Antigenic Drift as a 3D Random Walk Through Shape-Space
Every dot on the drift path is one month of real hemagglutinin mutation, walked as a correlated random step in a 3D antigenic map — the horizontal plane encodes antigenic distance, the vertical axis encodes time from the prior season to the next flu season.
- Seasonal change magnitude: controls how large each monthly mutation step is, exactly like the 2D version's slider — but here it directly scales the length of a 3D random-walk vector.
- Months: selection → flu season: sets how early the WHO-style committee has to commit to a strain, shortening how much real drift data they get to see before forecasting.
- Surveillance sample quality: adds directional noise to the committee's read of the drift trend — lower quality means their forecast vector points further from the true trajectory.
What the geometry actually computes
The vaccine strain position is a genuine forward extrapolation of the (possibly noisy) trend vector measured at the meeting point; the final vaccine match is the inverse of the real Euclidean distance between that forecast and where the true random walk actually ends up twelve months in — not a lookup table, an emergent geometric result of the walk itself.