Introduction: There has been much interest in spatial analysis of ALS to identify potential environmental or genetically caused clusters of disease. Results to date have been inconclusive. The Irish ALS register has been recently geocoded, presenting opportunity to perform a spatial analysis on national prospectively gathered data of incident cases over an 18-year period. Methods: 1,645 cases of ALS in Ireland from January 1995 to July 2013 were identified from the Irish ALS register. 1,638 cases were successfully geocoded. Census data from four censuses: 1996, 2002, 2006 & 2011 were used to calculate an average population for the period and standardized incidence rates (SIRs) were calculated for 3,355 areas (Electoral Divisions). Bayesian conditional auto-regression was applied to produce smoothed relative risks (RR). These were then mapped for all cases, males & females separately, and those under 55 vs over 55 at diagnosis. Bayesian and linear regression were used to examine the relationship between population density and RR. Results: Smoothed maps revealed no overall geographical pattern to ALS incidence in Ireland, although several areas of localized increased risk were identified. Stratified maps also suggested localized areas of increased RR, while dual analysis of the relationship between population density and RR of ALS yielded conflicting results, linear regression revealed a weak relationship. Discussion: In contrast to some previous studies our analysis did not reveal any large-scale geographic patterns of incidence, yet localized areas of moderately high risk were found in both urban and rural areas. Stratified maps by age revealed a larger number of cases in younger people in the area of County Cork - possibly of genetic cause. Bayesian auto-regression of population density failed to find a significant association with risk, however weighted linear regression of post Bayesian smoothed Risk revealed an association between population density and increased ALS risk. © 2014 Rooney et al.