Sets the epidemic parameters for stochastic network models
simulated with netsim.
param.net(
inf.prob,
inter.eff,
inter.start,
act.rate,
rec.rate,
a.rate,
ds.rate,
di.rate,
dr.rate,
inf.prob.m2,
rec.rate.m2,
a.rate.m2,
ds.rate.m2,
di.rate.m2,
dr.rate.m2,
...
)Probability of infection per transmissible act between a susceptible and an infected person. In bipartite models, this is the probability of infection to the mode 1 nodes. This may also be a vector of probabilities, with each element corresponding to the probability in that time step of infection (see Time-Varying Parameters below).
Efficacy of an intervention which affects the per-act probability of infection. Efficacy is defined as 1 - the relative hazard of infection given exposure to the intervention, compared to no exposure.
Time step at which the intervention starts, between 1 and
the number of time steps specified in the model. This will default to
1 if the inter.eff is defined but this parameter is not.
Average number of transmissible acts per partnership
per unit time (see act.rate Parameter below). This may also be a vector
of rates, with each element corresponding to the rate in in that time
step of infection (see Time-Varying Parameters below).
Average rate of recovery with immunity (in SIR models)
or re-susceptibility (in SIS models). The recovery rate is the
reciprocal of the disease duration. For bipartite models, this is the
recovery rate for mode 1 persons only. This parameter is only used for
SIR and SIS models. This may also be a vector
of rates, with each element corresponding to the rate in that time step
of infection (see Time-Varying Parameters below).
Arrival or entry rate. For one-mode models, the arrival rate is the
rate of new arrivals per person per unit time. For bipartite models, the
arrival rate may be parameterized as a rate per mode 1 person time (with
mode 1 persons representing females), and with the a.rate.g2
rate set as described below.
Departure or exit rate for susceptible. For bipartite models, it is the rate for the mode 1 susceptible only.
Departure or exit rate for infected. For bipartite models, it is the rate for the mode 1 infected only.
Departure or exit rate for recovered. For bipartite models, it is
the rate for the mode 1 recovered only. This parameter is only used for
SIR models.
Probability of transmission given a transmissible act between a susceptible mode 2 person and an infected mode 1 person. It is the probability of transmission to mode 2 members.
Average rate of recovery with immunity (in SIR models)
or re-susceptibility (in SIS models) for mode 2 persons. This
parameter is only used for bipartite SIR and SIS models.
Arrival or entry rate for mode 2. This may either be specified
numerically as the rate of new arrivals per mode 2 persons per unit time,
or as NA in which case the mode 1 rate, a.rate, governs
the mode 2 rate. The latter is used when, for example, the first mode
is conceptualized as female, and the female population size determines
the arrival rate. Such arrivalss are evenly allocated between the two modes.
Departure or exit rate for mode 2 susceptible.
Departure or exit rate for mode 2 infected.
Departure or exit rate for mode 2 recovered. This parameter is
only used for SIR model types.
Additional arguments passed to model.
A key difference between these network models and DCM/ICM classes is the
treatment of transmission events. With DCM and ICM, contacts or partnerships are
mathematically instantaneous events: they have no duration in time, and thus
no changes may occur within them over time. In contrast, network models allow
for partnership durations defined by the dynamic network model, summarized in
the model dissolution coefficients calculated in dissolution_coefs.
Therefore, the act.rate parameter has a different interpretation here,
where it is the number of transmissible acts per partnership per unit
time.
The inf.prob, act.rate, rec.rate arguments (and their
.m2 companions) may be specified as time-varying parameters by passing
in a vector of probabilities or rates, respectively. The value in each
position on the vector then corresponds to the probability or rate at that
discrete time step for the infected partner. For example, an inf.prob
of c(0.5, 0.5, 0.1) would simulate a 0.5 transmission probability for
the first two time steps of a person's infection, followed by a 0.1 for the
third time step. If the infected person has not recovered or exited the
population by the fourth time step, the third element in the vector will carry
forward until one of those events occurs or the simulation ends. For further examples,
see the NME tutorial,
Time-Varying Biology & Behavior.
To build original models outside of the base models, new process modules
may be constructed to replace the existing modules or to supplement the existing
set. These are passed into the control settings in control.net.
New modules may use either the existing model parameters named here, an
original set of parameters, or a combination of both. The ... allows
the user to pass an arbitrary set of original model parameters into
param.net. Whereas there are strict checks with default modules for
parameter validity, these checks are the user's responsibility with new modules.
param.net sets the epidemic parameters for the stochastic network
models simulated with the netsim function. Models
may use the base types, for which these parameters are used, or new process
modules which may use these parameters (but not necessarily). A detailed
description of network model parameterization for base models is found in
the Basic Network Models
tutorial.
For base models, the model specification will be chosen as a result of
the model parameters entered here and the control settings in
control.net. One-mode and two-mode models are available, where
the the latter assumes a heterogenous mixing between two distinct partitions
in the population (e.g., men and women). Specifying any bipartite parameters
(those with a .m2) implies the simulation of a bipartite model. All the
parameters for a desired model type must be specified, even if they are zero.
Use init.net to specify the initial conditions and
control.net to specify the control settings. Run the
parameterized model with netsim.