Modelling and Forecasting

Modelling And Forecasting Modelling And Forecasting

Understanding the patterns

This stream of work is focused on applying state-of-the-art mathematical models and statistical datasets to understand the patterns underlying COVID-19. Providing reliable estimates of key factors associated with COVID-19 help us better understand the dynamics of the virus and respond more effectively.

Key activities include:

  • Providing rapid and reliable estimates of important variables such as the basic reproduction, or ‘R’ and the proportion of COVID-19 cases which prove fatal (referred to as the case fatality ratio). The results of these analyses are being made easily available in real-time to public health authorities and other researchers.
  • Projecting demands on healthcare facilities in the immediate and short-term, which helps healthcare authorities plan effectively and allocate resources where most needed.
  • Generating a living database of the most up-to-date modelling research on COVID-19 which can be used by other researchers and experts.
  • Providing an overarching assessment of the pandemic’s key patterns and drivers, gathering information on the levels of immunity and the effectiveness of control measures taken.

1 Year of EpiPose: Christian Althaus

In this video, Dr. Christian Althaus talks about the work EpiPose is doing to understand how COVID-19 is transmitted and the impact of different interventions.

Collecting data

To make these activities possible, we’re collecting high-quality clinical data which is being used to inform the estimates and projections developed. All the partners in EpiPose work with public health agencies and hospitals to collect incidence data on COVID-19. The types of data we use include: confirmed COVID-19 cases, number of tests, hospitalisations and available hospital beds, and the number of deaths from the virus. The data we collect from hospitals and public health agencies is complemented by other types of data, such as mobility patterns and social security information (for example, levels of workplace absenteeism). Along with other research groups, we use platforms like the data dashboard to make our findings visible.

1 year of EpiPose: Prof. Nicola Low and #LivingEvidence

Hear Prof. Nicola Low discuss how Living Evidence is supporting researchers and others to find the most relevant information about SARS-CoV-2 and COVID-19.

Scientific outputs

This work package is led by the team at RIVM, supported by UHasselt, University of Bern and LSHTM.