COVID-19 epidemic modelling for policy decision support in Victoria, Australia 2020-2021.

BACKGROUND: Policy responses to COVID-19 in Victoria, Australia over 2020-2021 have been supported by evidence generated through mathematical modelling. This study describes the design, key findings, and process for policy translation of a series of modelling studies conducted for the Victorian Department of Health COVID-19 response team during this period. METHODS: An agent-based model, Covasim, was used to simulate the impact of policy interventions on COVID-19 outbreaks and epidemic waves. The model was continually adapted to enable scenario analysis of settings or policies being considered at the time (e.g. elimination of community transmission versus disease control). Model scenarios were co-designed with government, to fill evidence gaps prior to key decisions. RESULTS: Understanding outbreak risk following incursions was critical to eliminating community COVID-19 transmission. Analyses showed risk depended on whether the first detected case was the index case, a primary contact of the index case, or a 'mystery case'. There were benefits of early lockdown on first case detection and gradual easing of restrictions to minimise resurgence risk from undetected cases. As vaccination coverage increased and the focus shifted to controlling rather than eliminating community transmission, understanding health system demand was critical. Analyses showed that vaccines alone could not protect health systems and need to be complemented with other public health measures. CONCLUSIONS: Model evidence offered the greatest value when decisions needed to be made pre-emptively, or for questions that could not be answered with empiric data and data analysis alone. Co-designing scenarios with policy-makers ensured relevance and increased policy translation.

Hospital at Home: An Evolving Model for Comprehensive Healthcare.

Hospital at Home (HaH) is a sustainable, innovative, and next-generation model of healthcare. From the healthcare management point of view, this model provides cost benefits and quality improvement, and from the physicians' point of view, it helps in providing patient-centered medical care and keeps patients away from hospital admission and its complications. The HaH model was first introduced at John Hopkins in the United States in 1995, which showed very promising results in context to the length of stay, readmission rates, patient satisfaction, and hospital-acquired infections. The HaH model of care provides acute critical care to patients at home and reduces unnecessary hospitalization and related complications. The identified patients for this model of care are elderly patients with chronic conditions and multiple comorbidities. The emergence of technology in today's world and the impact of coronavirus disease 2019 (COVID-19) have increased the demand for the HaH model of care. Although there are many benefits and advantages, the HaH model of care has significant barriers and limitations, such as reimbursement for payment, physician and patient resistance, patient safety, and lack of quantifying research data to support the use of this model. Specific training for the physician, nursing, and other members of the HaH multidisciplinary team is necessary for HaH treatment protocols, along with patient and family caregiver education for those who elect the HaH model of care. HaH is the future of comprehensive healthcare services and helps in achieving the triple aim of access to healthcare, improved quality of care, and reduced cost for healthcare.

Measuring Training Disruptions Using an Informatics Based Tool.

OBJECTIVE: Training disruptions, such as planned curricular adjustments or unplanned global pandemics, impact residency training in ways that are difficult to quantify. Informatics-based medical education tools can help measure these impacts. We tested the ability of a software platform driven by electronic health record data to quantify anticipated changes in trainee clinical experiences during the COVID-19 pandemic. METHODS: We previously developed and validated the Trainee Individualized Learning System (TRAILS) to identify pediatric resident clinical experiences (i.e. shifts, resident provider-patient interactions (rPPIs), and diagnoses). We used TRAILS to perform a year-over-year analysis comparing pediatrics residents at a large academic children's hospital during March 15-June 15 in 2018 (Control #1), 2019 (Control #2), and 2020 (Exposure). RESULTS: Residents in the exposure cohort had fewer shifts than those in both control cohorts (P < .05). rPPIs decreased an average of 43% across all PGY levels, with interns experiencing a 78% decrease in Continuity Clinic. Patient continuity decreased from 23% to 11%. rPPIs with common clinic and emergency department diagnoses decreased substantially during the exposure period. CONCLUSIONS: Informatics tools like TRAILS may help program directors understand the impact of training disruptions on resident clinical experiences and target interventions to learners' needs and development.

social Pathology after Pandemia & armed conflicts: abuse, depression & other Psychosocial disorders importancy of legal support to continue Vaccination

Another 4 papers are more optimistic, showing legal responses of major EU and US courts, unequivocally calling for respect for humans rights;putting the right to health protection and public health interests;upgrading them in front of other HR issues (Sikuta et al., Costello, Abdulaziz Naji, Shahum et al.), Brussels, EU and Saudi experience show that law in alll 3 systems - constitutional, custom, Islamic and Christian values are concerning law protection not only on one ,, rail,, but also to one direction, protection of public and individual health. Public Health Law & the COVID-19 Pandemic (Letter to the Editor), Clinical Social Work and Health Intervention, No.6, Vol 13,2022. Retail Pharmacies are not just any Businesses - The lack of Public Discussion about the Death of Pharmacies (Letter to the Editor), Clinical Social Work and Health Intervention, No.6, Vol 13, 2022.

Enhancing epidemiological surveillance of the emergence of the SARS-CoV-2 Omicron variant using spike gene target failure data, England, 15 November to 31 December 2021.

When SARS-CoV-2 Omicron emerged in 2021, S gene target failure enabled differentiation between Omicron and the dominant Delta variant. In England, where S gene target surveillance (SGTS) was already established, this led to rapid identification (within ca 3 days of sample collection) of possible Omicron cases, alongside real-time surveillance and modelling of Omicron growth. SGTS was key to public health action (including case identification and incident management), and we share applied insights on how and when to use SGTS.

Replace, amplify, transform: a qualitative study of how postgraduate trainees and supervisors experience and use telehealth for instruction in ambulatory patient care.

BACKGROUND: Little is known about using telehealth patient visits as an educational mode. Therefore, rapid implementation of telehealth during the COVID-19 pandemic had to be done without understanding how to optimize telehealth for education. With the likely sustained/post-pandemic use of telehealth in ambulatory patient care, filling gaps in our understanding of how telehealth can be used for instruction in this context is critical. This study sought to understand perceptions of pediatric postgraduate trainees and supervisors on the use of telehealth for instruction in ambulatory settings with the goal of identifying effective ways to enhance learning during telehealth visits. METHODS: In May-June of 2020, the authors purposefully sampled first- and third-year postgraduate trainees and supervising attendings from pediatric fellowship programs at one institution that implemented telehealth for instructional activities. They conducted semi-structured interviews; interviews lasted a median of 51 min (trainees) and 41 min (supervisors). They conducted interviews and data analysis iteratively until reaching saturation. Using thematic analysis, they created codes and constructed themes from coded data. They organized themes using the Replace-Amplify-Transform (RAT) model, which proposes that technology can replace in-person learning and/or amplify and transform learning. RESULTS: First-year trainees (n = 6), third-year trainees (n = 5) and supervisors (n = 6) initially used telehealth to replace in-person learning. However, skills that could be practiced in telehealth visits differed from in-person visits and instructional activities felt rushed or awkward. Trainees and supervisors adapted and used telehealth to amplify learning by enhancing observation and autonomy. They also transformed learning, using telehealth to develop novel skills. CONCLUSIONS: To harness telehealth for instructional activities, our findings indicated that trainees and supervisors should shift from using it as a direct replacement for in-person education to taking advantage of novel opportunities to amplify and transform education in PGME. The authors provide data-driven recommendations to help PGME trainees, supervisors and educators capitalize on the educational advantages of telehealth.