Evaluating the performance of a climate-driven mortality model during heat waves and cold spells in Europe.

The impact of climate change on human health is a serious concern. In particular, changes in the frequency and intensity of heat waves and cold spells are of high relevance in terms of mortality and morbidity. This demonstrates the urgent need for reliable early-warning systems to help authorities prepare and respond to emergency situations. In this study, we evaluate the performance of a climate-driven mortality model to provide probabilistic predictions of exceeding emergency mortality thresholds for heat wave and cold spell scenarios. Daily mortality data corresponding to 187 NUTS2 regions across 16 countries in Europe were obtained from 1998-2003. Data were aggregated to 54 larger regions in Europe, defined according to similarities in population structure and climate. Location-specific average mortality rates, at given temperature intervals over the time period, were modelled to account for the increased mortality observed during both high and low temperature extremes and differing comfort temperatures between regions. Model parameters were estimated in a Bayesian framework, in order to generate probabilistic simulations of mortality across Europe for time periods of interest. For the heat wave scenario (1-15 August 2003), the model was successfully able to anticipate the occurrence or non-occurrence of mortality rates exceeding the emergency threshold (75th percentile of the mortality distribution) for 89% of the 54 regions, given a probability decision threshold of 70%. For the cold spell scenario (1-15 January 2003), mortality events in 69% of the regions were correctly anticipated with a probability decision threshold of 70%. By using a more conservative decision threshold of 30%, this proportion increased to 87%. Overall, the model performed better for the heat wave scenario. By replacing observed temperature data in the model with forecast temperature, from state-of-the-art European forecasting systems, probabilistic mortality predictions could potentially be made several months ahead of imminent heat waves and cold spells

RISK MANAGEMENT AT TECHNICAL FACILITIES DESIGNING, BUILDING AND COMMISSIONING

The publication subject is to show the risk management of complex technical facilities at a stage involving the design, construction, outfit by technology equipment, testing and commissioning. The safety of this technical facility is related to the entire technical facility because, as a result of the interconnections among different parts, the set of the safe parts is generally not safe. The safety also considers the dynamic evolution of the world. Therefore, it is going on managing the risks caused by all possible causes in time and space. Based on the original database of failures and accidents of technical facilities, which also included weaknesses in the area of design, building, construction, testing and commissioning, they are determined the basic categories of risk causes. Through the procedures of advanced risk disciplines, there are developed the tools for working with risks in the monitored stage of the technical facility aimed at ensuring the technical facility safety throughout its life time, namely: decision support system; and risk management plan. Both tools are in two versions. The book shortly summarizes results of specific research performed in project “Řízení rizik a bezpečnost složitých technologických objektů (RIRIZIBE)“ CZ.02.2.69/0.0 /0.0/16_018/000”. The detail results are in original Czech monograph, which is cited

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

uncertainty and complexity in the context of COVID-19

Although the first coronavirus disease 2019 (COVID-19) wave has peaked with the second wave underway, the world is still struggling to manage potential systemic risks and unpredictability of the pandemic. A particular challenge is the “superspreading” of the virus, which starts abruptly, is difficult to predict, and can quickly escalate into medical and socio-economic emergencies that contribute to long-lasting crises challenging our current ways of life. In these uncertain times, organizations and societies worldwide are faced with the need to develop appropriate strategies and intervention portfolios that require fast understanding of the complex interdependencies in our world and rapid, flexible action to contain the spread of the virus as quickly as possible, thus preventing further disastrous consequences of the pandemic. We integrate perspectives from systems sciences, epidemiology, biology, social networks, and organizational research in the context of the superspreading phenomenon to understand the complex system of COVID-19 pandemic and develop suggestions for interventions aimed at rapid responses.publishersversionpublishe

Crowdsourcing as a tool for urban emergency management: lessons from the literature and typology

Recently, citizen involvement has been increasingly used in urban disaster prevention and management, taking advantage of new ubiquitous and collaborative technologies. This scenario has created a unique opportunity to leverage the work of crowds of volunteers. As a result, crowdsourcing approaches for disaster prevention and management have been proposed and evaluated. However, the articulation of citizens, tasks, and outcomes as a continuous flow of knowledge generation reveals a complex ecosystem that requires coordination efforts to manage interdependencies in crowd work. To tackle this challenging problem, this paper extends to the context of urban emergency management the results of a previous study that investigates how crowd work is managed in crowdsourcing platforms applied to urban planning. The goal is to understand how crowdsourcing techniques and quality control dimensions used in urban planning could be used to support urban emergency management, especially in the context of mining-related dam outages. Through a systematic literature review, our study makes a comparison between crowdsourcing tools designed for urban planning and urban emergency management and proposes a five-dimension typology of quality in crowdsourcing, which can be leveraged for optimizing urban planning and emergency management processes

Assessing the cost-effectiveness of facility-based emergency care in low resource settings

Background Emergency conditions comprise nearly half of the total global burden of disease, and disproportionately affect low-resource settings (LRS). This burden of life-threatening yet treatable conditions can be ameliorated by effective, timely emergency care (EC) interventions, so significantly that the Disease Control Priorities project estimates over half of deaths in the lowest-income countries could be addressed though the implementation of effective EC. Interest in developing better facility-based EC is expanding rapidly, yet there is a large gap in the cost-effectiveness literature to support informed resource allocation. Distinguishing the "value for money" of EC is crucial, especially in contexts of extreme resources limitations. Developing robust and setting-specific data on the cost of implementing EC cultivates the ability to understand the impacts of, and plan improvements in, EC in LRS. The aim of this thesis was to investigate the cost-effectiveness of interventions forming a systematic approach to EC in health facilities in LRS. Aims and Objectives The primary aim of this research was to investigate the cost-effectiveness of implementing the WHO emergency care toolkit to reduce mortality related to emergency conditions in health facilities in an LRS. To achieve this aim, the following objectives were established: synthesise evidence relating to the costeffectiveness of EC in LRS, enumerate context specific costs of delivering facility-based EC, and retrospectively study the impact of implementing a low-cost set of EC interventions in low-resource EC naïve health facilities on cost and outcome (mortality), to derive a measure of cost effectiveness. Methods The dissertation is comprised of 3 studies. First, Chapter 3 undertakes a systematic review of literature on EC interventions in LRS, using PRISMA guidelines and the Consolidated Health Economics Evaluation Reporting Standards (CHEERS) checklist. Secondly, to enumerate context specific costs of delivering facility-based EC, data were collected over a 4-week period in Uganda using direct activity-based costing and presented in Chapter 6. Measures of central tendency were derived by condition and by intervention. Variations in cost between conditions were explored using a Kruskal-Wallis H test and a post-hoc Nemenyi test were performed to make pairwise comparisons between conditions. Third, in Chapter 7 a cost-effectiveness analysis model was developed using Microsoft Excel to calculate both the costs and effects of scalable investments strengthening facility-based EC on morbidity and mortality. Costs and consequences associated with piloting the WHO Emergency Care Toolkit package of interventions in Uganda were analysed using the decision tree model. Pre- and post-intervention groups were compared from a societal perspective. Cost and health outcomes were discounted using a microsimulation and parameter uncertainty assessed using Monte-Carlo simulation probabilistic sensitivity analyses. Results 35 studies were included in the final review; most were methodologically weak and focused on singleintervention analyses rather than intervention packages or system changes. This body of literature represented only 24 of 137 low- and middle-income countries (LMICs) globally, and was heterogeneous in methods, settings, and presentation of results of the identified studies. Accordingly, formulating a general conclusion about the wider implication of the findings on the cost–effectiveness of EC is problematic. The overall median (IQR) cost of care across all conditions was $15.53 (14.44 to 19.22). A Krauskal-Wallis test yielded statistically significant difference in cost values between sentinel conditions (H=94.89, p=1.20E-19). At a P value of < .05, the post-hoc Nemenyi test revealed paediatric diarrhoea has a statistically significant lower median cost compared to all other conditions, but did not yield any significant differences in median cost between the remaining four sentinel conditions. In running the decision tree model with a 1753 patient cohort, sampled 10000 times, the intervention averted 509 DALYs over standard care. The model found implementing the WHO Toolkit saved$664,231 ($658,552 to$669,910), and yielded an additional 27 lives saved, or an additional 1,826 life years. Conclusions and relevance This dissertation makes important conceptual, analytical and empirical contributions in exploring the application of local economic evidence-informed priority setting to ensure that decisions made around EC are guided by the populations they serve. In conducting one of the first cost-effectiveness analyses of investments that create a systematic approach to facility-based EC, we found that this is a very low-cost, high-yield intervention. In many cases it may not only be cost-effective, but actually cost saving. This finding is especially relevant in LRS contexts where associated additional costs may be considered affordable given the high burden of emergency conditions

EJP-CONCERT. D3.7 Second joint roadmap for radiation protection research

EJP-CONCERT Work Package 3, Deliverable 3.7