Researchers from several leading universities have published a conceptual framework in the CDC journal Emerging Infectious Diseases arguing that the scientific community should draw on data from common animal-to-human virus spillovers to develop prevention strategies against the rare spillover events that trigger pandemics. The paper addresses a fundamental gap in pandemic preparedness: the lack of reliable data on how pandemic-capable viruses first enter human populations.
The authors define the class of interventions they are concerned with as primary prevention, measures that reduce the initial risk of a virus passing from an animal host to a human, as distinct from the vaccines and treatments deployed after a pathogen is already spreading. They argue that primary prevention strategies have been underutilized in pandemic preparedness planning, in part because the evidence base for them remains underdeveloped.
The Data Problem at the Heart of Pandemic Prevention
The core scientific challenge the paper identifies is straightforward: pandemics are rare, and the spillover events that cause them are therefore also rare. The conditions that allowed past pandemic viruses to cross from animals into humans and then spread globally have never been comprehensively documented for any known pandemic pathogen. That absence of data makes it difficult to design evidence-based strategies to prevent future spillovers of the same type.
The authors contrast this with a different category of zoonotic virus: pathogens that spill over from animals to humans frequently, but fail to spread efficiently between people. Diseases such as rabies, Lassa fever, and Puumala virus infection collectively generate thousands of documented spillover events each year. Because every human case of these diseases results directly from animal contact rather than person-to-person transmission, they offer a relatively clean and data-rich window into the ecological, biological, and social conditions that allow viruses to cross the species barrier.
The central question the paper poses is whether insights from these frequent, poorly spreading spillovers can be legitimately applied to the prevention of rare spillovers by viruses capable of causing pandemics. The authors refer to the latter as Pathogen X, a term used in global health security circles to describe a hypothetical but plausible unknown pathogen with pandemic potential.
A Framework for Classifying Zoonotic Risk
To organize the available evidence, the authors propose classifying known zoonotic viruses along two dimensions: how frequently they spill over from animals to humans, and how efficiently they spread between humans once a spillover occurs. This produces four broad categories, ranging from viruses that spill over constantly but spread poorly, such as rabies, to those that spill over rarely but spread efficiently enough to cause epidemics or pandemics, such as pandemic influenza and HIV.
The authors note that viruses are not fixed in these categories. Monkeypox virus, for example, spread poorly when smallpox vaccination provided cross-protection across much of the global population, but has caused major outbreaks as that immunity has waned following the end of mass smallpox vaccination programs. Ebola virus has demonstrated more sustained human-to-human transmission in densely connected populations than in more isolated ones. Changing land use practices, wildlife trade patterns, and occupational exposures can also shift where a given virus falls within the framework.
Pathogen X, the authors argue, most likely occupies the rare spillover and spreads well quadrant, either because it already spreads efficiently at the time of spillover or because it has the capacity to rapidly evolve that ability.
Can Data from Common Spillovers Inform Prevention of Rare Ones?
The paper does not claim to resolve the question it raises. The authors acknowledge that the relationship between spillover frequency and pandemic potential is not straightforward, and that many factors governing whether a virus can spread efficiently among humans remain poorly understood. Some viral characteristics appear to influence both spillover risk and human-to-human transmission, but numerous examples exist of closely related viruses that behave very differently across both dimensions.
What the authors propose instead is a phased research agenda that would systematically compare spillover pathways across viruses in different quadrants of their framework, looking for shared and divergent patterns. They suggest, for example, comparing the conditions that allow Nipah virus to spill over, a pathogen that spreads via respiratory routes but rarely passes between people, with those that allowed SARS-CoV-1 to do the same but then spread efficiently. Identifying what those pathways share, and where they differ, could begin to reveal generalizable principles applicable to primary prevention.
The paper concludes that building an evidence base for primary prevention now, even amid scientific uncertainty, is preferable to waiting for more data while conditions that could enable the next pandemic continue to develop.
Sources and further reading:
Holmes I, Vora NM, Gurley ES, et al. Assessing Evidence to Guide Primary Prevention of Pathogen X. Emerging Infectious Diseases, May 27, 2026