Modeling COVID-19 pandemic using Bayesian analysis with application to Slovene data

DOI10.1016/j.mbs.2020.108466zbMath1453.92310OpenAlexW3085257293WikidataQ99399981 ScholiaQ99399981MaRDI QIDQ2207162

Rok Blagus, Nataša Kejžar, Damjan Manevski, Nina Ružić Gorenjec

Publication date: 22 October 2020

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482592

zbMATH Keywords

Bayesian inferencereproduction numbernon-pharmaceutical interventionsdiscrete renewal processmodeling epidemics

Mathematics Subject Classification ID

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

Related Items (3)

Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil ⋮ Estimation of SARS‐CoV‐2 antibody prevalence through serological uncertainty and daily incidence ⋮ Trends in COVID-19 prevalence and mortality: a year in review

Uses Software

• R
• BayesDA
• RStan
• rstan
• GitHub
• epiABC

Cites Work

• Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
• A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods
• Analysis and forecast of COVID-19 spreading in China, Italy and France
• Modeling behavioral change and COVID-19 containment in Mexico: a trade-off between lockdown and compliance
• Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability
• Staggered release policies for COVID-19 control: costs and benefits of relaxing restrictions by age and risk
• Analysis of household data on influenza epidemic with Bayesian hierarchical model
• A tutorial introduction to Bayesian inference for stochastic epidemic models using approximate Bayesian computation
• Statistical Studies of Infectious Disease Incidence

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