Right now, somewhere in your city or your country, someone is sick with something that spreads fast from person to person. Their body might not be fighting it off successfully; they might not even realize they're sick yet, or they might have already picked up the phone and called a doctor.

The questions that keep public health professionals up at night are deceptively simple. How do we know that this person is sick, and how can we know sooner? How do we see patterns before they become crises, and catch an outbreak while it's still small enough to stop? And very importantly, what information do we actually need to collect to make all of that possible?

I'm Nancy Ejuma, and this post is about something fundamental to public health IT: how public health actually sees what's happening in communities.

This isn't the dramatic emergency response you see on the news. It's way, way quieter than that. It's really more like a constant effort to gather information, connect the dots, and understand a community's health before things start to fall apart.

The first thing to understand is that public health is not the same as healthcare. When you go to your doctor, they're focused on you. They're focused on your symptoms, your history, and your treatment. That's healthcare, and it operates the way it's supposed to because it's personal and individual, and it's rightly focused on you.

Public health is different. Public health is asking what's happening to everyone. What patterns show up across the whole population? Where are the risks? Where are the gaps? To answer those questions, public health needs information. It needs lots of data, and it needs to get it from lots of different places.

One way to really understand what that looks like is to imagine someone asking you to decide whether your community has a safe water supply. You can't just ask one person. You would need to know how many people have access to the water, test that water at different points in the system, examine the pipes it travels through, and find out whether anyone's actually gotten sick from using and drinking it.

The same logic applies if I want to understand whether a disease is spreading. You can't just wait for people to come to the hospital. You need to know who's getting sick, where they live, who they've been around, what symptoms they had, when they got sick, and any other details that help you understand how and where the disease could have spread.

That information comes from an enormous range of places. It comes from doctors, labs, hospitals, people who call or text hotlines, community health workers, health inspectors, sensors, and surveys. All of that information flows from all those places and lands with public health.

When someone goes to a doctor, and it turns out they have a serious disease, the doctor has to know whether that disease is one that local law requires to be reported. If the law says yes, they report it using whatever system is in place for sending that positive result to their local health department. We call that a notifiable disease, and reporting it isn't optional. The law requires it whether the doctor wants to or not. One thing you can actually do for yourself is look up the list of notifiable conditions in your community. It gives you a real sense of the diseases your health department is actively monitoring and working to control.

Separately, in most communities, if you get a vaccine, that information goes into an immunization registry, which is simply a database that tracks who got vaccinated and when. If you get a lab test and the result is positive, the lab may be required to send that result to a few different destinations. They send it to your doctor, the person who ordered it, but they may also have to send it to a public health laboratory or to a disease surveillance system.

If you went to the hospital, that encounter gets recorded in the hospital's system. And depending on where you are, the thing that brought you to the hospital, what we call the chief complaint, flows to public health through something called syndromic surveillance. This is where public health looks at de-identified emergency room data to try to spot patterns of symptoms that no individual clinician or hospital might notice until it's too late.

In one real case, syndromic surveillance helped a public health agency in Georgia realize that a single local water park had contaminated water. There was a sudden spike in gastrointestinal symptoms, and a lot of people were showing up in different emergency rooms complaining of diarrhea and cramping. By searching keywords across all that ER data, investigators were able to link the cases back to a single water park that had opened without a permit. They shut it down and treated the water to kill the parasite that was making people sick.

All of that data collection and response happens without you necessarily knowing it's there. And none of this is new. Public health has been collecting this kind of information for decades. What has really changed is the scale and the speed at which it can be gathered.

Before there were computers, a health department would receive paper forms, and a nurse would read through them and write the information into a ledger by hand, looking for patterns, making phone calls, and investigating in person as she went. It was slow and labor-intensive, but it worked.

We don't have to do all of that today because we now have systems capable of collecting information from hundreds of thousands of people in real time. But whether we're talking about the paper era or the systems we use now, the fundamental question hasn't changed. What does public health really need to know to protect communities, and how should it get that information?

The broader public health community has settled on a set of eleven core questions that reveal exactly what it needs to know. That's a lot to unpack in one post, so I'll be publishing a separate piece that walks through each question individually, explains why public health needs to answer it, and shows you exactly where that data comes from. For now, what matters most is this: public health doesn't rely on one data source, and it never has. It is, and always has been, an ecosystem. Understanding that ecosystem is the foundation for understanding how your own health information actually moves through the system.

The questions public health tries to answer range from "who and where is the population and where" to "what did public health do, and did it work?" Each of those questions pulls from a different corner of that ecosystem. Population counts come from census records and civil registration, while information about who's getting sick comes from hospitals, laboratories, and disease reports. Data on hazards come from environmental testing and inspections, and information on whether services are actually reaching people comes from program records and surveys. Even information about what communities believe and trust often has a source, such as hotlines, social media, and community health workers.

Every piece of data collected is trying to answer one of those questions, and together they build a single, coherent picture of a community's health.

In some places, the systems work well, and data flows smoothly from one point to the next. Information reaches decision-makers quickly, so action happens without much delay. In other places, systems are fragmented, and the data gets stuck. Information arrives late, and sometimes opportunities to intervene are missed entirely.

No matter where you are, public health doesn't collect information to spy on people. What it collects is used to protect communities by catching outbreaks early, directing resources to where they're needed most, and making sure services actually reach the people who need them.

So the real question isn't whether public health should collect information. It's how we do it in a way that protects both individual privacy and public safety, how we collect exactly what we need without collecting more than that, how we make sure information is used for its intended purpose and nothing else, and how we make sure people actually know what's happening to their data.

Those are the hard questions, and they're the ones I'll be exploring in the posts ahead, one system at a time.

AI made PMs faster. Multiplayer mode is still broken.

A PM can summarize research, draft a PRD, and mock up a prototype before lunch. The hard part starts when the team has to decide what actually gets built.

Jira Product Discovery gives product teams one place to capture insights, prioritize ideas with consistent frameworks, and build living roadmaps stakeholders can rally around.

And because it’s connected to Jira, the context behind every decision stays with the work—so developers and their agents know not just what to build, but why.

AI helps PMs move faster. Jira Product Discovery helps the whole team build with confidence.

Get Started for Free.