The convergence approach may be critical to improving early situational awareness in hostile radioactive environments.

This study explores the impact of a simulated radiological dispersal device (RDD) event in an urban area on young adults around 20 years old. The RDD releases radioactive Cs-137 (7.0E+3 Ci), a common industrial sterilization source. The study aims to demonstrate that combining computational codes and epidemiological models can produce valuable data to guide initial actions when confronting a hostile radioactive environment. The HotSpot Health Physics and RESRAD-RDD codes were used in the simulation to evaluate the event's initial phase. The codes were executed together, and the HotSpot output data was input into RESRAD-RDD. Based on simulated radiation dose levels, estimated doses were incorporated into radioepidemiological models proposed by the Committee on Biological Effects of Ionizing Radiation (BEIR V or VII report). Despite limitations, data transfer between the models revealed no discontinuities or antagonisms. Radiation doses were simulated under three exposure conditions and two atmospheric release modes (day or night), suggesting that atmospheric conditions, sex, and exposure routine can strongly influence the perception of radiation impacts. This combination of methods can increase situational awareness and help with decision-making and developing coping strategies.