Demographic and training descriptive analysis of National and American Hockey League team physicians.

Aims/objective: Assess the demographic/education backgrounds of team physicians (TPs) in the National Hockey League (NHL) and American Hockey League (AHL).

Materials/methods: Orthopedic Surgeon (O) and Primary Care (PC) TPs for each NHL and AHL team were recorded based on an internet search. Age, sex, and race were collected.

Optimizing Disease Outbreak Forecast Ensembles.

On the basis of historical influenza and COVID-19 forecasts, we found that more than 3 forecast models are needed to ensure robust ensemble accuracy. Additional models can improve ensemble performance, but with diminishing accuracy returns. This understanding will assist with the design of current and future collaborative infectious disease forecasting efforts.

Effectiveness of interventions to reduce COVID-19 transmission in schools.

School reopenings in 2021 and 2022 coincided with the rapid emergence of new SARS-CoV-2 variants in the United States. In-school mitigation efforts varied, depending on local COVID-19 mandates and resources. Using a stochastic age-stratified agent-based model of SARS-CoV-2 transmission, we estimate the impacts of multiple in-school strategies on both infection rates and absenteeism, relative to a baseline scenario in which only symptomatic cases are tested and positive tests trigger a 10-day isolation of the case and 10-day quarantine of their household and classroom.

Projecting Omicron scenarios in the US while tracking population-level immunity.

Throughout the COVID-19 pandemic, changes in policy, shifts in behavior, and the emergence of new SARS-CoV-2 variants spurred multiple waves of transmission. Accurate assessments of the changing risks were vital for ensuring adequate healthcare capacity, designing mitigation strategies, and communicating effectively with the public. Here, we introduce a model of COVID-19 transmission and vaccination that provided rapid and reliable projections as the BA.

Model for Interpreting Discordant SARS-CoV-2 Diagnostic Test Results.

We devised a model to interpret discordant SARS-CoV-2 test results. We estimate that, during March 2020-May 2022, a patient in the United States who received a positive rapid antigen test result followed by a negative nucleic acid test result had only a 15.4% (95% CI 0.

Evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. Forecasting teams were asked to provide national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one through four weeks ahead for the 2021-22 and 2022-23 influenza seasons. Across both seasons, 26 teams submitted forecasts, with the submitting teams varying between seasons.

Optimizing COVID-19 testing strategies on college campuses: Evaluation of the health and economic costs.

Colleges and universities in the US struggled to provide safe in-person education throughout the COVID-19 pandemic. Testing coupled with isolation is a nimble intervention strategy that can be tailored to mitigate the changing health and economic risks associated with SARS-CoV-2. We developed a decision-support tool to aid in the design of university-based screening strategies using a mathematical model of SARS-CoV-2 transmission.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.

Informing pandemic response in the face of uncertainty. .

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.

Real time monitoring of COVID-19 intervention effectiveness through contact tracing data.

Communities worldwide have used vaccines and facemasks to mitigate the COVID-19 pandemic. When an individual opts to vaccinate or wear a mask, they may lower their own risk of becoming infected as well as the risk that they pose to others while infected. The first benefit-reducing susceptibility-has been established across multiple studies, while the second-reducing infectivity-is less well understood.

Disproportionate impacts of COVID-19 in a large US city.

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas.

Estimating the undetected emergence of COVID-19 in the US.

As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and local authorities were left to make rapid decisions based on limited case data and scientific information to protect their communities.

The risk of SARS-CoV-2 Omicron variant emergence in low and middle-income countries (LMICs).

We estimated the probability of undetected emergence of the SARS-CoV-2 Omicron variant in 25 low and middle-income countries (LMICs) prior to December 5, 2021. In nine countries, the risk exceeds 50 %; in Turkey, Pakistan and the Philippines, it exceeds 99 %. Risks are generally lower in the Americas than Europe or Asia.

Optimizing COVID-19 testing strategies on college campuses: evaluation of the health and economic costs.

Colleges and universities in the US struggled to provide safe in-person education throughout the COVID-19 pandemic. Testing coupled with isolation is a nimble intervention strategy that can be tailored to mitigate health and economic costs, as the virus and our arsenal of medical countermeasures continue to evolve. We developed a decision-support tool to aid in the design of university-based testing strategies using a mathematical model of SARS-CoV-2 transmission.

Shoulder injuries in ice hockey players: Prevalence, common management, and return to play.

Background: The sport of ice hockey has reached worldwide popularity, and it continues to grow. With this growth, however, there has also been an increase in the number of injuries related to the high-speed physical nature of the sport. Upper extremity related traumas and maladies are amongst the most commonly experienced injuries in this population of athletes.

The effectiveness of COVID-19 testing and contact tracing in a US city.

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries worldwide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Projecting the Combined Health Care Burden of Seasonal Influenza and COVID-19 in the 2020-2021 Season.

Unlabelled: In mid-2020, there was significant concern that the overlapping 2020-2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020-2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021.

Impact of the Timing of Stay-at-Home Orders and Mobility Reductions on First-Wave COVID-19 Deaths in US Counties.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission continues to evolve, understanding the contribution of location-specific variations in nonpharmaceutical interventions and behaviors to disease transmission during the initial epidemic wave will be key for future control strategies. We offer a rigorous statistical analysis of the relative effectiveness of the timing of both official stay-at-home orders and population mobility reductions during the initial stage of the US coronavirus disease 2019 (COVID-19) epidemic. We used a Bayesian hierarchical regression to fit county-level mortality data from the first case on January 21, 2020, through April 20, 2020, and quantify associations between the timing of stay-at-home orders and population mobility with epidemic control.