The objective of this research was to establish a method of identifying locations with a high concentration of individuals `at risk\u27 of becoming homeless in order to select mitigation strategies that target the specific needs of the individuals. Each state was evaluated based on the concentration of characteristics that may contribute to homelessness. These characteristics include: low median incomes, high unemployment rates, high housing cost-burdens, high concentrations of veterans and single-mother households, and high rates of mental disabilities and substance abuse reports. A differentiation was made between temporary and chronic homelessness as the mitigation strategies that prove to be the most effective varies between the two; temporary homelessness typically only involves economic factors while chronic homelessness is thought to be the result of existing social vulnerabilities that are compounded by economic factors. The median value of each characteristic was identified for each state. These values were then calculated as a percentage of the national median values and compiled. This compilation of values was imported into ArcMap and evaluated using the quantile function in order to identify the states that comprise the top twenty percent of risk. This process was then utilized to evaluate selected states on the county level. This method proved effective at identifying areas with a high concentration of characteristics that may contribute to homelessness. Therefore, it is concluded that areas with a high concentration of individuals `at risk\u27 of becoming homeless can be identified statistically and graphically by following the method that was established. By following this method, mitigation strategies that target the specific needs of the individuals can be selected and implemented. This is significant because funding is currently being cut for many social welfare programs and it is highly unlikely that there will be funding that is significant enough to address each and every need of the homeless population in the near future; addressing the characteristics that are shown to be highly concentrated in particular locations could be more efficient and cost-effective than attempting to address all characteristics of homelessness
