Long ago, Edward Jenner made medical history by inoculating a young boy with cowpox and demonstrating protection against smallpox. Jenner had no idea why it worked, he just rolled with it, and thus inoculation was born. For nearly two centuries, vaccine developers operated in a similar vein, testing their creations in large populations and hoping for the best, often without fully understanding the biological mechanisms working underneath.
Today, scientists have a powerful tool that Jenner could only dream of: correlates of protection. These biological markers can predict whether a vaccine will work before testing it in tens of thousands of people, transforming how we develop vaccines, potentially saving years of research time and billions of dollars. But the terminology around these correlates is notoriously confusing and has caused me many hours of sighing and furrowing my brow. Therefore, I thought I’d provide a light introduction to the essential concepts.
A single drop of blood holds many stories—assays are how we listen. Your lab collaborator sends you a spreadsheet of data with columns labelled “ELISA_OD,” “PRNT50,” “HI_titre,” and “PVNT_ID50.” You know this has something to do with how many antibodies are in a sample, but what do these numbers actually mean? Which ones can you trust? And how is it that the same sample can tell a different story depending on which assay you look at? The key to answering these questions is understanding serological assays.
Defining infection is like reading tarot cards - the interpretation depends on who’s asking and what they’re looking for. You wake up with a sore throat. You take a lateral flow test, negative. The next day, still negative. A PCR comes back “positive”. Meanwhile, your flatmate tested positive on a rapid test but felt fine throughout.
So who was infected? You, your friend, both, or neither?