| Type: | Package |
| Title: | Interactive Plotting for Mathematical Models of Infectious Disease Spread |
| Version: | 0.1.2 |
| Date: | 2020-09-30 |
| Maintainer: | Sinead E. Morris <sinead.morris@columbia.edu> |
| Description: | 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. The package is a useful teaching tool as students can visualize how changing different parameters can impact model dynamics, with minimal knowledge of coding in R. The built-in models are inspired by those featured in Keeling and Rohani (2008) <doi:10.2307/j.ctvcm4gk0> and Bjornstad (2018) <doi:10.1007/978-3-319-97487-3>. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 6.1.1 |
| Depends: | dplyr (≥ 0.8.0.1), tidyr (≥ 0.8.3), ggplot2 (≥ 3.1.1), shiny (≥ 1.3.2), deSolve (≥ 1.2.1) |
| Suggests: | knitr (≥ 1.22), rmarkdown (≥ 1.12), testthat (≥ 2.2.0) |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2020-10-18 18:38:16 UTC; sineadmorris |
| Author: | Sinead E. Morris 
[aut, cre],
Ottar N. Bjornstad [ctb] |
| Repository: | CRAN |
| Date/Publication: | 2020-10-18 18:50:02 UTC |
SIR model
Description
These equations describe the classic SIR model with no births or deaths.
Usage
SIR(t, y, parms)
Arguments
t |
numeric vector of time points. |
y |
numeric vector of variables. |
parms |
named vector of model parameters. |
Value
equation list
SIRS model
Description
These equations describe the classic SIRS model without births or deaths.
Usage
SIRS(t, y, parms)
Arguments
t |
numeric vector of time points. |
y |
numeric vector of variables. |
parms |
named vector of model parameters. |
Value
equation list
SIRS model with demography
Description
These equations describe the classic SIRS model with equal birth and death rates.
Usage
SIRSbirths(t, y, parms)
Arguments
t |
numeric vector of time points. |
y |
numeric vector of variables. |
parms |
named vector of model parameters. |
Value
equation list
SIRS model with vaccination at birth
Description
These equations describe the classic SIRS model with equal birth and death rates and vaccination at birth.
Usage
SIRSvaccination(t, y, parms)
Arguments
t |
numeric vector of time points. |
y |
numeric vector of variables. |
parms |
named vector of model parameters. |
Value
equation list
SIR model with demography
Description
These equations describe the classic SIR model with equal births and deaths.
Usage
SIRbirths(t, y, parms)
Arguments
t |
numeric vector of time points. |
y |
numeric vector of variables. |
parms |
named vector of model parameters. |
Value
equation list
SIR model with vaccination at birth
Description
These equations describe the classic SIR model with births and deaths, constant population size, and (optional) vaccination at birth.
Usage
SIRvaccination(t, y, parms)
Arguments
t |
numeric vector of time points |
y |
numeric vector of variables |
parms |
named vector of model parameters. |
Value
equation list
SIS model
Description
These equations describe the classic SIS model with no births or deaths.
Usage
SIS(t, y, parms)
Arguments
t |
numeric vector of time points |
y |
numeric vector of variables |
parms |
named vector of model parameters. |
Value
equation list
SIS model with demography
Description
These equations describe the classic SIR model with equal births and deaths.
Usage
SISbirths(t, y, parms)
Arguments
t |
numeric vector of time points. |
y |
numeric vector of variables. |
parms |
named vector of model parameters. |
Value
equation list
Model help
Description
This function prints a list of all built in models, along with their parameter arguments and a short description.
Usage
default_models()
Value
data frame of model descriptions.
Examples
default_models()
Get default initial conditions
Description
This function returns the default parameter vectors for a particular built-in model.
Usage
get_ics(model)
Arguments
model |
name of the model to be solved. Examples include: SIR and SIR vaccination. |
Value
named vector of default initial conditions.
Get model display names
Description
This function gets the display name for any built-in model.
Usage
get_name(model)
Arguments
model |
character specifying the name of the built-in model. |
Value
character of the corresponding display name.
Examples
get_name(model = "SIR")
Get default parameters
Description
This function returns the default parameter vectors for a particular built-in model.
Usage
get_params(model)
Arguments
model |
name of the model to be solved. Examples include: SIR and SIR vaccination. |
Value
list of default parameter vectors.
Examples
get_params(model = "SIR")
Plot model output. This function plots the output of a fitted model data frame.
Description
Plot model output. This function plots the output of a fitted model data frame.
Usage
plot_model(output, linesize, textsize, xlabel, ylabel, legend_title,
levels, values, ...)
Arguments
output |
data frame output from solve_eqns(). |
linesize |
numeric value for line width in ggplot. |
textsize |
numeric value for textsize in ggplot. |
xlabel |
character string for x axis label. |
ylabel |
character string for y axis label. |
legend_title |
character string for legend title. |
levels |
character vector of the variable names in the order they should be plotted. Default is to obtain the order from the initial conditions vector 'ics'. |
values |
vector specifying manual color scale. Length must equal the number of model variables. |
... |
extra argument to be passed through to ggplot scale_colour_manual: use 'labels' to change the legend names |
Value
ggplot object
Solve equations
Description
This function solves an ODE model using 'deSolve' and returns the output as a data frame.
Usage
run_shiny(model = "SIR", neweqns = NULL, ics = NULL, tstart = 0,
timestep = 1, tmax = 365, parm0 = NULL, parm_names = NULL,
parm_min = NULL, parm_max = NULL, sigfigs = 4, showtable = TRUE,
linesize = 1.2, textsize = 14, xlabel = "Time",
ylabel = "Number of individuals", legend_title = "Compartment",
slider_steps = NULL, values = NULL, ...)
Arguments
model |
name of the model to be solved. Examples of built-in models are: "SIR", "SIR vaccination". Default is "SIR". |
neweqns |
function specifying the equations of the user-defined model. Only to be used if a model is required that is not built-in. Default is NULL. |
ics |
named numeric vector specifying the initial conditions i.e. the initial values of all model variables. Default is c(S = 9999, I = 1, R = 0) for the SIR model. |
tstart |
numerical value of form c(tmin, tmax) indicating the time to start simulations. Default value is 0. |
timestep |
numerical value indicating time step be used when solving equations. Default value is 1/365. |
tmax |
numerical value indicating maximum time point to be considered. |
parm0 |
named numeric vector of starting parameter values. Names must correspond to those used in the model equations. |
parm_names |
character vector of parameter names to be displayed in shiny menu. Must be in the same order as 'parm0'. |
parm_min |
named numeric vector of minimum parameter values. |
parm_max |
named numeric vector of maximum parameter values. |
sigfigs |
number of significant figures to round parameter input vectors. Default is 4. |
showtable |
logical TRUE/FALSE. Should the table of transformed parameters be shown? Only applies to built-in models. Default is TRUE. |
linesize |
numeric value for line width in ggplot output. Default is 1.2. |
textsize |
numeric value for textsize in ggplot output. Default is 14. |
xlabel |
character string for x axis plotting label. Default is "Time". |
ylabel |
character string for y axis plotting label. Default is "Number of individuals". |
legend_title |
character string for legend title. Default is "Compartment". |
slider_steps |
numeric vector of step size to include between slider input values. Should be NULL or a vector with an entry for each parameter input. Default is NULL. |
values |
vector specifying manual color scale (if desired). Length must equal the number of model variables. |
... |
extra argument to be passed through to ggplot scale_colour_manual: use 'labels' to change the legend names. |
Value
data frame of model solutions in long format.
Examples
run_shiny(model = "SIR")
Launch a shiny-app simulating the seasonal SEIR model
Description
#' This launches an app running the SEIR model i.e. a model incorporating latency and seasonal forcing in transmission.
Usage
seir.app
Format
An object of class shiny.appobj of length 5.
Details
Launch app for details
Examples
## Not run: seir.app
Launch a shiny-app simulating the SEIRS model
Description
This launches an app running the SEIRS model i.e. a model incorporating latency and loss of immunity.
Usage
seirs.app
Format
An object of class shiny.appobj of length 5.
Details
Launch app for details
Examples
## Not run: seirs.app
Solve equations
Description
This function solves an ODE model using 'deSolve' and returns the output as a data frame.
Usage
solve_eqns(eqns, ics, times, parms)
Arguments
eqns |
name of the model to be solved. Examples include: SIR and SIR vaccination. |
ics |
named numeric vector specifying the initial conditions i.e. the initial values of all model variables. |
times |
numerical vector indicating the time points at which the equation should be solved. |
parms |
named numeric vector of parameter values. |
Value
data frame of model solutions in long format.