Why Infectious and Chronic Disease Should Not Be Studied in Silos
For most of the past century, public health science has organized itself around a clean division of labor. Infectious disease specialists studied acute exposures, transmission, immune response, and outbreaks. Chronic disease specialists studied cardiovascular conditions, diabetes, cancer, and the long arc of behavioral and environmental risk. The two fields developed separate journals, separate funding streams, separate training pathways, separate surveillance systems, and largely separate clinical infrastructure.
The division has produced real scientific advances within each domain. It has also produced a consistent and largely unaddressed blind spot: the populations who carry both burdens at once.
In Houston, where I work, that population is large and concentrated. Black and Hispanic adults experience higher rates of hypertension, diabetes, cardiovascular disease, and obesity than their white counterparts and they also experience higher rates of acute infection from the diseases that have most stressed public health systems in recent years, from HIV to influenza to COVID-19. The same communities show up in both the chronic disease ledger and the infectious disease ledger. They have always been showing up in both. The field has just been organized in a way that makes it difficult to see them as a single phenomenon.
At the Center for Transformative Health, we argue this organizational separation has costs we have not adequately reckoned with. Specifically, that infectious and chronic disease are not separate domains that occasionally intersect. They are interacting systems that shape each other, in both directions, and the interaction is concentrated in the populations the field has been least equipped to study well.
What the bidirectional argument is
The argument is straightforward in principle, even if it has been hard to operationalize.
Infections shape chronic disease trajectories. We have known for decades that some infections produce chronic sequelae (i.e. hepatitis to liver disease, HPV to cervical cancer, H. pylori to gastric cancer). COVID-19 has dramatically expanded the range of infections we now know can produce chronic post-acute conditions, and Long COVID has forced the field to confront that this is not an exotic phenomenon but a common one. Infections leave damage. Some of that damage becomes chronic disease. We have substantially undercounted how often this happens, in part because the surveillance and clinical infrastructure for tracking infection-to-chronic-disease pathways was never built at scale.
Chronic disease shapes vulnerability to infection and recovery from it. Hypertension, diabetes, obesity, and cardiovascular disease all increase the severity of acute infection and the likelihood of complications. They also slow recovery and increase the probability that an acute infection becomes a chronic problem. Populations with high baseline chronic disease burden are populations that experience worse infectious disease outcomes not because of separate risks, but because chronic and infectious disease are biologically connected through shared mechanisms of inflammation, vascular function, and immune response.
The communities that carry the highest burden of both are the communities where the bidirectional relationship is most consequential, most clinically urgent, and least studied. This is not coincidence. The field's siloed organization made it predictable.
Why the silo persists
A reasonable question: if the bidirectional relationship is so significant, why has the field been so slow to address it?
Part of the answer is institutional. NIH study sections are organized by disease and by mechanism. Funding streams are often disease-specific. Specialty training in infectious disease is separate from specialty training in chronic disease management. Surveillance systems collect data on infectious disease outcomes through one infrastructure (CDC NNDSS, WHO reporting, lab-based surveillance) and chronic disease outcomes through another (BRFSS, NHANES, vital statistics, EHR-based registries). A research enterprise organized into silos produces evidence within silos, even when the underlying biology and the underlying populations refuse to respect the boundaries.
Part of the answer is also methodological. Studying a bidirectional relationship requires data infrastructure that follows individuals across both infectious and chronic disease events, ideally over years. That infrastructure exists in some places (large cohort studies, integrated health systems) but not in most of the populations where the relationship matters most. Communities that have been undersurveilled for both infectious and chronic disease are doubly invisible to research that requires high-quality data on both.
Lastly, part of the answer is conceptual. The framework that would make the bidirectional relationship visible has not been adequately developed in mainstream public health. Treating it as a defined area of study with named mechanisms, accepted measurement approaches, and a research community oriented toward it is how fields advance. That work is underway in some quarters but has not yet consolidated.
What the field should do differently
CTH's argument is that the bidirectional infection-chronic disease interface should be named, studied, and resourced as a defined research domain in its own right. Concretely, this means several things.
Surveillance systems should be built to track infectious-to-chronic-disease pathways at the population level, particularly in communities carrying high baseline burden of both. Long COVID is the immediate test case — we are learning in real time how badly the existing infrastructure handles a chronic post-acute infectious syndrome — but the principle generalizes.
Clinical care should integrate the recognition that acute infections in patients with chronic disease are different events than acute infections in healthier patients, with different recovery trajectories and different long-term implications. Care models, follow-up protocols, and rehabilitation pathways should reflect that difference.
Research funding should support work explicitly at the interface, not only work within the silos. NIH, foundation, and federal contracting opportunities for studies that follow populations across infectious and chronic disease events, with the analytical and conceptual frameworks to interpret what they find, would catalyze a research community that currently lacks institutional definition.
And research enterprises in communities carrying both burdens — communities that have been studied through one disease frame at a time, often without seeing their full health pattern represented — should be resourced to lead this work. Closing the gap between institutional research and the lived health of communities where the bidirectional relationship is most consequential is, in our view, one of the most important things public health science can do in the next decade.
A note on where this work lives
The argument summarized here is developed in fuller form in a forthcoming Viewpoint paper in Clinical Infectious Diseases. CTH's research programs in Long COVID and Post-Acute Infection, and in Infection–Chronic Disease Interactions, are organized around testing components of this framework empirically. We welcome conversations with researchers, funders, and partners working in adjacent territory.