Correcting notification delay and forecasting of COVID-19 data

DOI10.1016/j.jmaa.2021.125202zbMath1491.92122OpenAlexW3148784411MaRDI QIDQ2147784

Alessandro J. Q. Sarnaglia, Fabio A. Fajardo Molinares, Bartolomeu Zamprogno, Luciana G. de Godoi, Nátaly A. Jiménez Monroy

Publication date: 20 June 2022

Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmaa.2021.125202

zbMATH Keywords

predictionoverdispersionCOVID-19notification delay

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Identification of time delays in COVID-19 data ⋮ Qualitative analysis of a mathematical model with presymptomatic individuals and two SARS-CoV-2 variants

Cites Work

• Unnamed Item
• Overdispersion: Models and estimation.
• Mathematical analysis of the global dynamics of a HTLV-I infection model, considering the role of cytotoxic T-lymphocytes
• A robust nonlinear mixed-effects model for COVID-19 death data
• Saving human lives: what complexity science and information systems can contribute
• A SEIR model for control of infectious diseases with constraints
• Compartmental Models in Epidemiology
• A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2
• Forecasting the daily and cumulative number of cases for the COVID-19 pandemic in India
• Pǿlya–Aeppli regression model for overdispersed count data

This page was built for publication: Correcting notification delay and forecasting of COVID-19 data