No title provided

Grant number: 335516

Grant search

Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $861,134.5
  • Funder

    Academy of Finland
  • Principal Investigator

    Ossi Naukkarinen
  • Research Location

    Finland
  • Lead Research Institution

    Aalto University
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Diagnostics

  • Special Interest Tags

    Innovation

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Aalto University proposes a selection of projects with high potential to support and accelerate research into the coronavirus epidemic and the mitigation of its effects. A group of sub-applications focuses on (i) ICT tools for supporting health care and self-isolation. Others propose mathematical models of the pandemic, also exploiting AI methods. Aalto even suggests technological innovations comprising (ii) novel materials and production chains for medical equipment, (iii) improved diagnostic and detection methods for the SARS-CoV-2 virus, sometimes also accompanied by effective disinfection procedures and even a few suggestions for (iv) the treatment of COVID-19 patients. To limit the spread of the disease, we also included a few sub-applications studying (v) physical phenomena and spreading mechanisms. In addition to technological solutions, Aalto offers research actions in (vi) limiting the economic impact of the pandemic and in (vii) solving societal and wellbeing challenges.

Publicationslinked via Europe PMC

Superspreading of SARS-CoV-2 at a choir rehearsal in Finland-A computational fluid dynamics view on aerosol transmission and patient interviews.

Modelling aerosol-based exposure to SARS-CoV-2 by an agent based Monte Carlo method: Risk estimates in a shop and bar.