Amplification of the power of network hubs and degree skewness over infectious disease spread during lulls
Benjamin Cornwell, Shiyu Ji, Shane G. Henderson, Gen Meredith
TL;DR
The paper shows how network hubs and degree skewness influence disease spread, especially during lulls in transmission like with COVID-19.
Contribution
The study reveals that network hubs and degree skewness amplify disease spread during lulls but are less impactful during high transmissibility.
Findings
Network hubs and high degree skewness increase peak prevalence during low to moderate transmissibility.
The effect of hubs is amplified during lulls in disease spread.
Highly transmissible diseases show suppressed hub effects.
Abstract
Just as individuals’ personal social network connections shape their susceptibility to disease, the structure of larger networks in communities shapes the extent of disease spread. We examine how heterogeneity in network structure at the population level affects the spread of disease – namely, COVID-19 – considering varying levels of disease transmissibility and in-person contact rates. Using dynamic simulations that take into account network structure, social contact rates given contextual features of the community (informed by real-life data on family local family structure, schools, workplaces, and daily shopping activities), and disease infection rates, we first confirm that the presence of network hubs and high network degree skewness results in a higher level of infected peak prevalence with infectious diseases such as COVID-19 during periods of low to moderate transmissibility.…
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Taxonomy
TopicsComplex Network Analysis Techniques · COVID-19 epidemiological studies · Opinion Dynamics and Social Influence