Second waves, social distancing, and the spread of COVID-19 across the USA

Wellcome Open Research

article

Karl J. Friston¹  Thomas Parr¹  Peter Zeidman¹  Adeel Razi¹  Guillaume Flandin¹  Jean Daunizeau³  Oliver J. Hulme⁴  Alexander J. Billig⁶  Vladimir Litvak¹  Catherine J. Price¹  Rosalyn J. Moran⁷  Christian Lambert¹ 

[1] The Wellcome Centre for Human Neuroimaging, University College London;Turner Institute for Brain and Mental Health, Monash University;Institut du Cerveau et de la Moelle épinière;Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre;London Mathematical Laboratory;Ear Institute, University College London;Centre for Neuroimaging Science, Department of Neuroimaging, IoPPN, King's College London

关键词: coronavirus;    epidemiology;    compartmental models;    dynamic causal modelling;    variational;    Bayesian;   

DOI  :  10.12688/wellcomeopenres.15986.3

学科分类：内科医学

来源: Wellcome

【 摘 要 】

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several instantiations of this (epidemic) model to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity—and the exchange of people between regions—and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

【 授权许可】

CC BY