The European Virus Archive goes global: A growing resource for research

The European Virus Archive (EVA) was created in 2008 with funding from the FP7-EU Infrastructure Programme, in response to the need for a coordinated and readily accessible collection of viruses that could be made available to academia, public health organisations and industry. Within three years, it developed from a consortium of nine European laboratories to encompass associated partners in Africa, Russia, China, Turkey, Germany and Italy. In 2014, the H2020 Research and Innovation Framework Programme (INFRAS projects) provided support for the transformation of the EVA from a European to a global organization (EVAg). The EVAg now operates as a non-profit consortium, with 26 partners and 20 associated partners from 21 EU and non-EU countries. In this paper, we outline the structure, management and goals of the EVAg, to bring to the attention of researchers the wealth of products it can provide and to illustrate how end-users can gain access to these resources. Organisations or individuals who would like to be considered as contributors are invited to contact the EVAg coordinator, Jean-Louis Romette, at [email protected]

An integer linear programming model for fair multitarget tracking in cooperative multirobot systems

Cooperative Multi-Robot Observation of Multiple Moving Targets (CMOMMT) denotes a class of problems in which a set of autonomous mobile robots equipped with limited-range sensors keep under observation a (possibly larger) set of mobile targets. In the existing literature, it is common to let the robots cooperatively plan their motion in order to maximize the average targets’ detection rate, defined as the percentage of mission steps in which a target is observed by at least one robot. We present a novel optimization model for CMOMMT scenarios which features fairness of observation among different targets as an additional objective. The proposed integer linear formulation exploits available knowledge about the expected motion patterns of the targets, represented as a probabilistic occupancy maps estimated in a Bayesian framework. An empirical analysis of the model is performed in simulation, considering multiple scenarios to study the effects of the amount of robots and of the prediction accuracy for the mobility of the targets. Both centralized and distributed implementations are presented and compared to each other evaluating the impact of multi-hop communications and limited information sharing. The proposed solutions are also compared to two algorithms selected from the literature. The model is finally validated on a real team of ground robots in a limited set of scenarios

The European Virus Archive goes global: A growing resource for research

The European Virus Archive (EVA) was created in 2008 with funding from the FP7-EU Infrastructure Programme, in response to the need for a coordinated and readily accessible collection of viruses that could be made available to academia, public health organisations and industry. Within three years, it developed from a consortium of nine European laboratories to encompass associated partners in Africa, Russia, China, Turkey, Germany and Italy. In 2014, the H2020 Research and Innovation Framework Programme (INFRAS projects) provided support for the transformation of the EVA from a European to a global organization (EVAg). The EVAg now operates as a non-pro fi t consortium, with 26 partners and 20 associated partners from 21 EU and non-EU countries. In this paper, we outline the structure, management and goals of the EVAg, to bring to the attention of researchers the wealth of products it can provide and to illustrate how end-users can gain access to these re- sources. Organisations or individuals who would like to be considered as contributors are invited to contact the EVAg coordinator, Jean-Louis Romette, at [email protected] Reviewe

Risk factors for infections caused by carbapenem-resistant Enterobacterales: an international matched case-control-control study (EURECA)

Background: Data on risk factors for carbapenem-resistant Enterobacterales (CRE) with wider applicability are needed to inform preventive measures and efficient design of randomised trials. Methods: An international matched case-control-control study was performed in 50 hospitals with high CRE incidence from March 2016 to November 2018 to investigate different aspects of infections caused by CRE (NCT02709408). Cases were patients with complicated urinary tract infection (cUTI), complicated intraabdominal (cIAI), pneumonia or bacteraemia from other sources (BSI-OS) due to CRE; control groups were patients with infection caused by carbapenem-susceptible Enterobacterales (CSE), and by non-infected patients, respectively. Matching criteria included type of infection for CSE group, ward and duration of hospital admission. Conditional logistic regression was used to identify risk factors. Findings: Overall, 235 CRE case patients, 235 CSE controls and 705 non-infected controls were included. The CRE infections were cUTI (133, 56.7%), pneumonia (44, 18.7%), cIAI and BSI-OS (29, 12.3% each). Carbapenemase genes were found in 228 isolates: OXA-48/like, 112 (47.6%), KPC, 84 (35.7%), and metallo-β-lactamases, 44 (18.7%); 13 produced two. The risk factors for CRE infection in both type of controls were (adjusted OR for CSE controls; 95% CI; p value) previous colonisation/infection by CRE (6.94; 2.74–15.53; <0.001), urinary catheter (1.78; 1.03–3.07; 0.038) and exposure to broad spectrum antibiotics, as categorical (2.20; 1.25–3.88; 0.006) and time-dependent (1.04 per day; 1.00–1.07; 0.014); chronic renal failure (2.81; 1.40–5.64; 0.004) and admission from home (0.44; 0.23–0.85; 0.014) were significant only for CSE controls. Subgroup analyses provided similar results. Interpretation: The main risk factors for CRE infections in hospitals with high incidence included previous colonization, urinary catheter and exposure to broad spectrum antibiotics. Funding: The study was funded by the e Medicines Initiative Joint Undertaking (https://www.imi.europa.eu/) under Grant Agreement No. 115620 (COMBACTE-CARE). © 2023 The Author(s