A multivariate statistical approach to predict COVID‐19 count data with epidemiological interpretation and uncertainty quantification-Reference-Cited by-同舟云学术

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A multivariate statistical approach to predict COVID‐19 count data with epidemiological interpretation and uncertainty quantification

Published:2021-08-10 Issue:24 Volume:40 Page:5351-5372
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Bartolucci Francesco¹^ORCID,Pennoni Fulvia²^ORCID,Mira Antonietta³⁴^ORCID

Affiliation:

1. Department of Economics University of Perugia Perugia Italy

2. Department of Statistics and Quantitative Methods University of Milano‐Bicocca Milan Italy

3. Faculty of Economics Università della Svizzera italiana (CH) Lugano Italy

4. University of Insubria Varese Italy

Funder

Regione Lombardia

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9129

Reference49 articles.

1. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations

2. Why is it difficult to accurately predict the COVID-19 epidemic?

3. COVID-19: a novel coronavirus and a novel challenge for critical care

4. Monitoring COVID‐19 contagion growth;Agosto A;Stat Med,2021

5. An Inquiry into the Nature of Frequency Distributions Representative of Multiple Happenings with Particular Reference to the Occurrence of Multiple Attacks of Disease or of Repeated Accidents

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2. Dynamic Network Poisson Autoregression with Application to COVID-19 Count Data;Journal of Data Science;2024

3. The coming Omicron waves and factors affecting its spread after China reopening borders;BMC Medical Informatics and Decision Making;2023-09-15

4. Explicit modeling of antibody levels for infectious disease simulations in the context of SARS-CoV-2;iScience;2023-09

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