Examining the Spatial Concentration and Longitudinal Stability of Mental Health-related Calls for Service at Micro Places over a 10-year Period

Prior research on crime and place has shown that crime incidents and calls for service (CFS) are highly concentrated at micro places and that the concentration patterns are stable over time. However, little is known about the stability of the geographical distribution of mental health-related (MH) CFS in suburban and rural contexts. This study addresses this gap by analyzing 10-year MH CFS data from Roanoke County Police Department in Southwestern Virginia. We geocoded 4,456 mental health calls from 2013 to 2022 to the nearest street segments in Roanoke County (totally 14,201 street segments). The results show an extreme spatial concentration of MH calls, with the traditional metric, 50% observed at only 0.21% to 0.36% of street segments annually. Using the generalized 50-X metric, 50% of MH calls were generated by about 6.82% to 13.09% of segments in a given year. The generalized Gini coefficient of 0.865 indicates high spatial inequality in the distribution of MH calls. To assess spatial stability over time, we used the spatial point pattern tests (SPPT) and group-based trajectory modeling (GBTM). SPPT results show that robust S-indices between any consecutive two years are greater than 0.94, indicating high longitudinal spatial stability of MH calls. The trajectory analysis identified a 5-group model that fitted the data the best. While the majority of the street segments were either free of any MH calls or had a very low rate of mental health calls over the 10-year study period, a small proportion of street segments (n = 98) showed various developmental patterns of MH calls, including high-rate decreasing, moderate increasing, and moderate decreasing trajectory groups.