Screening & Surveillance

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Adobe Stock 416534355
Adobe Stock 416534355
Adobe Stock 416534355
Adobe Stock 416534355
Screening & Surveillance

Agreement hopes to spur enhanced, global access to COVID testing technologies

June 16, 2022
A new, open, transparent sublicense agreement between the Medicines Patent Pool (MPP) on behalf of C-TAP, and South African pharmaceutical company Biotech Africa will accelerate...
Photo by Andrea Piacquadio from Pexels
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Pexels Andrea Piacquadio 3791136
Pexels Andrea Piacquadio 3791136
Pexels Andrea Piacquadio 3791136
Pexels Andrea Piacquadio 3791136
Screening & Surveillance

Poor sleep can triple risk for heart disease

Feb. 11, 2022
Individual aspects of poor sleep can be detrimental to heart health. But if you combine them, the risk of heart disease can increase by as much as 141 percent. The study was published...
Screening & Surveillance

Shortness of breath, fatigue, muscle weakness, and cognitive dysfunction symptoms found 1-5 months after SARS-CoV-2 infection

Feb. 7, 2022
A new study published in JAMA Open, found that understanding the frequency with which new symptoms and conditions emerge in the months following SARS-CoV-2 infection is important...
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Screening & Surveillance

OHSU forecaster credits Oregonians for reducing infections, lowering per-capita hospitalizations compared with other states

Feb. 7, 2022
The number of people hospitalized for COVID-19 in Oregon were forecast to peak in early February near current levels, and then steadily recede to pre-Omicron levels by the end...
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Corona Gd2078d787 1920
Corona Gd2078d787 1920
Corona Gd2078d787 1920
Corona Gd2078d787 1920
Screening & Surveillance

Sources report US COVID-19 cases continue steep decline

Feb. 4, 2022
Cases of COVID-19 continue to drop significantly across the country, as the most recent surge caused by the Omicron variant is declining at a rapid pace according to a CIDRAP ...
Courtesy of University of Texas at Austin.
Fig. 1 Retrospective validation of the forecasting model using data from March 12, 2020, through February 1, 2021. The graph compares the number of COVID-19 ICU patients in the Austin area (black dots) to forecasts that were made two weeks in advance (blue lines). The blue shading around each two-week forecast indicates the 95% prediction intervals. The yellow, orange, and red shading in the background indicate the timing of COVID-19 alert stages 3, 4, and 5 in the Austin area, respectively. Courtesy of University of Texas at Austin.
Fig. 1 Retrospective validation of the forecasting model using data from March 12, 2020, through February 1, 2021. The graph compares the number of COVID-19 ICU patients in the Austin area (black dots) to forecasts that were made two weeks in advance (blue lines). The blue shading around each two-week forecast indicates the 95% prediction intervals. The yellow, orange, and red shading in the background indicate the timing of COVID-19 alert stages 3, 4, and 5 in the Austin area, respectively. Courtesy of University of Texas at Austin.
Fig. 1 Retrospective validation of the forecasting model using data from March 12, 2020, through February 1, 2021. The graph compares the number of COVID-19 ICU patients in the Austin area (black dots) to forecasts that were made two weeks in advance (blue lines). The blue shading around each two-week forecast indicates the 95% prediction intervals. The yellow, orange, and red shading in the background indicate the timing of COVID-19 alert stages 3, 4, and 5 in the Austin area, respectively. Courtesy of University of Texas at Austin.
Fig. 1 Retrospective validation of the forecasting model using data from March 12, 2020, through February 1, 2021. The graph compares the number of COVID-19 ICU patients in the Austin area (black dots) to forecasts that were made two weeks in advance (blue lines). The blue shading around each two-week forecast indicates the 95% prediction intervals. The yellow, orange, and red shading in the background indicate the timing of COVID-19 alert stages 3, 4, and 5 in the Austin area, respectively. Courtesy of University of Texas at Austin.
Fig. 1 Retrospective validation of the forecasting model using data from March 12, 2020, through February 1, 2021. The graph compares the number of COVID-19 ICU patients in the Austin area (black dots) to forecasts that were made two weeks in advance (blue lines). The blue shading around each two-week forecast indicates the 95% prediction intervals. The yellow, orange, and red shading in the background indicate the timing of COVID-19 alert stages 3, 4, and 5 in the Austin area, respectively. Courtesy of University of Texas at Austin.
Screening & Surveillance

COVID forecasting using hospital and cell phone data proves it can reliably guide US cities through pandemic threats

Feb. 3, 2022
The University of Texas at Austin has reliably forecasted regional hospital demands for almost two years, using cell phone mobility data and COVID-19 hospital admissions data,...