Abstract: Disclosed are various embodiments for a rapid disaster response management system. In one embodiment, data is received indicating a plurality of event drivers for a first plurality of geographic areas respecting one or more historical events. Data is received indicating whether individual ones of the plurality of geographic areas were assigned first disaster designations for the one or more historical events. A machine learning model is trained to determine correlations between the plurality of event drivers and the first disaster designations.

Abstract: Disclosed are various embodiments for the visualization and analysis of therapeutic regimen effects on human physical performance metrics. In one embodiment, data is obtained respecting at least one population of individuals having a respective physical impairment. The data indicates for each of the individuals a respective subset of a set of therapeutic regimens used to treat the respective physical impairment, and a set of performance measures of the respective individual following the respective subset of the set of therapeutic regimens. The data is analyzed to automatically determine a reduced set of therapeutic regimens and a reduced set of performance measures. A user interface is generated that facilitates a comparison of individual ones of the reduced set of therapeutic regimens to the reduced set of performance measures for the at least one population.