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Additional file 4: Figure 2. Description of data: Use of medication. Differences of use of (a) corticosteroids, (b) remdesivir, and (c) chloroquine between anakinra group and control group during 10 days before and 10 days after alignment day (day 0). P values were calculated using Fisher’s exact tests.

In late 2019, Covid-19 emerged and was soon declared a pandemic causing until now a massive health disruption and a huge impact on the global economy. Several governments around the world are still forced to take containment measures to curb the spread of the virus including partial or full lockdowns. At the same time, they rely heavily on human resources to perform manual Contact Tracing (CT) for alerting known contacts of the confirmed cases and breaking the infection chains early enough. However, CT does not scale well when the cases increase exponentially, due to the limited capacity of national public health authorities, and cannot identify possible hidden infections due to random encounters with strangers in crowded spaces such as restaurants, bars, theaters, public transportation, etc. To this end, Digital Contact Tracing (DCT) is becoming increasingly popular to enhance and empower CT, enabling automatic and faster identification and notification of exposed users. This presentation will first overview the different generations of DCT solutions from the privacy-invasive use of subscriber location data provided by cellular operators, to location monitoring mobile apps on GPS-equipped smartphones, to privacy-preserving mobile apps based on proximity sensing through Bluetooth. It will discuss the findings of recent studies with regards to the effectiveness of DCT and debate whether it has been ��� or has the potential to become ��� a game changer. Finally, it will outline the latest developments and trends in this active research field that are of interest to the IPIN community including presence tracing that aims to notify anonymously those users that have been in the same place (especially indoors) with an infected user, without necessarily satisfying the proximity constraint. Keynote @ 2021 International Conference on Indoor Positioning and Indoor Navigation.

Additional file 1. Tracheal and cloacal shedding of virus RNA of birds, in experiment 2. Shedding is expressed as both RRT-PCR Ct individual values and means ± standard deviations. Statistical was set at a P

Middle East respiratory syndrome coronavirus (MERS-CoV) continues infecting humans and dromedary camels. While MERS-CoV strains from the Middle East region are subdivided into two clades (A and B), all the contemporary epidemic viruses belong to clade B. Thus, MERS-CoV clade B strains may display adaptive advantages over clade A in humans and/or reservoir hosts. To test this hypothesis in vivo, we compared an early epidemic clade A strain (EMC/2012) with a clade B strain (Jordan-1/2015) in an alpaca model monitoring virological and immunological parameters. Further, the Jordan-1/2015 strain has a partial amino acid (aa) deletion in the double-stranded (ds) RNA binding motif of the open reading frame ORF4a protein. Animals inoculated with the Jordan-1/2015 variant had higher MERS-CoV replicative capabilities in the respiratory tract and larger nasal viral shedding. In the nasal mucosa, the Jordan-1/2015 strain caused an early IFN response, suggesting a role for ORF4a as a moderate IFN antagonist in vivo. However, both strains elicited maximal transcription of antiviral interferon-stimulated genes (ISGs) at the peak of infection on 2 days post inoculation, correlating with subsequent decreases in tissular viral loads. Genome alignment analysis revealed several clade B-specific amino acid substitutions occurring in the replicase and the S proteins, which could explain a better adaptation of clade B strains in camelid hosts. Differences in replication and shedding reported herein indicate a better fitness and transmission capability of MERS-CoV clade B strains than their clade A counterparts.

This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the OpenAIRE COVID-19 Gateway, identified via full-text mining and inference techniques applied to the OpenAIRE Research Graph. The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a tar archive containing gzip files with one json per line. Each json is compliant to the schema available at https://doi.org/10.5281/zenodo.4723499.

MedLexSp is an unified medical lexicon for Medical Natural Language Processing in Spanish. It includes terms and inflected word forms with part-of-speech information and Unified Medical Language System (UMLS) semantic types, groups and Concept Unique Identifiers (CUIs). To create it, we used Natural Language Processing techniques and domain corpora (e.g. MedlinePlus). We also collected terms from the Dictionary of Medical Terms from the Spanish Royal Academy of Medicine, the Medical Subject Headings (MeSH), the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED-CT), the Medical Dictionary for Regulatory Activities Terminology (MedDRA), the International Classification of Diseases vs 10, the Anatomical Therapeutical Classification, the National Cancer Institute (NCI) Dictionary, the Online Mendelian Inheritance in Man (OMIM) and OrphaData. Terms related to COVID-19 were assembled by applying a similarity-based approach with word embeddings trained on a large corpus. This dataset was collected during the NLPMedTerm project and the CLARA-MeD project, with the goal of creating a lexical resource for medical text processing in the Spanish language. - MedLexSp.dsv: a delimiter-separated value file, with the following data fields: Field 1 is the UMLS CUI of the entity; field 2, the lemma; field 3, the variant forms; field 4, the part-of-speech; field 5, the semantic types(s); and field 6, the semantic group. - MedLexSp.xml: an XML-encoded version using the Lexical Markup Framework (LMF), which includes the morphological data (number, gender, verb tense and person, and information about affix/abbreviation data). The Document Type Definition file is also provided (lmf.dtd). - Lexical Record files: in subfolder "LR/": · LR_abr.dsv: list of equivalences between acronyms/abbreviations and full forms. · LR_affix.dsv: provides the equivalence between affixes/roots and their meanings. · LR_n_v.dsv: list of deverbal nouns. · LR_adj_n.dsv: list of adjectives derived from nouns. - Spacy lemmatizer (in subfolder "spacy_lemmatizer/"): lemmatizer.py - Stanza lemmatizer (in subfolder "stanza_lemmatizer/"): ancora-medlexsp.pt File List: 1) MedLexSp.dsv; 2) MedLexSp.xml and lmf.dtd (Document Type Definition); 3) Lexical Record files: in subfolder "LR/": 3.1) LR_abr.dsv; 3.2) LR_affix.dsv; 3.3) LR_n_v.dsv; 3.4) LR_adj_n.dsv; 4) Spacy lemmatizer (in subfolder "spacy_lemmatizer/"): lemmatizer.py 5) Stanza lemmatizer (in subfolder "stanza_lemmatizer/"): ancora-medlexsp.pt See more information about the format below. Companion code and files can be found in the github repository: https://github.com/lcampillos/MedLexSp This dataset was collected in the NLPMedTerm project, funded by the European Union’s Horizon 2020 research programme under the Marie Skodowska-Curie grant agreement nº. 713366 (InterTalentum UAM), and the CLARA-MeD project (PID2020-116001RA-C33), funded by MCIN/AEI/10.13039/501100011033/, in project call: "Proyectos I+D+i Retos Investigación". MedLexSp is an unified medical lexicon for Medical Natural Language Processing in Spanish. It includes 100 887 lemmas, 302 543 inflected forms (conjugated verbs, and number/gender variants), and 42 958 Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). Spain, Latin America and United States of America (data from MedlinePlus Spanish and the Spanish version of the National Cancer Institute Dictionary of Medical Terms). Peer reviewed

The survey aimed to gather data on the impact of the COVID19 outbreak on the food support providers active in Greater Manchester. The lockdown created organizational hurdles to many services providing food to the most vulnerable. The survey explored more in depth the obstacles, the needs and the prospects of 55 organizations that were on the frontline in the first months of the crisis.

{"references": ["Greiss, J. et al. (2022). Food aid in Europe in times of the COVID-19 crisis. An international survey project. CSB Working Paper Series, University of Antwerp."]} The dataset is linked to a cross-sectional study on the organisation of food aid in different European countries before and during the COVID-19 crisis. Funding: The Research Foundation – Flanders (FWO) (G056121N)

Additional file 12: Figure 6. Description of data: Use of medication in propensity score-matched groups. Differences of use of (a) corticosteroids, (b) remdesivir, and (c) chloroquine between anakinra group and control group during 10 days before and 10 days after alignment day (day 0). p values were calculated using Fisher’s exact tests.