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R
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1
#685214
CONTEXT
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EIDM »
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
Software☜Learn more about the software being used across the EIDM network.☜C78CB7
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Software languages »
Software languages
Software languages☜☜76A4CF
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R
R☜☜76A4CF
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R Packages »
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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R Shiny »
R Shiny
R Shiny☜☜76A4CF
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Rmarkdown »
Rmarkdown
Rmarkdown☜☜76A4CF
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diseasemapping »
diseasemapping
diseasemapping☜[Archived on 21 March 2022]☜FFFACD
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epi base package for SyncroSim »
epi base package for SyncroSim
epi base package for SyncroSim☜A scenario-based modelling framework for generating locally relevant forecasts of COVID-19☜FFFACD
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epigrowthfit »
epigrowthfit
epigrowthfit☜epigrowthfit 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]☜FFFACD
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EpiILM »
EpiILM
EpiILM☜The 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).☜FFFACD
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EpiILMCT »
EpiILMCT
EpiILMCT☜The 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]☜FFFACD
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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-19☜Estimating the infection fatality rate of Covid-19 using demographics data and deaths records from Italys hardest hit area. [1]☜FFFACD
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geostatsp »
geostatsp
geostatsp☜[Archived on 2021-12-09]☜FFFACD
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Hexagonalfan »
Hexagonalfan
Hexagonalfan☜An 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.☜FFFACD
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localEM »
localEM
localEM☜localEM is an R package that implements the kernel smoothing local-EM algorithm for estimating spatial risk on areal disease data. [1]☜FFFACD
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McMasterPandemic »
McMasterPandemic
McMasterPandemic☜Compartmental 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).☜FFFACD
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MultiBD »
MultiBD
MultiBD☜MultiBD is an R package for direct likelihood-based inference of multivariate birth-death processes. [1]☜FFFACD
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Open Data Model »
Open Data Model
Open Data Model☜Metadata 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]☜FFFACD
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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 outbreaks☜This 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]☜FFFACD
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SyncroSim »
SyncroSim
SyncroSim☜Delivering geospatial forecasting models direct to decision makers. SyncroSim streamlines the process of delivering your map-based forecasting models to non-technical users☜FFFACD
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Age-Patch Mobility Mixing »
Age-Patch Mobility Mixing
Age-Patch Mobility Mixing☜Deriving contact patterns for age & patch mixing, based on recurrent mobility data. [1]☜FFFACD
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COVID Hospital Surge »
COVID Hospital Surge
COVID Hospital Surge☜COVID-19 Healthcare Surge Model for Greater Toronto Area Hospitals.☜FFFACD
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COVID-19 Re - Generation Time »
COVID-19 Re - Generation Time
COVID-19 Re - Generation Time☜Estimating the effective reproduction number Re(t) for COVID19 in GTA, Canada. [1]☜FFFACD
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Mathematical epidemiology in a data-rich world »
Mathematical epidemiology in a data-rich world
Mathematical epidemiology in a data-rich world☜An exciting trend for modellers, which started 5–10 years ago and is becoming increasingly common, are open data initiatives. Such initiatives see governments (local or higher) create portals where data is centralised and made accessible, usually with very few constraints.☜FFFACD
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Efficacy of quarantine »
Efficacy of quarantine
Efficacy of quarantine☜R files linked to the paper Quarantine and the risk of COVID-19 importation [2]☜FFFACD
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covidseir »
covidseir
covidseir☜covidseir fits a Bayesian SEIR (Susceptible, Exposed, Infectious, Recovered) model to daily COVID-19 case data. The package focuses on estimating the fraction of the usual contact rate for individuals participating in physical distancing (social distancing). The model is coded in Stan. The model can accommodate multiple types of case data at once (e.g., reported cases, hospitalizations, ICU admissions) and accounts for delays between symptom onset and case appearance. [1]☜FFFACD
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R Epidemics Consortium (RECON) »
R Epidemics Consortium (RECON)
R Epidemics Consortium (RECON)☜The R Epidemics Consortium (RECON) is an international not-for-profit, non-governmental organisation gathering experts in data science, modelling methodology, public health, and software development to create the next generation of analytics tools for informing the response to disease outbreaks, health emergencies and humanitarian crises, using the R software and other free, open-source resources.☜FFFACD
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Entered by:-
David Price
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#685214
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Entry date (GMT):
9/26/2021 9:27:00 PM
Last edit date (GMT):
9/26/2021 9:27:00 PM
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