Details

Autor(en) / Beteiligte

• Levesque, Jérôme
• Maybury, David W.
• Shaw, R.H.A. David

Titel

A model of COVID-19 propagation based on a gamma subordinated negative binomial branching process

Ist Teil von

• Journal of theoretical biology, 2021-03, Vol.512, p.110536-110536, Article 110536

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2021

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• •Analytical properties of the branching processes describe COVID-19 propagation.•As an outbreak begins, the model allows for comparisons between mitigation scenarios.•The asymptotics of the process permit calibration to COVID-19 case count data. We build a parsimonious Crump-Mode-Jagers continuous time branching process of COVID-19 propagation based on a negative binomial process subordinated by a gamma subordinator. By focusing on the stochastic nature of the process in small populations, our model provides decision making insight into mitigation strategies as an outbreak begins. Our model accommodates contact tracing and isolation, allowing for comparisons between different types of intervention. We emphasize a physical interpretation of the disease propagation throughout which affords analytical results for comparison to simulations. Our model provides a basis for decision makers to understand the likely trade-offs and consequences between alternative outbreak mitigation strategies particularly in office environments and confined work-spaces. Combining the asymptotic limit of our model with Bayesian hierarchical techniques, we provide US county level inferences for the reproduction number from cumulative case count data over July and August of this year.