“No woman should fear for her life when giving birth.” The trial cut severe bleeding by 60 percent and lowered transfusion rates, showing that simple tools and training can revolutionize maternal care.
At Lilongwe’s Area 25 Health Centre in Malawi, clinicians rely on an AI-operated fetal monitoring tool that watches a baby’s vital signs during labor.
Dr. Chikondi Chiweza, head of maternal care at the center, recounts one incident when AI detected sudden distress in an expectant mother, Kaphamtengo, prompting an emergency cesarean.
“In her case, we would have only discovered the problem either later on, or with the baby as a stillbirth,” she says. Since its introduction three years ago, stillbirths and neonatal deaths have dropped 82 percent.
The software, provided by PeriGen alongside Malawi’s health ministry and Texas Children’s Hospital, offers real-time monitoring that transforms outcomes in settings with thin staffing and limited infrastructure.
Digital innovation and artificial intelligence are increasingly becoming central to building a more sustainable and equitable future, especially in public health.
Technology is changing how health care works in rich and poor countries alike. From drones that deliver blood in Rwanda to AI systems that scan the news for disease threats, the tools are new, but the goals are old. Save lives. Use money well. Reach people who have been left out.
The United Nations system and its partners are trying to make that change work for the public good while keeping a close eye on risks such as bias, privacy, and unequal access.
Maternal health is a clear test. The latest UN estimates say about 260,000 women died from pregnancy or childbirth in 2023. That is one woman every two minutes. The world has cut maternal deaths by about 40 percent since 2000, but progress has slowed in recent years.
Most deaths still occur in low and lower-middle income countries. These numbers are not abstract. They set the stage for why better tools for prevention, diagnosis, and rapid response are urgent. They also explain why UN agencies invest in simple, proven actions that reach the last mile.
One example is how the World Health Organization responded to new evidence on postpartum bleeding, which is the leading cause of maternal death worldwide. In 2023, WHO updated clinical guidance to promote a bundle approach to treat bleeding without delay.
The approach became widely known through the E-MOTIVE trial, a large study across several countries that showed that using a calibrated blood-collection drape, giving uterotonics and tranexamic acid early, doing uterine massage, and checking for and treating lacerations as one package improves outcomes.
Dr. Pascale Allotey, WHO’s director for sexual and reproductive health, said, “No woman should fear for her life when giving birth.” The trial cut severe bleeding by 60 percent and lowered transfusion rates, showing that simple tools and training can revolutionize maternal care.
Professional groups like the International Federation of Gynecology and Obstetrics (FIGO) and the International Confederation of Midwives (ICM) reinforce the early use of tranexamic acid based on the WOMAN trial.
A recent summary for practitioners explains how the 2023 guideline differs from older ones by emphasizing early, bundled care rather than single steps.
For countries where resources are tight, this kind of practical change matters because it cuts delays on the ward and sets a shared standard that nurses and doctors can apply fast.
The case for early treatment is supported by strong evidence. The WOMAN trial found that giving tranexamic acid soon after birth when bleeding starts can reduce the risk of death from haemorrhage by about one third.
Other trials have tested where it does and does not help, such as findings on prophylactic use after some caesarean deliveries. The point is not that one drug or device is the answer. It is that a clear, evidence-based package, backed by WHO guidance, helps frontline staff work as a team and act in minutes, not hours.
Better care inside the facility will not save every mother if the system around the facility is weak. Roads, cold chains, blood banks, and reliable communications make a difference between life and death.
Rwanda shows how logistics can be reinvented. Since 2016, Rwanda’s health service has used autonomous drones to deliver blood and medicines from regional hubs to hospitals over mountains and poor roads. A peer-reviewed study in The Lancet Global Health found that drone delivery shortened delivery times and was linked to fewer blood product expirations.
A case study from the Reach Alliance describes how, by early 2020, drones were delivering more than three quarters of Rwanda’s blood supply outside the capital. These reports do not claim drones solve every problem.
They do show that the right technology, built into the public system, can reduce waste and speed up care in rural areas.
Digital records and real-time data are another pillar. In Ghana, a country that faces both urban and rural delivery challenges, the e-Tracker system is used in primary care for maternal, child health, and immunization services.
A recent open-access study reports gains in health worker skills and workflow when the system is used consistently. A 2025 mapping of Ghana’s health data ecosystem lists e-Tracker alongside DHIS2, SORMAS for outbreak control, and the national logistics system.
Together these tools help managers see gaps and respond quicker than paper registers ever could. The role of WHO and UNICEF in these programs is visible through technical support, standards, and training.
Public health is not only about hospitals. It also depends on trust and timely information. During COVID-19, Nigeria’s Centre for Disease Control, with UNICEF support, launched a free chatbot on WhatsApp, Facebook, and SMS in multiple local languages.
The idea was simple. Give people a way to check symptoms, read prevention tips, and find answers that counter rumours at no cost. Official press releases explain how the service was meant to cut misinformation by meeting people on platforms they already use.
These approaches matter today, not only for COVID-19, but for outbreaks of Lassa fever, cholera, and mpox that still hit towns and villages.
At the global level, the World Health Organization runs the Epidemic Intelligence from Open Sources (EIOS) platform. EIOS scans media and other open sources around the world to flag possible outbreaks.
The WHO describes it as a community, a set of collaborators, and a fit-for-purpose system. New evaluations are testing how well it catches early signals in Africa, and WHO’s Pandemic and Epidemic Intelligence Hub in Berlin has published updates on how the system is evolving.
This is a place where AI is already part of daily public service work. Algorithms help sift vast streams of information, but it is human analysts in public health agencies who verify signals and decide what to do next.
None of these tools will help if people cannot get online or afford data. The latest GSMA Mobile Gender Gap report shows that in low and middle income countries women remain 14 percent less likely than men to use mobile internet.
That gap represents 235 million fewer women online, with the largest share of the gap in South Asia and Sub-Saharan Africa. When women and girls do not have affordable data or a smartphone, digital health services miss the very people who need them most.
The gender gap in connectivity is not a side issue. It is central to whether digital health builds fairness or deepens inequality.
Funding pressures are also real. UNICEF’s 2025 situation report for Northern Nigeria says that 8.8 million people need humanitarian assistance, including almost five million children, and warns that reduced donor support is disrupting health, nutrition, and protection services.
News reports from trusted outlets and statements from UN agencies warn that aid cuts could reverse gains in maternal health if clinics close and staff leave. Digital tools cannot fill a clinic that has no midwives or medicines. They work only when the basics are funded and in place.
When we look beyond Africa, the same lessons appear, but the tools and rules change with context. In Europe, the Artificial Intelligence Act came into force in 2024.
It sets strict requirements for high-risk AI systems, which include many uses in health care. The law is dense, but the core idea is clear. If AI could affect people’s safety or rights, providers must meet strong standards on data quality, risk management, transparency, and human oversight.
This seems to protects patients. Compliance may also slow start-ups down. What matters for public service is that systems used for triage, diagnosis, or resource planning are built and used in a way that is safe, fair, and open to scrutiny.
WHO has also published guidance on the ethics and governance of AI in health, including new advice on large multi-modal models. These documents give ministries, hospitals, and vendors a shared map of what responsible AI should look like.
The Americas offer a second kind of lesson. Digital health platforms can help track vaccination and keep records in one place, which supports public trust and service quality.
At the same time, breaches and outages remind governments why privacy and security matter. Dr. Jarbas Barbosa, Director of the Pan American Health Organization (PAHO) urged immediate steps to strengthen primary health care as a key pathway to achieving health equity and closing persistent gaps in the treatment of noncommunicable diseases (NCDs) and mental health.
He emphasized the need to expand access to diagnostics, treatment, and digital health tools throughout the Americas.
Speaking at the Foreign Policy Global Health Forum, held alongside the 78th World Health Assembly (WHA78) in Geneva, Dr. Barbosa highlighted that 35.2% of people in the Americas have unmet healthcare needs, with the figure rising above 40% in lower-middle-income countries.
The details differ by country, but the principles are close to those in WHO’s global strategy. Digital building blocks should be open, interoperable, and guided by public values rather than vendor lock-in.
Across these regions, three cross-cutting issues keep coming up. The first is the need for clear evidence of impact. Programmes like E-MOTIVE were tested in rigorous trials before WHO embedded them in guidance.
Drone delivery was studied by independent researchers, not only by vendors. Electronic records in Ghana are being evaluated in peer-reviewed papers and in national reviews of the health data ecosystem.
This kind of transparent evidence lets journalists, civil society, and taxpayers hold institutions to account. It also lets front-line users push back if a tool adds workload without adding value.
The second is equity in access. A mother in a rural Nigerian village may now get health messages by SMS or WhatsApp and meet a nurse who uses a tablet to check her antenatal history.
That is progress. But if the clinic has no steady power, or if data is too costly for her to read follow-up instructions at home, digital services will not change her outcome.
The GSMA data on the gender gap in mobile internet use should be on every policymaker’s desk. It explains why programmes need offline modes, toll-free numbers, and designs that work on basic phones.
UNICEF and WHO field teams see this gap every day. Their reports from the northeast of Nigeria and other crisis settings are careful to show where connectivity and funding fail.
The third is governance. Europe’s AI Act will shape how AI is built and approved. WHO’s guidance offers a global view of ethics. But rules have to reach the ward, the lab, and the district office in ways that staff can understand.
In practice that means procurement that asks for audit trails and bias testing. It means data sharing agreements that protect patients. It means involving midwives, community health workers, and patients in choosing and maintaining the tools they will use every day.
In low resource settings, that often requires donors to support not just the pilot, but long-term salaries, electricity, and maintenance.
AI for surveillance deserves a special note. The WHO EIOS platform uses algorithms to scan open sources for signals of outbreaks. A recent evaluation focused on Africa is testing how early and how accurately it can flag events. A report from the WHO Pandemic Hub shows how the system is being scaled with partners.
The promise is early detection. The risk is chasing noise or missing local context. The practical answer so far has been to combine machine help with human judgment from national public health institutes.
That mirrors a broader point in health technology. Digital tools are aids. They do not replace skilled people with local knowledge.
For Nigeria and other African countries, the path forward is clear. Keep investing in what works. Build and maintain logistics systems that cut delays, whether by motorcycle, drone, or better blood bank management. Scale digital records that help nurses and midwives do their jobs without extra burden. Use chatbots and community platforms that meet people where they are, in plain language and local languages. And do all of this with a tight focus on equity, gender gaps, and the basics of power, staffing, and supply chains.
Where UN agencies have a unique role is in setting norms, and sharing lessons across borders so countries need not reinvent the wheel.
New tech should be tested in the places where it will be used. Centralize systems should not be so tight that local teams cannot adapt. Total cost of ownership should not be ignored. Tool that needs constant data or power should be budgeted for. Open standards should be used so that ministries own their data and can move it if needed. These are not new lessons. WHO, UNICEF, and PAHO have been saying them in strategies for years. The difference now is that some AI tools and rapid logistics may make the gap between good and bad choices wider. A well chosen system can save many lives. A poor fit can waste scarce money and time.
The larger context matters. Health technology works inside real societies. In places where poverty is deep, where women cannot afford data, and where governance is weak, new tools can make inequalities worse if they are rolled out without care. The mobile gender gap shows who is likely to be left out. Funding cuts show how fragile gains can be. That is why the UN’s role in field operations remains essential.
The goal is a health system that is more efficient, more personal, and more fair. That goal will only be met if technology is used to serve people, not the other way round.
Digital innovation can move beyond pilot projects to create long-term, sustainable improvements in health and other public services by pairing technological progress with inclusive policies, training, and investment in infrastructure.