Type
PreprintKAUST Department
Applied Mathematics and Computational Science ProgramBiological and Environmental Sciences and Engineering (BESE) Division
Biostatistics Group
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Marine Science Program
Numerical Mathematics Group
Red Sea Research Center (RSRC)
Statistics Program
Date
2020-05-15Permanent link to this record
http://hdl.handle.net/10754/663490
Metadata
Show full item recordAbstract
{We describe a model for estimating past and current infections as well as future deaths due to the ongoing COVID-19 pandemic. The model does not use confirmed case numbers and is based instead on recorded numbers of deaths and on the age specific population distribution. A regularized deconvolution technique is used to infer past infections from recorded deaths. Forecasting is based on a compartmental SIR-type model, combined with a probability distribution for the time from infection to death. The effect of non-pharmaceutical interventions (NPIs) is modelled empirically, based on recent trends in the death rate. The model can also be used to study counterfactual scenarios based on hypothetical NPI policies.Citation
Ketcheson, D. I., Ombao, H. C., Moraga, P., Ballal, T., & Duarte, C. M. (2020). Estimating and forecasting COVID-19 attack rates and mortality. doi:10.1101/2020.05.11.20097972Publisher
Cold Spring Harbor LaboratoryAdditional Links
http://medrxiv.org/lookup/doi/10.1101/2020.05.11.20097972ae974a485f413a2113503eed53cd6c53
10.1101/2020.05.11.20097972