Complications Associated with Catheter Ablation of Atrial Fibrillation in Current Practice: Insights from a Large, Real-World Collaboration

Background: Catheter ablation is a cornerstone treatment for symptomatic atrial fibrillation (AF) with major improvements in safety over time. However, rates of adverse events with use of current techniques in a contemporary quality-focused network remain undefined. Objective(s): Across a large, real-world sample, we sought to describe (1) rates of major, adverse events associated with catheter ablation of AF and (2) patient-level factors associated with complications. Method(s): Utilizing the REAL-AF collaboration, a registry of contemporary AF ablation procedures with granular patient, procedural and follow-up data comprised of cases from over 50 operators across academic and non-academic sites, we evaluated all patients undergoing their first ablation procedure from January 2018 - June 2022. Risk-adjusted analyses were conducted to evaluate the relationship between patient factors and complications. Result(s): Among 3144 patients (age 66.1 +/- 11.0 years, 42% female, 67.1% paroxysmal, 32.9% persistent) who underwent AF ablation, procedure-related complications (n =77) were identified in 65 patients (2.1%) with multiple complications occurring in 9 patients (0.2%). Most complications (n=70, 93.5%) occurred in the peri-procedural (within 30 days) period and 6.5% (n=5) after 30 days, the latter of which all represented vascular injuries (Figure). Major complications (18 of 72 peri-procedural complications, 25.0%) are defined, detailed, and associated data reported in the Figure. Unadjusted (16.0% without CHF vs. 33.3% with CHF, p = 0.045) and risk-adjusted (OR 2.8, 95% CI 1.03-7.60, p=0.045) analyses indicated history of CHF was associated with a composite outcome of major complications. Analyses of independent complications showed those who suffered from peri-procedural stroke (n=3) were of significantly greater age (77.3 +/- 5.5 years vs. 66.1 +/- 10.9 years, p=0.035). Risk-adjusted analyses showed history of vascular disease (OR 2.9, 95% CI 1.02-8.20, p=0.045) was associated with vascular injury (n=18). From 0-695 days post-procedure, 31 deaths occurred (unknown cause: 17, COVID-19 related: 4, heart failure: 2, cardiac arrest: 2). Conclusion(s): Major complications represent rare events among those undergoing AF ablation in current practice. Risk-adjusted analyses suggest a history of CHF is associated with major complications. Similarly, older age and a history of vascular disease are associated with stroke and vascular complications, respectively. [Formula presented]Copyright © 2023

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support

This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of (i) an automatic semantic-aware scheduling method that coordinates jobs across two separate high performance computing systems;(ii) a data pipeline to collect, integrate and organize national and county-level disaggregated data for initialization and post-simulation analysis;(iii) a digital twin of national social contact networks made up of 288 Million individuals and 12.6 Billion time-varying interactions covering the US states and DC;(iv) an extension of a parallel agent-based simulation model to study epidemic dynamics and associated interventions. This pipeline can run 400 replicates of national runs in less than 33 h, and reduces the need for human intervention, resulting in faster turnaround times and higher reliability and accuracy of the results. Scientifically, the work has led to significant advances in real-time epidemic sciences. © The Author(s) 2022.

Understanding Asymptomatic Testing Uptake Amongst School Aged Children and Staff for Sars-Cov-2 Testing in Elementary and Secondary Schools

BACKGROUND: Enhanced health and safety measures, such as symptom screening, physical distancing, cohorting, masking, and asymptomatic testing for children have been introduced into schools to prevent SARSCoV- 2 transmission. Although asymptomatic testing has been considered a measure to reduce in-school transmission, it has not been broadly implemented or evaluated. To address this, a pilot project with public health, school boards, and hospital-based testing partners was established to assess the feasibility of offering on-site and low barrier SARS-CoV-2 polymerase chain reaction (PCR) testing across schools in the Toronto region. OBJECTIVE(S): The primary objective of this study was to assess the feasibility of offering on-site and low barrier PCR asymptomatic testing across schools in the Toronto region. DESIGN/METHODS: A six-week testing pilot across the Greater Toronto Area took place. Schools were selected to participate in expanded testing to determine case prevalence in high-risk settings of school-based SARSCoV- 2. Students and staff were excluded if they had tested positive for COVID-19 in the last 3 months. Different testing opportunities were offered based on the testing partner and school preference including location and modality. Descriptive methods were used to assess the uptake of testing and case positivity by individuals recommended to be tested. RESULT(S): Eighteen schools participated in the pilot testing. All students and staff were invited to participate in asymptomatic testing. Testing was offered to 9282 students and 1000 staff, and testing uptake was 29% (2729 students) and 54% (544 staff), respectively. Forty-eight percent of tests (1645) were oral nasal tests, 18% (622) were NP swab tests and 33% (1120) were saliva tests. Of the saliva tests, 52% (590) were on-site saliva tests and 48% (530) were take-home saliva kits. The staff and student positivity rate for on-site testing was 1.9% and 4.9% for tests completed at the COVID-19 Assessment Center at SickKids. CONCLUSION(S): Results from this pilot project demonstrate that on-site PCR testing uptake remained low despite offering in-school testing, specialized support, and reduced barriers by using non-invasive testing with the use of saliva/ oral nasal/PCR testing kits. Results highlight the challenges of asymptomatic testing and the balance of resource utilization for low case counts. Future studies should examine alternate means of symptomatic testing.

Accessible and Specialized Covid-19 Testing for Children and Youth with Medical Complexity

BACKGROUND: COVID-19 testing for symptomatic individuals is a key public health measure for infection prevention and control. However, COVID-19 testing can be uncomfortable without appropriate supports and can lead to testing hesitancy amongst certain populations such as children with medical complexity (CMC) and those with underlying neurological and respiratory conditions. To support COVID-19 testing, a specialized initiative was developed for CMC and their families onsite at The Hospital for Sick Children to enhance testing uptake, reduce barriers to access, and support a safe and accommodated testing environment for families. Multiple modalities of testing were involved and could be completed in their personal vehicle, with specialized support from nurses and child life if needed. OBJECTIVE(S): The objectives of our study were to investigate the characteristics of CMC and their families who underwent COVID-19 testing through our program, evaluate indications for testing, and collect case positivity rates. DESIGN/METHODS: Prospective data, including testing and population characteristics, were collected from December 2020-August 2021 through a centralized system, and was analyzed using descriptive methods. RESULT(S): 335 children (Table 1) with medical complexity came to the COVID-19 Assessment Center for testing. Of those who were tested 88% (294) had neurodevelopmental conditions with highly challenging behaviours (e.g. autism, developmental delay), and 12% (28) were classified as CMC (i.e. those with active use of medical technology e.g. tracheostomy, G-tube etc.). Of those tested, 6% (21) tested positive for COVID-19. Sixty percent (199) were tested due to having symptoms consistent with COVID-19, 27% (90) had a COVID-19 exposure, 8% (26) were exposed and tested as part of outbreak management and 5% were of an unknown criteria. The majority of completed tests (74%) were nasopharyngeal (NP) swabs, 18% completed saliva tests and 6% completed anterior nares/throat swab tests. Thirteen percent (43) of families requested additional supports such as extra nurses, child life specialists or other accommodations. All patients had a dedicated paediatric nurse and received testing in their personal vehicle. CONCLUSION(S): CMC and their families face unique barriers to COVID-19 testing. A specialized testing centre for CMC was able to support families by providing unique opportunities for testing, revealing a 6% COVID-19 positivity rate. NP swabs that can be painful were supported through in-vehicle testing with dedicated pediatric nurses. Robust health and safety measures, including a coordinated testing approach, are necessary to ensure accessible testing opportunities for CMC and their families. Further research is needed to be able to support this unique population.

The effect of the initial months of the COVID-19 national lockdown on MMed training activities at the University of the Free State, South Africa

AFRICAN DEVELOPMENT : Background. Shortly after the first case of SARS-CoV-2 infection (COVID-19) had been reported in South Africa, a national lockdown was declared. Subsequently, the University of the Free State (UFS) changed from a contact delivery mode to remote multimodal teaching, learning and assessment.Objectives. To determine the effect of the initial months of the COVID-19 lockdown on MMed training activities at the UFS, specifically the demographic and health profile of students, research progress, academic activities and the clinical training environment.Methods. A cross-sectional study using an anonymous self-administered questionnaire was used. All registered MMed students at the UFS were eligible to participate.Results. A response was obtained from 134 (51.9%) of 258 registrars, most of whom were included in the analysis (n=118;45.7%). Significant associations between the effect of the COVID-19 lockdown on day-to-day clinical work and the ability to work on MMed research (p<0.01) and self-directed learning time (p<0.01) were noted. Changes in domestic circumstances affecting MMed research were reported by 26.9% of respondents. Worsening or new symptoms of stress were reported by 40.0% of respondents.Conclusion. The initial months of the COVID-19 lockdown might have far-reaching implications for registrars' academic progress. Registrars experienced adverse psychosocial consequences that might impede their academic progress

Effective Social Network-Based Allocation of COVID-19 Vaccines

We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Using a realistic representation of a social contact network for the Commonwealth of Virginia, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals' degree (number of social contacts) and total social proximity time is significantly more effective than the usually used age-based allocation strategy in reducing the number of infections, hospitalizations and deaths. The overall strategy is robust even: (i) if the social contacts are not estimated correctly;(ii) if the vaccine efficacy is lower than expected or only a single dose is given;(iii) if there is a delay in vaccine production and deployment;and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are significant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed. © 2022 Owner/Author.

High Performance Agent-Based Modeling to Study Realistic Contact Tracing Protocols

Contact tracing (CT) is an important and effective intervention strategy for controlling an epidemic. Its role becomes critical when pharmaceutical interventions are unavailable. CT is resource intensive, and multiple protocols are possible, therefore the ability to evaluate strategies is important. We describe a high-performance, agent-based simulation model for studying CT during an ongoing pandemic. This work was motivated by the COVID-19 pandemic, however framework and design are generic and can be applied in other settings. This work extends our HPC-oriented ABM framework EpiHiper to efficiently represent contact tracing. The main contributions are: (i) Extension of EpiHiper to represent realistic CT processes. (ii) Realistic case study using the VA network motivated by our collaboration with the Virginia Department of Health. © 2021 IEEE.

Informing University Covid-19 Decisions Using Simple Compartmental Models

Tracking the COVID-19 pandemic has been a major challenge for policy makers. Although several efforts are ongoing for accurate forecasting of cases, deaths, and hospitalization at various resolutions, few have been attempted for college campuses despite their potential to become COVID-19 hot-spots. In this paper, we present a real-time effort towards weekly forecasting of campus-level cases during the fall semester for four universities in Virginia, United States. We discuss the challenges related to data curation. A causal model is employed for forecasting with one free time-varying parameter, calibrated against case data. The model is then run forward in time to obtain multiple forecasts. We retrospectively evaluate the performance and, while forecast quality suffers during the campus reopening phase, the model makes reasonable forecasts as the fall semester progresses. We provide sensitivity analysis for the several model parameters. In addition, the forecasts are provided weekly to various state and local agencies. © 2021 IEEE.

AI-Driven Agent-Based Models to Study the Role of Vaccine Acceptance in Controlling COVID-19 Spread in the US

We study the role of vaccine acceptance in controlling the spread of COVID-19 in the US using AI-driven agent-based models. Our study uses a 288 million node social contact network spanning all 50 US states plus Washington DC, comprised of 3300 counties, with 12.59 billion daily interactions. The highly-resolved agent-based models use realistic information about disease progression, vaccine uptake, production schedules, acceptance trends, prevalence, and social distancing guidelines. Developing a national model at this resolution that is driven by realistic data requires a complex scalable workflow, model calibration, simulation, and analytics components. Our workflow optimizes the total execution time and helps in improving overall human productivity.This work develops a pipeline that can execute US-scale models and associated workflows that typically present significant big data challenges. Our results show that, when compared to faster and accelerating vaccinations, slower vaccination rates due to vaccine hesitancy cause averted infections to drop from 6.7M to 4.5M, and averted total deaths to drop from 39.4K to 28.2K nationwide. This occurs despite the fact that the final vaccine coverage is the same in both scenarios. Improving vaccine acceptance by 10% in all states increases averted infections from 4.5M to 4.7M (a 4.4% improvement) and total deaths from 28.2K to 29.9K (a 6% increase) nationwide. The analysis also reveals interesting spatio-temporal differences in COVID-19 dynamics as a result of vaccine acceptance. To our knowledge, this is the first national-scale analysis of the effect of vaccine acceptance on the spread of COVID-19, using detailed and realistic agent-based models. © 2021 IEEE.

Scalable epidemiological workflows to support COVID-19 planning and response

The COVID-19 global outbreak represents the most significant epidemic event since the 1918 influenza pandemic. Simulations have played a crucial role in supporting COVID-19 planning and response efforts. Developing scalable workflows to provide policymakers quick responses to important questions pertaining to logistics, resource allocation, epidemic forecasts and intervention analysis remains a challenging computational problem. In this work, we present scalable high performance computing-enabled workflows for COVID-19 pandemic planning and response. The scalability of our methodology allows us to run fine-grained simulations daily, and to generate county-level forecasts and other counterfactual analysis for each of the 50 states (and DC), 3140 counties across the USA. Our workflows use a hybrid cloud/cluster system utilizing a combination of local and remote cluster computing facilities, and using over 20, 000 CPU cores running for 6-9 hours every day to meet this objective. Our state (Virginia), state hospital network, our university, the DOD and the CDC use our models to guide their COVID-19 planning and response efforts. We began executing these pipelines March 25, 2020, and have delivered and briefed weekly updates to these stakeholders for over 30 weeks without interruption. © 2021 IEEE.

Evaluation of patient satisfaction for telehealth (phone and video) in rheumatology outpatients during COVID-19 pandemic

Background: Telehealth via phone (TPhone) or video conference (TVideo) in rheumatology has been a topic of interest for many years. Its use was rapidly expanded due to the international public health emergency of coronavirus disease-19 (COVID-19) outbreak in 2020. Australian Medicare Benefits Schedule (MBS) swiftly enabled temporary MBS telehealth items on 13 March 2020, currently extended until 31 March 20211. In the early phase of the COVID-19 pandemic, Antony et al. conducted a single-centre public survey to assess patient perception of rheumatology telehealth. Their results showed that 98.4% of patients consider telehealth acceptable during the pandemic2. It is unclear, however, whether this positive perception persists after patients experience a telehealth. In addition, a survey data in 2019 suggested more than half of Australian rheumatologists work in private practice3. Therefore, inclusion of private patients will better represent patient perception of telehealth. Objectives: The aim of this study was to evaluate patient satisfaction with telehealth during the COVID-19 pandemic. This would determine its feasibility to be integrated in future rheumatology outpatient model. Methods: A questionnaire containing 30 questions was sent to rheumatology patients who attended telehealth appointments at a level 2 public hospital and a local private clinic between April and May 2020. The questionnaires aimed to obtain information on baseline demographics (sex, age, public or private patient, employment status, visual or auditory impairment), appointment details (TPhone or TVideo, usual arrangement for face-to-face (F2F) appointment, cost effectiveness) and appointment satisfaction using a 5-point Likert scale. Descriptive statistical analysis was conducted. Results: The questionnaire was sent to 1452 patients, of which 494 patients responded (34%). Female predominance (77.1%) and a higher proportion of TPhone (79.1%) was seen in the respondents. A majority of patients were existing patients known to the services (90.9%). More than 70% of responses indicated overall satisfaction in specialist care via telehealth, and 88.7% perceived this suitable during a pandemic. Of all respondents, 21.7% were prescribed new medication, and the majority of these patients were confident in taking the new medication after the telehealth appointment. Future acceptability for TPhone was significantly lower in private patients compared to public patients (p= 0.01). Subgroup analysis revealed that higher telehealth satisfaction was associated with needing to take time off work to attend face-to-face appointment (p= 0.02), perception of cost effectiveness (p<0.001) and TVideo (p=0.03). Conclusion: This is the first study which included both public and private rheumatology patients to evaluate patient satisfaction for telehealth during the COVID-19 pandemic. Overall high level of satisfaction was seen in telehealth most notably associated with its cost effectiveness. A higher percentage of patients who had TVideo compared to TPhone were receptive to future telehealth via TVideo, supportive of the importance of visual cues. This in turn will have significant administrative and technological burdens to coordinate in comparison to a F2F or TPhone review. This qualitative study provides valuable insight of patient perception of telehealth, which has the potential to compliment the traditional rheumatology outpatient model of care following the pandemic.

Commentary on Ferguson, et al., "Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand".

A recent manuscript (Ferguson et al. in Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, Imperial College COVID-19 Response Team, London, 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf) from Imperial College modelers examining ways to mitigate and control the spread of COVID-19 has attracted much attention. In this paper, we will discuss a coarse taxonomy of models and explore the context and significance of the Imperial College and other models in contributing to the analysis of COVID-19.