Evaluating Scalable Distributed Erlang for Scalability and Reliability

Large scale servers with hundreds of hosts and tens of thousands of cores are becoming common. To exploit these platforms software must be both scalable and reliable, and distributed actor languages like Erlang are a proven technology in this area. While distributed Erlang conceptually supports the engineering of large scale reliable systems, in practice it has some scalability limits that force developers to depart from the standard language mechanisms at scale. In earlier work we have explored these scalability limitations, and addressed them by providing a Scalable Distributed (SD) Erlang library that partitions the network of Erlang Virtual Machines (VMs) into scalable groups (s_groups). This paper presents the first systematic evaluation of SD Erlang s_groups and associated tools, and how they can be used. We present a comprehensive evaluation of the scalability and reliability of SD Erlang using three typical benchmarks and a case study. We demonstrate that s_groups improve the scalability of reliable and unreliable Erlang applications on up to 256 hosts (6,144 cores). We show that SD Erlang preserves the class-leading distributed Erlang reliability model, but scales far better than the standard model. We present a novel, systematic, and tool-supported approach for refactoring distributed Erlang applications into SD Erlang. We outline the new and improved monitoring, debugging and deployment tools for large scale SD Erlang applications. We demonstrate the scaling characteristics of key tools on systems comprising up to 10 K Erlang VMs

ESGAP inventory of target indicators assessing antibiotic prescriptions: A cross-sectional survey

Background A variety of indicators is commonly used to monitor antibiotic prescriptions as part of national antimicrobial stewardship (AMS) programmes. Objectives To make an inventory of indicators that assess antibiotic prescriptions and are linked to specific targets and incentives, at a national level. Methods A cross-sectional survey (three-item questionnaire) was conducted in 2017 among all ESGAP (ESCMID Study Group for Antimicrobial stewardshiP) members, coming from 23 European countries and 16 non-European countries. Results Almost all (20/23, 87%) European countries belonging to the ESGAP network participated, as well as one non-European country. Computerized systems routinely linking antibiotic prescriptions to clinical diagnoses were reported for only two countries (Turkey and Croatia). Only 6/21 (29%) countries had national indicators with both clear targets and incentives (Bulgaria, Croatia, France, the Netherlands, Norway and Portugal). We identified a total of 21 different indicators used in these countries, 16 concerning inpatients (9 quality indicators and 7 quantity metrics) and 8 concerning outpatients (all quantity metrics); some indicators were used in both settings. Three types of incentives were used: financing mechanism, hospitals' accreditation and public reporting. Some respondents reported that such indicators with both clear targets and incentives were used at a regional level in their country (e.g. Andalusia in Spain and England in the UK). Conclusions National indicators, with clear targets and incentives, are not commonly used in Europe and we observed wide variations between countries regarding the selected indicators, the units of measure and the chosen targets

Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis

Background: The spread of antibiotic-resistant bacteria poses a substantial threat to morbidity and mortality worldwide. Due to its large public health and societal implications, multidrug-resistant tuberculosis has been long regarded by WHO as a global priority for investment in new drugs. In 2016, WHO was requested by member states to create a priority list of other antibiotic-resistant bacteria to support research and development of effective drugs. Methods: We used a multicriteria decision analysis method to prioritise antibiotic-resistant bacteria; this method involved the identification of relevant criteria to assess priority against which each antibiotic-resistant bacterium was rated. The final priority ranking of the antibiotic-resistant bacteria was established after a preference-based survey was used to obtain expert weighting of criteria. Findings: We selected 20 bacterial species with 25 patterns of acquired resistance and ten criteria to assess priority: mortality, health-care burden, community burden, prevalence of resistance, 10-year trend of resistance, transmissibility, preventability in the community setting, preventability in the health-care setting, treatability, and pipeline. We stratified the priority list into three tiers (critical, high, and medium priority), using the 33rd percentile of the bacterium's total scores as the cutoff. Critical-priority bacteria included carbapenem-resistant Acinetobacter baumannii and Pseudomonas aeruginosa, and carbapenem-resistant and third-generation cephalosporin-resistant Enterobacteriaceae. The highest ranked Gram-positive bacteria (high priority) were vancomycin-resistant Enterococcus faecium and meticillin-resistant Staphylococcus aureus. Of the bacteria typically responsible for community-acquired infections, clarithromycin-resistant Helicobacter pylori, and fluoroquinolone-resistant Campylobacter spp, Neisseria gonorrhoeae, and Salmonella typhi were included in the high-priority tier. Interpretation: Future development strategies should focus on antibiotics that are active against multidrug-resistant tuberculosis and Gram-negative bacteria. The global strategy should include antibiotic-resistant bacteria responsible for community-acquired infections such as Salmonella spp, Campylobacter spp, N gonorrhoeae, and H pylori. Funding: World Health Organization