arXiv subjects

Jenna Vergeynst

Publications and source records attributed to Jenna Vergeynst.

2 recordsLinked to original sources

arXiv2023

A Stochastic Mobility-Driven Spatially Explicit SEIQRD COVID-19 Model with VOCs, Seasonality, and Vaccines

In this work, we extend our previously developed compartmental SEIQRD model for SARS-CoV-2 in Belgium. We introduce SARS-CoV-2 variants of concern, vaccines, and seasonality in our model, as their addition has proven necessary for modelling SARS-CoV-2 transmission dynamics during the 2020-2021 COVID-19 pandemic in Belgium. The model is geographically stratified into eleven spatial patches (provinces), and a telecommunication dataset provided by Belgium's biggest operator is used to incorporate interprovincial mobility. We calibrate the model using the daily number of hospitalisations in each province and serological data. We find the model adequately describes these data, but the addition of interprovincial mobility was not necessary to obtain an accurate description of the 2020-2021 SARS-CoV-2 pandemic in Belgium. We further demonstrate how our model can be used to help policymakers decide on the optimal timing of the release of social restrictions. We find that adding spatial heterogeneity by geographically stratifying the model results in more uncertain model projections as compared to an equivalent nation-level model, which has both communicative advantages and disadvantages. We finally discuss the impact of imposing local mobility or social contact restrictions to contain an epidemic in a given province and find that lowering social contact is a more effective strategy than lowering mobility.

physics.soc-ph↗

arXiv2023

Mobility and the spatial spread of SARS-CoV-2 in Belgium

We analyse and mutually compare time series of COVID-19-related data and mobility data across Belgium's 43 arrondissements (NUTS 3). In this way, we reach three conclusions. First, we could detect a decrease in mobility during high-incidence stages of the pandemic. This is expressed as a significant change in the average amount of time spent outside one's home arrondissement, investigated over five distinct periods, and in more detail using an inter-arrondissement ``connectivity index'' (CI). Second, we analyse spatio-temporal COVID-19-related hospitalisation time series, after smoothing them using a generalise additive mixed model (GAMM). We confirm that some arrondissements are ahead of others and morphologically dissimilar to others, in terms of epidemiological progression. The tools used to quantify this are time-lagged cross-correlation (TLCC) and dynamic time warping (DTW), respectively. Third, we demonstrate that an arrondissement's CI with one of the three identified first-outbreak arrondissements is correlated to a significant local excess mortality some five to six weeks after the first outbreak. More generally, we couple results leading to the first and second conclusion, in order to demonstrate an overall correlation between CI values on the one hand, and TLCC and DTW values on the other. We conclude that there is a strong correlation between physical movement of people and viral spread in the early stage of the SARS-CoV-2 epidemic in Belgium, though its strength weakens as the virus spreads

physics.soc-ph↗