Package index • ramp.library

MYZ - Adult Mosquito The model library for adult mosquito infection dynamics
The Adult Mosquito RMG Model A behavioral state 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_MYZpars(<RMG>)`	Return the parameters as a list
`set_MYZpars(<RMG>)`	Return the parameters as a list
`get_MYZinits(<RMG>)`	Return initial values as a vector
`set_MYZinits(<RMG>)`	Set new MYZ parameter values
`setup_MYZinits(<RMG>)`	Setup initial values for the RMG model
`setup_MYZpar(<RMG>)`	Setup MYZpar for the RMG model
`make_MYZinits_RMG()`	Make inits for RMG adult mosquito model
`make_MYZpar_RMG()`	Make parameters for RM ODE adult mosquito model
`setup_MYZix(<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
The Adult Mosquito SBRQ Model A behavioral state model
`F_eggs(<SBRQ>)`	Number of eggs laid by adult mosquitoes
`F_fqZ(<SBRQ>)`	Blood feeding rate of the infective mosquito population
`F_fqM(<SBRQ>)`	Blood feeding rate of the infective mosquito population
`MBaseline(<SBRQ>)`	Reset bloodfeeding and mortality rates to baseline
`MBionomics(<SBRQ>)`	Reset bloodfeeding and mortality rates to baseline
`dMYZdt(<SBRQ>)`	Derivatives for adult mosquitoes
`get_MYZpars(<SBRQ>)`	Return the parameters as a list
`set_MYZpars(<SBRQ>)`	Return the parameters as a list
`get_MYZinits(<SBRQ>)`	Return initial values as a vector
`set_MYZinits(<SBRQ>)`	Set new MYZ parameter values
`setup_MYZinits(<SBRQ>)`	Setup initial values for the SBRQ model
`setup_MYZpar(<SBRQ>)`	Setup MYZpar for the SBRQ model
`make_MYZinits_SBRQ()`	Make inits for SBRQ adult mosquito model
`make_MYZpar_SBRQ()`	Make parameters for RM ODE adult mosquito model
`setup_MYZix(<SBRQ>)`	Add indices for adult mosquitoes to parameter list
`parse_MYZorbits(<SBRQ>)`	Parse the output of deSolve and return variables for the SBRQ model
`update_MYZinits(<SBRQ>)`	Make inits for SBRQ adult mosquito model
`get_g(<SBRQ>)`	Get the feeding rate
`get_f(<SBRQ>)`	Get the feeding rate
`get_q(<SBRQ>)`	Get the feeding rate
`get_sigma(<SBRQ>)`	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
`setup_MYZpar(<ENBRQ_dts>)`	Setup MYZpar for the ENBRQ_dts model
`make_MYZpar_ENBRQ_dts()`	Make parameters for ENBRQ_dts adult mosquito model
`setup_MYZinits(<ENBRQ_dts>)`	Setup initial values for the ENBRQ_dts model
`make_MYZinits_ENBRQ_dts()`	Make inits for ENBRQ_dts adult mosquito model
`list_MYZvars(<ENBRQ_dts>)`	Return the variables as a list
`setup_MYZix(<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
The SEI compartment model Specialized methods for simple infection dynamics for an adult mosquito population
`dMYZdt(<SEI>)`	\(\cal MYZ\) Component Derivatives for the `SEI` Mosquito Model
`MBaseline(<SEI>)`	Set mosquito bionomics to baseline
`MBionomics(<SEI>)`	Set mosquito bionomics to baseline
`xde_steady_state_MYZ(<SEI>)`	Steady States: MYZ-SEI
`Update_MYZt(<SEI>)`	Derivatives for adult mosquitoes
`setup_MYZpar(<SEI>)`	Setup MYZpar for the SEI model
`make_MYZpar_SEI()`	Make parameters for SEI ODE adult mosquito model
`F_fqZ(<SEI>)`	The net blood feeding rate of the infective mosquito population in a patch
`F_fqM(<SEI>)`	The net blood feeding rate of the infective mosquito population in a patch
`F_eggs(<SEI>)`	Number of eggs laid by adult mosquitoes
`list_MYZvars(<SEI>)`	Return the variables as a list
`get_MYZpars(<SEI>)`	Return the parameters as a list
`set_MYZpars(<SEI>)`	Return the parameters as a list
`put_MYZvars(<SEI>)`	Return the variables as a list
`setup_MYZinits(<SEI>)`	Setup initial values for the SEI model
`make_MYZinits_SEI()`	Make inits for SEI adult mosquito model
`setup_MYZix(<SEI>)`	Add indices for adult mosquitoes to parameter list
`parse_MYZorbits(<SEI>)`	Parse the output of deSolve and return variables for the SEI model
`get_MYZinits(<SEI>)`	Return initial values as a vector
`set_MYZinits(<SEI>)`	Set new MYZ parameter values
`update_MYZinits(<SEI>)`	Make inits for SEI adult mosquito model
`get_f(<SEI>)`	Get the feeding rate
`get_q(<SEI>)`	Get the feeding rate
`get_g(<SEI>)`	Get the feeding rate
`get_sigma(<SEI>)`	Get the feeding rate
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
`setup_Lpar(<stages_dts>)`	Setup Lpar for the stages_dts model
`setup_Linits(<stages_dts>)`	Setup the stages_dts model
`make_Lpar_stages_dts()`	Make parameters for stages_dts competition aquatic mosquito model
`make_Linits_stages_dts()`	Make inits for stages_dts competition aquatic mosquito model
`setup_Lix(<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_prevalence(<garki>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<garki>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<garki>)`	Derivatives for human population
`setup_Xpar(<garki>)`	make Xpar for the Garki model
`make_Xpar_garki()`	Make parameters for garki human model
`setup_Xinits(<garki>)`	Setup Xinits.garki
`make_Xinits_garki()`	Make inits for garki human model.
`list_Xvars(<garki>)`	Return the variables as a list
`setup_Xix(<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
`set_Xinits(<garki>)`	Set Xinits.garki
`set_Xpars(<garki>)`	Return the parameters as a list
`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 workhorse model
`F_X(<workhorse>)`	Size of effective infectious human population
`F_H(<workhorse>)`	Size of effective infectious human population
`F_prevalence(<workhorse>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<workhorse>)`	Infection blocking pre-erythrocytic immunity
`dXdt(<workhorse>)`	Derivatives for human population
`setup_Xinits(<workhorse>)`	Setup Xinits.workhorse
`list_Xvars(<workhorse>)`	Return the variables as a list
`setup_Xpar(<workhorse>)`	make Xpar.workhorse
`make_Xpar_workhorse()`	Make parameters for workhorse human model, with defaults
`make_Xinits_workhorse()`	Make initial values for the workhorse human model, with defaults
`setup_Xix(<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
`setup_Xpar(<SIR>)`	Setup Xpar.SIR
`make_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_prevalence(<SIR>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SIR>)`	Infection blocking pre-erythrocytic immunity
`setup_Xinits(<SIR>)`	Setup Xinits.SIR
`list_Xvars(<SIR>)`	Return the variables as a list
`make_Xinits_SIR()`	Make initial values for the SIR human model, with defaults
`setup_Xix(<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
`set_Xinits(<SIR>)`	Return the parameters as a list
`set_Xpars(<SIR>)`	Return the parameters as a list
`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
`Update_Xt(<SIR>)`	DTS updating for the SIS model for human / vertebrate host infections
`dts_steady_state_X(<SIR>)`	Compute the steady states for the dts SEIS 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_prevalence(<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
`setup_Xpar(<SIRS>)`	Setup Xpar.SIRS
`setup_Xinits(<SIRS>)`	Setup Xinits.SIRS
`list_Xvars(<SIRS>)`	Return the variables as a list
`make_Xpar_SIRS()`	Make parameters for SIRS human model, with defaults
`make_Xinits_SIRS()`	Make initial values for the SIRS human model, with defaults
`setup_Xix(<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
`set_Xinits(<SIRS>)`	Return the parameters as a list
`set_Xpars(<SIRS>)`	Return the parameters as a list
`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
`Update_Xt(<SIRS>)`	DTS updating for the SIS model for human / vertebrate host infections
`dts_steady_state_X(<SIRS>)`	Compute the steady states for the dts SEIS 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_prevalence(<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
`setup_Xpar(<SEIR>)`	Setup Xpar.SEIR
`setup_Xinits(<SEIR>)`	Setup Xinits.SEIR
`list_Xvars(<SEIR>)`	Return the variables as a list
`make_Xpar_SEIR()`	Make parameters for SEIR human model, with defaults
`make_Xinits_SEIR()`	Make initial values for the SEIR human model, with defaults
`setup_Xix(<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
`set_Xinits(<SEIR>)`	Return the parameters as a list
`set_Xpars(<SEIR>)`	Return the parameters as a list
`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
`Update_Xt(<SEIR>)`	DTS updating for the SIS model for human / vertebrate host infections
`dts_steady_state_X(<SEIR>)`	Compute the steady states for the dts SEIS 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_prevalence(<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
`setup_Xpar(<SEIRV>)`	Setup Xpar.SEIRV
`setup_Xinits(<SEIRV>)`	Setup Xinits.SEIRV
`make_Xpar_SEIRV()`	Make parameters for SEIRV human model, with defaults
`make_Xinits_SEIRV()`	Make initial values for the SEIRV human model, with defaults
`setup_Xix(<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
`set_Xinits(<SEIRV>)`	Return the parameters as a list
`set_Xpars(<SEIRV>)`	Return the parameters as a list
`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
`Update_Xt(<SEIRV>)`	DTS updating for the SIS model for human / vertebrate host infections
`dts_steady_state_X(<SEIRV>)`	Compute the steady states for the dts SEIS model as a function of the daily EIR
SEIS Specialized methods for the SEIS (Susceptible-Infected-Susceptible) model of human dynamics.
`dXdt(<SEIS>)`	\(\cal X\) Component Derivatives for the `SEIS` Model
`Update_Xt(<SEIS>)`	DTS updating for the SEIS model for human / vertebrate host infections
`setup_Xpar(<SEIS>)`	Setup Xpar.SEIS
`make_Xpar_SEIS()`	Make parameters for SEIS xde human model, with defaults
`setup_Xinits(<SEIS>)`	Setup Xinits.SEIS
`make_Xinits_SEIS()`	Make initial values for the SEIS xde human model, with defaults
`setup_Xix(<SEIS>)`	Add indices for human population to parameter list
`list_Xvars(<SEIS>)`	Return the variables as a list
`get_Xpars(<SEIS>)`	Return the parameters as a list
`put_Xvars(<SEIS>)`	Return the SEIS model variables as a list, returned from Update_Xt.SISd
`F_X(<SEIS>)`	Size of effective infectious human population
`F_H(<SEIS>)`	Size of effective infectious human population
`F_prevalence(<SEIS>)`	Compute the "true" prevalence of infection / parasite rate
`F_prevalence_lm.SEIS()`	Compute the prevalence of infection by light microscopy
`F_prevalence_pcr.SEIS()`	Compute the prevalence of infection by pcr
`F_prevalence_rdt.SEIS()`	Compute the prevalence of infection by RDT
`F_ni(<SEIS>)`	Compute the NI
`F_b(<SEIS>)`	Infection blocking pre-erythrocytic immunity
`parse_Xorbits(<SEIS>)`	Parse the output of deSolve and return variables for the SEIS model
`get_Xinits(<SEIS>)`	Return initial values as a vector
`set_Xinits(<SEIS>)`	Return the parameters as a list
`set_Xpars(<SEIS>)`	Return the parameters as a list
`update_Xinits(<SEIS>)`	Update inits for the SEIS xde human model from a vector of states
`HTC(<SEIS>)`	Compute the HTC for the SEIS model
`xds_plot_X(<SEIS>)`	Plot the density of infected individuals for the SEIS model
`add_lines_X_SEIS()`	Add lines for the density of infected individuals for the SEIS model
`xde_steady_state_X(<SEIS>)`	Compute the steady states for the SEIS model as a function of the daily EIR
`dts_steady_state_X(<SEIS>)`	Compute the steady states for the dts SEIS model as a function of the daily EIR
SEISd Specialized methods for the SEISd (Susceptible-Infected-Susceptible) model of human dynamics.
`dXdt(<SEISd>)`	\(\cal X\) Component Derivatives for the `SEISd` Model
`Update_Xt(<SEISd>)`	DTS updating for the SEISd model for human / vertebrate host infections
`setup_Xpar(<SEISd>)`	Setup Xpar.SEISd
`make_Xpar_SEISd()`	Make parameters for SEISd xde human model, with defaults
`xde_steady_state_X(<SEISd>)`	Compute the steady states for the SEISd model as a function of the daily EIR
`setup_Xinits(<SEISd>)`	Setup Xinits.SEISd
`make_Xinits_SEISd()`	Make initial values for the SEISd xde human model, with defaults
`setup_Xix(<SEISd>)`	Add indices for human population to parameter list
`list_Xvars(<SEISd>)`	Return the variables as a list
`set_Xpars(<SEISd>)`	Return the parameters as a list
`put_Xvars(<SEISd>)`	Return the SEISd model variables as a list, returned from Update_Xt.SISd
`F_X(<SEISd>)`	Size of effective infectious human population
`F_H(<SEISd>)`	Size of effective infectious human population
`F_b(<SEISd>)`	Infection blocking pre-erythrocytic immunity
`parse_Xorbits(<SEISd>)`	Parse the output of deSolve and return variables for the SEISd model
`get_Xinits(<SEISd>)`	Return initial values as a vector
`set_Xinits(<SEISd>)`	Return the parameters as a list
`get_Xpars(<SEISd>)`	Return the parameters as a list
`update_Xinits(<SEISd>)`	Update inits for the SEISd xde human model from a vector of states
`HTC(<SEISd>)`	Compute the HTC for the SEISd model
`F_prevalence(<SEISd>)`	Compute the "true" prevalence of infection / parasite rate
`F_prevalence_by_lm.SEISd()`	Compute the prevalence of infection by light microscopy
`F_prevalence_by_pcr.SEISd()`	Compute the prevalence of infection by pcr
`F_prevalence_by_rdt.SEISd()`	Compute the prevalence of infection by RDT
`F_ni(<SEISd>)`	Compute the NI
`xds_plot_X(<SEISd>)`	Plot the density of infected individuals for the SEISd model
`add_lines_X_SEISd()`	Add lines for the density of infected individuals for the SEISd model
SIP Specialized methods for the SIP (Susceptible-Infected-Prophylaxis) model of human dynamics.
`dXdt(<SIP>)`	Derivatives for the `SIP` Module (X Component)
`Update_Xt(<SIP>)`	Derivatives for human population
`setup_Xpar(<SIP>)`	Setup `Xpar` for an `SIP`
`make_Xpar_SIP()`	Make parameters for SIP human model, with defaults
`xde_steady_state_X(<SIP>)`	Compute the steady states for the SIP model as a function of the daily foi
`dts_steady_state_X(<SIP>)`	Compute the steady states for the dts SIP model as a function of the daily EIR
`setup_Xinits(<SIP>)`	Setup Xinits.SIP
`make_Xinits_SIP()`	Make initial values for the SIP human model, with defaults
`setup_Xix(<SIP>)`	Add indices for human population to parameter list
`list_Xvars(<SIP>)`	Return the variables as a list
`get_Xpars(<SIP>)`	Return the parameters as a list
`set_Xpars(<SIP>)`	Return the parameters as a list
`F_X(<SIP>)`	Size of effective infectious human population
`F_H(<SIP>)`	Size of effective infectious human population
`F_b(<SIP>)`	Infection blocking pre-erythrocytic immunity
`parse_Xorbits(<SIP>)`	Parse the output of deSolve and return variables for the SIP model
`get_Xinits(<SIP>)`	Return initial values as a vector
`set_Xinits(<SIP>)`	Return the parameters as a list
`update_Xinits(<SIP>)`	Update inits for the SIP human model from a vector of states
`HTC(<SIP>)`	Compute the HTC for the SIP model
`F_prevalence(<SIP>)`	Compute the "true" prevalence of infection / parasite rate
`F_pfpr_by_lm(<SIP>)`	Compute the prevalence of infection by light microscopy
`F_pfpr_by_rdt(<SIP>)`	Compute the prevalence of infection by RDT
`F_pfpr_by_pcr(<SIP>)`	Compute the prevalence of infection by pcr
`F_ni(<SIP>)`	Compute the "true" prevalence of infection / parasite rate
`xds_plot_X(<SIP>)`	Plot the density of infected individuals for the SIP model
`add_lines_X_SIP()`	Add lines for the density of infected individuals for the SIP model
SIPd Specialized methods for the SIPd (Susceptible-Infected-Prophylaxis) model of human dynamics.
`dXdt(<SIPd>)`	\(\cal X\) Component Derivatives for the `SIPd` Model
`Update_Xt(<SIPd>)`	Derivatives for human population
`setup_Xpar(<SIPd>)`	Setup `Xpar` for an `SIPd`
`make_Xpar_SIPd()`	Make parameters for SIPd human model, with defaults
`xde_steady_state_X(<SIPd>)`	Compute the steady states for the SIPd model as a function of the daily foi
`dts_steady_state_X(<SIPd>)`	Compute the steady states for the dts SIPd model as a function of the daily EIR
`setup_Xinits(<SIPd>)`	Setup Xinits.SIPd
`make_Xinits_SIPd()`	Make initial values for the SIPd human model, with defaults
`setup_Xix(<SIPd>)`	Add indices for human population to parameter list
`list_Xvars(<SIPd>)`	Return the variables as a list
`get_Xpars(<SIPd>)`	Return the parameters as a list
`set_Xpars(<SIPd>)`	Return the parameters as a list
`F_X(<SIPd>)`	Size of effective infectious human population
`F_H(<SIPd>)`	Size of effective infectious human population
`F_b(<SIPd>)`	Infection blocking pre-erythrocytic immunity
`parse_Xorbits(<SIPd>)`	Parse the output of deSolve and return variables for the SIPd model
`get_Xinits(<SIPd>)`	Return initial values as a vector
`set_Xinits(<SIPd>)`	Return the parameters as a list
`update_Xinits(<SIPd>)`	Update inits for the SIPd human model from a vector of states
`HTC(<SIPd>)`	Compute the HTC for the SIPd model
`F_prevalence(<SIPd>)`	Compute the "true" prevalence of infection / parasite rate
`F_pfpr_by_lm(<SIPd>)`	Compute the prevalence of infection by light microscopy
`F_pfpr_by_rdt(<SIPd>)`	Compute the prevalence of infection by RDT
`F_pfpr_by_pcr(<SIPd>)`	Compute the prevalence of infection by pcr
`F_ni(<SIPd>)`	Compute the "true" prevalence of infection / parasite rate
`xds_plot_X(<SIPd>)`	Plot the density of infected individuals for the SIPd model
`add_lines_X_SIPd()`	Add lines for the density of infected individuals for the SIPd model
The SIPmav3 model
`dXdt(<SIPmav3>)`	Derivatives for human population
`setup_Xpar(<SIPmav3>)`	Setup the Xpar for the SIPmav3_xde model
`make_Xpar_SIPmav3()`	Make parameters for SIPmav3_xde human model, with defaults
`F_X(<SIPmav3>)`	Compute Infectious Density, \(X\), for `SIPmav3`
`F_H(<SIPmav3>)`	Size of effective infectious human population
`F_prevalence(<SIPmav3>)`	Compute the "true" prevalence of infection / parasite rate
`F_b(<SIPmav3>)`	Infection blocking pre-erythrocytic immunity
`setup_Xinits(<SIPmav3>)`	Setup Xinits.SIPmav3
`make_Xinits_SIPmav3()`	Make initial values for a SIPmav3 human model, with defaults
`list_Xvars(<SIPmav3>)`	Return the SIPmav3 model variables as a list
`setup_Xix(<SIPmav3>)`	Add indices for human population to parameter list
`parse_Xorbits(<SIPmav3>)`	Parse the output of deSolve and return variables for SIPmav3 models
`get_Xinits(<SIPmav3>)`	Return initial values as a vector from a SIPmav3 model
`update_Xinits(<SIPmav3>)`	Update inits for SIPmav3 models from a vector of states
`HTC(<SIPmav3>)`	Compute the HTC for the SIPmav3_xde model
`xds_plot_X(<SIPmav3>)`	Plot the density of infected individuals for the SIPmav3 model
`xds_lines_X_SIPmav3()`	Add lines for the density of infected individuals for the SIP model
`xde_steady_state_X(<SIPmav3>)`	Compute the steady states for the SIP model as a function of the daily foi
New SIPmav3 model
`F_clear()`	Natural Parasite Clearance
`F_clear(<r>)`	Natural Parasite Clearance
`F_detect_mav()`	Infection blocking pre-erythrocytic immunity
`F_detect_vars()`	Set up a model for detection
`F_detect_vars(<d>)`	Infection blocking pre-erythrocytic immunity
`F_detect_vars(<mav>)`	Infection blocking pre-erythrocytic immunity
`F_detect_y()`	Set up a model for detection
`F_detect_y(<d>)`	Infection blocking pre-erythrocytic immunity
`F_detect_y(<mav>)`	Infection blocking pre-erythrocytic immunity
`F_force_malaria()`	Mass Treatment
`F_force_malaria(<func>)`	Mass Treatment
`F_force_malaria(<val>)`	Mass Treatment
`F_incidence_h()`	Malaria Incidence from Exposure
`F_incidence_h(<p>)`	Malaria from Exposure
`F_incidence_h(<protect>)`	Malaria Incidents, per infection
`F_incidence_x()`	Malaria Incidence from Infection
`F_incidence_x(<protect>)`	Malaria Incidents, per infection
`F_incidence_x(<rate>)`	Basic model for
`setup_incidence_x(<rate>)`	Setup Malaria from Infection, Basic
`setup_incidence_x_protect()`	Setup an `F_incidence_h.protect` model object
`F_infect_im()`	Infections per Infectious Bite
`F_infect_vars()`	Infections per Infectious Bite
`F_infect_vars(<b>)`	Infections per Infectious Bite
`F_infect_vars(<im>)`	Infections per Infectious Bite
`F_infect_y()`	Infections per Infectious Bite
`F_infect_y(<b>)`	Infections per Infectious Bite
`F_infect_y(<im>)`	Infections per Infectious Bite
`F_pfpr_by_lm(<SIPmav3>)`	Compute PR by light microscopy
`F_pfpr_by_pcr(<SIPmav3>)`	Compute PR by PCR
`F_pfpr_by_rdt(<SIPmav3>)`	Compute PR by RDT
`F_take_drugs()`	Mass Treatment
`F_take_drugs(<func>)`	Mass Treatment
`F_transmit_dim()`	A model for detection
`F_transmit_vars()`	Compute Infectiousness with Named Variables
`F_transmit_vars(<c>)`	Infectiousness, basic
`F_transmit_vars(<dim>)`	A model for detection
`F_transmit_y()`	Compute Infectiousness from the State Variables
`F_transmit_y(<c>)`	Infectiousness, basic
`F_transmit_y(<dim>)`	A model for detection
`F_treat()`	Treat and Cure
`F_treat(<p>)`	Basic Treat and Cure
`F_treat(<p3>)`	Basic Treat and Cure
`setup_F_clear()`	Setup an `F_clear` model object
`setup_F_clear(<r>)`	Set up default F_clear
`setup_F_detect()`	Set up default detect
`setup_F_detect(<d>)`	Set up a basic model for detection
`setup_F_detect(<mav>)`	Set up a basic model for detection
`setup_F_infect()`	Setup an `F_infect` model object
`setup_F_infect(<b>)`	Setup an `F_infect.b` model object
`setup_F_infect(<im>)`	Setup an `F_infect.b` model object
`setup_incidence_x()`	Setup Malaria from Infection
`setup_incidence_x(<protect>)`	Setup an `F_incidence_x.protect` model object
`setup_F_infect_im()`	Setup an `F_infect.b` model object
`setup_F_transmit()`	Setup Infectiousness
`setup_F_transmit(<c>)`	Set up default F_transmit
`setup_F_transmit(<dim>)`	Setup an `F_transmit.dim` model object
`setup_F_transmit_dim()`	Setup an `F_transmit.dim` model object
`setup_F_treat()`	Set up F_treat
`setup_F_treat(<p>)`	Set up a basic F_treat
`setup_F_treat(<p3>)`	Set up a basic F_treat
`setup_drug_taking_function()`	Make a function to simulate mass treatment
`setup_force_malaria()`	Make a function to simulate mass treatment
`setup_force_malaria(<func>)`	Make a function to simulate mass treatment
`setup_force_malaria(<val>)`	Make a function to simulate mass treatment
`setup_force_malaria_func()`	Make a function to simulate mass treatment
`setup_force_malaria_val()`	Make a function to simulate mass treatment
`setup_incidence_h()`	Setup Incidence from Exposure
`setup_incidence_h(<p>)`	Setup Malaria from Exposure, Basic
`setup_incidence_h(<protect>)`	Setup an `F_incidence_h.protect` model object
`setup_incidence_h_protect()`	Setup an `F_incidence_h.protect` model object

Reference

MYZ - Adult Mosquito

The Adult Mosquito RMG Model

The Adult Mosquito SBRQ Model

ENBRQ_dts

The SEI compartment model

bionomics

L-Aquatic Mosquito

stages_dts

X-Vertebrate Hosts

The Garki model

XH Component

The workhorse model

The SIR model

The SIRS Model

The SEIR model

The SEIRV model

SEIS

SEISd

SIP

SIPd

The SIPmav3 model

New SIPmav3 model