mosquito to control malaria, or vaccinate every person to prevent
epidemics. Or the assumption that banking systems are naturally
stable and online content is highly contagious. It has also meant
hunting for new explanations: why cases of Guillain-Barré Syndrome
were appearing on Pacific Islands, why computer viruses persist for
so long, why most ideas struggle to spread as easily as diseases.
In outbreak analysis, the most significant moments aren’t the ones
where we’re right. It’s those moments when we realise we’ve been
wrong. When something doesn’t look quite right: a pattern catches
our eye, an exception breaks what we thought was the rule. Whether
we want an innovation to take off or an infection to decline, these are
the moments we need to reach as early as possible. The moments
that allow us to unravel chains of transmission, searching for weak
links, missing links, and unusual links. The moments that let us look
back, to work out how outbreaks really happened in the past. Then
look forward, to change how they happen in future.