BiodiverCities: A roadmap to enhance the biodiversity and green infrastructure of European cities by 2030

BiodiverCities is a European Parliament Pilot Project, developed with the aim of enhancing the use of Urban Green Infrastructure (UGI) to enhance the condition of urban ecosystems, providing benefits for people and nature. In this report, an evaluation around the most appropriate reporting unit for an urban ecosystems assessment is carried out, comparing Functional Urban Areas (FUA) and Local Administrative Units (LAU). Furthermore, UGI are assessed from a multi-scale perspective. The status and scenarios of UGI in European urbanised areas is first analysed measuring the urban green areas and the tree canopy cover. Secondly, the contribution of UGI to the overall European Green Infrastructure (EU-GI) is quantified, evaluating the respective role of FUA and LAU. Finally, the effect of urban characteristics on biotic homogenization is analysed exploring how urbanised areas impact on avian population and communities in French cities. The results of this study will inform the development of a roadmap for greening cities in Europe in the 2020-2030 decade

EU-wide methodology to map and assess ecosystem condition

The EU Biodiversity Strategy for 2030 calls for developing an EU-wide methodology to map, assess and achieve good condition of ecosystems, so they can deliver benefits to society through the provision of ecosystem services. The EU-wide methodology presented in this report addresses this methodological gap. The EU-wide methodology has adopted the System of Environmental Economic Accounting - Ecosystem Accounting (SEEA EA) as reference framework. The SEEA EA is an integrated framework for organizing biophysical information about ecosystems, adopted as a global statistical standard by the United Nations. The SEEA EA is also the reference framework under the proposal for the amendment of Regulation (EU) No 691/2011 on European environmental economic accounts. Building on previous work done within the MAES initiative, the EU-wide methodology presents useful insights to operationalise the SEEA EA at EU level by integrating different EU data streams in a consistent way with this global statistical standard to consistently map and assess ecosystem condition in the EU across all ecosystem types. The adoption of the SEEA EA framework offers the flexibility to integrate different data flows, leveraging the use of available EU data, such as data reported by MS under EU legislation and EU geospatial data. The EU-wide methodology. The implementation of the EU-wide methodology, making use of available data, will provide the scientific knowledge base to support a range of policies and legal instruments

The Integrated system for Natural Capital Accounting (INCA) in Europe: twelve lessons learned from empirical ecosystem service accounting

Open Access Article; Published online: 16 Sep 2022The Integrated system for Natural Capital Accounting (INCA) was developed and supported by the European Commission to test and implement the System of integrated Environmental and Economic Accounting – Ecosystem Accounting (SEEA EA). Through the compilation of nine Ecosystem Services (ES) accounts, INCA can make available to any interested ecosystem accountant a number of lessons learned. Amongst the conceptual lessons learned, we can mention: (i) for accounting purposes, ES should be clustered according to the existence (or not) of a sustainability threshold; (ii) the assessment of ES flow results from the interaction of an ES potential and an ES demand; (iii) the ES demand can be spatially identified, but for an overarching environmental target, this is not possible; ES potential and ES demand could mis-match; (iv) because the demand remains unsatisfied; (v) because the ES is used above its sustainability threshold or (vi) because part of the potential flow is missed; (vii) there can be a cause-and-effect relationship between ecosystem condition and ES flow; (viii) ES accounts can complement the SEEA Central Framework accounts without overlapping or double counting. Amongst the methodological lessons learned, we can mention: (ix) already exiting ES assessments do not directly provide ES accounts, but will likely need some additional processing; (x) ES cannot be defined by default as intermediate; (xi) the ES remaining within ecosystems cannot be reported as final; (xii) the assessment and accounting of ES can be undertaken throughout a fast track approach or more demanding modelling procedures

A MACHINE LEARNING PIPELINE ARTICULATING SATELLITE IMAGERY and OPENSTREETMAP for ROAD DETECTION

Satellite imagery from earth observation missions enable processing big data to gather information about the world. Automatizing the creation of maps that reflect ground truth is a desirable outcome that would aid decision makers to take adequate actions in alignment with the United Nations Sustainable Development Goals. In order to harness the power that the availability of the new generation of satellites enable, it is necessary to implement techniques capable of handling annotations for the massive volume and variability of high spatial resolution imagery for further processing. However, the availability of public datasets for training machine learning models for image segmentation plays an important role for scalability.This work focuses on bridging remote sensing and computer vision by providing an open source based pipeline for generating machine learning training datasets for road detection in an area of interest. The proposed pipeline addresses road detection as a binary classification problem using road annotations existing in OpenStreetMap for creating masks. For this case study, Planet images of 3m resolution are used for creating a training dataset for road detection in Kenya

NRand-K: Minimizing the impact of location obfuscation in spatial analysis

Location privacy, or geoprivacy, is critical to secure users’ privacy in context‐aware applications. Location‐based services pose privacy risks for users, due to the inferences that could be made about them from their location information and the potential misuse of this data by service providers or third‐party companies. A common solution is to apply masking or location obfuscation, which degrades location information quality while keeping a geographic coordinate structure. However, there is a trade‐off between privacy, quality of service, and quality of information, the last one being a valuable asset for companies. NRand is a location privacy mechanism with obfuscation capabilities and resistance against filtering attacks. In order to minimize the impact on location information quality, NRand‐K has been introduced. This algorithm is designed for use when releasing location information to third parties or as open data with privacy concerns. To assess the impact of location obfuscation on exploratory spatial data analysis (ESDA), a comparison is performed between obfuscated data with NRand, NRand‐K, and unaltered data. For the experiments, geolocated tweets collected during the Central Italy 2016 earthquake are used. Results show that NRand‐K reduces the impact on ESDA, where inferences were similar to those obtained with the unaltered data

Cas groupés d’infections invasives à méningocoque de sérogroupe W dans un campus universitaire

International audienceIntroduction : In France, the expansion of an hypervirulent strain causing serogroup W invasive meningococcal disease (MenW) has been observed since 2015/16. We describe a cluster of three MenW cases, causing two deaths, at the end of 2016 in a university campus, and the vaccination campaign which was consequently organized.Methods : Epidemiological and microbiological analyses led a multidisciplinary expertise group to recommend the organization of a mass vaccination campaign using ACWY vaccine targeting more than 30,000 students and staff in the university campus. Individual data on vaccination was collected using the lists of students and staff registered at the university to estimate vaccine coverage.Results : Three MenW cases occurred within a 2-month period among students in different academic courses. All three isolates were identical and belonged to the “UK-2013 strain” phylogenetic branch. The attack rate was 10.8/100,000 students. The vaccination campaign was organized only 15 days after the third case occurred. In total, 13,198 persons were vaccinated. Vaccine coverage was estimated at 41% for students of the university and 35% for university staff.Conclusion : Timely notification of cases to health authorities was essential for the detection of the cluster and the rapid implementation of the vaccination campaign. No further cases occurred in the campus in the year following the vaccination campaign. This episode is the second cluster of MenW caused by the “UK-2013 strain” in a university since 2016.Introduction : Une souche hypervirulente de méningocoque de sérogroupe W est en expansion en France depuis 2015/16. Cet article décrit un foyer de trois cas d’infection invasive à méningocoque de sérogroupe W (IIMW), à l’origine de deux décès, survenu à la fin de l’année 2016 dans une université, et la campagne de vaccination organisée par les autorités sanitaires.Méthodes : Les analyses épidémiologiques et microbiologiques ont conduit une cellule d’expertise multidisciplinaire à recommander l’organisation d’une campagne de vaccination par les vaccins ACWY ciblant plus de 30 000 étudiants et personnel sur le campus universitaire. Les données individuelles de vaccination ont été recueillies et rapportées aux listes d’étudiants et des personnels inscrits à l’université pour estimer la couverture vaccinale.Résultats : Les trois cas d’IIM W sont survenus dans un délai de 2 mois chez des étudiants dans des filières différentes. Les souches des trois cas étaient identiques (souche UK-2013). Le taux d’attaque était de 10,8/100 000 étudiants. Au total, 13 198 personnes ont été vaccinées. La couverture vaccinale à l’université a été estimée à 41 % pour les étudiants et 35 % pour le personnel.Conclusion : Le signalement réactif des cas a permis de détecter ces cas groupés et de mettre en œuvre rapidement la campagne de vaccination. Aucun nouveau cas d’IIM W n’est survenu dans le campus dans l’année qui a suivi la campagne de vaccination. Cet épisode constitue le deuxième foyer de cas groupés d’IIM W lié à la souche hypervirulente UK-2013 survenant en milieu étudiant depuis 2016

Strengthened Ebola surveillance in France during a major outbreak in West Africa: March 2014–January 2016

International audienceSUMMARY Introduction An unprecedented outbreak of Ebola virus diseases (EVD) occurred in West Africa from March 2014 to January 2016. The French Institute for Public Health implemented strengthened surveillance to early identify any imported case and avoid secondary cases. Methods Febrile travellers returning from an affected country had to report to the national emergency healthcare hotline. Patients reporting at-risk exposures and fever during the 21st following day from the last at-risk exposure were defined as possible cases, hospitalised in isolation and tested by real-time polymerase chain reaction. Asymptomatic travellers reporting at-risk exposures were considered as contact and included in a follow-up protocol until the 21st day after the last at-risk exposure. Results From March 2014 to January 2016, 1087 patients were notified: 1053 were immediately excluded because they did not match the notification criteria or did not have at-risk exposures; 34 possible cases were tested and excluded following a reliable negative result. Two confirmed cases diagnosed in West Africa were evacuated to France under stringent isolation conditions. Patients returning from Guinea ( n = 531; 49%) and Mali ( n = 113; 10%) accounted for the highest number of notifications. Conclusion No imported case of EVD was detected in France. We are confident that our surveillance system was able to classify patients properly during the outbreak period

First cases of Omicron in France are exhibiting mild symptoms, November 2021–January 2022

International audienceObjectivesWe aimed to investigate the first Omicron cases detected in France in order to assess case characteristics and provide supporting information on the possible impact of this variant on the healthcare system.MethodsA standardized questionnaire was used to collect information from confirmed and probable Omicron cases.ResultsMedian age of 468 investigated cases was 35 years, 376 were symptomatic (89%); 64% were vaccinated with two doses and 7% had received three doses. Loss of smell and taste were reported by 8.3% and 9% of cases, respectively. Seven cases were hospitalized, three of those were unvaccinated (including two with reported precondition). No admissions to intensive care and no deaths were reported.ConclusionsOur results confirm a mild clinical presentation among the first Omicron cases detected in France and highlight the importance for the national COVID-19 surveillance system to quickly detect and adapt to the emergence of a new variant