So let’s get practical. How have correlates of protection actually been used to license vaccines? What can we learn from both the successes and failures? And what does this mean for the next pandemic or the next vaccine waiting in the pipeline?
The Early Days: Stumbling Toward Success Remember Edward Jenner from last time? While he had no clue about correlates of protection (the term wouldn’t exist for another two centuries), the seeds were planted early.
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.
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?
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?
It sounds simple, but defining someone as “infected” is not as clear-cut as it first appears.
A Bayesian tool for inferring infection timing and antibody kinetics from longitudinal serological data, validated with SARS-CoV-2 data from The Gambia.