New statistical model for misreported data with application to current public health challenges

David Moriña*, Amanda Fernández-Fontelo, Alejandra Cabaña, Pedro Puig

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículoInvestigaciónrevisión exhaustiva

1 Cita (Scopus)

Resumen

The main goal of this work is to present a new model able to deal with potentially misreported continuous time series. The proposed model is able to handle the autocorrelation structure in continuous time series data, which might be partially or totally underreported or overreported. Its performance is illustrated through a comprehensive simulation study considering several autocorrelation structures and three real data applications on human papillomavirus incidence in Girona (Catalonia, Spain) and Covid-19 incidence in two regions with very different circumstances: the early days of the epidemic in the Chinese region of Heilongjiang and the most current data from Catalonia.

Idioma originalInglés
Número de artículo23321
Número de páginas10
PublicaciónSCIENTIFIC REPORTS
Volumen11
N.º1
DOI
EstadoPublicada - dic 2021

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