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PURPOSE
The threat of national and international terrorism remains high. Preparation is the key requirement for the resilience of hospitals and out-of-hospital rescue forces. The scientific evidence for defining medical and tactical strategies often feeds on the analysis of real incidents and the lessons learned derived from them. This systematic review of the literature aims to identify and systematically report lessons learned from terrorist attacks since 2001.
METHODS
PubMed was used as a database using predefined search strategies and eligibility criteria. All countries that are part of the Organization for Economic Cooperation and Development (OECD) were included. The time frame was set between 2001 and 2018.
RESULTS
Finally 68 articles were included in the review. From these, 616 lessons learned were extracted and summarized into 15 categories. The data shows that despite the difference in attacks, countries, and casualties involved, many of the lessons learned are similar. We also found that the pattern of lessons learned is repeated continuously over the time period studied.
CONCLUSIONS
The lessons from terrorist attacks since 2001 follow a certain pattern and remained constant over time. Therefore, it seems to be more accurate to talk about lessons identified rather than lessons learned. To save as many victims as possible, protect rescue forces from harm, and to prepare hospitals at the best possible level it is important to implement the lessons identified in training and preparation.
Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia
(2022)
The current study evaluates the regional climate model REMO (v2015) and its new version REMO-iMOVE, including interactive vegetation and plant functional types (PFTs), over two Central Asian domains for the period of 2000–2015 at two different horizontal resolutions (0.44° and 0.11°). Various statistical metrices along with mean bias patterns for precipitation, temperature, and leaf area index have been used for the model evaluation. A better representation of the spatial pattern of precipitation is found at 0.11° resolution over most of Central Asia. Regarding the mean temperature, both model versions show a high level of agreement with the validation data, especially at the higher resolution. This also reduces the biases in maximum and minimum temperature. Generally, REMO-iMOVE shows an improvement regarding the temperature bias but produces a larger precipitation bias compared to the REMO conventional version with interannually static vegetation. Since the coupled version is capable to simulate the mean climate of Central Asia like its parent version, both can be used for impact studies and future projections. However, regarding the new vegetation scheme and its spatiotemporal representation exemplified by the leaf area index, REMO-iMOVE shows a clear advantage over REMO. This better simulation is caused by the implementation of more realistic and interactive vegetation and related atmospheric processes which consequently add value to the regional climate model.