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.
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.
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.
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.
- Led by UBern: Real-time modeling and projections of the COVID-19 epidemic in Switzerland
- Led by UBern: Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: A modeling study in Hubei, China, and six regions in Europe
- Led by UBern: Living Evidence on COVID-19
- Led by UHasselt: Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020
- Led by UHasselt: Authors’ response: Estimating the generation interval for COVID-19 based on symptom onset data
- Led by UBern: Asymptomatic SARS-CoV-2 infections: a living systematic review and meta-analysis
- Led by LSHTM: Estimating number of cases and spread of coronavirus disease (COVID-19) using critical care admissions, United Kingdom, February to March 2020
- Led by UAntwerp: Seroprevalence of IgG antibodies against SARS coronavirus 2 in Belgium: a prospective cross-sectional study of residual samples
- Led by LSHTM: Changing travel patterns in China during the early stages of the COVID-19 pandemic
- Led by LSHTM: Global, Regional, and National Estimates of the Population at Increased Risk of Severe COVID-19 Due to Underlying Health Conditions in 2020: A Modelling Study
- Led by UHasselt and UAntwerp: Modelling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories
- Led by UHasselt: Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients
- Led by UBern: Early evidence of effectiveness of digital contact tracing for SARS-CoV-2 in Switzerland
- Led by UHasselt: Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research
- Led by UBern: Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis
- Led by UHasselt: Belgian COVID-19 Mortality, Excess Deaths, Number of Deaths per Million, and Infection Fatality Rates (8 March – 9 May 2020)
- Led by UHasselt: Quantifying superspreading for COVID-19 using Poisson mixture distributions
- Led by LSHTM: Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
- Led by UBern: Outbreaks of publications about emerging infectious diseases: the case of SARS-CoV-2 and Zika virus
- Led by RVIM: Practical considerations for measuring the effective reproductive number, Rt
- Led by RVIM: Modelling the spread of the coronavirus SARS-CoV-2
- Led by UHasselt and UAntwerp: Can COVID-19 symptoms as reported in a large-scale online survey be used to optimise spatial predictions of COVID-19 incidence risk in Belgium?
- Led by LSHTM: The contribution of asymptomatic SARS-CoV-2 infections to transmission on the Diamond Princess cruise ship
- Led by UHasselt and UAntwerp: Belgian COVID-19 Mortality, Excess Deaths, Number of Deaths per Million, and Infection Fatality Rates (9 March — 28 June 2020)
- Led by UHasselt: A linear Mixed Model to Estimate COVID-19-induced Excess Mortality
- Led by UBern: A tale of two variants: Spread of SARS-CoV-2 variants Alpha in Geneva, Switzerland, and Beta in South Africa
This work package is led by the team at RIVM, supported by UHasselt, University of Bern and LSHTM.