Virtual hospital-level care-feasibility, acceptability, safety and impact of a pilot Hospital-In-The-Home model for COVID-19 infection.

Background: Hospital-in-the-Home (HITH) delivers hospital level care to patients in the comfort of their own home. Traditionally HITH involves clinicians travelling to patients' homes. We designed and implemented a virtual model of care leveraging a combination of virtual health modalities for children with COVID-19 in response to rising patient numbers, infection risk and pressures on protective equipment. In contrast to other models for COVID-19 infection in Australia at the time, our HITH service catered only for children who were unwell enough to meet criteria for hospitalisation (ie bed-replacement). Aims: To measure the feasibility, acceptability, safety and impact of a virtual model of care for managing children with COVID-19 infection requiring hospital-level care. Methods: Retrospective study of a new virtual model of care for all children admitted to the Royal Children's HITH service with COVID-19 infection between 7th October 2021 and 28th April 2022. The model consisted of at least daily video consultations, remote oximetry, symptom tracking, portal messaging and 24 h phone and video support. Patients were eligible if they met a certain level of severity (work of breathing, dehydration, lower oxygen saturations) without requiring intravenous fluids, oxygen support or intensive care. Online surveys were distributed to staff and consumers who experienced the model of care. Results: 331 patients were managed through the virtual HITH program with a mean length of stay of 3.5 days. Of these, 331 (100%) engaged in video consultations, 192 (58%) engaged in the patient portal and completed the symptom tracker a total of 634 times and communicated via a total of 783 messages. Consumer satisfaction (n = 31) was high (4.7/5) with the most useful aspect of the model rated as video consultation. Clinician satisfaction (n = 9) was also high with a net promoter score of 8.9. There were no adverse events at home. Eight children (2.4%) represented to hospital, 7 (2.1%) of whom were readmitted. The impact is represented by a total of 1,312 hospital bed-days saved in the seven-month period (2,249 bed-days per year). In addition, 1,480 home visits (travel time/ protective equipment/ infection risk) were avoided. Conclusion: A virtual HITH program for COVID-19 in children is feasible, acceptable and safe and has a substantial impact on bed-days saved and nursing travel time. The implications for management of other acute respiratory viral illnesses that contribute to hospital bed pressure during winter months is immense. Virtual HITH is likely to be a key enabler of a sustainable healthcare system.

The impact of Tiktok contents on students' social perceptions and lifestyles during the COVID-19 pandemic

Tiktok rose in the COVID-19 pandemic as a platform for video-sharing that ensures community connection and prevention of pessimism during social distancing. It is of special importance to thoroughly understand its potential in providing information and lockdown optimism, and its potential to cause harm on impressionable young users who occupy a great part of the Tiktok community. This research is implemented in order to learn more about young users' behaviours and their reaction towards common Tiktok contents which depict Tiktok impacts. We developed a survey using both quantitative and qualitative questions, concentrating on user habits, well-known content categories on Vietnamese Tiktok and how they may affect users' perception. 253 participants aged 16-22 in Mekong Delta, Vietnam were involved. Data revealed that young users had higher awareness of toxic contents than was assumed by previous academic works, and eager to diminish these harms. Qualitative answers provided notions about several toxic and inappropriate contents that were not previously addressed. The research also noticed a slight hint of "Tiktok prejudice"which was the fixed concept that Tiktok was negative, inspiring future extensive research. © 2022 ACM.

An Innovative Model to Ensure Access to Hcv Treatment among Vulnerable Inner City Residents in Covidworld

Background: Due to public health regulations, many outreach programs aimed at identifying and treating disengaged populations at high risk of HCV infection were suspended. This led to a significant decrease in treatment starts and, quite likely, an increase in disease incidence among this group of core transmitters. There is an urgent need to design and evaluate novel approaches to ensure that this unmet need is addressed in concert with COVID-related programs to mitigate disease transmission, optimize COVID vaccination rates as well as timely diagnosis and treatment of COVID cases in this unique environment. Method(s): We designed a program of intervention based in single room occupancy residences in the inner city of Vancouver, Canada. Events were held in common areas and conformed to all social distancing/personal protective equipment regulations. Only residents of the building were allowed to participate, to minimize social mixing. Point of care testing for HCV was offered by finger stick rather than oral swab, to allow constant masking. Education was offered about COVID transmission, the importance of vaccination and the availability of treatment. Access to COVID rapid tests at the time of the event and beyond was facilitated, along with (more recently) an offer of antiviral treatment if eligible. In all cases, an offer of broader engagement in multidisciplinary care was made, to address HCV infection and other essential needs. Result(s): Since July 2020, 80 events have been held. We have reached 1193 individuals (71.1% male, 23.8% Aboriginal). HCV antibody positivity rate was 36.3%. Viremia testing was completed in 358 individuals, with 173 (48.3%) being positive. Of these, 97 have initiated treatment, 64 have completed treatment, with SVR12 rate of 53/54 (98.1%), and 31 patients remain in care, awaiting HCV treatment initiation. Data on COVID vaccination and disease transmission rates are being analyzed. Conclusion(s): It is still possible to design programs of intervention for inner city residents while respecting COVID regulations. Such events (conducted within a population where 1/3 are infected with HCV), conducted within the context of an offer of broader care, are highly successful and will contribute significantly towards an increase in HCV treatment starts in a group that has been particularly disadvantaged in the pandemic era.

Predicting the Impact of COVID-19 on Air Transportation Volumes

COVID-19 has significant impacts on air transportation. This paper aims to predict domestic and international transportation volumes during the pandemic. Daily trips by distance are novel variables in the prediction. Additionally, COVID-19 severity, vaccination, and economic index are other predictors. Artificial Neural Networks and Monte Carlo simulations were used to develop and validate the predictive models using data from various sources in 2021. The findings confirm the importance of daily trips by distance and vaccination as significant predictors. Airlines can use the models to predict air transportation volumes and formulate appropriate strategies to meet the air travel demand and improve profitability. © 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

Predicting Risk of Stroke in Hospitalized Patients with COVID-19: A Machine Learning Approach

Objective: The aim of this study is to leverage advanced analytics to develop an accurate, individualized risk prediction paradigm for stroke in hospitalized patients with COVID-19. Background: Patients hospitalized with COVID-19 have significantly higher risk of developing stroke compared to the general population. Predicting stroke in these patients, particularly those who are encephalopathic or ventilator-dependent, remains a challenge. Design/Methods: Patients admitted to a network of hospitals in the Austin metropolitan area with laboratory-confirmed COVID-19 were analyzed from March 2020 to June 2021. Using each patient's demographic, medication, laboratory and clinical assessment data, several machinelearning algorithms were developed to predict probability of stroke. Results: A total of 8,183 patients hospitalized with COVID-19 met our inclusion criteria. Among this cohort, 174 patients experienced a stroke. Of the machine learning algorithms that were developed and evaluated for stroke prediction, the random forest model achieved the highest prediction accuracy with a strong overall discriminatory performance. The features with the most significant prognostic value include ventilator dependence, history of hyperlipidemia, history of cancer and administration of aspirin. Conclusions: Machine learning models are capable of multi-dimensional analysis and can be leveraged to predict risk of stroke in patients hospitalized with COVID-19. Further studies are underway to incorporate a final model into the clinical pipeline for automated, patient-specific risk stratification.

School Psychology Unified Call for Deeper Understanding, Solidarity, and Action to Eradicate Anti-AAAPI Racism and Violence

Racist rhetoric blaming the Asian, Asian American, and Pacific Islander (AAAPI) community for the COVID-19 pandemic has precipitated a surge of violence against the AAAPI community in the United States, including the Atlanta mass shooting on March 16, 2021. These incidents resurfaced the ongoing racism against AAAPIs that has largely been unaddressed despite lasting almost 2 centuries. The erasure of AAAPIs’ historical oppression, unique cultures, languages, immigration experiences, and contributions to scientific and social justice advancement in the United States has hindered AAAPI voices from being heard. School psychologists are ethically bound to promote equity and dismantle racism;it is imperative to increase visibility of AAAPIs’ experiences across training levels (P–12 and graduate programs), settings, and systems. In this unified statement, school psychology organizations have come together to reaffirm the field’s commitment to anti-racism by offering proactive strategies to effectively promote visibility and equity for AAAPI students, families, and communities. Impact Statement Although there has been a complete absence of discussion of anti-AAAPI racism and anti-racism in school psychology, the field is actively committed to dismantling systemic racism and inequalities in P–12 schools, institutions of higher education, and communities across our nation. This statements seeks to address this absence by providing (a) a much-needed starting point for school psychologists to learn about the history of discrimination, racism, and violence targeting AAAPIs in the United States that has been virtually unaddressed;(b) a critical context for the recent rise in COVID-19-related anti-AAAPI violence while shedding critical light on the deep-seated racism that has oppressed AAAPIs for centuries in America;and (c) beginning strategies that school psychology faculty members, practitioners, and students can engage in to dismantle anti-AAAPI racism across individual and systems levels. © 2021 National Association of School Psychologists.

Hepatitis c treatment for vulnerable inner-city populations: impact on treatment initiation during COVID-19 era

Background: To achieve the World Health Organization's goal to eliminate hepatitis C (HCV) as a public health concern by 2030, treatment starts will have to be maintained, especially among vulnerable inner-city populations With the advent of the SARS-CoV-2 pandemic, treatment starts were reduced due to diversion of resources away from HCV programs The inner-city population was further marginalized by essential public health measures designed to control the pandemic It is important to document the impact on HCV programs and the measures that may have already been taken to address them in the context of the evolving measures to address the SARS-CoV-2 pandemic Methods: Within our multidisciplinary program of care to address HCV among vulnerable populations (most of whom reside in the inner city), we calculated our usual rate of monthly treatment starts from 01/19 to 02/20 We then calculated treatment starts in 03/20 to 05/20, when programs to identify HCV-infected patients and engage them in care were suspended This was further compared to starts from 06/1/20 to 07/15/20 when outreach programs were slowly re-initiated in conjunction with TeleHealth initiatives to provide enhanced support to patients Results: In the 14 months from 01/19 - 02/20, there was an average of 10 treatment starts/month at our centre Key demographics of the treated population were mean age 50 (25-76) years, 79% male, 93% drug users, 89% on opioid substitution therapy (OST), 27% homeless, and 38% with psychiatric co-morbidities From 03/1/20 - 07/15/20 there were 23 treatment starts: mean age 47 (22-75) years, 83% male, 70% drug users, 65% on OST, 22% with psychiatric co-morbidities, and 17% homeless In the 3 months from 03/20 - 05/20, there were only 9 starts and in 06/20, there were 6 starts. In the first half of 07/20, there were 8 starts. This represents a 60% increase in treatment starts/month compared to our long-term average, and likely represents a partial 'warehouse' effect Conclusion: Among established programs such as ours, the advent of the SARS-CoV-2 pandemic led to a virtual suspension of HCV treatment starts for a period of 3 months As the pandemic came under control in our jurisdiction, we were able to resume our programming in a way that is consistent with the public health measures needed to control the pandemic while still optimizing HCV care delivery In order to stay on track to achieve HCV elimination goals, we must control SARS-CoV-2 transmission to allow treatment programs to resume optimal function within the framework of the 'better normal' of the evolving pandemic response.