Alpha-gal syndrome (AGS) is a tick bite-associated allergic condition induced by the lone star tick (Amblyomma americanum). Illinois had no confirmed AGS case data as of January 2026, when mandatory reporting began under the state's TICK Act, leaving practitioners without data to guide screening or resource allocation. We constructed a county-level proxy risk score using a Bayesian conditional autoregressive spatial model applied to three Illinois surveillance sources from 2019-2022: tick abundance, ehrlichiosis cases, and tick establishment status, all linked by a shared vector. Ehrlichiosis was modeled as a population-adjusted rate, ticks as a relative-intensity index, and establishment status as a fixed ecological component. The combined risk score identified a high-risk cluster in far southern Illinois that remained stable across alternative weighting scenarios. This approach is transferable to jurisdictions lacking direct AGS surveillance and offers a starting point for clinician education pending validation against confirmed case data.