Mathematical simulation models have become indispensable tools for forecasting and studying the effectiveness of intervention strategies such as lockdowns and screening during the SARS-CoV-2 pandemic. Estimation of key modeling quantities uses the serological footprint of an infection on the host. However, although depending on the type of assay, SARS-CoV-2 antibody titers were frequently not found in young and/or asymptomatic individuals and were shown to wane after a relatively short period, especially in asymptomatic individuals. In contrast, T-cells have been found in different situations – also without antibodies being present - ranging from convalescent asymptomatic to mild SARS-CoV-2 patients and their household members, thereby indicating that T-cells offer more sensitivity to detect past exposure to SARS-CoV-2 than the detection of antibodies can. In this project, we will gather on a population level T-cell and antibody SARS-CoV-2 specific data from different well-described cohorts including 300 individuals (and 200 household members) who have had proven covid-19 infection > 3 months earlier, 100 general practitioners, 100 hospital workers, 500 randomly selected individuals and 75 pre-covid-era PBMC/sera. This data will be used in comparative simulation models and will lead to a reassessment of several key epidemiological estimates such as herd immunity and the reproduction number R that will significantly inform covid-19 related public health interventions.
|Effective start/end date
|1/11/20 → 31/10/23
- Research Fund - Flanders: €12,750.00
- Adaptive immunology
- Health promotion and policy
- Infectious diseases
- Modelling and simulation
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