Before I worked in surveillance systems and data dashboards, I worked in a district hospital operating room in Bassila, Benin, performing abdominal surgeries, laparoscopic procedures, and endoscopies for a rural population with limited access to specialized care. It’s about as far from a KPI framework as clinical work gets. But it’s where I first understood what “infrastructure” really means in public health — because I spent years working without much of it.
Resource constraints force clarity
In a well-resourced hospital system, inefficiency is often invisible — there’s enough slack in the system to absorb it. In a resource-limited district hospital, there’s no slack. Every gap in infrastructure shows up immediately: in delayed care, in outcomes, in what procedures are even possible to perform safely.
That environment forces a kind of clarity that’s easy to lose in better-resourced systems. You learn quickly which processes are actually essential and which are just how things have always been done. You learn to prioritize ruthlessly, because you don’t have the luxury of doing everything. That instinct — separating what’s essential from what’s just familiar — has stayed with me in every data and program role since.
Infrastructure is invisible until it’s missing
Public health infrastructure — data systems, surveillance protocols, supply chains, referral networks — tends to get attention only when it fails. Nobody notices a well-functioning immunization registry. Everybody notices when a coverage gap goes undetected for months.
Working in a district hospital taught me to see infrastructure as the thing that determines outcomes long before any individual clinical decision does. A skilled surgeon can’t overcome a supply chain that doesn’t reliably deliver what’s needed for a procedure. A well-designed treatment protocol can’t overcome a referral system with no reliable way to get a patient from a rural clinic to a hospital that can actually treat them.
This is the same lesson that shows up later in surveillance and data work, just at a different scale: the system around the intervention usually matters as much as the intervention itself.
Community trust is infrastructure too
Organizing a biannual surgical conference for regional physicians while working in Bassila taught me something I didn’t expect: that professional infrastructure — networks, shared knowledge, trust between providers — is just as real a constraint as physical infrastructure. Growing that conference’s attendance over time wasn’t just a networking exercise. It was building exactly the kind of provider-to-provider trust that makes a referral system actually function, and that lets surveillance data flow between a rural clinic and a regional or national system in the first place.
Public health programs designed without accounting for that human infrastructure — the relationships and trust that make a system work in practice, not just on paper — tend to underperform their technical design. The best surveillance protocol in the world doesn’t help if the clinic on the ground doesn’t trust the system enough to report into it consistently.
Bringing that lesson forward
I think about this constantly in data and program leadership roles now. It’s tempting to treat public health infrastructure as purely technical — better software, better dashboards, better data pipelines. Those matter. But the deepest lesson from working in a resource-limited surgical setting is that infrastructure is ultimately about reliability: can the people depending on this system trust that it will work, consistently, when they need it.
That’s the standard I try to hold every system I help build to now — not just whether it’s technically sophisticated, but whether the people on the ground can actually rely on it.