A note on tools for prediction under uncertainty and identifiability of SIR-like dynamical systems for epidemiology

Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China

(2020) Huwen Wang et al.   Cell Discovery

Multilevel double loop Monte Carlo and stochastic collocation methods with importance sampling for Bayesian optimal experimental design

(2020) Joakim Beck et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy

(2020) Giulia Giordano et al.   NATURE MEDICINE

Data-based analysis, modelling and forecasting of the COVID-19 outbreak

(2020) Cleo Anastassopoulou et al.   PLoS One

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures

(2020) Marino Gatto et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges

(2020) Amani Alahmadi et al.   Epidemics

Global Identifiability of Differential Models

(2020) Hoon Hong et al.   COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS

Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’

(2020) Enrico Lavezzo et al.   NATURE

A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic

(2020) Fabio Della Rossa et al.   Nature Communications

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

Introductory overview of identifiability analysis: A guide to evaluating whether you have the right type of data for your modeling purpose

(2019) Joseph H.A. Guillaume et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain

(2018) Joakim Beck et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements

(2018) Marco Iglesias et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Structural and practical identifiability analysis of outbreak models

(2018) Necibe Tuncer et al.   MATHEMATICAL BIOSCIENCES

Profile likelihood-based analyses of infectious disease models

(2018) Christian Tönsing et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment

(2018) Yu-Han Kao et al.   Epidemics

A Bayesian information criterion for singular models

(2017) Mathias Drton et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Accurate Solution of Bayesian Inverse Uncertainty Quantification Problems Combining Reduced Basis Methods and Reduction Error Models

(2016) A. Manzoni et al.   SIAM-ASA Journal on Uncertainty Quantification

A Laplace method for under-determined Bayesian optimal experimental designs

(2015) Quan Long et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Approximation of high-dimensional parametric PDEs

(2015) Albert Cohen et al.   ACTA NUMERICA

Determining identifiable parameter combinations using subset profiling

(2014) Marisa C. Eisenberg et al.   MATHEMATICAL BIOSCIENCES

Inverse modeling of geochemical and mechanical compaction in sedimentary basins through Polynomial Chaos Expansion

(2014) G. Porta et al.   WATER RESOURCES RESEARCH

Model selection on solid ground: Rigorous comparison of nine ways to evaluate Bayesian model evidence

(2014) Anneli Schöniger et al.   WATER RESOURCES RESEARCH

Stochastic finite element methods for partial differential equations with random input data

(2014) Max D. Gunzburger et al.   ACTA NUMERICA

Sparse, adaptive Smolyak quadratures for Bayesian inverse problems

(2013) Claudia Schillings et al.   INVERSE PROBLEMS

Global sensitivity analysis through polynomial chaos expansion of a basin-scale geochemical compaction model

(2012) Luca Formaggia et al.   COMPUTATIONAL GEOSCIENCES

Epidemic models with uncertainty in the reproduction number

(2012) M. G. Roberts   JOURNAL OF MATHEMATICAL BIOLOGY

Towards uncertainty quantification and inference in the stochastic SIR epidemic model

(2012) Marcos A. Capistrán et al.   MATHEMATICAL BIOSCIENCES

Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion

(2012) S. Oladyshkin et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Using the negative binomial distribution to model overdispersion in ecological count data

(2011) Andreas Lindén et al.   ECOLOGY

On Identifiability of Nonlinear ODE Models and Applications in Viral Dynamics

(2011) Hongyu Miao et al.   SIAM REVIEW

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

(2010) Ivo Babuška et al.   SIAM REVIEW

Inverse problems: A Bayesian perspective

(2010) A. M. Stuart   ACTA NUMERICA

An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach

(2010) Andrej-Nikolai Spiess et al.   BMC Pharmacology & Toxicology

MARGINALIZATION OF UNINTERESTING DISTRIBUTED PARAMETERS IN INVERSE PROBLEMS—APPLICATION TO DIFFUSE OPTICAL TOMOGRAPHY

(2010) Ville Kolehmainen et al.   International Journal for Uncertainty Quantification

Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood

(2009) A. Raue et al.   BIOINFORMATICS

Plug-and-play inference for disease dynamics: measles in large and small populations as a case study

(2009) D. He et al.   Journal of the Royal Society Interface

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

(2009) Håvard Rue et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY