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spread
Infectious Disease Spread Models
RELATED ARTICLES
Explain
⌅
EIDM
EIDM ☜The Emerging Infectious Diseases Modelling Initiative (EIDM) – by the Public Health Agency of Canada and NSERC – aims to establish multi-disciplinary network(s) of specialists across the country in modelling infectious diseases to be applied to public needs associated with emerging infectious diseases and pandemics such as COVID-19. [1]☜F1CEB7
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Software
Software☜Learn more about the software being used across the EIDM network.☜C78CB7
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Software languages
Software languages☜☜76A4CF
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R
R☜☜76A4CF
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R Packages
R Packages☜List of ten most popular R packages in infectious disease modelling as measured by the pkgsearch package (on 2021-06-09).☜76A4CF
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spread
spread☜Infectious Disease Spread Models☜C78CB7
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EpiModel
EpiModel☜EpiModel is an R package that provides tools for simulating and analyzing mathematical models of infectious disease dynamics. Supported epidemic model classes include deterministic compartmental models, stochastic individual contact models, and stochastic network models. Disease types include SI, SIR, and SIS epidemics with and without demography, with utilities available for expansion to construct and simulate epidemic models of arbitrary complexity. [1]☜C78CB7
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epitrix
epitrix☜A collection of small functions useful for epidemics analysis and infectious disease modelling. This includes computation of basic reproduction numbers from growth rates, generation of hashed labels to anonymize data, and fitting discretized Gamma distributions. [2]☜C78CB7
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hhh4contacts
hhh4contacts☜Age-Structured Spatio-Temporal Models for Infectious Disease Counts – Meyer and Held (2017) present an age-structured spatio-temporal model for infectious disease counts. The approach is illustrated in a case study on norovirus gastroenteritis in Berlin, 2011-2015, by age group, city district and week, using additional contact data from the POLYMOD survey. [2]☜C78CB7
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ibmcraftr
ibmcraftr☜Toolkits to Develop Individual-Based Models in Infectious Disease – It provides a generic set of tools for initializing a synthetic population with each individual in specific disease states, and making transitions between those disease states according to the rates calculated on each timestep. The new version 1.0.0 has C++ code integration to make the functions run faster. It has also a higher level function to actually run the transitions for the number of timesteps that users specify. [1]☜C78CB7
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idmodelr
idmodelr☜The primary aim of idmodelr is to provide a library of infectious disease models for researchers. These models can be used to understand the underlying dynamics and as a reference point when developing models for research. idmodelr also provides a range of utilities. These include: plotting functionality; a simulation wrapper; scenario analysis tooling; an interactive dashboard; tools for handling mult-dimensional models; and both model and parameter look up tables. [1]☜C78CB7
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pspline.inference
pspline.inference☜Estimation of Characteristics of Seasonal and Sporadic Infectious Disease Outbreaks Using Generalized Additive Modeling with Penalized Basis Splines. [1]☜C78CB7
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shinySIR
shinySIR☜Interactive Plotting for Mathematical Models of Infectious Disease Spread – Provides interactive plotting for mathematical models of infectious disease spread. Users can choose from a variety of common built-in ordinary differential equation (ODE) models (such as the SIR, SIRS, and SIS models), or create their own. This latter flexibility allows shinySIR to be applied to simple ODEs from any discipline. [1]☜C78CB7
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SimBIID
SimBIID☜Simulation-Based Inference Methods for Infectious Disease Model – Provides some code to run simulations of state-space models, and then use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) algorithm of Toni et al. (2009) and a bootstrap particle filter based particle Markov chain Monte Carlo (PMCMC) algorithm (Andrieu et al., 2010). Also provides functions to plot and summarise the outputs. [1]☜C78CB7
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socialmixr
socialmixr☜Social Mixing Matrices for Infectious Disease Modelling — Provides methods for sampling contact matrices from diary data for use in infectious disease modelling, as discussed in Mossong et al. (2008)☜C78CB7
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Graph of this discussion
Graph of this discussion☜Click this to see the whole debate, excluding comments, in graphical form☜dcdcdc
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David Price
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Entry date (GMT):
1/30/2023 10:52:00 PM
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1/30/2023 11:36:00 PM
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