Data streams and mathematical modelling pipelines to support preparedness and decision making for COVID-19 and future pandemics

Grant number: 105572

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Key facts

  • Disease

    COVID-19
  • start year

    -99
  • Known Financial Commitments (USD)

    $0
  • Funder

    NordForsk
  • Principal Investigator

    Tom Britton
  • Research Location

    Finland, Norway
  • Lead Research Institution

    Stockholm University
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Impact/ effectiveness of control measures

  • Special Interest Tags

    N/A

  • Study Type

    Unspecified

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

The goal of this programme is to, for the first time, create a joint Nordic long-term academic collaboration on pandemic preparedness using advanced mathematical modelling and systematically collected health data from a broad range of sources. To start off the programme involves Finland, Norway, and Sweden, but our ambition is to also include Denmark, Iceland, and the Baltic countries later on. The programme participants comprise epidemiologists, statisticians, mathematicians, and computer scientists, and will involve several participants from each of the three national public health institutes, with the directors of the institutes contributing as members of the Scientific Advisory Board of the programme. The aim of the programme is to use clinical health data combined with real-time data streams representing social activity and human mobility, together with advanced mathematical modelling and computational methods to address several of the most urgent questions for COVID-19 and future pandemics: What effects do community structure, individual heterogeneities, and spatial mobility have on reproduction numbers, community immunity, and the efficacy of different preventive measures? How can real-time data streams of social activity and human mobility combined with clinical health data aid in making more accurate predictions and more informed control decisions related to structurally and geographically targeted nonpharmaceutical interventions? How can Nordic health data and novel data streams of relevance for the ongoing COVID-19 and future pandemics be shared and published in a way that allows for better analyses without compromising data privacy of the individuals? The programme will develop methods, tools, and operational procedures for implementing cross-Nordic interoperable health data pipelines, novel methodology published in international scientific journals, and support the national public health institutes in their aim to keep disease spreading low without causing too high burden on Nordic societies.

Publicationslinked via Europe PMC

Strength and weakness of disease-induced herd immunity in networks.

A counterfactual analysis quantifying the COVID-19 vaccination impact in Sweden.

SIRS epidemics with individual heterogeneity of immunity waning.

Extending susceptible-infectious-recovered-susceptible epidemics to allow for gradual waning of immunity.

Collaborative nowcasting of COVID-19 hospitalization incidences in Germany.

Bayesian nowcasting with leading indicators applied to COVID-19 fatalities in Sweden.

A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting.

Discovery of host-directed modulators of virus infection by probing the SARS-CoV-2-host protein-protein interaction network.

Increased household transmission and immune escape of the SARS-CoV-2 Omicron compared to Delta variants.