Confronting mobile phone signal coverage and helicopter emergency medical service travel time: A geospatial analysis in the northwest macro-region of Paraná State, Brazil.

ABSTRACT

OBJECTIVE: The aim of this study was to conduct a detailed geospatial analysis of mobile phone signal coverage in the northwest macro-region of Paraná State, Brazil, seeking to identify areas where limitations in coverage may be related to lengthy travel times of the helicopter emergency medical service (HEMS) for the assistance of victims of road traffic injuries (RTIs). METHODS: An observational study was conducted to examine mobile phone signal coverage and HEMS travel times from 2017 to 2021. HEMS travel times were categorized into four groups T1 (0-15 min), T2 (16-30 min), T3 (31-45 min), and T4 (over 45 min). Empirical Bayesian Kriging was used to map areas with low mobile signal coverage. The Kruskal-Wallis test and Dwass-Steel-Critchlow-Fligner comparative analyses were performed to explore how mobile signal coverage relates to HEMS travel times to RTI locations. RESULTS: There were 470 occurrences of RTIs attended by HEMS, of which 108 (23%) resulted in on-site fatalities. Among these deaths, 47 (26.85%) occurred in areas with low mobile phone signal coverage ("shadow areas"). Low mobile phone signal coverage identified at 175 (37.24%) RTIs locations, was unevenly distributed across the macro-region. The lowest medians of mobile signal quality were predominantly found in areas with HEMS travel times exceeding 30 min, corresponding to signal strength values of -98.44 (T3) and -100.75 (T4) dBm. This scenario represents a challenge for effective communication to activate HEMS. In the multiple comparison analysis among travel time groups, significant differences were observed between T1 and T2 (p < 0.001), T1 and T3 (p < 0.001), T1 and T4 (p < 0.001), and T2 and T3 (p < 0.001), indicating a potential association between lower mobile phone signal coverage and longer HEMS travel times. CONCLUSION: It can be concluded that poor mobile phone signals in remote areas can hinder HEMS activation, potentially delaying the start of treatment for RTIs. Identification of the shadow areas can help communication and health managers in designing and implementing the necessary changes to improve mobile phone signal coverage and consequently reduce delays in the initial response to RTIs.