Modelling and Forecasting

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.

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.

• 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 RIVM: Practical considerations for measuring the effective reproductive number, Rt
• Led by RIVM: 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
• Led by UBern: Spread of a SARS-CoV-2 variant through Europe in the summer of 2020
• Led by UBern: PRELIMINARY - NOT PEER REVIEWED: Rapid replacement of the Beta variant by the Delta variant in South Africa
• Led by UHasselt, RIVM & UBern: EpiLPS: A fast and flexible Bayesian tool for estimation of the time-varying reproduction number
• Led by UBern: Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa
• Led by UHasselt: PRELIMINARY - NOT YET PEER REVIEWED An approximate Bayesian approach for estimation of the reproduction number under misreported epidemic data
• Led by UHasselt: Laplacian‐P‐splines for Bayesian inference in the mixture cure model
• Led by UBern: Replacement of the Gamma by the Delta variant in Brazil: Impact of lineage displacement on the ongoing pandemic
• Led by LSHTM: The potential for vaccination-induced herd immunity against the SARS-CoV-2 B.1.1.7 variant
• Led by LSHTM: Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England
• Led by LSHTM: Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection 
• Led by LSHTM: Global and national estimates of the number of healthcare workers at high risk of SARS-CoV-2 infection
• 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: PRELIMINARY - NOT YET PEER REVIEWED Observed serial intervals of SARS-CoV-2 for the Omicron and Delta variants in Belgium based on contact tracing data, 19 November to 31 December 2021
• Led by RIVM: Shorter serial intervals in SARS-CoV-2 cases with Omicron BA.1 variant compared with Delta variant, the Netherlands, 13 to 26 December 2021
• Led by UBern: Socioeconomic position and the COVID-19 care cascade from testing to mortality in Switzerland: a population-based analysis
• Led by UBern: Quantification of the spread of SARS-CoV-2 variant B.1.1.7 in Switzerland 
• Led by RIVM: PRELIMINARY - NOT YET PEER REVIEWED Dose-response modelling of endemic coronavirus and SARS-CoV-2: human challenge trials reveal the individual variation in susceptibility
• Led by RIVM: PRELIMINARY - NOT YET PEER REVIEWED The estimated disease burden of acute COVID-19 in the Netherlands in 2020, in disability-adjusted life-years
• Led by RIVM: Estimating the asymptomatic proportion of SARS-CoV-2 infection in the general population: Analysis of nationwide serosurvey data in the Netherlands
• Led by UBern: Survival among people hospitalized with COVID-19 in Switzerland: a nationwide population-based analysis
• Led by UHasselt: PRELIMINARY - NOT YET PEER REVIEWED Bayesian nowcasting with Laplacian-P-splines
• Led by UBern: Impact of cross-border-associated cases on the SARS-CoV-2 epidemic in Switzerland during summer 2020 and 2021
• Led by UBern: Thesis paper on the escalation model of the Swiss Epidemics Act (EpidA)
• Led by UBern: Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland
• Led by UBern: Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region
• Led by UHasselt: A joint spatial model to analyse self-reported survey data of COVID-19 symptoms and lagged surveillance-based COVID-19 incidence data
• Led by UBern: Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: Update of a living systematic review and meta-analysis
• Led by UBern: Importation of Alpha and Delta variants during the SARS-CoV-2 epidemic in Switzerland: phylogenetic analysis and intervention scenarios
• Led by LSHTM: Comparing human and model-based forecasts of COVID-19 in Germany and Poland
• Led by RIVM: Age-specific severity of SARS-CoV-2 in February 2020 – June 2021 in the Netherlands
• Led by UH: Key performance indicators of COVID-19 contact tracing in Belgium from September 2020 to December 2021
• Led by UH: Reconstruction of SARS-CoV-2 outbreaks in a primary school using epidemiological and genomic data
• Led by LSHTM: Projected epidemiological consequences of the Omicron SARS-CoV-2 variant in England, December 2021 to April 2022
• Led by UBern: How to update a living systematic review and keep it alive during a pandemic: a practical guide

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