The EMM Survey Registry is a database of quantitative surveys that have been undertaken with EMM (sub)samples across Europe and beyond since January 2000. Survey-level metadata is available for each of the surveys included in the EMM Survey Registry. The EMM Survey Registry is one of the main outputs generated by COST Action 16111 Ethmigsurveydata jointly with the Sciences Po team of the SSHOC (Social Sciences and Humanities Open Cloud) project. It is also a result of the collective efforts by the national delegations of the participating countries in the COST Action who have contributed to an initial comprehensive compilation of all the surveys targeting EMM respondents since January 2000 and until 2020 in their respective country. The EMM Survey Registry work has been coordinated by Laura Morales, Mónica Méndez, Anikó Bernat and Johannes Bergh as the leaders of Work Groups (WG) 1 and 2 of the COST Action, and by Ami Saji at Sciences Po as the researcher in the SSHOC project. Nevertheless, numerous researchers in the COST Action and the SSHOC project have contributed at various stages of the process, providing feedback on various iterations of the methodological guidelines and data collection templates as well as offering advice on the technical aspects of implementation, and participating in the quality control process. Unfortunately, they are too numerous to be listed here, but we wish to publicly acknowledge their contributions. The technical design and implementation of the registry was undertaken by Youngminds. The EMM Survey Registry is currently in version 1.0. This means that it is fully functional and displays all the metadata compiled and contributed by the national delegations of Ethmigsurveydata. Access to the dataset here: https://registry.ethmigsurveydatahub.eu/

The objectives of this study were to understand how healthcare systems are incorporating equity into performance measurement and to uncover trends that inform healthcare systems’ efforts to advance equity. A national cross-sectional survey was designed and administered during Spring 2022 to evaluate organizational efforts to track and measure health equity. The survey examined clinical and non-clinical health equity metrics/indicators tracked at the executive-level. We identified variation in how health equity is measured. Of the 27 respondents, seven (25.9%) were in the planning phase, nine (33.3%) were in early implementation, seven (25.9%) had practices implemented for one to two years, and four (14.8%) had practices implemented for three or more years. Most systems were tracking clinical metrics and evaluating metrics across subpopulations. Metrics related to chronic disease management and preventive care were mentioned most frequently (23.6% and 16.0%, respectively). Race/ethnicity was the most utilized demographic filter to evaluate equity. Systems at later stages of implementation were tracking fewer metrics, yet many systems were still in early stages of implementation. Health systems need specific and pragmatic guidance to develop and implement equity measures tracked at the executive level. Insights from current health system initiatives can help inform guidelines from national quality organizations for disparity reduction in clinical outcomes.

BackgroundDynamic HIV transmission models can provide evidence-based guidance on optimal combination implementation strategies to treat and prevent HIV/AIDS. However, these models can be extremely data intensive, and the availability of good-quality data characterizing regional microepidemics varies substantially within and across countries. We aim to provide a comprehensive and transparent description of an evidence synthesis process and reporting framework employed to populate and calibrate a dynamic, compartmental HIV transmission model for six US cities.MethodsWe executed a mixed-method evidence synthesis strategy to populate model parameters in six categories: (i) initial HIV-negative and HIV-infected populations; (ii) parameters used to calculate the probability of HIV transmission; (iii) screening, diagnosis, treatment and HIV disease progression; (iv) HIV prevention programs; (v) the costs of medical care; and (vi) health utility weights for each stage of HIV disease progression. We identified parameters that required city-specific data and stratification by gender, risk group and race/ethnicity a priori and sought out databases for primary analysis to augment our evidence synthesis. We ranked the quality of each parameter using context- and domain-specific criteria and verified sources and assumptions with our scientific advisory committee.FindingsTo inform the 1,667 parameters needed to populate our model, we synthesized evidence from 59 peer-reviewed publications and 24 public health and surveillance reports and executed primary analyses using 11 data sets. Of these 1,667 parameters, 1,517 (91%) were city-specific and 150 (9%) were common for all cities. Notably, 1,074 (64%), 201 (12%) and 312 (19%) parameters corresponded to categories (i), (ii) and (iii), respectively. Parameters ranked as best- to moderate-quality evidence comprised 39% of the common parameters and ranged from 56%-60% across cities for the city-specific parameters. We identified variation in parameter values across cities as well as within cities across risk and race/ethnic groups.ConclusionsBetter integration of modelling in decision making can be achieved by systematically reporting on the evidence synthesis process that is used to populate models, and by explicitly assessing the quality of data entered into the model. The effective communication of this process can help prioritize data collection of the most informative components of local HIV prevention and care services in order to reduce decision uncertainty and strengthen model conclusions.

This repository contains: - the Content Type Dataset Version 1.5 (in the folder "Datasets"); - the latest version of the guidelines for annotating Content Types; the data statement related to CTD V1.5; - a set of spreadsheets containing metadata about the documents included in the dataset, e.g. year of publication, author's name, author's nationality, author's gender (in the folder "Documents_Metadata"); - the data to replicate a set of experiments for the identification of Content Types (in the folder "Datasets"); - the best model for the identification of Content Types obtained adopting the BiLSTM-CNN-CRF with ELMo-Representations for Sequence Tagging implementation by Nils Reimers and Iryna Gurevych (in the folder "Best_Model"); - the data used to calculate the Inter-Annotator Agreement (in the folder "IAA"): the script used for calculating Cohen's k is available here: https://github.com/johnnymoretti/CAT_R_Kappa_Cohen To replicate the experiments / Run the models To replicate the experiments or run the models, you have to clone and install the BiLSTM-CNN-CRF with ELMo-Representations for Sequence Tagging implementation by Nils Reimers and Iryna Gurevych available at https://github.com/UKPLab/elmo-bilstm-cnn-crf To replicate the experiments, you have to rename the data in Datasets/Cross-Genre and Datasets/Cross-Time to "train.txt", "dev.txt", and "test.txt" To run the model on new data, the input file must be in CoNLL-like format one token per line with empty lines separating sentences. From the BiLSTM-CNN-CRF with ELMo-Representations repository you can use "RunModel_CoNLL_Format.py" Data statement CURATION RATIONALE: We adopt a broad perspective on texts selection assuming that good computational models for NLP must be able to deal with different genres (synchronic dimension) as well as with different times (diachronic dimension). This approach aims at facilitating the re-use of models in different fields of study, and promoting the cross-fertilisation among disciplines, especially in the area of Humanities. On the basis of this approach, we collected texts in English from three different genres: newspaper articles, travel reports, and travel guides. For each of these genres, we collected data published between the second half of the 1800s and the beginning of the 2000s. In designing the corpus, one of our goals was to keep the combination of time and genre as much balanced as possible, in terms of number of tokens and clauses. Furthermore, given the phenomenon under study, we decided to preserve documents' integrity rather than truncating them. LANGUAGE VARIETY: en-GB, en-US, en-AU. ANNOTATOR DEMOGRAPHIC Annotator #1: Age: 36 years old Gender: female Race/ethnicity: caucasian Native language: Italian Socioeconomic status Training in linguistics/other relevant discipline: MA in Computational Linguistics Annotator #2: Age: 37 years old Gender: male Race/ethnicity: caucasian Native language: Italian Socioeconomic status Training in linguistics/other relevant discipline: PhD in Computational Linguistics Annotator #3: Age: 25 years old Gender: female Race/ethnicity: caucasian Native language: Italian Socioeconomic status Training in linguistics/other relevant discipline: MA in Linguistics SPEAKER DEMOGRAPHIC & SPEECH SITUATION: Information included in the spreadsheets.

In order to temporarily protect the land use rights of the indigenous ethnic minority communities, the General Secretariat of the Council for Land Policy and the MLMUPC shall work together with the State Land Management Committee of concerned provinces, to guide the implementation of interim measures through conducting pilot projects in three areas in Leoun Kren village Ou Chum commune, Ou Chum district, and in La In village, Teun commune, Kon Mom district of Rattanakiri province, and in Andong Kraleung village, Ou Riang commune, Ou Riang district of Modulkiri province, in accordance with the Sub-decree No. 118 on state land management.

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

BackgroundSickle Cell Disease (SCD) is an inherited condition that is widespread globally and especially in malaria-endemic West African countries. Limited epidemiological data on SCD are available for Guinea Bissau, where newborn screening is not yet implemented, routine diagnosis is not available, and care is case directed.MethodsDried blood spots were collected from children accessing two hospitals managed by Italian Non-Governmental Organizations in the capital city of Bissau and sent to Padova for Hemoglobin (Hb) quantification through HPLC and molecular analysis. Beta globin gene analysis was performed in all; and Hb haplotype of the HbSS and HbSA patients was performed in South Africa. One hundred samples belonging to the most frequent ethnic groups were randomly selected for detection of G6PD mutations.ResultsSamples from 848 consecutive children (498 males and 350 females, mean age 6.8 years) accessing the two hospitals were analyzed: 6.95% AS (4.42% allelic frequency), 0.94% SS, and 0.23% AC. 376G G6PD allelic frequency was 24%; 14.8% in AS individuals. The Senegal haplotype was the most prevalent (31%), and the proposition of chromosomes with the atypical haplotype was surprisingly high (56%).ConclusionOur study demonstrates a significant frequency of the HbS allele in the population of Guinea Bissau supporting the implementation of screening strategies. The differences among ethnic groups can help guide targeted interventions for SCD awareness campaigns and determine priority areas for public health interventions. The pilot analysis on haplotypes reveals a large proportion of the atypical haplotype, which may be indicative of a genetically heterogeneous population.