Parrish Tobin (turrettrip12)

This paper presents the results of a new approach to discover related health and social factors during the COVID-19 pandemic. The approach leverages a knowledge graph of related concepts mined from a corpus of published evidence (PubMed) prior to the pandemic. Population trends from online searches were used to identify social determinants of health (SDoH) concepts that trended high at the outset of the pandemic from a list of SDoH topics from the World Health Organization (WHO). The trending concepts were then mapped to the knowledge graph and a subsequent analysis of the derived insights, spanning two years, was conducted. This paper suggests an approach to derive new related health and social factors that may have either played a role in, or been affected by, the onset of the global COVID-19 pandemic. In particular, our results show how, from a list of SDoH topics, Food Security, Unemployment trended the highest at the start of the pandemic. Further work is needed to continue to ascertain the validity of the derived relations in a population health context and to improve mining insights from published evidence.In Finland, it is possible to quickly produce medical symptom self-assessment tools within the existing infrastructure. The Finnish Omaolo Covid-19 web-based symptom self-assessment tool (symptom checker) was launched on March 16, 2020 after a 6-day development period. By using the web-based Omaolo Covid-19 symptom checker during the second wave of the epidemic, some 1.72 million questionnaires were recorded, out of which 1.55 million from symptomatic persons. Some 15% of the responses (245,500) were directed to seek emergency medical care based on the online screening by respondent response profiles.The paper analyzes the evolution of COVID-19 cases in Romanian counties over a period of 10 months, to highlight possible similarities that may contribute to a better understanding of the spreading pattern. The study uses the numbers of active cases for each county in Romania, as well as Bucharest and the whole country, reported daily by the Romanian Ministry of Health (https//datelazi.ro) between April 2nd, 2020 and January 25th, 2021. We compared the disease's evolution in Suceava county (the first outbreak of spread) with other counties in Romania in order to highlight the gaps between them. We calculated the cross-correlations between counties, interpreted as time series. The recorded lags varied between 1-15 days, the most counties having a lag of 6-7 days compared with Suceava. Therefore, on long term there are no important discrepancies between the regions in Romania regarding the evolution of the disease, which shows that the intervention efforts of the medical staff were uniform in efficiency. The existence of a lag of only one day between Suceava and the whole country shows that on long term, even in this county the situation is not very discrepant, belonging to the general evolution.Cognitive Behavioural Therapy (CBT) is an action-oriented psychotherapy that combines cognitive and behavioural techniques for psychosocial treatment for depression, and is considered by many to be the golden standard in psychotherapy. More recently, computerized CBT (CCBT) has been deployed to help increase availability and access to this evidence-based therapy. In this vein, a CBT ontology, as a shared common understanding of the domain, can facilitate the aggregation, verification, and operationalization of computerized CBT knowledge. Moreover, as opposed to black-box applications, ontology-enabled systems allow recommended, evidence-based treatment interventions to be traced back to the corresponding psychological concepts. We used a Knowledge Management approach to synthesize and computerize CBT knowledge from multiple sources into a CBT ontology, which allows generating personalized action plans for treating mild depression, using the Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL). We performed a formative