Disaster Victim Identification: Psychological Distress and Posttraumatic Stress in Dentists After the 2011 Fukushima Disaster.

OBJECTIVE: To evaluate the correlates of psychological responses in dentists who conducted disaster victim identification (DVI) in Fukushima following the 2011 earthquake/tsunami/nuclear disaster. METHOD: Self-report questionnaires were administered to 49 male dentists six to nine months after the disaster. Psychological distress and posttraumatic stress were measured using the General Health Questionnaire-30 (GHQ-30) and Impact of Event Scale-Revised (IES-R), respectively. Independent variables included sociodemographic characteristics, participant disaster exposures, DVI-related exposures, and fear of radiation exposure during DVI. Hierarchical multiple regression analysis was performed to examine independent-dependent variable relations. RESULTS: Thirty-eight participants (77.6%) had examined ≥ 40 corpses, 20 (40.8%) reported ≥ 4 corpse-related exposures, and six (12.2%) reported ≥ 5 gruesome corpse exposures. Mean (SD) GHQ-30 and IES-R scores were 5.08 (5.31) and 9.90 (10.1), respectively. Higher levels of psychological distress were associated with younger age (adjusted ß = -0.29), extensive property loss (ß = 0.34), and anxiety for the future (ß = 0.33). Higher levels of posttraumatic stress were associated with extensive property loss (adjusted R2 = 17.7%, ß = 0.30). Neither outcome was associated with DVI-related exposures or fear of radiation exposure during DVI (p < 0.05). CONCLUSIONS: Dentists' psychological burden was associated with disaster, but not DVI, exposures.

Use of Facial Recognition Software to Identify Disaster Victims With Facial Injuries.

OBJECTIVE: After large-scale disasters, victim identification frequently presents a challenge and a priority for responders attempting to reunite families and ensure proper identification of deceased persons. The purpose of this investigation was to determine whether currently commercially available facial recognition software can successfully identify disaster victims with facial injuries. METHODS: Photos of 106 people were taken before and after application of moulage designed to simulate traumatic facial injuries. These photos as well as photos from volunteers' personal photo collections were analyzed by using facial recognition software to determine whether this technology could accurately identify a person with facial injuries. RESULTS: The study results suggest that a responder could expect to get a correct match between submitted photos and photos of injured patients between 39% and 45% of the time and a much higher percentage of correct returns if submitted photos were of optimal quality with percentages correct exceeding 90% in most situations. CONCLUSIONS: The present results suggest that the use of this software would provide significant benefit to responders. Although a correct result was returned only 40% of the time, this would still likely represent a benefit for a responder trying to identify hundreds or thousands of victims. (Disaster Med Public Health Preparedness. 2017;11:568-572).

A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

Estruturação da vigilância epidemiológica em situação de emergência em saúde pública decorrente de incêndio em boate no município de Santa Maria, RS / Structuring epidemiological surveillance in an emergency situation in public health due to a fire in a nightclub in the municipality of Santa Maria, RS, Brazil

O objetivo deste trabalho é descrever a experiência da estruturação do gerenciamento das informações para VE a em situação de emergência em saúde pública, decorrente do incêndio da casa noturna de Santa Maria, RS. (AU)

Clínica postraumática tras una catástrofe: Madrid, 11M-2004 / No disponible

En el presente artículo se describe, tras una breve aproximación al concepto de trauma, la atención psicológica prestada a la población infanto-juvenil tras los atentados del 11-M en Madrid, puesta en marcha por la Oficina de Salud Mental de la Comunidad de Madrid y en especial las características sociodemográficas y la sintomatología observada y la intervención realizada desde el Centro de Salud Mental de Alcalá de Henares (AU)

No disponible