Inferring the effect of interventions on COVID-19 transmission networks

TL;DR

This paper models COVID-19 transmission networks to analyze how nonpharmaceutical interventions (NPIs) alter contact patterns, revealing a transition to a constant case regime and providing insights for designing effective NPIs.

Contribution

It introduces an agent-based model with explicit individual contacts on a Watts-Strogatz network to study NPI effects on transmission dynamics, including a novel constant case regime.

Findings

NPIs reduce random contacts and increase clustering in transmission networks.

The disease spread transitions from exponential to wave-like with finite speed under NPIs.

A new regime of constant new cases emerges due to NPIs, beyond the known exponential regimes.

Abstract

Countries around the world implement nonpharmaceutical interventions (NPIs) to mitigate the spread of COVID-19. Design of efficient NPIs requires identification of the structure of the disease transmission network. We here identify the key parameters of the COVID-19 transmission network for time periods before, during, and after the application of strict NPIs for the first wave of COVID-19 infections in Germany combining Bayesian parameter inference with an agent-based epidemiological model. We assume a Watts-Strogatz small-world network which allows to distinguish contacts within clustered cliques and unclustered, random contacts in the population, which have been shown to be crucial in sustaining the epidemic. In contrast to other works, which use coarse-grained network structures from anonymized data, like cell phone data, we consider the contacts of individual agents explicitly. We show that NPIs drastically reduced random contacts in the transmission network, increased network clustering, and resulted in a change from an exponential to a constant regime of newcases. In this regime, the disease spreads like a wave with a finite wave speed that depends on the number of contacts in a nonlinear fashion, which we can predict by mean field theory. Our analysis indicates that besides the well-known transitionbetween exponential increase and exponential decrease in the number of new cases, NPIs can induce a transition to another, previously unappreciated regime of constant new cases.