More than 3 months after being shut down due to the pandemic, the first labs began returning to physical worksites under strict safety guidelines and with significant restrictions. Days later, several scientists in Group A described the unprecedented period from a researcher’s perspective.
The ski town of Ischgl in the Austrian Alps was the site of an early Covid-19 outbreak; more than 10,000 people would be infected with SARS-CoV-2 in Ischgl, or by someone who had visited there. But astonishingly, only two people there would die. More than 42 percent of residents carried coronavirus antibodies, among the highest rates of seroprevalence ever detected.
There’s a flood of epidemiological data pouring in daily on Covid-19. How do we integrate this deluge of data into a usable format? Dr. John Holmes, having just returned from a sabbatical in Italy, discusses ways to make sense of the data through statistical modeling and machine learning.
NINDS recently held its 14th nonprofit forum, “Progress through Partnership,” drawing its largest crowd, albeit virtually, to date. More than 200 participants gathered in cyberspace via Zoom.
On the Cover
Mouse, trachea, scanning electron microscopy. Cilia (turquoise) microvilli on ciliated cells (yellow) goblet cells (red).
Photo: Dan Sackett, NHGRI; John Burke, NHGRI; Patricia Zerfas, ORS; Erina He, ORS
