Forecasting epidemics through nonparametric estimation of time-dependent transmission rates using the SEIR model

DOI10.1007/s11538-017-0284-3zbMath1430.92109OpenAlexW2611371042WikidataQ30401615 ScholiaQ30401615MaRDI QIDQ2283902

Linda deCamp, Gerardo Chowell, Alexandra B. Smirnova

Publication date: 13 January 2020

Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11538-017-0284-3

zbMATH Keywords

parameter estimationregularizationVolterra equation

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

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Cites Work

• Parameter identification in epidemic models
• Stochasticity and the limits to confidence when estimating \(\mathcal R_0\) of Ebola and other emerging infectious diseases
• Reconstruction of disease transmission rates: applications to measles, dengue, and influenza
• Parameter estimation of some epidemic models. The case of recurrent epidemics caused by respiratory syncytial virus
• The basic reproductive number of Ebola and the effects of public health measures: the cases of Congo and Uganda
• A nonstandard approximation of pseudoinverse and a new stopping criterion for iterative regularization
• Extracting the time-dependent transmission rate from infection data via solution of an inverse ODE problem
• Time Series Modelling of Childhood Diseases: A Dynamical Systems Approach
• Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study
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