Optimizing automated external defibrillator incremental deployment to improve out-of-hospital cardiac arrest...

Public access defibrillation (PAD) is critical for out-of-hospital cardiac arrest (OHCA) response, yet the effectiveness of existing automated external defibrillator (AED) networks remains limited in many urban settings. Evidence is lacking on how incremental AED deployment translates into coverage gains and when diminishing returns occur, particularly in resource-constrained cities.

A retrospective spatial analysis was conducted using Utstein-compliant OHCA registry data from Haikou City, China (2015-2021). AED coverage was assessed using Euclidean distance across response radii of 100-500 m. Incremental AED deployment was simulated using the maximal covering location problem (MCLP) model while holding the existing network fixed. Changes in coverage, marginal gains, saturation thresholds, and optimized location types were evaluated using geographic information system methods.

Among 5792 eligible OHCA events, baseline AED coverage was limited (14.6% within 100 m; 45.7% within 500 m). Incremental deployment produced rapid early coverage gains across all distance thresholds, followed by diminishing marginal returns and eventual saturation. Near-saturation required substantially more AEDs at shorter radii (approximately 1467 additional devices at 100 m) compared with larger radii (308-499 devices at 300-500 m). Optimized deployment shifted priority toward restaurants and commercial/industrial settings, while home or private residence, transportation hubs, and government/educational institution yielded lower marginal gains despite hosting most existing AEDs.

Existing AED networks provide limited OHCA coverage due to spatial mismatch between placement and demand. MCLP-guided deployment shows early gains but diminishing returns, supporting phased, locally-calibrated expansion that maximizes effective emergency access, especially in resource-constrained settings.