CoviChron: Covid-19 and Chronic illness interactions in transmission dynamics

The purpose of this study was to quantify changes in transmission dynamics of COVID-19 over time, and the effect of vaccination for individuals with low and high risk of severe disease. Researchers estimated what vaccination coverage is necessary in different ages and risk groups to avoid overburdening hospitals.

By gathering and merging different data, they classified the Dutch population into 3 risk categories for severe disease: low, medium and high. They improved and extended a model they had previously developed, estimated it over 2020–2022, and validated it against peak hospitalisations in 2023–2024.

Together with their collaborators, they developed potential vaccination strategies to counter additional overburdening of hospitals by COVID-19 patients. By analysing a large set of future scenarios, they showed that a substantial (40%) vaccination coverage in all groups above 60 years of age was necessary to achieve this goal. 

The project group brings together researchers  from UMC Utrecht, Tilburg University, RIVM, GGD Amsterdam, Amsterdam UMC, UvA, CBS and  University of Oslo. Additionally, they consulted patient organisations, public health officials, and NIVEL employees.

This project has:

• Developed a new model of COVID-19 that quantifies interactions among different age and risk groups. The contact network among them is estimated with RIVM PICO data.
• Quantified the infection and hospitalisation burden for the first two years of the pandemic in these age/risk groups.

The simulated scenarios show that vaccinating only individuals at risk of severe disease is insufficient to avoid overburdening hospitals during a fall wave, and that a substantial vaccination coverage among all individuals age 60 and above is necessary to achieve this goal.

They simulated additional vaccination scenarios to estimate the optimal degree of vaccination (that required the fewest vaccines) to avoid overburdening hospitals during a COVID-19 wave.