ArticleBMC infectious diseases2023
The impact of national and international travel on spatio-temporal transmission of SARS-CoV-2 in Belgium in 2021.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- A scoping review of COVID-19 modelling studies in Belgium 2020-2024: incorporation of behaviour and lessons learned.Archives of public health = Archives belges de sante publique · 2026Pooled it
- Endemic-epidemic modeling of the COVID-19 pandemic in South Africa.BMC infectious diseases · 2026Article
- Capturing the spatiotemporal spread of COVID-19 in 30 European countries during 2020 - 2022.BMC public health · 2025Article
- Article
- Article
- Endemic-epidemic modelling of school closure to prevent spread of COVID-19 in Switzerland.BMC infectious diseases · 2024Article
- Evolution of COVID-19 dynamics in Guangdong Province, China: an endemic-epidemic modeling study.Archives of public health = Archives belges de sante publique · 2024Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rapidly spread over the world and caused tremendous impacts on global health. Understanding the mechanism responsible for the spread of this pathogen and the impact of specific factors, such as human mobility, will help authorities to tailor interventions for future SARS-CoV-2 waves or newly emerging airborne infections. In this study, we aim to analyze the spatio-temporal transmission of SARS-CoV-2 in Belgium at municipality level between January and December 2021 and explore the effect of different levels of human travel on disease incidence through the use of counterfactual scenarios.
methodsWe applied the endemic-epidemic modelling framework, in which the disease incidence decomposes into endemic, autoregressive and neighbourhood components. The spatial dependencies among areas are adjusted based on actual connectivity through mobile network data. We also took into account other important factors such as international mobility, vaccination coverage, population size and the stringency of restriction measures.
resultsThe results demonstrate the aggravating effect of international travel on the incidence, and simulated counterfactual scenarios further stress the alleviating impact of a reduction in national and international travel on epidemic growth. It is also clear that local transmission contributed the most during 2021, and municipalities with a larger population tended to attract a higher number of cases from neighboring areas.
conclusionsAlthough transmission between municipalities was observed, local transmission was dominant. We highlight the positive association between the mobility data and the infection spread over time. Our study provides insight to assist health authorities in decision-making, particularly when the disease is airborne and therefore likely influenced by human movement.
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