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Recent studies have examined the impact of the COVID-19 pandemic on the practice of total joint arthroplasty. A scoping review of the literature with compiled recommendations is a useful tool for arthroplasty surgeons as they resume their orthopedic practices during the pandemic.

In June 2020, PubMed, Embase (Ovid), Cochrane Library (Wiley), Scopus, LitCovid, CINAHL, medRxiv, and bioRxiv were queried for articles using controlled vocabulary and keywords pertaining to COVID-19 and total joint arthroplasty. Studies were characterized by their region of origin, design, and Center of Evidence Based Medicine level of evidence. The identified relevant studies were grouped into 6 categories changes to future clinical workflow, education, impact on patients, impact on surgeons, technology, and surgical volume.

The COVID-19 pandemic has had a significant impact on arthroplasty practice, including the disruption of the clinical teaching environment, personal and financial consequences for patients and physicians, and the drastic reduction in surgical volume. New pathways for clinical workflow have emerged, along with novel technologies with applications for both patients and trainees.

The COVID-19 pandemic emphasizes the recent trend in arthroplasty toward risk stratification and outpatient surgery, which may result in improved clinical outcomes and significant cost-savings. Furthermore, virtual technologies are a promising area of future focus that may ultimately improve upon previous existing inefficiencies in the education and clinical environments.
The COVID-19 pandemic emphasizes the recent trend in arthroplasty toward risk stratification and outpatient surgery, which may result in improved clinical outcomes and significant cost-savings. Furthermore, virtual technologies are a promising area of future focus that may ultimately improve upon previous existing inefficiencies in the education and clinical environments.
The COVID-19 pandemic has had a severe impact on the practices of adult reconstruction surgeons, primarily due to the elective nature of hip and knee arthroplasty.

To capture the impact of COVID-19 on its members, the American Association of Hip and Knee Surgeons sent 6 surveys over a span of 7months from late March until September of 2020 querying its members regarding the effects of COVID on the health and well-being of their personal, financial, and clinical practice.

Ninety-two percent of surgeons reported a cessation of elective inpatient cases during the height of the crisis. The reduction was greatest for surgeries performed in hospital-based sites of care. Ninety-one percent reported a drop in clinic volume. At the final surveys, these numbers where 7% and 59%, respectively. In addition, there was a widespread increase in the use of telemedicine during this period. Only a small number of orthopedic practices permanently closed because of COVID-19; 68% of surgeons, however, sought federal funding adaptive recovery of 2020.The coronavirus disease 2019 (COVID-19) spread rapidly across the world since its appearance in December 2019. This data set creates one-, three-, and seven-day forecasts of the COVID-19 pandemic's cumulative case counts at the county, health district, and state geographic levels for the state of Virginia. Forecasts are created over the first 46 days of reported COVID-19 cases using the cumulative case count data provided by The New York Times as of April 22, 2020. From this historical data, one-, three-, seven, and all-days prior to the forecast start date are used to generate the forecasts. Forecasts are created using (1) a Naïve approach; (2) Holt-Winters exponential smoothing (HW); (3) growth rate (Growth); (4) moving average (MA); (5) autoregressive (AR); (6) autoregressive moving average (ARMA); and (7) autoregressive integrated moving average (ARIMA). Median Absolute Error (MdAE) and Median Absolute Percentage Error (MdAPE) metrics are created with each forecast to evaluate the forecast with respect toe annotations provide the instructions needed to accomplish both routes. This data can be used to generate the same set of forecasts and error metrics for any US state by altering the state parameter within the source code. learn more Users can also generate health district forecasts for any other state, by providing a file which maps each county within a state to its respective health-district. The source code can be connected to the most up-to-date version of The New York Times COVID-19 dataset allows for the generation of forecasts up to the most recently reported data to facilitate near real-time forecasting.This article presents an extensive comparison of survey data on tolerance attitudes of 1758 participants from two public universities in sub-Saharan Africa, the University of Ghana and North-West University. Multi-stage and other sampling procedures were employed to collect the data between 2016 and 2017. Data were analysed using frequencies, percentages and cross-tabulations for each institution separately. Overall, participants expressed a high level of tolerance to others of different racial and ethnic backgrounds, albeit higher for those in the University of Ghana than North-West University. The findings further revealed that participants' gender, academic level, family socioeconomic status, and parental educational level were significantly associated with tolerant attitudes, depending on the educational institution.Scientific discoveries are the result of global collaboration and often the multidisciplinary nature of collaborations. A core element of these successful collaborations will materialise through a researcher's mobility in location and disciplinary focus. Researchers experience numerous opportunities to practice locational mobility throughout their careers as well as by conducting multidisciplinary research. Both changes have short- and long-term impacts on individual researchers and science, technology, and innovation systems that have an immediate interest for the public and private research and development funding mechanisms. With the advancement in data science tools and increasing computational capacities, we can use bibliometric data for calculating a researcher's mobility on location and a disciplinary focus over time. We looked at Finland as a case, and by incorporating analytical procedures, the processed data is capable of delivering insights on researcher mobility between cities over time as well as disciplinary change over time.
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