Estimated Covid-19 burden in Spain: ARCH underreported non-stationary time series.

ABSTRACT:

Background

The problem of dealing with misreported data is very common in a wide range of contexts for different reasons. The current situation caused by the Covid-19 worldwide pandemic is a clear example, where the data provided by official sources were not always reliable due to data collection issues and to the high proportion of asymptomatic cases. In this work, a flexible framework is proposed, with the objective of quantifying the severity of misreporting in a time series and reconstructing the most likely evolution of the process.

Methods

The performance of Bayesian Synthetic Likelihood to estimate the parameters of a model based on AutoRegressive Conditional Heteroskedastic time series capable of dealing with misreported information and to reconstruct the most likely

SUBMITTER: Morina D 

PROVIDER: S-EPMC10043853 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature