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1.
J Biomed Semantics ; 12(1): 15, 2021 08 09.
Article in English | MEDLINE | ID: covidwho-1350153

ABSTRACT

BACKGROUND: The ontology authoring step in ontology development involves having to make choices about what subject domain knowledge to include. This may concern sorting out ontological differences and making choices between conflicting axioms due to limitations in the logic or the subject domain semantics. Examples are dealing with different foundational ontologies in ontology alignment and OWL 2 DL's transitive object property versus a qualified cardinality constraint. Such conflicts have to be resolved somehow. However, only isolated and fragmented guidance for doing so is available, which therefore results in ad hoc decision-making that may not be the best choice or forgotten about later. RESULTS: This work aims to address this by taking steps towards a framework to deal with the various types of modeling conflicts through meaning negotiation and conflict resolution in a systematic way. It proposes an initial library of common conflicts, a conflict set, typical steps toward resolution, and the software availability and requirements needed for it. The approach was evaluated with an actual case of domain knowledge usage in the context of epizootic disease outbreak, being avian influenza, and running examples with COVID-19 ontologies. CONCLUSIONS: The evaluation demonstrated the potential and feasibility of a conflict resolution framework for ontologies.


Subject(s)
Biological Ontologies/statistics & numerical data , Computational Biology/statistics & numerical data , Information Storage and Retrieval/statistics & numerical data , Semantic Web , Semantics , Vocabulary, Controlled , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/virology , Computational Biology/methods , Databases, Factual/statistics & numerical data , Epidemics/prevention & control , Humans , Information Storage and Retrieval/methods , Logic , SARS-CoV-2/physiology
2.
BMJ Open ; 11(7): e053402, 2021 07 23.
Article in English | MEDLINE | ID: covidwho-1322829

ABSTRACT

OBJECTIVE: To examine inequalities in COVID-19 vaccination rates among elderly adults in England. DESIGN: Cohort study. SETTING: People living in private households and communal establishments in England. PARTICIPANTS: 6 655 672 adults aged ≥70 years (mean 78.8 years, 55.2% women) who were alive on 15 March 2021. MAIN OUTCOME MEASURES: Having received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted ORs using logistic regression models. RESULTS: By 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of black African and black Caribbean ethnic backgrounds, where only 67.2% and 73.8% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 to 5.16) and 4.85 (4.75 to 4.96) times greater than the white British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socioeconomic position (proxied by living in a rented home), being disabled and living either alone or in a multigenerational household were also associated with higher odds of not having received the vaccine. CONCLUSION: Research is now urgently needed to understand why disparities exist in these groups and how they can best be addressed through public health policy and community engagement.


Subject(s)
COVID-19 Vaccines , COVID-19 , Adult , Aged , Aged, 80 and over , Cohort Studies , England , Female , Humans , Male , SARS-CoV-2 , Semantic Web , Vaccination , Vaccination Coverage
3.
Int J Environ Res Public Health ; 18(13)2021 06 28.
Article in English | MEDLINE | ID: covidwho-1295818

ABSTRACT

BACKGROUND: Many countries around the world are currently threatened by the COVID-19 pandemic, and nurses are facing increasing responsibilities and work demands related to infection control. To establish a developmental strategy for infection control, it is important to analyze, understand, or visualize the accumulated data gathered from research in the field of nursing. METHODS: A total of 4854 articles published between 1978 and 2017 were retrieved from the Web of Science. Abstracts from these articles were extracted, and network analysis was conducted using the semantic network module. RESULTS: 'wound', 'injury', 'breast', "dressing", 'temperature', 'drainage', 'diabetes', 'abscess', and 'cleaning' were identified as the keywords with high values of degree centrality, betweenness centrality, and closeness centrality; hence, they were determined to be influential in the network. The major topics were 'PLWH' (people living with HIV), 'pregnancy', and 'STI' (sexually transmitted infection). CONCLUSIONS: Diverse infection research has been conducted on the topics of blood-borne infections, sexually transmitted infections, respiratory infections, urinary tract infections, and bacterial infections. STIs (including HIV), pregnancy, and bacterial infections have been the focus of particularly intense research by nursing researchers. More research on viral infections, urinary tract infections, immune topic, and hospital-acquired infections will be needed.


Subject(s)
COVID-19 , HIV Infections , Nursing Research , Sexually Transmitted Diseases , Female , HIV Infections/epidemiology , Humans , Pandemics , Pregnancy , SARS-CoV-2 , Semantic Web , Sexually Transmitted Diseases/epidemiology
4.
Age Ageing ; 50(5): 1482-1492, 2021 09 11.
Article in English | MEDLINE | ID: covidwho-1219031

ABSTRACT

BACKGROUND: understanding care-home outbreaks of COVID-19 is a key public health priority in the ongoing pandemic to help protect vulnerable residents. OBJECTIVE: to describe all outbreaks of COVID-19 infection in Scottish care-homes for older people between 01/03/2020 and 31/03/2020, with follow-up to 30/06/2020. DESIGN AND SETTING: National linked data cohort analysis of Scottish care-homes for older people. METHODS: data linkage was used to identify outbreaks of COVID-19 in care-homes. Care-home characteristics associated with the presence of an outbreak were examined using logistic regression. Size of outbreaks was modelled using negative binomial regression. RESULTS: 334 (41%) Scottish care-homes for older people experienced an outbreak, with heterogeneity in outbreak size (1-63 cases; median = 6) and duration (1-94 days, median = 31.5 days). Four distinct patterns of outbreak were identified: 'typical' (38% of outbreaks, mean 11.2 cases and 48 days duration), severe (11%, mean 29.7 cases and 60 days), contained (37%, mean 3.5 cases and 13 days) and late-onset (14%, mean 5.4 cases and 17 days). Risk of a COVID-19 outbreak increased with increasing care-home size (for ≥90 beds vs <20, adjusted OR = 55.4, 95% CI 15.0-251.7) and rising community prevalence (OR = 1.2 [1.0-1.4] per 100 cases/100,000 population increase). No routinely available care-home characteristic was associated with outbreak size. CONCLUSIONS: reducing community prevalence of COVID-19 infection is essential to protect those living in care-homes. More systematic national data collection to understand care-home residents and the homes in which they live is a priority in ensuring we can respond more effectively in future.


Subject(s)
COVID-19 , Aged , Cohort Studies , Disease Outbreaks , Humans , Nursing Homes , SARS-CoV-2 , Scotland/epidemiology , Semantic Web
5.
ASAIO J ; 67(1): 18-24, 2021 01 01.
Article in English | MEDLINE | ID: covidwho-717252

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has revealed deep gaps in our understanding of the clinical nuances of this extremely infectious viral pathogen. In order for public health, care delivery systems, clinicians, and other stakeholders to be better prepared for the next wave of SARS-CoV-2 infections, which, at this point, seems inevitable, we need to better understand this disease-not only from a clinical diagnosis and treatment perspective-but also from a forecasting, planning, and advanced preparedness point of view. To predict the onset and outcomes of a next wave, we first need to understand the pathologic mechanisms and features of COVID-19 from the point of view of the intricacies of clinical presentation, to the nuances of response to therapy. Here, we present a novel approach to model COVID-19, utilizing patient data from related diseases, combining clinical understanding with artificial intelligence modeling. Our process will serve as a methodology for analysis of the data being collected in the ASAIO database and other data sources worldwide.


Subject(s)
Artificial Intelligence , Big Data , COVID-19/diagnosis , COVID-19/physiopathology , Data Science , Semantic Web , Symptom Assessment/methods , Humans , Machine Learning , Medical Informatics/methods , Models, Theoretical , Reproducibility of Results , Semantics
6.
Age Ageing ; 49(4): 516-522, 2020 07 01.
Article in English | MEDLINE | ID: covidwho-186591

ABSTRACT

Older people are particularly affected by the COVID-19 outbreak because of their vulnerability as well as the complexity of health organisations, particularly in the often-compartmentalised interactions between community, hospital and nursing home actors. In this endemic situation, with massive flows of patients requiring holistic management including specific and intensive care, the appropriate assessment of each patient's level of care and the organisation of specific networks is essential. To that end, we propose here a territorial organisation of health care, favouring communication between all actors. This organisation of care is based on three key points: To use the basis of territorial organisation of health by facilitating the link between hospital settings and geriatric sectors at the regional level.To connect private, medico-social and hospital actors through a dedicated centralised unit for evaluation, geriatric coordination of care and decision support. A geriatrician coordinates this multidisciplinary unit. It includes an emergency room doctor, a supervisor from the medical regulation centre (Centre 15), an infectious disease physician, a medical hygienist and a palliative care specialist.To organise an ad hoc follow-up channel, including the necessary resources for the different levels of care required, according to the resources of the territorial network, and the creation of a specific COVID geriatric palliative care service. This organisation meets the urgent health needs of all stakeholders, facilitating its deployment and allows the sustainable implementation of a coordinated geriatric management dynamic between the stakeholders on the territory.


Subject(s)
Coronavirus Infections , Geriatric Assessment/methods , Health Services for the Aged , Pandemics , Patient Care Management , Pneumonia, Viral , Regional Medical Programs/organization & administration , Aged , Betacoronavirus/isolation & purification , COVID-19 , Community Networks/organization & administration , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , France/epidemiology , Health Care Rationing/trends , Health Services for the Aged/ethics , Health Services for the Aged/organization & administration , Health Services for the Aged/trends , Humans , Organizational Innovation , Palliative Care/methods , Pandemics/prevention & control , Patient Care Management/ethics , Patient Care Management/organization & administration , Patient Care Management/trends , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , SARS-CoV-2 , Semantic Web , Stakeholder Participation
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