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Detecting critical slowing down in high-dimensional epidemiological systems

Tobias Brett, Marco Ajelli, Quan-Hui Liu, Mary G. Krauland, John J. Grefenstette, Willem G. van Panhuis, Alessandro Vespignani, John M. Drake, Pejman Rohani, Virginia E. Pitzer
2020 PLoS Computational Biology  
Our five models included: i) a nonseasonal homogeneous Susceptible-Exposed-Infectious-Recovered (SEIR) model, ii) a homogeneous SEIR model with seasonality in transmission, iii) an age-structured SEIR  ...  For EWS to be useful at detecting future (re-)emergence, CSD needs to be a generic (model-independent) feature of epidemiological dynamics irrespective of system complexity.  ...  Three models were variants of the Susceptible-Exposed-Infectious-Recovered (SEIR) model, a canonical model of mathematical epidemiology: the basic nonseasonal SEIR model, the SEIR model with seasonality  ... 
doi:10.1371/journal.pcbi.1007679 pmid:32150536 fatcat:kram24wkkfaglf6cydfx3gue5e

Optimal Control and Numerical Optimization Applied to Epidemiological Models [article]

Helena Sofia Rodrigues
2014 arXiv   pre-print
The relationship between epidemiology, mathematical modeling and computational tools allows to build and test theories on the development and battling of a disease.  ...  An analytical study is made related to equilibrium points, their stability and basic reproduction number.  ...  [26] estimates the basic reproduction number for Dengue using spatial epidemic data. In [100] the author studies the spread of Dengue thought statistical analysis, while in Tewa et al.  ... 
arXiv:1401.7390v1 fatcat:3b4yv7xnmvczxgybdi6rhnye6i

Modeling Epidemics: A Primer and Numerus Software Implementation [article]

Wayne M. Getz, Richard Salter, Oliver Muellerklein, Hyun S Yoon, Krti Tallam
2017 biorxiv/medrxiv   pre-print
Here we review the continuous and discrete deterministic and discrete stochastic formulations of the SEIR dynamical systems models, and we outline how they can be easily and rapidly constructed using the  ...  We also demonstrate how to extend these models to a metapopulation setting using both the Numerus Model Builder network and geographical mapping tools.  ...  A free version of NMB software can be downloaded at  ... 
doi:10.1101/191601 fatcat:ug3f4fai6vf7tpkmvy2dw66xse

The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale

Wouter Van den Broeck, Corrado Gioannini, Bruno Gonçalves, Marco Quaggiotto, Vittoria Colizza, Alessandro Vespignani
2011 BMC Infectious Diseases  
These features make the GLEaMviz computational tool a convenient teaching/training tool as well as a first step toward the development of a computational tool aimed at facilitating the use and exploitation  ...  of computational models for the policy making and scenario analysis of infectious disease outbreaks.  ...  Acknowledgements We are grateful to the International Air Transport Association for making the airline commercial flight database available to us.  ... 
doi:10.1186/1471-2334-11-37 pmid:21288355 pmcid:PMC3048541 fatcat:qfnut3abnngcfnkbzlvisfwwee

Dynamics of infectious diseases

Kat Rock, Sam Brand, Jo Moir, Matt J Keeling
2014 Reports on progress in physics (Print)  
Modern infectious disease epidemiology has a strong history of using mathematics both for prediction and to gain a deeper understanding.  ...  Throughout we relate the mathematical models and their results to a variety of real-world problems.  ...  methodology allows us to compute extinction probabilities for a wide spectrum of model formulations.  ... 
doi:10.1088/0034-4885/77/2/026602 pmid:24444713 fatcat:ijwhlezbhjadxeoueiltsjmyau


Keith R. Bisset, Jiangzhuo Chen, Suruchi Deodhar, Xizhou Feng, Yifei Ma, Madhav V. Marathe
2014 ACM Transactions on Modeling and Computer Simulation  
We describe the design and prototype implementation of INDEMICS (Interactive Epidemic Simulation) -a modeling environment utilizing high-performance computing technologies for supporting complex epidemic  ...  INDEMICS goes beyond traditional epidemic simulations by providing a simple and powerful way to represent and analyze policy-based as well as individualbased adaptive interventions.  ...  We also thank members of the Network Dynamics and Simulation Science Laboratory (NDSSL) for their helpful suggestions and comments.  ... 
doi:10.1145/2501602 pmid:25346586 pmcid:PMC4207128 fatcat:zxypz3vn5fcsxliskq53hacqqm

Modeling epidemics: A primer and Numerus Model Builder implementation

Wayne M. Getz, Richard Salter, Oliver Muellerklein, Hyun S. Yoon, Krti Tallam
2018 Epidemics  
A B S T R A C T Epidemiological models are dominated by compartmental models, of which SIR formulations are the most commonly used.  ...  We also demonstrate how to extend these models to a metapopulation setting using NMB network and mapping tools.  ...  A free version of NMB software can be downloaded at  ... 
doi:10.1016/j.epidem.2018.06.001 pmid:30017895 fatcat:5262jmv2qfdmbiczdhhjqroedq

An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City [article]

Sheng Zhang, Joan Ponce, Zhen Zhang, Guang Lin, George Em Karniadakis
2021 medRxiv   pre-print
Here, we develop a general framework for building a trustworthy data-driven epidemiological model, consisting of a workflow that integrates data acquisition and event timeline, model development, identifiability  ...  In particular, we apply this framework to propose a modified susceptible-exposed-infectious-recovered (SEIR) model, including new compartments and model vaccination in order to forecast the transmission  ...  , the basic reproduction number, R 0 , is 350 computed by using β = β 1 . 351 The transmission of the disease slows down when there are more immune individuals. 352 Since R c is the number in an entirely  ... 
doi:10.1101/2021.02.22.21252255 fatcat:p3iytqq7fvdptmsur3htkc5txu

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

Ernesto Estrada
2020 Physics reports  
This includes a wide range of approaches - deterministic, data-driven, stochastic, agent-based, and their combinations - to forecast the progression of the epidemic as well as the effects of non-pharmaceutical  ...  demands the use of physical modeling of proteins, protein-inhibitors interactions, virtual screening of drugs against virus targets, predicting immunogenicity of small peptides, modeling vaccinomics and  ...  Acknowledgments The author is indebted to A. Aleta  ... 
doi:10.1016/j.physrep.2020.07.005 pmid:32834430 pmcid:PMC7386394 fatcat:ytcgwdnjvjffhpe2qpxivpv5ge

Modeling COVID-19 scenarios for the United States

IHME COVID-19 Forecasting Team
2020 Nature Medicine  
Using this SEIR model, and projections of critical driving covariates (pneumonia seasonality, mobility, testing rates and mask use per capita), we assessed scenarios of social distancing mandates and levels  ...  We use COVID-19 case and mortality data from 1 February 2020 to 21 September 2020 and a deterministic SEIR (susceptible, exposed, infectious and recovered) compartmental framework to model possible trajectories  ...  We also extend a note of particular thanks to J. Stanton and J. Nordstrom for their generous support.  ... 
doi:10.1038/s41591-020-1132-9 pmid:33097835 fatcat:fa56xtrq6rfbpndlruiu7t2oeq

Networks and the Epidemiology of Infectious Disease

Leon Danon, Ashley P. Ford, Thomas House, Chris P. Jewell, Matt J. Keeling, Gareth O. Roberts, Joshua V. Ross, Matthew C. Vernon
2011 Interdisciplinary Perspectives on Infectious Diseases  
applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network.  ...  Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible.  ...  We would like to thank Kieran Sharkey for use of pre-publication MATLAB code and two anonymous reviewers for their comments. All authors contributed equally to this manuscript.  ... 
doi:10.1155/2011/284909 pmid:21437001 pmcid:PMC3062985 fatcat:k3exgqpjj5ch3kx3lh3fmwzxhi

From Epidemic to Pandemic Modelling [article]

Shannon Connolly, David Gilbert, Monika Heiner
2021 arXiv   pre-print
Our approach builds on the use of coloured stochastic and continuous Petri nets facilitating the sound component-based extension of basic SIR models to include population stratification and also spatio-geographic  ...  This method is inherently easy to use, producing scalable and reusable models with a high degree of clarity and accessibility which can be read either in a deterministic or stochastic paradigm.  ...  of a pandemic model is the concept of multiple intercommunicating epidemic models in a spatial (geographic) context.  ... 
arXiv:2107.00835v1 fatcat:3xe2l6n6bbgppc64xjavxmhauy

Emissions Trading [chapter]

2017 Encyclopedia of GIS  
and the basic reproductive number associated with the disease of interest).  ...  The basic analytical method family for raster datasets is map algebra (a term coined by Tomlin 1990), which extends the standard algebra of scalar values to raster data.  ...  Markov Chain Models Based on the obtained sequential patterns, a personalized location-based recommender system can predict the probability of a user visiting a new location through using a variety of  ... 
doi:10.1007/978-3-319-17885-1_100350 fatcat:qtqeulswn5fanpkosuygq57viq

Statistical physics of vaccination

Zhen Wang, Chris T. Bauch, Samit Bhattacharyya, Alberto d'Onofrio, Piero Manfredi, Matjaž Perc, Nicola Perra, Marcel Salathé, Dawei Zhao
2016 Physics reports  
Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks.  ...  behavior, to recent models that account for behavioral feedback and/or population spatial/social structure.  ...  Nonlinear contact rates as a phenomenological route to behavior change A limitation of mass-action-based SIR and SEIR models with and without vital dynamics, and of other epidemic models, is that they  ... 
doi:10.1016/j.physrep.2016.10.006 fatcat:hxq7di4j4zfilfv3m4ogbkzovu

The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges [article]

Amir Ahmada, Sunita Garhwal, Santosh Kumar Ray, Gagan Kumar, Sharaf J. Malebary, Omar Mohammed Omar Barukab
2020 arXiv   pre-print
Machine learning methods learn from the historical data and make a prediction about the event. Machine learning methods have been used to predict the number of confirmed cases of Covid-19.  ...  In this paper, we present a detailed review of these research papers. We present a taxonomy that groups them in four categories. We further present the challenges in this field.  ...  Model parameters are computed using Bayesian regression approach.  ... 
arXiv:2006.09184v1 fatcat:l65klxlkx5hgfikrfafhgepxgq
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