Function reference • ramp.library

MYZ - Adult Mosquito The model library for adult mosquito infection dynamics
The Adult Mosquito RMG Model
`F_eggs(<RMG>)`	Number of eggs laid by adult mosquitoes
`F_fqZ(<RMG>)`	Blood feeding rate of the infective mosquito population
`F_fqM(<RMG>)`	Blood feeding rate of the infective mosquito population
`MBaseline(<RMG>)`	Reset bloodfeeding and mortality rates to baseline
`MBionomics(<RMG>)`	Reset bloodfeeding and mortality rates to baseline
`dMYZdt(<RMG>)`	Derivatives for adult mosquitoes
`get_MYZinits(<RMG>)`	Return initial values as a vector
`make_MYZinits(<RMG>)`	Setup initial values for the RMG model
`create_MYZinits_RMG()`	Make inits for RMG adult mosquito model
`make_MYZpar(<RMG>)`	Setup MYZpar for the RMG model
`create_MYZpar_RMG()`	Make parameters for RM ODE adult mosquito model
`make_indices_MYZ(<RMG>)`	Add indices for adult mosquitoes to parameter list
`parse_MYZorbits(<RMG>)`	Parse the output of deSolve and return variables for the RMG model
`update_MYZinits(<RMG>)`	Make inits for RMG adult mosquito model
`get_g(<RMG>)`	Get the feeding rate
`get_f(<RMG>)`	Get the feeding rate
`get_q(<RMG>)`	Get the feeding rate
`get_sigma(<RMG>)`	Get the feeding rate
ENBRQ_dts Specialized methods for ENBRQ_dts, a model of adult mosquito dynamics with no parasite infection dynamics.
`MBionomics(<ENBRQ_dts>)`	Reset bloodfeeding and mortality rates to baseline
`F_fqZ(<ENBRQ_dts>)`	The net blood feeding rate of the infective mosquito population in a patch
`F_fqM(<ENBRQ_dts>)`	The net blood feeding rate of the infective mosquito population in a patch
`F_eggs(<ENBRQ_dts>)`	Number of eggs laid by adult mosquitoes
`dMYZdt(<ENBRQ_dts>)`	Derivatives for adult mosquitoes
`make_MYZpar(<ENBRQ_dts>)`	Setup MYZpar for the ENBRQ_dts model
`create_MYZpar_ENBRQ_dts()`	Make parameters for ENBRQ_dts adult mosquito model
`make_MYZinits(<ENBRQ_dts>)`	Setup initial values for the ENBRQ_dts model
`create_MYZinits_ENBRQ_dts()`	Make inits for ENBRQ_dts adult mosquito model
`list_MYZvars(<ENBRQ_dts>)`	Return the variables as a list
`make_indices_MYZ(<ENBRQ_dts>)`	Add indices for adult mosquitoes to parameter list
`parse_MYZorbits(<ENBRQ_dts>)`	Parse the output of deSolve and return variables for the ENBRQ_dts model
`make_inits_MYZ_ENBRQ_dts()`	Make inits for ENBRQ_dts adult mosquito model
`get_MYZinits(<ENBRQ_dts>)`	Return initial values as a vector
`update_MYZinits(<ENBRQ_dts>)`	Make inits for ENBRQ_dts adult mosquito model
`make_parameters_MYZ_ENBRQ_dts()`	Make parameters for ENBRQ_dts adult mosquito model
bionomics
`F_sigma(<dddn>)`	Dawn, day, dusk, night model for the human fraction
`F_f(<dddn>)`	Dawn, day, dusk, night model for the blood feeding rate
`F_q(<dddn>)`	Dawn, day, dusk, night model for the human fraction
`F_p(<dddn>)`	Dawn, day, dusk, night model for the human fraction
`F_nu(<dddn>)`	Dawn, day, dusk, night model for the human fraction
L-Aquatic Mosquito Models for parasites infecting human / vertebrate hosts
stages_dts Specialized methods for a stages_dts competition model of aquatic mosquito dynamics.
`LBionomics(<stages_dts>)`	Reset aquatic parameters to baseline
`F_emerge(<stages_dts>)`	Number of newly emerging adults from each larval habitat
`dLdt(<stages_dts>)`	Derivatives for aquatic stage mosquitoes
`make_Lpar(<stages_dts>)`	Setup Lpar for the stages_dts model
`make_Linits(<stages_dts>)`	Setup the stages_dts model
`create_Lpar_stages_dts()`	Make parameters for stages_dts competition aquatic mosquito model
`create_Linits_stages_dts()`	Make inits for stages_dts competition aquatic mosquito model
`make_indices_L(<stages_dts>)`	Add indices for aquatic stage mosquitoes to parameter list
`list_Lvars(<stages_dts>)`	Return the variables as a list
`parse_Lorbits(<stages_dts>)`	Parse the variable names for the stages_dts model
`make_inits_L_stages_dts()`	Make inits for stages_dts competition aquatic mosquito model
`get_Linits.stages_dts()`	Return initial values as a vector
`update_Linits(<stages_dts>)`	Update inits for the stages_dts aquatic mosquito competition model
`make_parameters_L_stages_dts()`	Make parameters for stages_dts competition aquatic mosquito model
X-Vertebrate Hosts Models for parasites infecting human / vertebrate hosts
The Garki model
`F_X(<garki>)`	Size of effective infectious human population
`F_H(<garki>)`	Size of effective infectious human population
`F_pr(<garki>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<garki>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<garki>)`	Derivatives for human population
`make_Xpar(<garki>)`	make Xpar.garki
`create_Xpar_garki()`	Make parameters for garki human model
`make_Xinits(<garki>)`	Setup Xinits.garki
`create_Xinits_garki()`	Make inits for garki human model. Note that the variables should sum up to H, so the initial value of x1 is not set. The values are passed in the same order as they are presented in the original paper.
`list_Xvars(<garki>)`	Return the variables as a list
`make_X_indices(<garki>)`	Add indices for human population to parameter list
`parse_Xorbits(<garki>)`	Parse the output of deSolve and return variables for the garki model
`get_Xinits(<garki>)`	Return initial values as a vector for the garki model
`update_Xinits(<garki>)`	Update inits for the garki model
`HTC(<garki>)`	Compute the HTC for the garki model
`xds_plot_X(<garki>)`	Plot the density of infected individuals for the garki model
`xds_lines_X_garki()`	Add lines for the density of infected individuals for the garki model
XH Component Models for parasites infecting human / vertebrate hosts
The SIPw model
`dXdt(<SIPw>)`	Derivatives for human population
`Update_Xt(<SIPw>)`	Derivatives for human population
`make_Xpar(<SIPw>)`	Setup the Xpar for the SIPw_xde model
`create_Xpar_SIPw()`	Make parameters for SIPw_xde human model, with defaults
`F_X(<SIPw>)`	Size of effective infectious human population
`F_H(<SIPw>)`	Size of effective infectious human population
`F_pr(<SIPw>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SIPw>)`	Infection blocking pre-erythrocytic immunity
`make_Xinits(<SIPw>)`	Setup Xinits.SIPw
`create_Xinits_SIPw()`	Make initial values for a SIPw human model, with defaults
`list_Xvars(<SIPw>)`	Return the SIPw model variables as a list
`put_Xvars(<SIPw>)`	Return the SIPw model variables as a list, returned from Update_Xt.SIPw
`make_X_indices(<SIPw>)`	Add indices for human population to parameter list
`parse_Xorbits(<SIPw>)`	Parse the output of deSolve and return variables for SIPw models
`get_Xinits(<SIPw>)`	Return initial values as a vector from a SIPw model
`update_Xinits(<SIPw>)`	Update inits for SIPw models from a vector of states
`HTC(<SIPw>)`	Compute the HTC for the SIPw_xde model
`xds_plot_X(<SIPw>)`	Plot the density of infected individuals for the SIPw model
`xds_lines_X_SIPw()`	Add lines for the density of infected individuals for the SIP model
`xde_steady_state_X(<SIPw>)`	Compute the steady states for the SIP model as a function of the daily foi
The workhorse model
`F_X(<workhorse>)`	Size of effective infectious human population
`F_H(<workhorse>)`	Size of effective infectious human population
`F_pr(<workhorse>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<workhorse>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<workhorse>)`	Derivatives for human population
`make_Xinits(<workhorse>)`	Setup Xinits.workhorse
`list_Xvars(<workhorse>)`	Return the variables as a list
`make_Xpar(<workhorse>)`	make Xpar.workhorse
`create_Xpar_workhorse()`	Make parameters for workhorse human model, with defaults
`create_Xinits_workhorse()`	Make initial values for the workhorse human model, with defaults
`make_X_indices(<workhorse>)`	Add indices for human population to parameter list
`parse_Xorbits(<workhorse>)`	Parse the output of deSolve and return variables for the workhorse model
`get_Xinits(<workhorse>)`	Return initial values as a vector
`update_Xinits(<workhorse>)`	Update inits for the workhorse human model from a vector of states
`HTC(<workhorse>)`	Compute the HTC for the workhorse model
`xds_plot_X(<workhorse>)`	Plot the density of infected individuals for the workhorse model
`xds_lines_X_workhorse()`	Add lines for the density of infected individuals for the workhorse model
The SIR model
`dXdt(<SIR>)`	Compute the derivatives for parasite infection dynamics in human population strata
`make_Xpar(<SIR>)`	Setup Xpar.SIR
`create_Xpar_SIR()`	Make parameters for SIR human model, with defaults
`F_X(<SIR>)`	Size of effective infectious human population
`F_H(<SIR>)`	Size of effective infectious human population
`F_pr(<SIR>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SIR>)`	Infection blocking pre-erythrocytic immunity
`make_Xinits(<SIR>)`	Setup Xinits.SIR
`list_Xvars(<SIR>)`	Return the variables as a list
`create_Xinits_SIR()`	Make initial values for the SIR human model, with defaults
`make_X_indices(<SIR>)`	Add indices for human population to parameter list
`parse_Xorbits(<SIR>)`	Parse the output of deSolve and return variables for the SIR model
`get_Xinits(<SIR>)`	Return initial values as a vector
`update_Xinits(<SIR>)`	Update inits for the SIR human model from a vector of states
`HTC(<SIR>)`	Compute the HTC for the SIR model
`xds_plot_X(<SIR>)`	Plot the density of infected individuals for the SIR model
`xds_lines_X_SIR()`	Add lines for the density of infected individuals for the SIR model
`xde_steady_state_X(<SIR>)`	Compute the steady states for the SIR model as a function of the daily EIR
The SIRS Model
`F_X(<SIRS>)`	Size of effective infectious human population
`F_H(<SIRS>)`	Size of effective infectious human population
`F_pr(<SIRS>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SIRS>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<SIRS>)`	Compute the derivatives for parasite infection dynamics in human population strata
`make_Xpar(<SIRS>)`	Setup Xpar.SIRS
`make_Xinits(<SIRS>)`	Setup Xinits.SIRS
`list_Xvars(<SIRS>)`	Return the variables as a list
`create_Xpar_SIRS()`	Make parameters for SIRS human model, with defaults
`create_Xinits_SIRS()`	Make initial values for the SIRS human model, with defaults
`make_X_indices(<SIRS>)`	Add indices for human population to parameter list
`parse_Xorbits(<SIRS>)`	Parse the output of deSolve and return variables for the SIRS model
`get_Xinits(<SIRS>)`	Return initial values as a vector
`update_Xinits(<SIRS>)`	Update inits for the SIRS human model from a vector of states
`HTC(<SIRS>)`	Compute the HTC for the SIRS model
`xds_plot_X(<SIRS>)`	Plot the density of infected individuals for the SIRS model
`xds_lines_X_SIRS()`	Add lines for the density of infected individuals for the SIRS model
`xde_steady_state_X(<SIRS>)`	Compute the steady states for the SIRS model as a function of the daily EIR
The SEIR model
`F_X(<SEIR>)`	Size of effective infectious human population
`F_H(<SEIR>)`	Size of effective infectious human population
`F_pr(<SEIR>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SEIR>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<SEIR>)`	Compute the derivatives for parasite infection dynamics in human population strata
`make_Xpar(<SEIR>)`	Setup Xpar.SEIR
`make_Xinits(<SEIR>)`	Setup Xinits.SEIR
`list_Xvars(<SEIR>)`	Return the variables as a list
`create_Xpar_SEIR()`	Make parameters for SEIR human model, with defaults
`create_Xinits_SEIR()`	Make initial values for the SEIR human model, with defaults
`make_X_indices(<SEIR>)`	Add indices for human population to parameter list
`parse_Xorbits(<SEIR>)`	Parse the output of deSolve and return variables for the SEIR model
`get_Xinits(<SEIR>)`	Return initial values as a vector
`update_Xinits(<SEIR>)`	Update inits for the SEIR human model from a vector of states
`HTC(<SEIR>)`	Compute the HTC for the SEIR model
`xds_plot_X(<SEIR>)`	Plot the density of infected individuals for the SEIR model
`xds_lines_X_SEIR()`	Add lines for the density of infected individuals for the SEIR model
`xde_steady_state_X(<SEIR>)`	Compute the steady states for the SIRS model as a function of the daily EIR
The SEIRV model
`F_X(<SEIRV>)`	Size of effective infectious human population
`F_H(<SEIRV>)`	Size of effective infectious human population
`F_pr(<SEIRV>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SEIRV>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<SEIRV>)`	Compute the derivatives for parasite infection dynamics in human population strata
`list_Xvars(<SEIRV>)`	Return the variables as a list
`make_Xpar(<SEIRV>)`	Setup Xpar.SEIRV
`make_Xinits(<SEIRV>)`	Setup Xinits.SEIRV
`create_Xpar_SEIRV()`	Make parameters for SEIRV human model, with defaults
`create_Xinits_SEIRV()`	Make initial values for the SEIRV human model, with defaults
`make_X_indices(<SEIRV>)`	Add indices for human population to parameter list
`parse_Xorbits(<SEIRV>)`	Parse the output of deSolve and return variables for the SEIRV model
`get_Xinits(<SEIRV>)`	Return initial values as a vector
`update_Xinits(<SEIRV>)`	Update inits for the SEIRV human model from a vector of states
`HTC(<SEIRV>)`	Compute the HTC for the SEIRV model
`xds_plot_X(<SEIRV>)`	Plot the density of infected individuals for the SEIRV model
`xds_lines_X_SEIRV()`	Add lines for the density of infected individuals for the SEIRV model
`xde_steady_state_X(<SEIRV>)`	Compute the steady states for the SEIRV model as a function of the daily EIR

Reference

MYZ - Adult Mosquito

The Adult Mosquito RMG Model

ENBRQ_dts

bionomics

L-Aquatic Mosquito

stages_dts

X-Vertebrate Hosts

The Garki model

XH Component

The SIPw model

The workhorse model

The SIR model

The SIRS Model

The SEIR model

The SEIRV model