Likelihood-Based Inference for Partially Observed Epidemics on Dynamic Networks
DOI10.1080/01621459.2020.1790376zbMath1506.62262arXiv1910.04221OpenAlexW3041326970MaRDI QIDQ5881105
Fan Bu, Jason Xu, Alexander Volfovsky, Unnamed Author
Publication date: 9 March 2023
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1910.04221
continuous-time Markov chainsconditional simulationcontact networksmobile healthcareBayesian data augmentationstochastic susceptible-infectious-removed model
Computational methods for problems pertaining to statistics (62-08) Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Missing data (62D10)
Cites Work
- Unnamed Item
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- SIR dynamics in random networks with heterogeneous connectivity
- Stochastic epidemic models: a survey
- Simulation from endpoint-conditioned, continuous-time Markov chains on a finite state space, with applications to molecular evolution
- Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease
- Birth/birth-death processes and their computable transition probabilities with biological applications
- Temporal network epidemiology
- Epidemics in adaptive social networks with temporary link deactivation
- The Mathematics of Infectious Diseases
- Likelihood-based inference for discretely observed birth-death-shift processes, with applications to evolution of mobile genetic elements
- Inference for dynamic and latent variable models via iterated, perturbed Bayes maps
- Flooding Time of Edge-Markovian Evolving Graphs
- Influence of non-homogeneous mixing on final epidemic size in a meta-population model
- Bayesian inference for stochastic multitype epidemics in structured populations using sample data
- Statistical Studies of Infectious Disease Incidence
- Bayesian Inference for Stochastic Epidemics in Populations with Random Social Structure
- Time Series Modelling of Childhood Diseases: A Dynamical Systems Approach
- Transmission of Pneumococcal Carriage in Families: A Latent Markov Process Model for Binary Longitudinal Data
- Particle Markov Chain Monte Carlo Methods
- The linear birth‒death process: an inferential retrospective
- Modelling approaches for simple dynamic networks and applications to disease transmission models
- Statistical inference and model selection for the 1861 Hagelloch measles epidemic
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