Rational evaluation of various epidemic models based on the COVID-19 data of China
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Rational evaluation of various epidemic models based on the COVID-19 data of China
Authors
Keywords
COVID-19, Model evaluation, Epidemic size, Akaike information criterion, Robustness
Journal
Epidemics
Volume 37, Issue -, Pages 100501
Publisher
Elsevier BV
Online
2021-09-27
DOI
10.1016/j.epidem.2021.100501
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions
- (2020) Biao Tang et al. Journal of Clinical Medicine
- Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China
- (2020) Huwen Wang et al. Cell Discovery
- Assessing parameter identifiability in compartmental dynamic models using a computational approach: application to infectious disease transmission models
- (2019) Kimberlyn Roosa et al. Theoretical Biology and Medical Modelling
- Assessing the performance of real-time epidemic forecasts: A case study of Ebola in the Western Area region of Sierra Leone, 2014-15
- (2019) Sebastian Funk et al. PLoS Computational Biology
- Simple framework for real-time forecast in a data-limited situation: the Zika virus (ZIKV) outbreaks in Brazil from 2015 to 2016 as an example
- (2019) Shi Zhao et al. Parasites & Vectors
- Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples
- (2019) Chelsea S. Lutz et al. BMC PUBLIC HEALTH
- Comparison and Assessment of Epidemic Models
- (2018) Gavin J. Gibson et al. STATISTICAL SCIENCE
- Modelling the global spread of diseases: A review of current practice and capability
- (2018) Caroline E. Walters et al. Epidemics
- The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt
- (2018) Cécile Viboud et al. Epidemics
- On the Identifiability of Transmission Dynamic Models for Infectious Diseases
- (2016) J. Lintusaari et al. GENETICS
- Statistical Inference for Partially Observed Markov Processes via theRPackagepomp
- (2016) Aaron A. King et al. Journal of Statistical Software
- Mathematical models to characterize early epidemic growth: A review
- (2016) Gerardo Chowell et al. Physics of Life Reviews
- Mathematical Modeling of the Transmission Dynamics of Clostridium difficile Infection and Colonization in Healthcare Settings: A Systematic Review
- (2016) Guillaume Gingras et al. PLoS One
- Complexity in Mathematical Models of Public Health Policies: A Guide for Consumers of Models
- (2013) Sanjay Basu et al. PLOS MEDICINE
- The R0 package: a toolbox to estimate reproduction numbers for epidemic outbreaks
- (2012) Thomas Obadia et al. BMC Medical Informatics and Decision Making
- Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood
- (2009) A. Raue et al. BIOINFORMATICS
- Real Time Bayesian Estimation of the Epidemic Potential of Emerging Infectious Diseases
- (2008) Luís M. A. Bettencourt et al. PLoS One
- A likelihood‐based method for real‐time estimation of the serial interval and reproductive number of an epidemic
- (2007) L. Forsberg White et al. STATISTICS IN MEDICINE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started