The role of connectivity on COVID-19 preventive approaches

Abstract

Preventive and modelling approaches to address the COVID-19 pandemic have been primarily based on the age or occupation, and often disregard the importance of the population contact structure and individual connectivity. To address this gap, we developed models that first incorporate the role of heterogeneity and connectivity and then can be expanded to make assumptions about demographic characteristics. Results demonstrate that variations in the number of connections of individuals within a population modify the impact of public health interventions such vaccination approaches. We conclude that the most effective vaccination strategy will vary depending on the underlying contact structure of individuals within a population and on timing of the interventions.

Omicron vs. the Rest: Assessing the Competitive Dynamics and Coinfection Scenarios of COVID-19 Strains on a Social Network

“…Verónica Miró Pina et al developed models based on Erdős-Rényi and a power-law degree distribution, which capture the role of heterogeneity and connectivity and can be extended to make hypotheses about demographic characteristics. They demonstrated that changes in the number of contacts in a population impact the effectiveness of public health interventions such as quarantine or vaccination strategies [41]. Pilar Hernández et al utilized the SEIR model and presented two types of agent-based model simulations: a homogeneous spatial simulation where contamination occurs through proximity and a model in a scale-free network with different clustering characteristics, where contamination occurs between any two agents through their link, if any [42].…”