Research into infections is in urgent need of funding.

When a new infection in humans emerges, one of the first questions concerns the location where the transmission to our species took place. In recent decades, this question has often been linked to changes in ecosystems: by altering the environment, we increase the opportunities for contact with animals that may harbour microorganisms capable of reaching us, and with this comes a greater likelihood of spillover – that is, the jump from an animal species to ours.

A major study published in Nature now seeks to verify the extent to which this explanation corresponds to the observed distribution of emerging diseases. Rory Gibb and his colleagues have compiled 58,319 epidemic events relating to 32 infections, observed in 169 countries between 1910 and 2022. The bulk of the data relates to the last two decades, when epidemiological surveillance became more widespread. The sample includes a wide variety of infections, ranging from dengue to Ebola, from yellow fever to the plague, and including Nipah, mpox and Lyme disease. For each outbreak, the researchers reconstructed the environmental characteristics of the location where it had been recorded, seeking to understand which conditions were most frequently associated with the emergence of an outbreak. The crucial issue, however, predates any ecological interpretation: an outbreak can only appear in a database when someone is able to recognise it. This introduces a significant distortion. Where the healthcare system is more accessible, a disease is more likely to be diagnosed and therefore to be included in the data. Where reaching a healthcare facility takes a long time, the same event may remain unnoticed. The map of observed outbreaks therefore also bears the mark of observational capacity.

The authors sought to correct for this effect by introducing variables into the models that describe the accessibility of healthcare services. The result is very robust. In models where it was possible to estimate journey times, every additional hour required to reach a healthcare facility corresponded to a median 32 per cent reduction in the probability of an outbreak appearing in the data. That figure varies greatly from one disease to another and therefore does not represent a general rule. However, it shows just how profoundly the geography of an infectious disease outbreak depends on the ability to detect it.

This point changes the way in which many maps of zoonoses should be interpreted. A region in which few outbreaks are recorded may genuinely be less exposed, or it may simply be a region where surveillance is less effective. When this distinction is not taken into account, it is easy to attribute to the environment factors that depend, at least in part, on the structure of the healthcare system.

After correcting this distortion as far as possible, the authors nevertheless find an ecological signal. However, no single cause emerges that can explain all the diseases under consideration in the same way.

Landscape structure is particularly significant in certain categories of infection. Areas where natural habitats and human-altered zones frequently intersect are associated with a higher risk for a substantial proportion of the diseases studied. The biological rationale is plausible: when the organisation of an ecosystem changes, so too do the opportunities for contact between animal hosts, vectors and humans.

This pattern is particularly evident in infections transmitted by arthropods. For a disease transmitted by mosquitoes or ticks, the environment has a direct impact on the distribution of the vector and, consequently, on the likelihood of the pathogen circulating. In these systems, certain ecological characteristics tend to produce similar effects even across different diseases.

One of the recurring patterns concerns long-term changes in precipitation. In several vector-borne infections, progressively drier conditions are associated with an increased risk. The interpretation depends on the biological system under consideration, as water availability affects the ecology of the species involved in different ways.

With regard to other factors that have been much discussed in recent years, the picture appears far less uniform. Recent deforestation shows a statistically significant association in only a minority of the diseases examined. Nor do temperature variations produce a common signature stable enough to be observed across the entire set of pathogens studied.

This does not allow us to conclude that deforestation or climate change are irrelevant to the emergence of infections. It means that their effect does not appear to be a universal mechanism, recognisable in the same way across profoundly different biological systems.

The distinction becomes even more evident in zoonoses where the pathogen is transmitted directly from an animal to humans. For infections such as Ebola, MERS or mpox, there is no common combination of environmental factors comparable to that observed in many vector-borne diseases. In these cases, the risk appears to depend much more on the specific ecology of the animal reservoir and the manner in which contact with humans occurs.

The general category of zoonoses therefore encompasses biological mechanisms that are too diverse to be described by a single environmental explanation. The fact that a pathogen originates from an animal does not imply that its transmission to humans depends on the same conditions that facilitate the transmission of another pathogen.

The study also has significant limitations. To make very different datasets comparable, the authors have often reduced the information to the presence or absence of at least one case in a particular location and in a particular year. This means that the scale of the outbreak is lost, and for many rare infections it becomes difficult to accurately reconstruct the timeline between environmental change and the emergence of the disease.

The authors partially verified the robustness of this approach using more comprehensive U.S. data for four arboviral diseases. In that context, the simplified analysis captured most of the key geographical determinants that emerged when incidence rates were considered directly.

The resulting picture is more complex than the general explanations that often accompany discussions of emerging diseases. Human impact on ecosystems matters, but its effect depends on the biology of the pathogen and the way in which transmission occurs. Above all, what matters is the ability to see what is happening.

This is why surveillance plays a crucial role in preventing future epidemics. Where a disease is detected early, it becomes possible to trace its origin and take action before transmission spreads. Where surveillance is weak, our understanding of the ecology of epidemics remains distorted.

The geography of emerging diseases thus reveals two inseparable phenomena: where pathogens manage to reach us, and where we manage to detect them. Before attributing a gap on the map to the absence of a disease, we must be certain that someone in that place was able to detect it.

Just as these figures highlight how dangerous epidemiological invisibility is, the international system designed to reduce it is undergoing a period of contraction. In 2025, the WHO asked its national offices to assess the effects of the sharp reduction in international health aid. Of the 108 countries surveyed, 66 per cent had already reported disruptions to public health surveillance, whilst 70 per cent reported consequences for emergency preparedness and response. By the end of that same year, the Organisation estimated that external health aid would decline by a total of 30–40 per cent compared with 2023.

The WHO, too, now has fewer resources than were anticipated a few years ago. The United States’ decision to withdraw from the Organisation and to halt its funding has had a significant impact, alongside the reduction in development aid decided upon by other countries. In April 2025, Director-General Tedros Adhanom Ghebreyesus indicated a projected salary shortfall of between 560 and 650 million dollars for the two-year period 2026–2027; the budget was subsequently reduced from 5.3 to 4.2 billion dollars, representing a 21 per cent cut compared with the original proposal. The resulting restructuring has led to a reduction in staff numbers and in the number of programmes the Organisation can support.

The effects have precisely targeted the functions that the study published in Nature identifies as essential. In its 2025 report on findings, the WHO states that financial constraints have limited the surveillance networks and monitoring required under the International Health Regulations; in many countries, laboratory activities and the capacity for early detection of emergencies have been scaled back. In the same year, however, the Organisation’s global systems still screened around 5.4 million potentially relevant alerts and verified around 693 possible health threats with governments. These figures illustrate the scale of the apparatus required to transform the local emergence of a disease into information available to the rest of the world.

There are also investments moving in the opposite direction: in 2025, the WHO updated the EIOS (Epidemic Intelligence from Open Sources) system, which is now used by more than 110 countries to detect early signs of potential health threats. However, its own strategy identifies the availability of stable, long-term funding as one of the necessary conditions. A system capable of gathering global signals is, in fact, only useful if, at the outset, there are people and structures capable of generating those signals.

This creates a very clear contradiction between what we are learning about the origins of epidemics and the direction in which some international health policies are heading. The work by Gibb and colleagues shows that one of the major obstacles to understanding infectious risk lies in the unequal probability of an outbreak being detected. Reducing surveillance in countries with more fragile healthcare systems makes that probability even more unequal and expands the areas in which a new pathogen can circulate before being recognised.

This issue also directly affects countries with much stronger healthcare systems. An unnoticed outbreak in a distant region does not necessarily remain confined to the place where it first appeared, whilst information gathered at an early stage can travel much more quickly than the pathogen itself, enabling other countries to prepare. International surveillance therefore constitutes a form of shared protection, the value of which also depends on the weakest links in the network.

If the key epidemiological lesson to be learnt from this data is that we cannot prevent what we cannot see, then reducing the world’s ability to see today means deliberately accepting a poorer understanding of the next infectious threat.