Demographers have been thrust to the frontlines of the world’s efforts to evaluate the coronavirus pandemic, but so far without any weapons. Lacking data, they cannot reliably assess the situation. And this is despite the fact that the Internet, it would seem, is flush with statistics. A webinar hosted by the HSE International Laboratory for Population and Health discussed the paradoxes of quantitative approaches to COVID-19. IQ.HSE spoke with webinar participants Vladimir Shkolnikov, Inna Danilova, and Dmitry Jdanov.
In the Expert Analytical Centre’s 2020 Publication Activity Ranking, HSE University placed among the top three Russian universities in seven general subject areas and two narrow subjects. HSE made the rankings in 14 subject areas and four specific subjects; of these, HSE placed first in four subjects and/or areas.
A mathematical model of Covid-19 spreading in Nizhny Novgorod Region, which has been created by the Big Data Laboratory at Nizhny Novgorod Development Strategy Project Office, has been widely discussed in the media and on social networks. The research was led by Anastasia Popova, a master’s student of HSE University in Nizhny Novgorod, repeat winner of machine learning competitions, and winner of Ilya Segalovich Award by Yandex. In the following interview given on April 15, Anastasia speaks about how the model was developed, the data it uses, and long-term potential applications.
The first research seminar of the International Laboratory of Statistical and Computational Genomics had been postponed almost a month due to COVID-19. In April, however, the event finally took place. Laboratory Head Vladimir Shchur discusses what life is like for scientists in self-isolation during the pandemic, what genomics is, and why gesturing is important when teaching online.