Dialing 911: Spatial Distribution of 911 Calls in Richmond County, NC A Look into Possible Spatial Trends Using GIS Abstract Every day, 911 dispatchers respond to emergency calls throughout the country. The goal of this project was to examine any possible correlations between the frequency and spatial distribution of 911 calls placed when compared to US Census data for Richmond County, NC. Using parcel data for the county, the researchers hypothesized there would be more calls placed in areas with a lower average income and in areas with higher minority populations. This was done by using ArcGIS to join 911 data with Richmond County parcel data. This graph was then compared to choropleth maps of the average incomes and the spatial distribution of minorities within the county. Results showed that more 911 calls came from areas with an average lower income and areas that had low minority populations percent. These findings can help emergency officials prepare for future call increases. Trends in 911 Data When a 911 call is received, emergency medical services aim to have an ambulance on scene in 10 minutes or less. Emergency management officials try to cover an ever-increasing call volume with limited apparatus and employees. Some organizations try to study patterns within 911 call distribution and peak demand periods. (Rajapagopalan 814). This allows organizations to plan for periods of high demand in advance. Based on one study, there is a higher demand for emergency response in areas with people who live below the poverty line, areas with a higher percentage of minorities, and in areas with older people (Cardigan and Bugarin 619) Areas of higher-income typically have a lower demand for emergency maintenance response. Due to the trend noted by Cardigan and Bugarin, this project aims to see if there are similar correlations within Richmond County, especially in areas of lower income and higher minority populations. Hypothesis: 911 Emergency medical calls occur more frequently in areas with a higher percentage of minority populations and in low income areas. Methodology Sorted and matched 911 Excel data with data in parcel set -entries marked as erroneous or as false calls were eliminated -addresses from excel -data that did not match with parcel data were eliminated Completed spatial join of excel data with parcel data Calculated minority percentages from Census data in Excel and joined the data with GIS Census data layer in ArcMap Created choropleth map of minorities in Richmond County Plotted 911 calls based on parcel location as points -overlaid point data with choropleth map Calculated average income from Census data in Excel and joined with GIS census layer in ArcMap Created choropleth map of income data Overlaid point data (911 calls) with choropleth income map Conclusion 911 calls occur more often in areas with lower than average incomes; the majority of calls are also coming from areas with a smaller percentage of minorities. Clusters of calls appear in Rockingham and Hamlet in places where there is both lower income areas and fewer minorities. These results disagree with the hypothesis in that we expected more calls to come from areas where there was a more diverse population. This study seemed to show that 911 calls in Richmond county are clustered more in areas with lower than average incomes with less diverse populations. One major limitation of this study is that many of the addresses from the 911 Excel data file could not be used because they were associated with an erroneous entry, a false call, or the address did not match with the GIS parcel set. Alter Emergency Medical Dispatch program format to simplify joins with ArcGIS Emergency management officials can use these trends to distribute emergency resources in areas more efficiently. Results Majority of calls received are clustered in downtown Rockingham, an area with an average income of $40,000 - $50,000 per year. -fewers calls were placed from the high income areas, averaging $75,000- $279,000 per year. Majority of calls also correlated with areas where there was less than 14% of minority population. Again, most of the calls are centered in downtown Rockingham and in the upper regions of Hamlet. Data Sources -Cadigan, Robert T., and Carol E. Bugarin. “Predicting Demand for Emergency Ambulance Service.” Annals of Emergency Medicine. 18(6): Online. -ESRI, , US Median Household Income. -ESRI, , USA Population Density -Rajapagopalan, Hari K., Cem Saydam and Jing Xiao. “ A multiperiod set covering location model for dynamic redeployment of ambulances.” Computers & Operations Research. 35(3): Online. -Richmond County Emergency Management, , 911 Emergency Medical Dispatch Information (1 December February 2010). -Richmond County GIS, , Richmond County Parcels Nick Stoll Grainne O’Grady Renee Jutras Hillary Fox