Modelling the future population health consequences of precipitation-induced healthcare disruptions in Malawi

Weather has long been known to shape human health in direct and dramatic ways. Heavy rains can swell rivers that carry disease-carrying mosquitoes, while scorching heat can overwhelm the body's ability to cool itself. These connections are well documented. Yet, a quieter, more indirect danger often goes unnoticed: the way storms and floods can sever the link between a sick person and the doctor they need. When roads wash away, clinics lose power, or staff are injured, the healthcare system itself becomes a victim of the weather. This breakdown does not just pause treatment; it can alter the course of a disease, turning a manageable condition into a life-threatening one. For nations already struggling with limited medical resources, the question is no longer just about how much rain falls, but how much care is lost when it does.

Researchers in London and Malawi have built a new way to measure this hidden cost. They created a computer simulation that acts as a digital twin of Malawi's entire healthcare system, tracking millions of individual people and their interactions with doctors, nurses, and clinics. This model, known as Thanzi La Onse, was designed to reflect the country's specific population, diseases, and the way people seek help. The team then overlaid a new layer of logic onto this system to mimic what happens when heavy rain disrupts the flow of care. They did not just look at the moment a clinic closes; they followed the ripple effects. They asked what happens when a patient misses an appointment: do they try again later, or do they give up? How long does the delay last, and does it matter if the illness is urgent, like a difficult birth, or routine, like a check-up for high blood pressure? By running these scenarios forward from 2025 to 2040, under a climate future that assumes a moderate increase in greenhouse gases, the researchers could see how the system would hold up against the storms of tomorrow.

The results reveal a system under significant strain, though the damage is not spread evenly. In the simulation, the most critical factor was not just the rain itself, but the behavior of the people trying to get care. When a disruption occurs, the outcome depends heavily on whether patients return to the clinic once the roads are passable. The study found that if people do return, the health system can recover much of its ground. However, if they do not, the consequences are severe. Under a standard set of assumptions for the coming decades, the model projects that nearly one in six healthcare visits in the hardest-hit months and regions will be disrupted. Over the fifteen-year period, more than 7 million people in Malawi are expected to experience a break in their care due to precipitation. This is a massive number, representing a significant portion of the population facing a gap in their medical support.

The impact of these gaps is not felt equally across all diseases. The simulation shows that the most severe health losses are concentrated in conditions where timing is everything. For mothers giving birth, for newborns, and for people suffering from acute respiratory infections, even a short delay can be fatal. In the districts most vulnerable to flooding, such as those bordering Lake Malawi, the disruption to care for these urgent needs leads to a measurable increase in illness and death. The model calculates that these delays result in thousands of additional years of life lost to disability and premature death. In contrast, for many chronic conditions where care is less urgent or where routine screening is already limited, the weather-induced delays cause far less immediate harm. This is partly because the model assumes that for some conditions, the care that is missed was not being sought in the first place, or because the delay does not immediately change the outcome of the disease.

A striking finding from the study is that the visible damage is only a small fraction of the total problem. The researchers found that while only a tiny fraction of appointments are directly cancelled because a clinic is flooded or inaccessible, the total number of missed appointments is much larger. This happens because healthcare is often a chain of events. If a patient misses an initial screening for cancer, they never get the follow-up tests, the diagnosis, or the treatment that would have followed. The model shows that for every appointment directly stopped by the weather, roughly seven others are lost downstream because the chain of care was broken. This "indirect" effect is roughly seven and a half times larger than the direct effect, meaning that the true scale of the disruption is far greater than what one might see by simply counting closed doors.

The study also looked at how different types of weather futures might change these outcomes. They tested scenarios ranging from a low-emission future to a high-emission one. Surprisingly, the results were similar across all these scenarios. The variation in rainfall patterns between different climate models was less significant than the uncertainty in how people and clinics would respond to the disruptions. This suggests that the biggest lever for improving health outcomes is not just predicting the weather, but understanding and supporting patient behavior. If people are encouraged and enabled to return to care after a storm, the health losses can be significantly reduced. Conversely, if barriers prevent them from returning, the system suffers a much heavier blow.

Ultimately, this research provides a lower-bound estimate of the problem. The authors note that their model assumes a certain level of resilience and that in reality, the lack of resources in Malawi means that even small disruptions could have larger consequences than simulated. The study highlights that climate change is not just an environmental issue but a direct threat to the reliability of healthcare. It shows that in a country where the health system is already stretched, the weather acts as a multiplier of existing weaknesses. The path forward requires more than just better infrastructure; it demands a deeper understanding of how patients navigate the system when it is broken, and how to ensure that the chain of care remains unbroken even when the rains come.