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News
October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.

 

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Modeling COVID-19 response in Cuba: a hybrid approach combining agent-based modeling and time series analysis

Population Health Metrics. 2025. Vol. 23. Article 71.
Orlando G., Bufalo M., Nazarova V.

The COVID-19 pandemic has disproportionately impacted vulnerable populations, such as low-income households, exacerbating existing health and economic challenges. In Cuba, the crisis exposed the effects of long-standing economic difficulties, worsened by sanctions, but the country’s robust public health system and independent vaccine development enabled an effective response. This study addresses the gap in understanding how socio- economic factors and individual behaviors interact to influence disease spread. It proposes a hybrid, efficient, and parsimonious model combining ABM (Agent-Based Modeling) and ARIMAX (AutoRegressive Integrated Moving Average with eXogenous variables) time series analysis to forecast COVID-19 cases, offering valuable insights for policymakers to tailor interventions and enhance crisis management.

Research target: Economics and Management Health Studies
Language: English
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Keywords: abmCOVID-19PCAARIMAXHealth Policies
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