I tested a Poisson regression on 18 months of call-for-service and intake data to forecast stray dog hotspots by census tract, and it cut missed pickups 22% in a 6-week pilot. Has anyone here calibrated deployment thresholds for similar models (e.g., minimum expected calls per shift) or tied TNVR scheduling for community cats to the same heat maps?
I’d set the ‘minimum expected calls per shift’ like a weather alert — pick the cutoff where a missed call’s cost equals rolling OT for an extra unit, then back-test by tract and season. For TNVR we smooth to 14 days and schedule traps 48–72 hours after a hotspot spike, weighted by colony/feeder reports (see https://bestfriends.org/resources/community-cat-program-handbook). What miss vs false-alarm cost ratio are you using?
That’s a solid result with a 22% cut in missed pickups! Have you considered adjusting your TNVR scheduling based on not just calls but also seasonal trends? That could give even more context to those heat maps.