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Parameters
parameter: days
default value: 240
type: INT
definition:
The number of days in a single simulation run. FRED runs for the given
number of days regardless of the epidemic state (that is, FRED does not
stop early if no one is currently infected.)
parameter: start_date
default value: 2012-01-02
type: STRING
definition:
The value used as the start date for each simulation run. The format is
YYYY-MM-DD.
parameter: seed
default value: 123456
type: INT
definition:
The seed for the random number generator. The seed values for all runs
of the simulation are based on the initial seed and the run number, and
are independent of the number of random numbers generated in other runs.
The user should not normally have to change the seed value.
parameter: verbose
default value: 1
type: INT
definition:
If set, print information for monitoring system progress to the LOG
file. Higher values produce more (probably too much) output.
parameter: debug
default value: 0
type: INT
definition:
If set, print verbose debugging output to stdout. Higher values produce
more output.
parameter: outdir
default value: OUT
type: STRING
definition:
The directory containing the output files. If the string beings with "/"
it is interpreted as an absolute path. If it begins with "$FRED_HOME/",
it is relative the ${FRED_HOME} directory. Otherwise, it is relative to
the current working directory.
parameter: quality_control
default value: 1
type: INT
definition:
If set, information about the size and age distribution for the various
types of places is printed out in the Log file.
parameter: report_age_of_infection
default value: 0
type: INT
definition:
If set, the output file includes info on daily incidence by age groups. You get
different info depending on the value of the parameter.
report_age_of_infection = 1
The output includes variables giving the daily incidence counts for the
following age groups (not including the upper bounds):
Infants: 0.0 - 0.5 yrs
Toddlers: 0.5 - 2.0
Pre_School: 2 - 6
Elementary 6 - 12
High_School: 12 - 18
Young_Adults: 18 - 21
Adults: 21 - 65
Elderly: 65 - 120
report_age_of_infection = 2
A slightly different set of age groups:
Infants: 0.0 - 1.5 yrs
Toddlers: 1.5 - 2.0
Pre_School: 2 - 5
Elementary 5 - 12
High_School: 12 - 18
Young_Adults: 18 - 21
Adults: 21 - 65
Elderly: 65 - 120
report_age_of_infection = 3
The output will include variables
A0, A1, ..., A120
which give the daily counts for new infections in people in each yearly
age group, and also variables
Age0, Age1, ... Age120
which give the daily counts per 100,000 people in each yearly age group.
parameter: report_place_of_infection
default value: 0
type: INT
definition:
If set to 1, the output file contains the daily incidence count by place
of infection, including the following:
X: number of people externally infected (seeds).
H: number of people infected in households.
Nbr: number of people infected in neighborhoods.
Sch: number of people infected in schools.
Cls: number of people infected in classrooms.
Wrk: number of people infected in workplaces.
Off: number of people infected in offices.
Hosp: number of people infected in hospitals.
parameter: report_generation time
default value: 0
type: INT
definition:
If set to 1, the output file contains the mean generation time for all
infections occurring on the given day. The generation time (or serial
interval) is defined as the number of days between the infection of the
infector and the current infectee.
The output variable for gneration time is "Tg".
parameter: report_serial_interval
default value: 0
type: INT
definition:
If set to 1, the output file contains the mean generation time for all
infections occurring on the given day. The generation time (or serial
interval) is defined as the number of days between the infection of the
infector and the current infectee.
The output variable for gneration time is "Tg".
parameter: report_incidence_by_county
default value: 0
type: INT
definition:
If set, the output file contains a daily report of incidence based on
the household of each infected person. The output variable is
"County_NNNNN", where NNNNN is the five digit FIPS code for the county.
For example, County_42003 for the incidence of Allegheny County, PA.
parameter: track_infection_events
default value: 0
type: INT
definition:
If set, then a file called infections<n>.txt is created for run <n>.
This file contains one line per disease transmission event, showing the
id of the infector, the infectee, and various other information. The
format for the infections file is:
DAY DISEASE_ID HOST_ID HOST_AGE INFECTOR_ID INFECTOR_AGE PLACE_ID
If track_infection_events > 1, additional data is written on each line.
For further details, see: Infection.cc.
The following parameters select the location that FRED simulates.
parameter: synthetic_population_id
default value: 2010_ver1_42003
type: STRING
definition:
The synthetic_population_id parameter is the default determinant of the
population files used in FRED. The default value corresponds to
Allegheny County Population (RTI 2010 Synthetic Population, Ver 1).
For convenience, the parameters "fips", "city", "county", and "state",
if set, will override the default, in that order of precedence. That
is, a specified FIPS code overrides a city name, which overrides county
and so on. In all cases, the name is ultimately transformed into a FIPS
code.
parameter: fips
default value: none
type: STRING
definition:
If set, has highest precedence and overrides city, state and county. See
explanation below. The synthetic_population_id parameter is the default
determinant of the population files used in FRED. The parameters
"fips", "city", "county", and "state", if set, will override the
default, in that order of precedence. That is, a FIPS code overrides a
city name, which overrides county and so on. In all cases, the name is
ultimately transformed into a FIPS code.
Example:
fips = 42003
**For a complete list of recognized fips codes, see the file
FRED/input_files/countries/usa/fips_county_state.txt
parameter: city
default value: none
type: STRING
definition:
If set, overrides state and county. Format is "name state_abbreviation".
The synthetic_population_id parameter is the default determinant of the
population files used in FRED. The parameters "fips", "city", "county",
and "state", if set, will override the default, in that order of
precedence. That is, a FIPS code overrides a city name, which overrides
county and so on. In all cases, the name is ultimately transformed into
a FIPS code.
Example:
city = Pittsburgh PA
parameter: county
default value: none
type: STRING
definition:
If set, overrides state. Format is "name state_abbreviation". The
synthetic_population_id parameter is the default determinant of the
population files used in FRED. The parameters "fips", "city", "county",
and "state", if set, will override the default, in that order of
precedence. That is, a FIPS code overrides a city name, which overrides
county and so on. In all cases, the name is ultimately transformed into
a FIPS code.
Example:
county = Allegheny County, PA
parameter: state
default value: none
type: STRING
**
definition:**
The state format can be the state name or abbreviation, such as:
state = New York
or
state = NY
Each new disease requires a set of required parameters to describe the disease. There are also optional parameters that enable various features in FRED.
The parameters below include the default parameters for influenza. To
define another disease, substitue the other disease name for
influenza.
We first list the required parameters:
parameter: disease_names
default value: 1 influenza
type: VECTOR
definition:
The list of diseases to be included in the current FRED simulation. The
first value indicates the number of diseases. This is followed by the
list of disease names.
Natural History Parameters
The Natural History parameters describe the distributions for the infectious and symtomatic periods, as well as the case fatality rates and other disease descriptors.
parameter: influenza_natural_history_model
default value: basic
type: STRING
definition:
The basic natural history model includes an incubation period and a
symptomatic period. The infectious period is assumed to be the same as
the symptomatic period.
Note: individuals can still be asymptomatic and infectious, as described
below.
parameter: influenza_days_latent
default value: None
type: vector CDF
definition:
The distribution of latency duration, expressed as a cumulative
distribution function (CDF). The first value is the size of the CDF and
the remaining values are the cumulative probability for each day,
starting with day 0.
Example:
influenza_days_latent = 3 0.0 0.8 1.0
This specifies that 80% of infected individuals will have an incubation
period of 1 day, and 20% will have an incubation of 2 days.
parameter: influenza_days_infectious
default value: None
type: vector CDF
definition:
The distribution of the duration of infectiousness, expressed as a
cumulative distribution function (CDF). The first value is the size of
the CDF and the remaining values are the cumulative probability for each
day, starting with day 0.
Example:
influenza_days_infectious = 7 0.0 0.0 0.0 0.3 0.7 0.9 1.0
This specifies that 30% of infected individuals will be infectious for 3
days, 40% will be infectious for 4 days, 20% will be infectious for 5
days, and 10% will be infectious for 6 days.
parameter: influenza_probability_of_symptoms
default value: 0.67
type: REAL
definition:
The probability that an infected person will develop symptoms.
Note: even if a person does not develop symptoms, they may still be
infectious, using the same infectious period distribution as symptomatic
people.
Example:
influenza_probability_of_symptoms = 0.67
This means that 67% of individual infected will develop symptoms.
parameter: influenza_prob_symptoms_age_groups
default value: 0
type: Vector of real values
definition:
The probability that an infected person of a given age group will
develop symptoms. If this is set, it overrides the single values
probability_of_symptoms parameter above.
parameter: influenza_prob_symptoms_values
default value: 0
type: Vector of real values
definition:
The probabilities associated with the influenza_prob_symptoms_age_groups.
Example:
influenza_prob_symptoms_age_group = 2 10 120
influenza_prob_symptoms_values = 2 0.9 0.5
This means that people between 0 and 10 years of age have a 90% chance
of developing symptoms, and people between 10 and 120 years of age have
a 50% chance of developing symptoms. (These values are for illustration
purposes only.)
Transmission Parameters
parameter: influenza_transmission_mode
default value: respiratory
type: STRING
definition:
FRED defaults to respiratory person-to-person transmission. Vector
transmission and sexual transmission modes are under dfevelopment, but
current considered experimental.
parameter: influenza_transmissibility
default value: 1
type: REAL
definition:
This is a coefficient that modulates the transmissibility of a
disease. Higher values correspond to higher values for R0.
parameter: influenza_asymp_infectivity
default value: 0.5
type: REAL
definition:
The relative infectivity of an asymptomatic person, compared to a
symptomatic person.
Immunity Parameters
parameter: influenza_residual_immunity_age_groups
default value: 0
type: Vector of real values
definition:
The age groups that may have different prior immunity.
parameter: influenza_residual_immunity_values
default value: 0
type: Vector of real values
definition:
The probability that a person of a given age group will have residual
(prior) immunity.
Example:
influenza_residual_immunity_age_groups = 2 20 120
influenza_residual_immunity_value = 2 0.5 0.1
This means that people between o and 20 years old have a 50% chance of
prior immunity, and those between 20 and 120 years have a 10% chance of
prior immunity.
parameter: influenza_infection_immunity_age_groups
default value: 1 120
type: Vector of real values
definition:
The age groups that may have different probability of immunity as the
result of infection.
parameter: influenza_infection_immunity_values
default value: 1 1.0
type: Vector of real values
definition:
The probability that a person of given age group will have immunity as
the result of infection.
parameter: influenza_immunity_loss_rate
default value: 0
type: REAL
definition:
The rate at which immunity wanes. A value of 0 means permanent
immunity after infection.
Optional Features
influenza_infectivity_threshold = 0.0
influenza_symptomaticity_threshold = 0.0
influenza_evolution = 0
influenza_enable_case_fatality = 0
© 2012-2015 [Public Health Dynamics Laboratory] (http://www.phdl.pitt.edu "PHDL website"), University of Pittsburgh