Gates Package — page 937

So how does that data make it up the chain, from a few people feeling sick to the WHO's decision to trigger a global response? To answer that question, we need to look in depth at how disease surveillance systems work. They're designed to gather data about health and illness in general, and so the better they run, the more likely they are to flag potential problems. One source of information, as you might expect, is the everyday operations of a health care system: doctors and nurses interacting with their patients. With a few exceptions such as the ones I mentioned earlier, a single case of some disease isn't going to set off alarm bells; most staffers at a clinic won't be unnerved by one individual who shows up with a cough and a fever. Generally, it's the suspicious-looking clusters of cases that will draw attention. This approach is called passive disease surveillance, and here's how it works. The staff at a clinic regularly pass information about the cases they're seeing up the chain to their public health agency. They won't share details about each case, but they will give the aggregate numbers of various illnesses. From there, ideally, the data will be fed into a regional or global database, which makes it easier for analysts to see patterns and respond accordingly. Countries in Africa, for example, enter aggregated data on certain diseases into something called the Integrated Disease Surveillance and Response system.1 Suppose their aggregate data shows an unusual number of patients with pneumonia whose cause couldn't be determined. That's a red flag, and hopefully an analyst for a state or national health agency who's monitoring the database will note the spike in cases and mark it for more investigation. In the world's most advanced health systems, the spike might be flagged by a computer system, which then notifies people at the health agency that they need to take a closer look.