Given the increase in flood events in recent years, accurate flood risk assessment is an important component of flood mitigation in urban areas. This research aims to develop updated and accurate flood risk maps in the Don River Watershed within the Great Toronto Area (GTA). The risk maps use geographical information systems (GIS) and multi-criteria analysis along with the application of Analytical Hierarchy Process methods to define and quantify the optimal selection of weights for the criteria that contribute to flood risk. The flood hazard maps were generated for four scenarios, each with different criteria (S1, S2, S3, and S4). The base case scenario (S1) is the most accurate, since it takes into account the floodplain map developed by the Toronto and Region Conservation Authority. It also considers distance to streams (DS), height above nearest drainage (HAND), slope (S), and the Curve Number (CN). S2 only considers DS, HAND, and CN, whereas S3 considers effective precipitation (EP), DS, HAND, and S. Lastly, S4 considers total precipitation (TP), DS, HAND, S, and CN. In addition to the flood hazard, the social and economic vulnerability was included to determine the total flood vulnerability in the watershed under three scenarios; the first one giving a higher importance to the social vulnerability, the second one giving equal importance to both social and economic vulnerability, and the third one giving more importance to the economic vulnerability. The results for each of the four flood scenarios show that the flood risk generated for S2 is the most similar to the base case (S1), followed by S3 and S4. The inclusion of social and economic vulnerability highlights the impacts of floods that are typically ignored in practice. It will allow watershed managers to make more informed decisions for flood mitigation and protection. The most important outcome of this research is that by only using the digital elevation model, the census data, the streams, land use, and soil type layers, it is possible to obtain a reliable flood risk map (S2) using a simplified method as compared to more complex flood risk methods that use hydraulic and hydrological models to generate flood hazard maps (as was the case for S1).

Amongst all natural disasters, floods have the greatest economic and social impacts worldwide, and their frequency is expected to increase due to climate change. Therefore, improved flood risk assessment is important for implementing flood mitigation measures in urban areas. The increasing need for quantifying the impacts of flooding have resulted in the development of methods for flood risk assessment. The aim of this study was to quantify flood risk under climate change scenarios in the Rockcliffe area within the Humber River watershed in Toronto, Canada, by using the Comprehensive Approach to Probabilistic Risk Assessment (CAPRA) method. CAPRA is a platform for stochastic disaster risk assessment that allows for the characterization of uncertainty in the underlying numerical models. The risk was obtained by integrating the (i) flood hazard, which considered future rainfall based on the Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5) for three time periods (short-term: 2020–2049, medium-term: 2040–2069, and long-term: 2070–2099); (ii) exposed assets within a flood-prone region; (iii) vulnerability functions, which quantified the damage to an asset at different hazard levels. The results revealed that rainfall intensities are likely to increase during the 21st century in the study area, leading to an increase in flood hazards, higher economic costs, and social impacts for the majority of the scenarios. The highest impacts were found for the climate scenario RCP 8.5 for the long-term period and the lowest for RCP 4.5 for the short-term period. The results from this modeling approach can be used for planning purposes in a floodplain management study. The modeling approach identifies critical areas that need to be protected to mitigate future flood risks. Higher resolution climate change and field data are needed to obtain detailed results required for a final design that will mitigate these risks.

The growing complexity of the environment makes explicit the fact that Human Social Systems must develop mechanisms that allow them to increase agility in decision-making. An alternative to achieve this is found in Collective Intelligence, which has been widely studied in Natural Social Systems, in Artificial Social Systems, and in Human Social Systems. Despite the research carried out in this last field, there is no clarity regarding the aspects that facilitate its understanding and emergency. This document identifies the structural and dynamic features in different Collective Intelligence models selected in the context of Human Social Systems. Finally, the possibility of proposing other features to be considered is discussed from the review of the factors that have explained the emergence of Collective Intelligence in Natural and Artificial Social Systems, and they are assessed in order to design Collective Intelligence models in future research.

La atención prehospitalaria es cada vez más reconocida en todo el mundo como una parte fundamental en el sistema de salud, sin embargo, no se le da mucha importancia en cuanto al control de infecciones. Para evitar que las ambulancias sean un foco de trasmisión, se deben implementar protocolos de limpieza y desinfección para disminuir las cargas bacterianas, ya que las ambulancias cuentan con dispositivos médicos que están en contacto con el paciente, y si estos no reciben la limpieza adecuada, se convierten en alto riesgo de infección; además se debe tener en cuenta que no siempre hay la información clara de si el paciente puede tener algún tipo de enfermedad infectocontagiosa, o incluso los profesionales de la salud algunas veces pueden padecer algún tipo de patología o han estado expuestos a pacientes quienes son posibles portadores de microorganismos, y al momento de realizar el traslado de ellos, estos patógenos se pueden propagar, lo cual es un evento adverso que atenta contra la seguridad del paciente y el mismo equipo sanitario, ya que estas infecciones podrían llevar a estancias hospitalarias innecesarias, o incluso a la muerte. Son pocos los estudios que se han realizado sobre estos factores de riesgo que están presentes en el transporte asistencial, por lo tanto, se considera un reto mundial para combatir esta exposición biológica.