I spent my early career as a physician — first as an emergency physician, then as a general surgeon, treating patients in district hospitals in Benin. Years later, I lead epidemiologic surveillance and data programs at health departments in the United States. On paper, those look like two different careers. In practice, they’re the same job, viewed from two different altitudes.
One patient at a time, then a population at a time
Clinical medicine teaches you to read a single case with total precision: this patient, this presentation, this decision, right now. Public health asks a version of the same question at scale — not “what’s wrong with this patient,” but “what’s happening across this population, and what do we do about it.”
The instinct doesn’t change. What changes is the unit of analysis. A surgeon has to notice the detail that changes a diagnosis. An epidemiologist has to notice the pattern in thousands of case reports that changes a response. Both require the same discipline: don’t trust the story until the evidence supports it, and don’t wait for perfect certainty to act when the stakes are high.
What clinical training gives you that a data background doesn’t
I’ve worked alongside excellent analysts who never set foot in a clinic, and their technical skills are often sharper than mine. But there’s something clinical experience gives you that’s hard to replicate from a spreadsheet: an instinct for what a number actually means for a person.
When a coverage dashboard shows a gap in immunization rates in a specific neighborhood, that gap isn’t abstract to me — it’s a family that has to take three buses to reach a clinic, or a parent who couldn’t get time off work for a same-day appointment. That grounding shapes how I build interventions. It’s the difference between a technically correct recommendation and one that actually accounts for why the gap exists in the first place.
Why I moved from treating patients to studying populations
The honest answer is that I kept running into the limits of one-on-one care. A physician can save the patient in front of them. But the conditions that bring that patient into the emergency room — a disease outbreak, a gap in vaccination access, a surveillance system that missed an early warning sign — are population-level problems. Fixing them requires population-level tools: epidemiology, data systems, program management, policy.
That’s why I went back for public health training, and later for the business and project management skills to actually run programs at scale, not just design them. Clinical instinct tells you what’s wrong. Public health training tells you where else it’s happening. Business and project management skills are what let you actually fix it — inside real budgets, real staffing constraints, and real bureaucracies.
The throughline
If there’s a single principle that survived the jump from surgery to surveillance, it’s this: rigor and urgency aren’t in tension — they’re the same requirement wearing different clothes. In a hospital, moving too slowly costs a life you can see. In public health, moving too slowly costs lives you often can’t see until much later, in a case count or a delayed outbreak response.
That’s what keeps me in this field. The tools are different. The stakes are the same.