Predictive Sensitivity Maps: Visualizing and Quantifying Parameter Sensitivity in Spatially Explicit Epidemic Networks

Inspired by Giles et al. (2020) and Saunders & Schwartz (2021), who emphasize the importance of parameter sensitivity in predicting disease spread, this research proposes an interactive tool that produces "sensitivity maps" overlaying real-world networks. By systematically perturbing key parameters (e.g., transmission rate, immunity duration, travel flow) at different nodes or regions, the tool would visualize the resulting shifts in outbreak size, speed, or predictability. Such maps could highlight geographic or demographic "tipping points"—locations or groups where modest parameter changes trigger disproportionate epidemic responses. This approach is innovative because it translates abstract sensitivity analyses into actionable, spatially resolved guidance for public health officials, supporting more precise and adaptive responses.

References:

1. Trip duration drives shift in travel network structure with implications for the predictability of spatial disease spread. J. Giles, D. Cummings, B. Grenfell, A. Tatem, Elisabeth Zu Erbach-Schoenberg, C. Metcalf, A. Wesolowski (2020). medRxiv.
2. COVID-19 vaccination strategies depend on the underlying network of social interactions. Helena A Saunders, J. Schwartz (2021). Scientific Reports.