Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case.

ABSTRACT: The present paper introduces a new model used to study and analyse the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) epidemic-reported-data from Spain. This is a Hidden Markov Model whose hidden layer is a regeneration process with Poisson immigration, Po-INAR(1), together with a mechanism that allows the estimation of the under-reporting in non-stationary count time series. A novelty of the model is that the expectation of the unobserved process's innovations is a time-dependent function defined in such a way that information about the spread of an epidemic, as modelled through a Susceptible-Infectious-Removed dynamical system, is incorporated into the model. In addition, the parameter controlling the intensity of the under-reporting is also made to vary with time to adjust

SUBMITTER: Fernandez-Fontelo A 

PROVIDER: S-EPMC7714127 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature