We examine the forecast sensitivity of two epidemic models. The largest sensitivity occurs at the epidemic threshold. Unexpectedly, superspreading events show heightened sensitivity, with noise pushing epidemics to be much larger or smaller than predicted.

09.02.2026 22:14 — 👍 0    🔁 0    💬 0    📌 0

Sensitivity analysis of epidemic forecasting and spreading on networks with probability generating functions Abstract. Epidemic forecasting tools embrace the stochasticity and heterogeneity of disease spread to predict the growth and size of outbreaks. Conceptuall

royalsocietypublishing.org/rsif/article...

Check out new work with @willthompson.bsky.social, @chrisdanforth.bsky.social, J-G Young, & @lhd.bsky.social in the Journal of the Royal Society Interface!

09.02.2026 22:08 — 👍 6    🔁 2    💬 1    📌 0