithm usually works well so that an undetected error could propagate. The key is to maintain a human-in-the-loop approach: AI should support, not replace, human expertise. Mechanisms for human review of AI outputs and fallback plans in case of system outages are essential.

Additionally, performing regular audits and updates of AI models can prevent performance from degrading unnoticed. In summary, while AI can increase efficiency, public health systems must guard against blindly relying on algorithms. A balanced approach that values human judgment and institutional memory, alongside AI’s computational power, will be safest in the long run.

Ethical and Regulatory Frameworks

Addressing the above risks requires robust ethical guidelines and regulatory oversight for AI in health. Globally, there is growing consensus on core ethical principles that should govern AI development and use in public health. The World Health Organization’s landmark 2021 report laid out six guiding principles for ethical AI in health: (1) Protect human autonomy — humans should remain in control of health decisions, with informed consent and respect for privacy; (2) Promote human well-being and safety — AI must be safe, effective, and designed to improve health outcomes; (3) Ensure transparency, explainability and intelligibility — stakeholders should have sufficient information about how AI systems work and decisions should be traceable; (4) Foster responsibility and accountability — developers and users are accountable for AI behaviour, and mechanisms for redress must exist; (5) Ensure inclusiveness and equity — AI should benefit all groups, enhancing fairness and not amplifying disparities; and (6) Promote AI that is responsive and sustainable — meaning AI should be adaptable, monitored, and designed for long-term societal benefit.

These principles, while high-level, provide a value framework to guide everything from design choices (e.g. using diverse training data to ensure equity) to deployment (e.g. always keeping a human in the loop to protect autonomy). Public health organisations are increasingly adopting such ethical frameworks. For instance, the WHO urges that AI deployments be accompanied by community engagement, training for health workers, and continuous evaluation to ensure technologies remain aligned with the public interest. The ethos is straightforward: AI must be people-centred and uphold human rights. Ethics committees or advisory boards can help oversee AI projects, reviewing them for compliance with these principles before they scale up.

On the regulatory front, governments are now moving to establish formal rules for AI in healthcare. The European Union’s AI Act is a pioneering example of comprehensive regulation. Passed in 2024, the EU AI Act takes a risk-based approach, classifying AI systems by risk level and imposing requirements accordingly. Health-related AI is generally deemed “high-risk” under this law, given its potential impact on people’s lives and rights. High-risk AI systems (including most AI used for medical diagnostics, decision support, or resource allocation in health) will face strict obligations. These include rigorous standards for transparency, risk management, and human oversight. For instance, developers of a clinical AI tool must implement a quality management system, ensure their model is trained on appropriate data, and provide documentation detailing the AI’s function and limitations. They must also conduct risk assessments and put in place human oversight measures to prevent automation bias. Notably, the EU AI Act doesn’t just apply to creators of AI — it also holds deployers (such as hospitals or public health agencies) accountable for the safe use of AI.

Health providers must monitor AI system performance, keep logs, and retain ultimate responsibility for decisions (clinicians must have the authority to override AI recommendations if needed). These provisions aim to ensure that human accountability and patient safety remain paramount even as AI becomes embedded in care delivery. Additionally, the Act has a broad reach: any AI system impacting people in Europe must comply, even if developed elsewhere. This could set an effective global benchmark as companies worldwide adjust their practices to meet the EU’s requirements.

Other jurisdictions are also crafting guidelines. The United States, through the FDA, has been evolving its regulatory approach for AI/ML-based medical devices, focusing on premarket evaluation and the idea of “continuously learning” algorithms needing ongoing monitoring. International bodies like the WHO have issued guidance and urged governance innovation, suggesting that governments update regulations to cover AI, establish certification processes, and possibly create registries of approved AI health products. We also see emerging governance models such as algorithmic impact assessments (to evaluate a health AI system’s potential societal impact before deployment) and independent reviewers’ bias audits. In some health systems, procurement of AI now requires meeting ethical checklists or obtaining approval from institutional review boards, similar to new medical interventions.

These steps are part of building a “responsible innovation” culture around AI, encouraging experimentation and advancement, but within guardrails that protect individuals and communities. Multi-stakeholder collaboration is key here — regulators, technologists, health professionals, and patient representatives need to work together to define safe and effective AI in practice and update those definitions as the technology evolves. As one example, the NHS AI Lab in the UK partnered with regulators to create a sandbox for AI developers, guiding them on navigating regulatory pathways and using synthetic data for testing. Such efforts show that with thoughtful governance, innovation and safety can advance hand in hand.

Future Directions and Recommendations

To fully realise AI’s promise in public health while minimising its downsides, several changes and strategic efforts are needed going forward:

• Investing in data and digital infrastructure: Health systems, especially in low- and middle-income countries, need support to build the data foundations for AI. This means digitising health records, improving data quality, and ensuring platform interoperability. Governments and global donors should prioritise funding for health information systems and broadband connectivity as part of public health capacity building. Better data infrastructure not only enables AI — it strengthens health systems overall. Innovative approaches like federated learning (where AI models train on distributed data without moving it) could be scaled to allow resource-constrained regions to benefit from AI insights without breaching privacy. The goal is to create a world where data flows securely and efficiently to wherever it can improve health outcomes.
• Strengthening workforce capacity and AI literacy: As AI becomes a standard tool, public health and healthcare workers must be equipped to use and oversee it. Training programmes are needed to raise AI literacy among the health workforce, including understanding AI’s capabilities and limitations. This may involve updating medical and public health curricula to cover data science basics. Additionally, new specialist roles (such as clinical AI safety officers or epidemiologists with AI expertise) could be developed to bridge the gap between tech and health domains. Frontline staff should be engaged in co-designing AI solutions so that tools are user-friendly and address actual pain points. When health workers understand and trust AI, they can become champions for its adoption and serve as critical watchdogs who notice when something isn’t right. Fostering a culture of continuous human oversight and feedback will ensure that AI remains a servant to health professionals, not a black box dictator.
• Ensuring inclusivity and equity in AI advancement: The global health community must actively work to prevent a digital divide in AI. Much cutting-edge AI development is concentrated in wealthier countries and tech companies. Deliberate efforts are needed to include researchers and perspectives from low- and middle-income countries in AI design so that solutions address diverse needs. This could consist of research funding earmarked for LMIC-led AI projects, technology transfer programs, and south-south collaboration on AI for health. Moreover, data from underrepresented populations should be collected (with consent and protection) to improve algorithms’ relevance in those settings. By democratising AI knowledge and resources, we can avoid a scenario where only certain countries or communities benefit from AI while others are left behind or subject to unchecked harm. Equity considerations should also extend to gender, age, and other demographics — for instance, ensuring women and minority groups are included in AI development teams and that tools serve users of different languages and literacy levels. An inclusive approach will make AI tools fairer and enlarge the talent pool working on creative AI solutions for entrenched public health challenges.
• Fostering collaboration between public health and technology sectors: Effective AI in public health sits at the intersection of epidemiology, medicine, data science, and engineering. No single sector can do it alone. We need stronger partnerships: governments linking with academia and tech firms, NGOs working with startups, and international agencies convening multi-sector consortia for global health AI initiatives. Such collaboration can accelerate innovation and ensure that public health priorities guide technological development (and vice versa, that technologists are aware of on-the-ground needs). For example, a partnership between a national health ministry and AI researchers might focus on building an early warning system for malaria outbreaks, combining epidemiological expertise with cutting-edge modelling. A pharmaceutical company could also collaborate with global health organisations to use AI in vaccine R&D for diseases of poverty. These cross-sector collaborations should be underpinned by fair agreements (e.g. around data sharing or intellectual property) so that all parties benefit and trust is maintained. The complexity of health + AI demands breaking down silos. International forums and networks can play a role here, enabling countries to share best practices and lessons learned (e.g. how one country successfully regulated an AI symptom-checker or how another trained health workers on AI). Since pathogens do not respect borders, a collaborative global approach to AI-enhanced public health security is in everyone’s interest.
• Adaptive governance and continuous evaluation: As AI tools roll out, it is critical to monitor their real-world impact and be ready to adjust course. Public health authorities should implement mechanisms to continuously evaluate AI interventions — collecting data on their accuracy, outcomes, and any unintended effects. Are the predictions helping improve disease control? Is a triage algorithm safely directing patients to the right level of care? This requires establishing key performance indicators and perhaps creating independent evaluation units. When problems are identified (such as an AI starting to drift in accuracy due to changes in data), there should be processes to update or pull back the tool until fixes are in place. Regulation must also remain adaptive; rigid rules could stifle innovation or become outdated as technology advances. One idea is regulatory sandboxes where new AI solutions can be tested under supervision, allowing regulators to learn and guidelines to evolve. Governance models should be proactive yet flexible, emphasising learning and iteration. Importantly, communities and civil society should have a voice in evaluating AI in public health — their feedback on whether these tools are culturally acceptable, understandable, and improving services is invaluable. Responsible AI is not a one-time certification but an ongoing commitment to quality and ethics throughout the technology’s lifecycle.

Looking ahead, it is clear that AI will play an expanding role in public health — whether in combating the next pandemic, extending healthcare to remote villages via smart apps, or analysing big data to pinpoint disease drivers. The revolution is already underway, but its trajectory depends on our current choices. With enlightened leadership, adequate safeguards, and inclusive collaboration, AI could usher in significant public health gains — from more efficient health systems to healthier communities worldwide. However, if we ignore the risks — allowing unchecked use, widening inequities, or losing the human touch in care — the potential benefits could unravel, and public trust could be irrevocably lost. The coming years are thus pivotal. Armed with decades of hard-won experience, public health professionals have a key role in steering this journey. By insisting on evidence, equity, transparency, and community engagement, they can ensure that the AI revolution in health truly becomes a boon and not a threat. The opportunity is immense, but so is the responsibility to guide AI’s integration into public health thoughtfully and ethically.

The post AI in Public Health: Revolution, Risk and Opportunity appeared first on Medika Life.

Panellists included Marion Gruber from IAVI, Marco Cavaleri from the European Medicines Agency, Hanna Nohynek from the National Institute for Health and Welfare, and Thomas Waite, the UK’s Deputy Chief Medical Officer. Through rich discussion, the panel underscored the importance of transparency, innovation, and public engagement in fostering vaccine confidence and uptake.

Misinformation and Trust in Vaccination

The conversation opened with Marco Cavaleri, who was reflecting on lessons from COVID-19. “To increase vaccine uptake, we need to rebuild trust,” he stated, adding that misinformation spread rapidly during the pandemic, leaving an “unfortunate, traumatic impact on public perception.” Cavaleri emphasised the role of regulators and public health authorities in maintaining “transparency about scientific data” and advocated engaging directly with citizens through modern communication channels, particularly social media, to counter misinformation.

Echoing this, Thomas Waite observed that while misinformation could be corrected through transparent education, disinformation posed a unique challenge due to its intentionally deceptive nature. “Engaging with disinformation on its terms is counterproductive,” he said, urging a clear communication approach firmly grounded in accurate, science-based information.

Transparency and Data Quality

Transparency emerged as a central pillar, with panellists stressing that open data and easy access to vaccination information play a vital role in public confidence. Hanna Nohynek spoke of Finland’s experience during COVID-19, where adverse events were reported in real time. This allowed the public to “see transparency in action,” building a stronger foundation of trust. Waite highlighted a similar approach in the UK, noting that the UK Health Security Agency’s data dashboard became a heavily used public resource, promoting transparency and providing real-time flu, RSV, and COVID-19 vaccination statistics.

Innovation and Access: Meeting New Vaccine Demands

The global vaccine pipeline is evolving rapidly, with innovations designed to address threats like respiratory diseases, antimicrobial resistance, and climate-related health impacts. Gruber remarked, “We are seeing new infectious diseases entering the northern hemisphere due to climate change, adding urgency to our need for innovative vaccines.” The conversation also spotlighted AMR (antimicrobial resistance), with Gruber discussing the advanced stages of tuberculosis vaccines. “AMR vaccines could be transformative in curbing resistance,” she added.

This innovation surge, however, brings challenges of its own. Waite noted that in the UK, “The immunisation schedule has become significantly more complex.” With the increase in adult vaccinations, including RSV, flu, shingles, and COVID-19, the programme now requires substantial public outreach to explain why vaccination remains crucial at each life stage. Gruber and Nohynek stressed that effective public engagement and education are essential to ensure uptake keeps pace with scientific advancements.

Bridging Health Inequities: Expanding Vaccine Access

Discussing global disparities, Nohynek raised the importance of equitable vaccine access, particularly for low- and middle-income countries. As she explained, the WHO’s Strategic Advisory Group of Experts (SAGE) has prioritised maternal vaccination for RSV in these regions. However, she pointed out gaps in clinical trials across continents, noting, “The absence of data from Asia, especially given high prematurity rates, underscores the need for global representation in trials.”

Gruber cited Argentina’s success with maternal RSV vaccinations as a promising case study. Argentina’s approach — a blend of government support, accessible vaccination points, and educational outreach — yielded 57% coverage in the first season. “Political will and cross-sector collaboration were key to this success,” she said, adding that lessons from Argentina could be instrumental as RSV vaccines roll out across Africa.

Economic Challenges and Prioritisation

Sibilia Quilici closed the panel by addressing the economic dimension of vaccine rollout. She argued for an economic perspective on immunisation, explaining that “vaccination is not just a health intervention but a key driver of societal and economic growth.” Nohynek highlighted the challenges her institution in Finland faces due to budget cuts, which she described as “counterproductive,” noting that restrictions on funding can hamper efforts to evaluate and introduce new vaccines effectively.

Cavaleri reinforced the need for a streamlined approach, remarking, “We need to integrate the vaccine approval process with recommendation systems to reduce the lag time. Six years from authorisation to patient arms is simply too long.”

The Path Forward: Building Resilient Immunisation Systems

The panel concluded with a unified call for increased transparency, streamlined regulatory frameworks, and sustained investment in vaccination programmes. Waite summarised the vision: “Advances in technology should make it easier for citizens to get vaccinated while service providers adapt to meet the needs of modern lifestyles.” Gruber echoed his sentiment, noting that “infections affect us all,” underscoring the importance of making vaccines accessible across diverse populations.

The panel’s insights ultimately emphasised that immunisation strategies must adapt to sustain progress, integrating public trust, technological advancements, and economic considerations. The panellists agreed that by addressing the challenges head-on, we can ensure vaccines continue to protect and empower communities globally.

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First, the guidance itself removes a specific reference to COVID-19 and groups it together with other respiratory viruses, such as influenza and RSV. This, in and of itself, is a significant change. And the new guidance says that if you do not have a fever for 24 hours and are feeling better, you do not have to isolate for five days and can continue normal activities.

As far as I’m concerned, this is a big deal. In many settings, especially in healthcare settings, if one or more staff members have to isolate at home for five days if they test positive for Covid, this can cause significant staffing difficulties. Now, the CDC finally recognizes that common sense needs to prevail.

That common sense includes the fact that, if you are sick, you need to stay home. This is true whether it is the flu, Covid, RSV, or any other illness. Once you’re feeling better, then you can resume normal activities.

Now, it is true that Covid can spread to other people even if the carrier does not have any symptoms. And so, again, common sense needs to prevail: if you are around people who are at high risk for severe illness with Covid, you should wear a mask around them. And, when you are sick, you should stay away from them completely. This is proper “virus etiquette” that more of us need to develop. It is the same as coughing or sneezing into one’s elbow.

The reason I am so excited about this change is because, today, the COVID-19 virus is a completely different pathogen. In the very beginning, COVID-19 caused severe illness in a great number of people. In the United States, it killed over 1 million people. That is a lot. I myself came down with COVID-19 in November 2020, and I have never had a viral illness like that one. It was unlike anything I have ever experienced. Now, however, for many people, COVID-19 is simply a bad cold.

It has been several months, if not years, that I have seen a life-threatening case of Covid ARDS in my ICU. Recently, I had a patient who tested positive for Covid and had severe lung infiltrates. It turns out that those were due to severe heart failure and not Covid. In fact, many of the patients we see in the hospital with Covid have other conditions that brought them in, and the Covid was simply a bystander.

That said, this does not mean that Covid cannot cause severe illness at all. The elderly, the frail and weak, and those with compromised immune systems are still at high risk for life-threatening illness, even with the current variant of Covid. They, of course, need to remain vigilant and careful. And those of us who are not at high-risk need to be cognizant of this and, again, have proper virus etiquette.

All of this having been said, this is a great change. I disagree with the those who say that this new guidance will make people dismiss Covid as a significant disease. People have already moved beyond Covid, and this is because the COVID-19 of 2024 is substantially different than the COVID-19 of 2020. This is reality, and I am very happy that the CDC has finally acknowledged this reality.

Listen to the podcast episode about this article.

The post It’s About Time: CDC Changes COVID Isolation Guidelines appeared first on Medika Life.

I often wonder how much walking I need to do to combat the blues. It turns out that even small volume increases in physical activity can reduce your depression risk or symptoms.

A new research study demonstrates that even small increases in physical activity can reduce your risk or symptoms of depression.

“Mental pain is less dramatic than physical pain, but it is more common and also more hard to bear. The frequent attempt to conceal mental pain increases the burden: it is easier to say, “My tooth is aching” than to say, “My heart is broken.” ― C.S. Lewis, The Problem of Pain.

Let’s briefly look at how movement can help us feel better. First, though, let’s pivot to the origins of the word “blues.”

The Blues

African Americans created the blues, a secular folk music, in the early 1900s, primarily in the American South.

Although instrumental accompaniment is nearly universal in the blues, it is essentially a vocal form.

Blues songs are usually lyrical rather than narrative because expressing feelings is foremost.

As a musical style, the blues is characterized by expressive “microtonal” pitch inflections (blue notes), a three-line textual stanza of the form AAB, and a 12-measure form.

Initial Use of “Blues”

But we need to go back to find the initial use of the term blues.

In the 1800s, the English phrase “blue devils” meant upsetting hallucinations precipitated by severe alcohol withdrawal.

“Blue devils” was later shortened to the blues, describing states of depression and upset.

Now that you have kindly indulged me in exploring the origin of the term “blues,” let’s move on to the new research findings.

The Mood-Boosting Minimum

I always feel better after walking for 30 minutes during my lunch hour. Could this be enough to provide a mood boost?

Scientists recently analyzed over 4000 individuals in the Republic of Ireland over a decade. The subjects were at least 50 years old.

The researchers wanted to know the minimal dose of moderate to vigorous physical activity (MVPA) associated with a reduced risk of depression and depressive symptoms in older adults with and without chronic disease.

Key Findings

Can you walk your way to a better mood? The answer is yes, and with fewer steps than you might think.

Researchers from the University of Limerick and Trinity College Dublin discovered the following:

A physical activity dose equivalent to 20 minutes a day (five days a week) of moderate-intensity physical activity, like brisk walking, was linked with less risk of depressive symptoms and odds of major depression.

About 400 MET minutes (MET = metabolic equivalent task) — about 100 minutes of low-intensity exercise (think a walk) or approximately 50 minutes of moderate-intensity exercise — provides significant mind protection.

Moreover, the more exercise you perform, the less likely you are to experience depressive symptoms. But you begin to accrue benefits with very little physical activity.

The presence of chronic disease did not affect the findings.

Dose-Response Curve

The investigators discovered a dose-response relationship between exercise volume and the risk of depression.

More moderate-to-vigorous physical activity was linked to greater depression protection.

Thirty minutes of exercise was associated with a small (seven percent relative risk reduction) improvement in the chances of developing depressive symptoms. However, the odds of major depression dropped by nearly one-half (44 percent).

Doses equivalent to 60 minutes daily of physical activity were associated with a 16 percent lower chance of depressive symptoms and 41 percent lower odds of major depression.

Finally, those getting 120 minutes of daily exercise were linked to a 23 percent lower probability of depressive symptoms and a halving (49 percent) of the odds of major depression.

Study Details

The team used ten years of Irish Longitudinal Study On Ageing data.

The scientists analyzed more than 4,000 older individuals over ten years.

The database included information on depression, moderate-to-vigorous physical activity, and other key health-related variables such as disease, lifestyle factors, and socio-economic status.

They controlled for health-related factors, including age, biological sex, alcohol and smoking use, obesity, and antidepressant use.

My Take

There is growing evidence that physical activity promotes neuroplasticity, your brain’s ability to adapt and reprogram.

Many depressed individuals have psychological inflexibility, which occurs when they get stuck in a feedback loop of negative thoughts and emotions.

Exercise, and you may re-route neural pathways. The result? More positive emotions, improved stress resilience, and less anxiety.

Physical activity at lower doses than World Health Organization recommendations for health appears to offer protection against depressive symptoms and Major Depression.

Aim for 20 minutes daily of moderate-intensity activity at least five days per week. Do more to get even more benefits.

Do you feel better after a short bout of exercise?

The post Unleash the Happy Hormones: The Surprising Magic of Just 2 Hours a Week to Beat the Blues appeared first on Medika Life.

In an effort to get ahead of a potential tripledemic this winter of COVID-19, flu, and RSV that could overwhelm hospitals, health officials have re-booted an important program: making COVID test kits free again. Those kits will be available by mail to households starting September 25.

Next comes the hard part: convincing enough people to get the kits and then persuading them to follow quarantine guidelines if they or their family members get sick.

This is not the time to roll out stale messaging delivered by a carousel of health officials trying to convince the public to get the test kits. Americans are weary of being told to keep their guard up against a disease that many view as more of an inconvenience than a threat. If the sales pitch to get the kits is off, health officials may find that the test kits no longer serve as an effective public health tool. Instead, they could become another partisan symbol of perceived government overreach, further impeding people’s freedom to live as they want.

In short, we have a messaging challenge ahead of us, and if we haven’t taken to heart the lessons learned during the worst early days of the pandemic, we’re doomed to repeat mistakes that cost lives.

How can we be more thoughtful about containing COVID and other dangerous diseases? To generate greater public compliance for fighting an endemic disease, communicators must provide a credible and compelling case of the risk of inaction and convince people that ignorance – of not knowing your infection status – is greater than the cost of knowing. These can be very high bars to clear since people have different thresholds for risk and for being informed.

It’s likely we won’t clear those hurdles with the roll-out of the free test kits. Because the perceived risk of COVID-19 infection and severity is low, many people have adopted a “no test, no stress” attitude, especially in light of the potential personal disruption that COVID infection causes. It’s a dangerous direction and one of the reasons why we will continue to see cases spike.

For communicators to overcome the twin challenges of infection risk perception and status aversion, they must use convert communicators – people who are credible to specific audiences and have changed their views to support disease intervention. There is mounting data showing that people who identified as Republicans were far likelier to get infected by COVID and die from the disease than those from left-leaning political parties. Messaging that taps into this research could point to breaking through to these audiences.

Successful public health interventions rely on a strong majority of the population participating in disease mitigation efforts, which means spotlighting conservative voters who see the value of COVID testing and can serve as credible messengers to similarly ideologically inclined individuals. This is where digital storytelling, data visualization and engagement of champions outside of the health sector can be potent measures to build the case for supporting new public health tools.   

It is also important to truly understand the pain points that different audience segments cite as reasons for not wanting to know their infection status and to provide targeted counterpoints. Most people can’t afford to miss work, even with a mild case, and families can be heavily impacted when a parent must choose between going to work or keeping their kids home. In these and other scenarios, the test result becomes the thing people may begin to dread more than the disease itself.

To ensure that people do not feel like they must choose between a host of the least bad options when COVID comes to their home, the government must consider new incentives for reporting positive test results and adhering to public health guidelines. These can range from reinstituting protected sick leave that was available as part of the Families First Coronavirus Response Act (FFCRA) during the pandemic to encouraging more employers to use the tax credits available through the American Recovery Plan Act (ARPA) to reimburse for employee sick leave. Without putting these and other options on the table, people will feel penalized even when they do the right thing.

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As a fetus, Charlie endured hearing his mother gasp for life during three heroin overdoses, heard the constant fighting and screaming between his birth mother and my son, endured severe malnutrition second to his parents’ homelessness, felt the poisonous effects of multiple substance abuse, and was the victim of the subsequent, injurious, powerful negative stress hormones pulsing through his mother’s veins.

The Origin Of A New Trauma-related Diagnosis

Addiction and overdose result in deep shame, guilt, and fear for persons suffering from addiction.

Most addicts report a heavy burden of anger and disgust for themselves for their addicted state. Subsequently, they acknowledge an absence of self-worth, which perpetuates hopelessness, low initiative for self-care, and an outward disregard for their lives and health as a way to offset dealing with the deep trauma roots of addiction.

A drug-addicted lifestyle is harder on the soul and body of an addict than on the people who love them, although family and friends suffer inexplicably living with and observing a loved one’s addiction.

However, there is a significant other victim of addiction who is most often never even acknowledged until the damage done to them is permanent. This person receives every spiritual, psychological, and physical impairment that the person in addiction experiences in active addiction and overdoses, but is incapable of processing or recovering from the events.

These lives helplessly experience repetitive, excessive drug use, and very often, overdose, in their body and mind. They can not escape the experiences or the source of those experiences and are unable to tell anyone or ask for protection from the effects of another’s drug abuse.

This is because they are not yet born.

How Excessive Prenatal Exposure To Drugs and Overdose Physiologically Affect A Newborn:

An addict’s excessive drug use is an overt sign of self-rejection. The user may not perceive initially that this is an originating factor of their addiction because there are many other valid facets to addiction.

However, a tragic consequence of addiction-related self-rejection is the destruction of innocence, both of the using individual and of any child growing in the womb of a pregnant addict.

A fetus has every capability to perceive love, affection, and its hopeful birth as it does to receive the innate rejection, disregard, and neglectful abuse occurring in substance abuse overdoses and drug abuse during its womb experience.

What transpires physically to the child through the onslaught of poisonous substances in-utero creates the intrinsic knowledge or perception that it is unwanted, alienable, and dismissible as being worthy of concern and love.

This is how addictive drug use causes any addict to feel. This deep trauma belief is transferred to the unborn through brain synapses, hormones, and the connective spirituality between mother and child.

My own grandson has been born from a severely multi-substance exposed pregnancy. Once home from the NICU, this tiny human being wore the look of the sadness and devastation of his intra-uterine experience in his countenance. I had never seen anything like it. It scared me to the core.

My experience with the result of a loved one’s addiction leads me to educate readers on the tragedies of prenatal opioid and substance abuse.

In my work as a NICU nurse, what always struck me about our “drug babies” was their direct inability to readily accept the human touch. I recognized that although sensory and neurological issues were a major component of that born trait, the inability to want or accept human touch was also resultant of the prenatal rejection occurring through pregnancy drug use and overdose.

They would grimace from touch first, as it appeared to hurt. Watching a new child recoil from another human being’s affection is heartbreaking.

An initial diagnosis of NAS or NOWS is not the separative long-term condition that these children go home with. Most NAS symptoms, some of which initially coincide with PORS symptoms, dissipate after several few weeks.

Most times, these babies were discharged home screaming, red-faced, uncomfortable, and heavily medicated. Their parent(s) would never have the patience and wherewithal to care for them, while still in active addiction or early recovery.

These children begin their fragile lives with both a biological and physical understanding/belief that life is pain, an intrinsic search to end that pain (which becomes a future central focus of existence), an inability to independently stop the physical and emotional pain of rejection (which creates a subhuman existence) and a disconnect from intimacy and self that permanently alters their perspective on self-worth, purpose, and trust for humanity.

Why Medical Intervention is Imperative in PORS and Active Parental Addiction

There are now new trauma classes for foster families accepting children from homes of drug use and other abuses, but few are well versed, if at all, on the subject of prenatal exposure to excessive substance use and overdose-related PTSD or the resultant rejection component in the newborn.

This is because the conditions in this delicate population are not yet medically recognized, documented, and treatable pediatric diagnoses.

It is especially not yet widely recognized that these brand new lives have severe PTSD.

Few professionals have or seek research on this.

Even with today’s recent increased trauma research, both the medical community and society seem to pull a sheet over both the inevitable and unexplainable realities occurring to a human being from prenatal drug exposure.

When medical professionals happen to note both the discord in the addict’s parental dynamics and in how prenatal and postnatal drug addiction (at home) affects those babies conceived in addiction, it is common to see the multitudinous signs and symptoms in a child who is suffering from PORS, dismissed as non-related diagnoses.

CPS can and will not intervene in most cases where a mother does not show up positive for substances at birth or just before. Addicts know to circumvent the system. Who confirms that she is sober a few days prior to the test and several days or weeks after discharge?

For the most part, no one.

An addict traditionally does not get sober during pregnancy just because an innocent life is at stake during or after childbirth.

Overall, there is little intervention from the medical community to acknowledge the delicate situation these children are born into or to actually protect their vulnerable and damaged lives from further damage.

Many times, it seems that this lack of response may stem from willful and/or fearful ignorance to address addiction and an age-old stigma that since an “addict begats an addict,” why intervene?

Few medical providers understand the devastating and insidious nature of the addicted mind. Many do not comprehend the further and continuing damage that occurs to a child who goes home to addiction in a post-exposure crisis medically, emotionally, and physically.

As a result, the formation of special parenting techniques is not addressed through counseling/therapy and things such as specialist referrals are not made or followed through with, compromising the child’s health and safety further.

Persons with an addiction can get better and someday give good care to and parent their child well but, in my experience and opinion as a nurse and observant custodial grandmother, the formative years of the child should not be under the care of addicts (even “functioning” ones) or newly recovered ones.

When an addict is in recovery, they learn that they must focus on themselves and their sobriety first and always to keep themselves in check to stay sober. Decisions must be made that leave out other members of that addict’s family and other life priorities in lieu of the priority of sobriety.

Only time, maturity, and experience weaving the recovery program’s requirements into all aspects of the addict’s life will eventually allow for that addict to be able to properly care for others, and achieve the self-awareness and discipline to do so while maintaining sobriety.

My professional and personal experience so far is the observation of the passive omission of the medical community to take initiative to reach out and engage these parents in any appropriate discussion or intervention of the care of their PORS-affected newborn, or the desperate need for addiction services.

Addressing Latent Effects of PORS and An Addicted Parental Response

A healthy baby whose pregnancy is free of substance abuse requires full-time, attentive, round-the-clock care.

A newborn who is riddled with the physical, mental, and emotional after-effects of prenatal substance abuse requires scrutiny and intervention in every aspect of care and an intimate understanding that their responses to everything around them are woven with distrust, fear, and disconnect.

In most cases, the obvious emotional and physical problems cannot be handled safely or appropriately either by addicts who remain in their addiction or by recovering addicts who are less than 1–2 years stable into their sobriety.

Beginning in the early months after birth, it takes a gentle hand, a calm demeanor, an overly attentive approach, and an excess of undistracted care to settle and restructure these children’s spirit after their womb trauma.

Keep in mind, rejection is a foundational component of their physical, mental, and emotional makeup.

The latent effects of this condition pose further danger to a child as they grow and age as most parents in recovery or in active addiction, will not recognize or understand prevailing and insidious symptoms such as the presence of sensory deprivation/overload, general sensorial problems, neurological delays, night terrors, processing disorders, speech/choking swallowing disorders and other serious maladaptations resulting from prenatal drug use and overdose.

Some of these diagnoses could take months or a few years to become visibly evident, although many are present right after birth.

This places the child in yet another traumatic situation because the uneducated, (uneducated to the problems associated with the diagnosis) addicted or sober parent is again, not traditionally sought out by the baby’s or mother’s medical professionals as an interventional risk or for the teaching of the probable issues to come.

Addicted or recovering parents are prone to getting angry easily (which is a result of their complicated mental and emotional condition in addiction) at the distracting crying, incessant need to eat and be soothed, or the refusal to eat and be held, as well as frequent illnesses.

What commonly happens in the manifestation of symptoms, is the parent(s) will react to the “irrational,” confusing behavior and excessive needs of the child and not to the cause of either. Subsequently, several types of abuse are common to occur, as the baby or older child’s behavior is intrinsically misunderstood.

Parents in active addiction or early recovery will usually misunderstand telltale signs that the baby is in need of a different kind of intense and patient parenting. The parents also do not have the ability in their current state to process or act on the needs of their child.

In one particular NICU environment I was employed in, the staff would read the city’s newspaper weekly on the unit to note which of our discharged babies had died by abuse or neglect. It was that common.

Others ended up in our emergency room completely malnourished and in active severe dehydration. Some made it, some did not.

The medical community as a whole must urgently re-examine the entire and intricate phenom of addiction. We must seriously re-examine sending a drug and overdose-exposed infant home to the people who had damaged them in utero, despite their “cleaned up” appearance and promises, and even despite any recent positive recovery status.

The menace that is relapse is an overshadowing, lurking danger, historically, and must be monitored very closely for a newly sober parent.

Self-coined Prenatal Overdose Rejection Syndrome Diagnosis.

Separate from my extensive nursing experience, I have gathered an immense amount of professional and personal expertise in managing, caring for, and in raising a child born into a heroin and meth addiction.

I noticed the symptoms of PORS in my professional career, but it was not until Charlie, my own grandson, was born from severe addiction that I could pen an actual name for the postnatal (and beyond) symptoms that I was seeing.

I have had legal custody of him since his fifth month of life. Charlie grew in-utero in my home from 28 weeks, was born at 38 weeks, and subsequently endured a month-long NICU stay and then was discharged to my home under the care of his birth mother and my youngest son, his father.

Both Charlie’s parents continue to struggle today with their recovery from heroin and meth, but for all their positive efforts (five years later) neither are in any kind of emotional or physical condition to parent Charlie and will not be for a long time, if ever.

During the pregnancy, in a rescue attempt to get help for her and for Charlie, I insisted that my grandson’s birth mother inform all her doctors and prenatal specialists of her heroin and meth addiction.

However, her specialists were not concerned.

They did not intervene and did not question her or even address her obvious positive drug screens occurring before her 28th week.

Not only was she not flagged as a risk to the baby at and after the birth, but the delivering ob/gyn actually told her that heroin and meth were not known to hurt a baby, so he “should be fine.”

This ridiculous and irresponsible line of thinking and under-education on this doctor’s part is reprehensible and did prove to be tragically wrong. Charlie was born with Gastroschisis, requiring immediate surgery after birth, and was subsequently diagnosed with 12 independent diagnoses.

Now, Prenatal Overdose Rejection Syndrome is an additional, undocumented and unrecognized problem I manage in his care and a focal point of intervention in his life.

Symptoms:

Charlie displays a constant need for reassurance of each family member’s role and connection with each other and to secure the idea that he and everyone “go together.” He continually looks for his proper place in the family, as it is clear he feels “out of place,” in general.

He is now almost five years old. Until very recently, he was inconsolable if I was not within sight and behaved as though he believed I was gone for good. This fear of abandonment began at birth. The few months his parents cared for him only cemented his fears as they did not know how and were not focused on meeting his needs…and they had both secretly returned to using just after he came home.

Charlie additionally had sudden, unexplained fevers, frequent illnesses (every 3 weeks almost on the dot) including pneumonia, RSV, strep, and other general maladies. He woke six to seven times a night, screaming inconsolably much of the time.

When a little older, he would hit himself when even gently corrected or if any situation seemed to place him in the spotlight for any reason. These issues are still present but improved now.

Charlie screams and talks angrily in his sleep often, now and seems to have dreams in which he is being threatened or attacked, as evidenced by this sleep speech and cries.

I sincerely believe this has to do with his prenatal and post-birth experiences with substance abuse, overdose, and the irresponsible, incomplete care he received from his parents in the first few months of his life.

For all the physical, neurological, and emotional difficulties (there are many more diagnoses), the most noted after effect of his prenatal exposure and trauma is his noticeable sense of rejection.

I am very careful in my one on one handling of his body when he walks and moves, as any accidental brush, scrape, or slight knock (think of getting a child into a car seat, dressing, or just moving about in general in the home) to his person sends him into a screaming fit, hitting himself.

The expectation of rejection and mistreatment is in his eyes, despite all my expressed care and love for him. I have also seen the same look in the eyes of other special needs children, both in my pediatric career and presently in other children attending therapy appointments at our therapy clinic.

Many things in a human being’s life can cause the rooted belief of unworthiness. It is incomprehensible that a developing fetus can be so poorly treated in the womb that this kind of root would begin before a first breath in the world, but it is an unfortunate reality.

Signs of PORS: (some can be characterized under other diagnoses as well)

If the caregiver/parent/grandparent of a child who suffered prenatal drug abuse and overdoses recognizes some or any of the following signs, immediate PCP’s therapy and developmental delay referrals needs to be made:

• excessive separation anxiety
• frequent night terrors
• social distancing from peers (can be observed as early as 12–18 months)
• delayed or difficult speech and conversation
• frequent, unexplained illnesses
• any purposeful self-injury
• the appearance of being persistently sad, aloof, disengaged or if they appear overexcited, excessively talkative ie: like the Energizer bunny and they are in a noticeable state of stress)
• anything else that appears to be “odd” or out of sorts with their communication methods, thought processes, and reactions to everyday activities and stressors.
• subtle and overt signs of problems processing daily communication and information, discipline, and social expectations. *
• Congenital mobility problems: weaknesses in various parts of the body showing as imbalance, toe-walking, odd gait, frequent falls, weak extremities, etc.

As a fetus, Charlie endured hearing his mother gasp for life during three heroin overdoses, heard the constant fighting and screaming between his birth mother and my son, endured severe malnutrition, felt the effects of multiple substance abuse, and was the victim of the negative stress hormones pulsing through his mother’s veins caused by the distinct chaos of another’s addiction.

Again, I continue to observe that the PORS phenomenon with all its nuances is not considered even when clinicians do work with addicts and their children. The effect of an addict’s life and abuse on the fetus is not addressed head-on.

Medical providers are bound to the search and research of best care and we are trained to unturn every stone for solutions and resolutions. If this is not accomplished, there are dire consequences for a patient who has experienced prenatal exposure to drugs, and especially, severe cases.

This type of unborn life, this type of prenatal rejection, affects the child’s whole physical, mental, emotional and spiritual makeup.

It is a permanent, invisible disfigurement.

Suggesting Further Solutions:

As with any health problem in our world, one effective and necessary solution is education, which is the purpose for my piece on this under-recognized and hugely epidemic medical and social problem.

Active and sober addicts, the parents and caregivers of the affected babies and children, and other involved (and medical) parties affected by Prenatal Overdose Rejection Syndrome need to be educated on the signs and symptoms of this not-yet-diagnosed condition.

Immediate, compassionate and consistent intervention should unequivocally begin at the positive test for pregnancy in an addict. As much as we, the medical community, can do to help that mother obtain permanent sobriety, we should do.

All parties affected by and involved in the care of Prenatal Overdose Rejection Syndrome also need a voice as a way to heal, educate, and be educated to implement treatments and cares and advocate for new research into this devastating issue. This begins by assessing, triaging, monitoring, and providing the utmost, loving and creative care are for these populations, as we are capable of.

This happens through the willful and purposeful engagement of physicians and other medical providers to swiftly address the symptoms of addiction in the parent and those of the child born out of that addiction. Researching and documenting these mental health and physical conditions and presentations is most imperative.

To summarize

Unborn babies in the womb of an active addict are the most at-risk type of patients in society and the medical community due to the inability of this type of patient to advocate for themselves and the inability of the addicted parent (s) to advocate appropriately for either of them.

The lives and health of these babies are severely compromised before birth. They are discarded and rejected prior to life outside the womb through the use and overdosing of substances, whether intentionally or neglectfully done.

Until research on the full psychosocial, psychological, and coinciding physical and emotional prenatal effects of drug use and overdose is addressed thoroughly, and protective measures for the unborn experiencing this abuse are put into effect, many an unborn child in the womb of an active addict will be plagued with a consciousness of intrinsic and lasting rejection before they are even seen or held.

This is unacceptable for our children and grandchildren and for any new human being.

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