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Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case
2020
PLoS ONE
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
doi:10.1371/journal.pone.0242956
pmid:33270713
pmcid:PMC7714127
fatcat:pnsw64qccrfyjkmgfghpi6vs4a