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Data analysis
Function
1
#686174
Immediately related elements
How this works
-
EIDMâ »
EIDMâ
EIDMââThe Emerging Infectious Diseases Modelling Initiative (EIDM) â by the Public Health Agency of Canada and NSERC â 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]âF1CEB7
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Software »
Software
SoftwareâLearn more about the software being used across the EIDM network.âC78CB7
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Software functionality »
Software functionality
Software functionalityââ8CC79C
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Data analysis
Data analysisââ8CC79C
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Age-Patch Mobility Mixing »
Age-Patch Mobility Mixing
Age-Patch Mobility MixingâDeriving contact patterns for age & patch mixing, based on recurrent mobility data. [1]âFFFACD
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COVID-19 Re - Generation Time »
COVID-19 Re - Generation Time
COVID-19 Re - Generation TimeâEstimating the effective reproduction number Re(t) for COVID19 in GTA, Canada. [1]âFFFACD
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Ontario pandemic mobility »
Ontario pandemic mobility
Ontario pandemic mobilityâThis interactive data tool uses publicly available Google Mobility data to generate graphs displaying overall mobility changes in Ontario. Google typically updates their datasets every 3-5 days, and the new data will contain data points with a 2-3 day lag. âFFFACD
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Dempster-Shafer Bayesian Network inference package »
Dempster-Shafer Bayesian Network inference package
Dempster-Shafer Bayesian Network inference packageâDS-BN is a C++ executable that accepts input data related to probabilistic belief networks and Dempster-Shafer belief networks through the use of files. According to provided instructions from one of the files, performs computations and writes inferred probability distributions or Dempster-Shafer models into an output file. [2]âFFFACD
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diseasemapping »
diseasemapping
diseasemappingâ[Archived on 21 March 2022]âFFFACD
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epigrowthfit »
epigrowthfit
epigrowthfitâepigrowthfit is an R package for fitting nonlinear mixed effects models of epidemic growth to collections of one or more disease incidence time series. It can be applied to birth processes other than epidemics, as the statistical machinery is agnostic to the precise interpretation of supplied count data. epigrowthfit is built on Template Model Builder. [1]âFFFACD
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EpiILM »
EpiILM
EpiILMâThe R package EpiILM provides tools for simulating from discrete-time individual level models for infectious disease data analysis. This epidemic model class contains spatial and contact-network based models with two disease types: Susceptible-Infectious (SI) and Susceptible-Infectious-Removed (SIR).âFFFACD
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EpiILMCT »
EpiILMCT
EpiILMCTâThe R package EpiILMCT provides tools for simulating from continuous-time individual level models of disease transmission, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based and contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed (SINR) compartmental frameworks. [2]âFFFACD
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Estimating the infection fatality rate of Covid-19 »
Estimating the infection fatality rate of Covid-19
Estimating the infection fatality rate of Covid-19âEstimating the infection fatality rate of Covid-19 using demographics data and deaths records from Italys hardest hit area. [1]âFFFACD
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geostatsp »
geostatsp
geostatspâ[Archived on 2021-12-09]âFFFACD
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Hexagonalfan »
Hexagonalfan
HexagonalfanâAn R script that generates a range of hexagonal fan designs. Hexagonal fans are triangular grids in which each successive row of triangles is larger than the previous, by some constant multiplier. Such designs can include a range of both (plant) densities and frequencies in a single plot, providing large economies in space and material for studying local interactions such as competition. However, in practice the fan design can be difficult to implement, hence why we have provided this script.âFFFACD
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localEM »
localEM
localEMâlocalEM is an R package that implements the kernel smoothing local-EM algorithm for estimating spatial risk on areal disease data. [1]âFFFACD
◄
McMasterPandemic »
McMasterPandemic
McMasterPandemicâCompartmental epidemic models for forecasting and analysis of infectious disease pandemics: contributions from Ben Bolker, Jonathan Dushoff, David Earn, Weiguang Guan, Morgan Kain, Michael Li, Irena Papst, Steve Walker (in alphabetical order).âFFFACD
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MultiBD »
MultiBD
MultiBDâMultiBD is an R package for direct likelihood-based inference of multivariate birth-death processes. [1]âFFFACD
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Open Data Model »
Open Data Model
Open Data ModelâMetadata and code to support covid-19 environmental surveillance for public health. Wastewater-based surveillance for Covid-19, with support for other health risks and environmental settings. [1]âFFFACD
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pathogen.jl »
pathogen.jl
pathogen.jlâSimulation, visualization, and inference tools for modelling the spread of infectious diseases with JuliaâFFFACD
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Prediction Codes »
Prediction Codes
Prediction CodesâDataset of COVID-19 outbreak and potential predictive features in the USA.âFFFACD
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python Population Modeller »
python Population Modeller
python Population ModellerâThe pyPM.ca software was developed to study and characterize the CoViD-19 epidemic.âFFFACD
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PyCoMod »
PyCoMod
PyCoModâPyCoMod is a Python package for building and running compartment models derived from systems of differential equations such as the Susceptible-Infectious-Recovered (SIR)model of infectious diseases.âFFFACD
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Stochastic simulations of classroom-level COVID-19 outbreaks »
Stochastic simulations of classroom-level COVID-19 outbreaks
Stochastic simulations of classroom-level COVID-19 outbreaksâThis repository contains code associated with a preprint exploring COVID-19 outbreaks in classrooms, and how these might be managed with several different protocols: COVID-19s unfortunate events in schools: mitigating classroom clusters in the context of variable transmission. [1]âFFFACD
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Entrée par:
Steven Walker
NodeID:
#686174
Node type:
Function
Date d'entrée (GMT):
10/7/2021 1:44:00 PM
Date de la derniĂšre modification (Heure GMT):
10/7/2021 1:44:00 PM
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