Demographics parameters#
The parameters described in this reference section can be added to the JSON (JavaScript Object Notation) formatted demographics file to determine the demographics of the population within each geographic node in a simulation. For example, the number of individuals and the distribution for age, gender, immunity, risk, and mortality. These parameters work closely with the Population dynamics parameters in the configuration file, which are simulation-wide and generally control whether certain events, such as births or deaths, are enabled in a simulation.
Generally, you will download a demographics file and modify it to meet the needs of your simulation. Demographics files for several locations are available on the Institute for Disease Modeling (IDM) GitHub EMOD-InputData repository or you can use COmputational Modeling Platform Service (COMPS) to generate demographics and climate files for a particular region. By convention, these are named using the name of the region appended with “_demographics.json”, but you may name the file anything you like.
Additionally, you can use more than one demographics file, with one serving as the base layer and the one or more others acting as overlays that override the values in the base layer. This can be helpful if you want to experiment with different values in the overlay without modifying your base file. For more information, see Demographics file.
At least one demographics file is required for every simulation unless you set the parameter Enable_Demographics_Builtin to 1 (one) in the configuration file. This setting does not represent a real location and is generally only used for testing and validating code pathways rather than actual modeling of disease.
Demographics files are organized into four main sections: Metadata, NodeProperties, Defaults, and Nodes. The following example shows the skeletal format of a demographics file.
{
"Metadata": {
"DateCreated": "dateTime",
"Tool": "scriptUsedToGenerate",
"Author": "author",
"IdReference": "Gridded world grump2.5arcmin",
"NodeCount": 2
},
"NodeProperties": [
{}
],
"Defaults": {
"NodeAttributes": {},
"IndividualAttributes": {},
"IndividualProperties": {},
},
"Nodes": [{
"NodeID": 1,
"NodeAttributes": {},
"IndividualAttributes": {},
"IndividualProperties": {},
}, {
"NodeID": 2,
"NodeAttributes": {},
"IndividualAttributes": {},
"IndividualProperties": {},
}]
}
All parameters except those in the Metadata and NodeProperties sections below can appear in either the Defaults section or the Nodes section of the demographics file. Parameters under Defaults will be applied to all nodes in the simulation. Parameters under Nodes will be applied to specific nodes, overriding the values in Defaults if they appear in both. Each node in the Nodes section is identified using a unique NodeID.
The tables below contain only parameters available when using the HIV simulation type.
Note
Parameters are case-sensitive. For Boolean parameters, set to 1 for true or 0 for false. Minimum, maximum, or default values of “NA” indicate that those values are not applicable for that parameter.
EMOD does not use true defaults; that is, if the dependency relationships indicate that a parameter is required, you must supply a value for it. However, many of the tools used to work with EMOD will use the default values provided below.
JSON format does not permit comments, but you can add “dummy” parameters to add contextual information to your files. Any keys that are not EMOD parameter names will be ignored by the model.
Metadata#
Metadata provides information about data provenance. IdReference is the only parameter used by EMOD, but you are encouraged to include information for your own reference. For example, author, date created, tool used, NodeCount and more are commonly included in the Metadata section. You can include any information you like here provided it is in valid JSON format. IDReference is used to connect the files together; the climate, migration, and demographics files all have IdReference so that there is some way to know that they go together (i.e. know about the same nodes).
If you generate input files using COMPS, the following IdReference values are possible and indicate how the NodeID values are generated:
- Gridded world grump30arcsec
Nodes are approximately square regions defined by a 30-arc second grid and the NodeID values are generated from the latitude and longitude of the northwest corner.
- Gridded world grump2.5arcmin
Nodes are approximately square regions defined by a 2.5-arc minute grid and the NodeID values are generated from the latitude and longitude of the northwest corner.
- Gridded world grump1degree
Nodes are approximately square regions defined by a 1-degree grid and the NodeID values are generated from the latitude and longitude of the northwest corner.
The algorithm for encoding latitude and longitude into a NodeID is as follows:
unsigned int xpix = math.floor((lon + 180.0) / resolution)
unsigned int ypix = math.floor((lat + 90.0) / resolution)
unsigned int NodeID = (xpix << 16) + ypix + 1
This generates a NodeID that is a 4-byte unsigned integer; the first two bytes represent the longitude of the node and the second two bytes represent the latitude. To reserve 0 to be used as a null value, 1 is added to the NodeID as part of the final calculation.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Author |
string |
NA |
NA |
NA |
The person who created the demographics file. Files generated by COMPS will include this value, but it is not used by EMOD simulations. |
{
"Metadata": {
"DateCreated": "Sun Sep 25 23:19:55 2011",
"Tool": "convertdemog.py",
"Author": "jdoe",
"IdReference": "Gridded world grump2.5arcmin",
"NodeCount": 1
}
}
|
DateCreated |
string |
NA |
NA |
NA |
The date the demographics file was created. Files generated by COMPS will include this value, but it is not used by EMOD simulations. |
{
"Metadata": {
"DateCreated": "09212017",
"IdReference": "Gridded world grump2.5arcmin",
"NodeCount": 23
}
}
|
IdReference |
string |
NA |
NA |
NA |
The identifier for a simulation; all input files (except configuration and campaign files) used in a simulation must have the same IdReference value. The value must be greater than 0. If the input files are generated using COMPS, this indicates the method used for generating the NodeID, the identifier used for each node in the simulation. |
{
"Metadata": {
"IdReference": "Gridded world grump30arcsec"
}
}
|
Metadata |
json object |
NA |
NA |
NA |
The structure that contains the metadata for the demographics file. |
{
"Metadata": {
"IdReference": "Gridded world grump30arcsec",
"NodeCount": 20
}
}
|
NodeCount |
integer |
1 |
Depends on available memory |
NA |
The number of nodes to expect in the input files. This parameter is required. |
{
"Metadata": {
"NodeCount": 2
}
}
|
Resolution |
integer |
NA |
NA |
NA |
The spatial resolution of the demographics file. Files generated by COMPS will include this value, but it is not used by EMOD simulations. |
{
"Metadata": {
"Resolution": 150
}
}
|
Tool |
string |
NA |
NA |
NA |
The software tool used to create the demographics file. Files generated by COMPS will include this value, but it is not used by EMOD simulations. |
{
"Metadata": {
"Tool": "convertdemog.py",
"Author": "jdoe",
"IdReference": "Gridded world grump2.5arcmin",
"Resolution": 150,
"NodeCount": 1
}
}
|
NodeProperties and IndividualProperties#
Node properties and individual properties are set similarly and share many of the same parameters. Properties can be thought of as tags that are assigned to nodes or individuals and can then be used to either target interventions to nodes or individuals with certain properties (or prevent them from being targeted). For example, you could define individual properties for disease risk and then target an intervention to only those at high risk. Similarly, you could define properties for node accessibility and set lower intervention coverage for nodes that are difficult to access.
Individual properties are also used to simulate health care cascades. For example, you can disqualify an individual who would otherwise receive an intervention; such as treating a segment of the population with a second-line treatment but disqualifying those who haven’t already received the first-line treatment. Then you can change the property value after the treatment has been received.
The NodeProperties section is a top-level section at the same level as Defaults and Nodes that contains parameters that assign properties to nodes in a simulation. The IndividualProperties section is under either Defaults or Nodes and contains parameters that assign properties to individuals in a simulation.
Individual and node properties provides more guidance.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Age_Bin_Edges_In_Years |
array |
NA |
NA |
NA |
An array of integers that represents the ages, in years, at which to demarcate the age groups for individuals. Used only with the Age_Bin property type. The first number must be 0, the last must be -1, and they must be listed in ascending order. Cannot be used with NodeProperties. EMOD automatically create the individual property Age_Bin with values based on the bin edges using the format Age_Bin_Property_From_X_To_Y. These appear in the property reports and can be used to target campaign interventions using Property_Restrictions_Within_Node. See Targeting interventions to nodes or individuals for more information. |
The following example creates three age groups: 0 to 5, older than 5 to 13, and older than 13 to the maximum age. {
"Defaults": {
"IndividualProperties": [
{
"Property": "Age_Bin",
"Age_Bin_Edges_In_Years": [
0,
5,
13,
-1
]
}
]
}
}
|
IndividualProperties |
array of objects |
NA |
NA |
[] |
An array that contains parameters that add properties to individuals in a simulation. For example, you can define values for accessibility, age, geography, risk, and other properties and assign values to different individuals. |
{
"Defaults": {
"IndividualProperties": [
{
"Property": "InterventionStatus",
"Values": [
"None",
"ARTStaging"
],
"Initial_Distribution": [
1,
0
]
},
{
"Property": "Risk",
"Values": [
"High",
"Medium",
"Low"
],
"Initial_Distribution": [
0.2,
0.5,
0.3
]
}
]
}
}
|
Initial_Distribution |
array of floats |
0 |
1 |
1 |
An array of floats that define the proportion of property values to assign to individuals or nodes at the beginning of the simulation and when new individuals are born. Their sum must equal 1 and the number of members in this array must match the number of members in Values. For Age_Bin property types, omit this parameter as the demographics file controls the age distribution. |
{
"NodeProperties": [
{
"Property": "InterventionStatus",
"Values": [
"NONE",
"RECENT_SPRAY"
],
"Initial_Distribution": [
1.0,
0.0
]
}
]
}
{
"Nodes": [
{
"NodeID": 25,
"IndividualProperties": [
{
"Initial_Distribution": [
0.2,
0.4,
0.4
]
}
]
}
]
}
|
NodeProperties |
array of objects |
NA |
NA |
NA |
An array that contains parameters that add properties to nodes in a simulation. Defined in the demographics file at the same level as Nodes and Defaults. For example, you can define values for intervention status, risk, and other properties and assign values to different nodes. |
{
"NodeProperties": [
{
"Property": "Place",
"Values": [
"RURAL",
"URBAN"
],
"Initial_Distribution": [
0.85,
0.15
]
},
{
"Property": "InterventionStatus",
"Values": [
"NONE",
"SPRAYED_A",
"SPRAYED_B",
"FENCE_AND_TRAP"
],
"Initial_Distribution": [
1,
0,
0,
0
]
}
],
"Nodes": [
{
"NodeID": 1,
"NodeAttributes": {
"Latitude": 0,
"Longitude": 0,
"Altitude": 0,
"Airport": 0,
"Region": 1,
"Seaport": 0,
"InitialPopulation": 10000,
"BirthRate": 5.48e-05,
"NodePropertyValues": [
"Place:URBAN"
]
}
}
]
}
|
Property |
enum |
NA |
NA |
NA |
The individual or node property type for which you will assign values to create groups. You can then update the property values assigned to individuals or nodes or target interventions to particular groups. Note that these types, with the exception of Age_Bin, are merely labels that do not affect the simulation unless specified to do so. Possible values are:
|
{
"NodeProperties": [
{
"Property": "InterventionStatus",
"Values": [
"NONE",
"RECENT_SPRAY"
],
"Initial_Distribution": [
1.0,
0.0
]
}
]
}
{
"Defaults": {
"IndividualProperties": [
{
"Property": "Age_Bin",
"Age_Bin_Edges_In_Years": [
0,
6,
10,
20,
-1
]
}
]
}
}
|
Transitions |
array |
NA |
NA |
NA |
An array that contains multiple JSON objects that each define how an individual transitions from one property value to another. See the transitions array table for information about the parameters to include in the Transitions object. For Age_Bin property types, set to an empty array, as individuals will transition to the next age bin based on the passing of time. Cannot be used with NodeProperties. |
{
"Defaults": {
"IndividualProperties": [
{
"Transitions": [
{
"From": "High",
"To": "Medium",
"Type": "At_Age",
"Coverage": 1,
"Probability_Per_Timestep": 0.3,
"Age_In_Years": 5,
"Timesteps_Until_Reversion": 0
},
{
"From": "Medium",
"To": "Low",
"Type": "At_Age",
"Coverage": 1,
"Probability_Per_Timestep": 0.3,
"Age_In_Years": 12,
"Timesteps_Until_Reversion": 0
}
]
}
]
}
}
|
Values |
array of strings |
NA |
NA |
NA |
An array of the user-defined values that can be assigned to individuals or nodes for this property. The order of the values corresponds to the order of the Initial_Distribution array. You can have up to 125 values for the Geographic and InterventionStatus property types and up to 5 values for all other types. For Age_Bin property types, omit this parameter and use Age_Bin_Edges_In_Years instead. |
{
"NodeProperties": [
{
"Property": "InterventionStatus",
"Values": [
"NONE",
"RECENT_SPRAY"
],
"Initial_Distribution": [
1.0,
0.0
]
}
]
}
{
"Defaults": {
"IndividualProperties": [
{
"Values": [
"Low",
"Medium",
"High"
]
}
]
}
}
|
NodeAttributes#
The NodeAttributes section contains parameters that add or modify information regarding the location, migration, habitat, and population of node. Some NodeAttributes depend on values set in the configuration parameters.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Airport |
boolean |
0 |
1 |
0 |
Indicates whether or not the node has an airport for air migration from (not to) the node. If set to 1, Enable_Air_Migration in the configuration file must be set to 1 or migration will not occur (see Migration parameters). Primarily used to turn off migration in a particular node. |
{
"Defaults": {
"NodeAttributes": {
"Airport": 0
}
}
}
|
BirthRate |
double |
0 |
1 |
0.00008715 |
The birth rate, in births per person per day. In the configuration file, Enable_Birth must be set to 1 and Birth_Rate_Dependence will affect how this rate is used (see Population dynamics parameters). |
{
"Nodes": [
{
"NodeID": 21,
"NodeAttributes": {
"BirthRate": 0.0001
}
}
]
}
|
InfectivityReservoirEndTime |
float |
InfectivityReservoirStartTime |
3.40282e+038 |
3.40282e+038 |
The ending of the exogeneous reservoir of infectivity. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1). |
{
"NodeAttributes": {
"InfectivityReservoirSize": 0.1,
"InfectivityReservoirStartTime": 90,
"InfectivityReservoirEndTime": 365
}
}
|
InfectivityReservoirSize |
float |
0 |
3.40282e+038 |
0 |
The quantity-per-timestep added to the total infectivity present in a node; it is equivalent to the expected number of additional infections in a node, per timestep. For example, if timestep is equal to a day, then setting InfectivityReservoirSize to a value of 0.1 would introduce an infection every 10 days from the exogenous reservoir. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1). |
{
"NodeAttributes": {
"InfectivityReservoirSize": 0.1,
"InfectivityReservoirStartTime": 90,
"InfectivityReservoirEndTime": 365
}
}
|
InfectivityReservoirStartTime |
float |
0 |
3.40282e+038 |
0 |
The beginning of the exogeneous reservoir of infectivity. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1). |
{
"NodeAttributes": {
"InfectivityReservoirSize": 0.1,
"InfectivityReservoirStartTime": 90,
"InfectivityReservoirEndTime": 365
}
}
|
InitialPopulation |
integer |
0 |
2147480000 |
1000 |
The number of people that will be populated into the node at the beginning of the simulation. You can scale this number using Base_Population_Scale_Factor in the configuration file (see Population dynamics parameters). |
{
"Nodes": [
{
"NodeID": 25,
"NodeAttributes": {
"InitialPopulation": 1000
}
}
]
}
|
Latitude |
float |
3.40282e+038 |
-3.40282e+038 |
-1 |
Latitude of the node in decimal degrees. This can be used for several things, including determining infectiousness by latitude and defining the size of grid cells. |
{
"Nodes": [
{
"NodeID": 25,
"NodeAttributes": {
"Latitude": 12.4,
"Longitude": 9.35
}
}
]
}
|
Longitude |
float |
-3.40282e+38 |
3.40282e+38 |
-1 |
Longitude of the node in decimal degrees. This can be used for several things, including defining the size of grid cells. |
{
"Nodes": [
{
"NodeID": 254,
"NodeAttributes": {
"Latitude": 25.4,
"Longitude": 9.1
}
}
]
}
|
NodeAttributes |
json object |
NA |
NA |
NA |
The structure that contains parameters that add or modify information regarding the location, migration, habitat, and population of a simulation. Some NodeAttributes depend on values set in the configuration parameters. |
{
"Nodes": [
{
"NodeID": 1487548419,
"NodeAttributes": {
"Latitude": 12.4208,
"Longitude": 9.15417
}
}
]
}
|
Region |
boolean |
0 |
1 |
0 |
Indicates whether or not the node has a road network for regional migration from (not to) the node. If set to 1, Enable_Regional_Migration in the configuration file must be set to 1 or migration will not occur (see Migration parameters). Primarily used to turn off migration in particular nodes. |
{
"Nodes": [
{
"NodeID": 12,
"NodeAttributes": {
"Region": 1
}
}
]
}
|
Seaport |
boolean |
0 |
1 |
0 |
Indicates whether or not the node is connected by sea migration from (not to) the node. If set to 1, Enable_Sea_Migration in the configuration file must be set to 1 or migration will not occur (see Migration parameters). Primarily used to turn off migration in particular nodes. |
{
"Nodes": [
{
"NodeID": 43,
"NodeAttributes": {
"Seaport": 1
}
}
]
}
|
IndividualAttributes#
The IndividualAttributes section contains parameters that initialize the distribution of attributes across individuals, such as the age or immunity. An initial value for an individual is a randomly selected value from a given distribution. These distributions can be configured using a simple flag system of three parameters or a complex system of many more parameters. The following table contains the parameters that can be used with either distribution system.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
IndividualAttributes |
json object |
NA |
NA |
NA |
The structure that contains parameters that add or modify the distribution of attributes across individuals in a simulation. For example, the age or immunity distribution. An initial value for an individual is a randomly selected value from a distribution. For example, if you use a uniform distribution to initialize age, the initial ages of individuals in the simulation will be evenly distributed between some minimum and maximum value. These distributions can be set using Simple distributions or Complex distributions. |
{
"Defaults": {
"IndividualAttributes": {
"AgeDistributionFlag": 0,
"AgeDistribution1": 25550,
"AgeDistribution2": 0
}
}
}
|
PercentageChildren |
float |
0 |
1 |
NA |
The percentage of individuals in the node that are children. Set Minimum_Adult_Age_Years to determine the age at which individuals transition to adults. |
{
"Nodes": {
"NodeID": 45,
"IndividualAttributes": {
"PercentageChildren": 0.7
}
}
}
|
Simple distributions#
Simple distributions are defined by three parameters where one is a flag for the distribution type and the other two are used to further define the distribution. For example, if you set the age flag to a uniform distribution, the initial ages of individuals in the simulation will be evenly distributed between some minimum and maximum value as defined by the other two parameters.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
AgeDistribution1 |
float |
-3.40282e+038 |
3.40282e+038 |
0.000118 |
The first value in the age distribution, the meaning of which depends upon the value set in AgeDistributionFlag. The table below shows the flag value and corresponding distribution value.
Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_SIMPLE (see Population dynamics parameters). |
{
"IndividualAttributes": {
"AgeDistributionFlag": 0,
"AgeDistribution1": 25550,
"AgeDistribution2": 0
}
}
|
||||||||||||||||||
AgeDistribution2 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The second value in the age distribution, the meaning of which depends upon the value set in AgeDistributionFlag. The table below shows the flag value and corresponding distribution value.
Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_SIMPLE (see Population dynamics parameters). |
{
"IndividualAttributes": {
"AgeDistributionFlag": 0,
"AgeDistribution1": 25550,
"AgeDistribution2": 0
}
}
|
||||||||||||||||||
AgeDistributionFlag |
integer |
0 |
7 |
3 |
The type of distribution to use for age. Possible values are:
Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_SIMPLE (see Population dynamics parameters). |
{
"IndividualAttributes": {
"AgeDistributionFlag": 0,
"AgeDistribution1": 25550,
"AgeDistribution2": 0
}
}
|
||||||||||||||||||
MigrationHeterogeneityDistribution1 |
float |
-3.40282e+38 |
3.40282e+38 |
1 |
The first value in the migration heterogeneity distribution, the meaning of which depends upon the value set in MigrationHeterogeneityFlag. The table below shows the flag value and corresponding distribution value.
Enable_Migration_Heterogeneity in the configuration file must be set to 1 (see Migration parameters). |
{
"IndividualAttributes": {
"MigrationHeterogeneityDistributionFlag": 0,
"MigrationHeterogeneityDistribution1": 1,
"MigrationHeterogeneityDistribution2": 0
}
}
|
||||||||||||||||||
MigrationHeterogeneityDistribution2 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The second value in the distribution, the meaning of which depends upon the value set in MigrationHeterogeneityDistributionFlag. The table below shows the flag value and corresponding distribution value.
Enable_Migration_Heterogeneity in the configuration file must be set to 1 (see Migration parameters). |
{
"IndividualAttributes": {
"MigrationHeterogeneityDistributionFlag": 0,
"MigrationHeterogeneityDistribution1": 1,
"MigrationHeterogeneityDistribution2": 0
}
}
|
||||||||||||||||||
MigrationHeterogeneityDistributionFlag |
integer |
0 |
7 |
0 |
The type of distribution to use for migration heterogeneity. Possible values are:
Enable_Migration_Heterogeneity in the configuration file must be set to 1 (see Migration parameters). |
{
"IndividualAttributes": {
"MigrationHeterogeneityDistributionFlag": 0,
"MigrationHeterogeneityDistribution1": 1,
"MigrationHeterogeneityDistribution2": 0
}
}
|
||||||||||||||||||
PrevalenceDistribution1 |
float |
-3.40282e+038 |
3.40282e+038 |
1 |
The first value in the prevalence distribution, the meaning of which depends upon the value set in PrevalenceDistributionFlag. The table below shows the flag value and corresponding distribution value.
|
{
"IndividualAttributes": {
"PrevalenceDistributionFlag": 0,
"PrevalenceDistribution1": 0.0,
"PrevalenceDistribution2": 0.0
}
}
|
||||||||||||||||||
PrevalenceDistribution2 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The second value in the distribution, the meaning of which depends upon the value set in PrevalenceDistributionFlag. The table below shows the flag value and corresponding distribution value.
|
{
"IndividualAttributes": {
"PrevalenceDistributionFlag": 0,
"PrevalenceDistribution1": 0.0,
"PrevalenceDistribution2": 0.0
}
}
|
||||||||||||||||||
PrevalenceDistributionFlag |
integer |
0 |
7 |
0 |
The type of distribution to use for prevalence. Possible values are:
|
{
"IndividualAttributes": {
"PrevalenceDistributionFlag": 0,
"PrevalenceDistribution1": 0.0,
"PrevalenceDistribution2": 0.0
}
}
|
||||||||||||||||||
RiskDistribution1 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The first value in the risk distribution, the meaning of which depends upon the value set in RiskDistributionFlag. The table below shows the flag value and corresponding distribution value.
|
{
"IndividualAttributes": {
"RiskDistributionFlag": 0,
"RiskDistribution1": 1,
"RiskDistribution2": 0
}
}
|
||||||||||||||||||
RiskDistribution2 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The second value in the distribution, the meaning of which depends upon the value set in RiskDistributionFlag. The table below shows the flag value and corresponding distribution value.
|
{
"IndividualAttributes": {
"RiskDistributionFlag": 0,
"RiskDistribution1": 1,
"RiskDistribution2": 0
}
}
|
||||||||||||||||||
RiskDistributionFlag |
integer |
0 |
7 |
0 |
The type of distribution to use for risk. Possible values are:
Enable_Demographics_Risk must be set to 1 (see Population dynamics parameters). |
{
"IndividualAttributes": {
"RiskDistributionFlag": 0,
"RiskDistribution1": 1,
"RiskDistribution2": 0
}
}
|
||||||||||||||||||
SusceptibilityDistribution1 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The first value in the susceptibility distribution, the meaning of which depends upon the value set in SusceptibilityDistributionFlag. The table below shows the flag value and corresponding distribution value.
In the configuration file, Enable_Immunity must be set to 1 and Susceptibility_Initialization_Distribution_Type must be set to DISTRIBUTION_SIMPLE (see Immunity parameters). |
{
"IndividualAttributes": {
"SusceptibilityDistributionFlag": 0,
"SusceptibilityDistribution1": 1,
"SusceptibilityDistribution2": 0
}
}
|
||||||||||||||||||
SusceptibilityDistribution2 |
float |
-3.40282e+038 |
3.40282e+038 |
0 |
The second value in the susceptibility distribution, the meaning of which depends upon the value set in SusceptibilityDistributionFlag. The table below shows the flag value and corresponding distribution value.
In the configuration file, Enable_Immunity must be set to 1 and Susceptibility_Initialization_Distribution_Type must be set to DISTRIBUTION_SIMPLE (see Immunity parameters). |
{
"IndividualAttributes": {
"SusceptibilityDistributionFlag": 0,
"SusceptibilityDistribution1": 1,
"SusceptibilityDistribution2": 0
}
}
|
||||||||||||||||||
SusceptibilityDistributionFlag |
integer |
0 |
7 |
0 |
The type of distribution to use for determining an individual’s probability of full susceptibility. Possible values are:
In the configuration file, Enable_Immunity must be set to 1 and Susceptibility_Initialization_Distribution_Type must be set to DISTRIBUTION_SIMPLE (see Immunity parameters). |
{
"IndividualAttributes": {
"SusceptibilityDistributionFlag": 0,
"SusceptibilityDistribution1": 1,
"SusceptibilityDistribution2": 0
}
}
|
Complex distributions#
Complex distributions are more effort to configure, but are useful for representing real-world data where the distribution does not fit a standard. Individual attribute values are drawn from a piecewise linear distribution. The distribution is configured using arrays of axes (such as gender or age) and values at points along each of these axes. This allows you to have different distributions for different groups in the population.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
AgeDistribution |
json object |
NA |
NA |
NA |
The structure defining a complex age distribution. Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX. |
The following example shows at age distribution in which 25% of individuals are under age 5, 50% are between 5 and 20, and 25% are between 20 and 35. {
"IndividualAttributes": {
"AgeDistribution": {
"ResultUnits": "years",
"ResultScaleFactor": 365,
"ResultValues": [
0,
0.25,
0.75,
1
],
"DistributionValues": [
0,
5,
20,
35
]
}
}
}
|
AxisNames |
array of strings |
NA |
NA |
NA |
An array of the names used for each axis of a complex distribution. The list below shows the axis names to use (in the order given) for each of the distribution types:
|
{
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisUnits": [
"male=0,female=1",
"years"
],
"AxisScaleFactors": [
1,
365
],
"NumPopulationGroups": [
2,
1
],
"PopulationGroups": [
[
0,
1
],
[
0
]
],
"ResultUnits": "annual deaths per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
0
],
[
0
]
]
}
}
}
|
AxisScaleFactors |
array of floats |
3.40282e+038 |
-3.40282e+038 |
1 |
A list of the scale factors used to convert axis units to data measurements in a complex distribution. For example, 365 to convert daily mortality to annual mortality. The array must contain one factor for each axis. |
{
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisUnits": [
"male=0,female=1",
"years"
],
"AxisScaleFactors": [
1,
365
],
"NumPopulationGroups": [
2,
1
],
"PopulationGroups": [
[
0,
1
],
[
0
]
],
"ResultUnits": "annual deaths per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
0
],
[
0
]
]
}
}
}
|
AxisUnits |
array of strings |
NA |
NA |
NA |
An array that describes the scale factors used to convert the units for the axes into the units expected by EMOD. For example, when age is provided in years but must be scaled to days. EMOD does not use this value; it is only informational. |
{
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisUnits": [
"male=0,female=1",
"years"
],
"AxisScaleFactors": [
1,
365
]
}
}
}
|
DistributionValues |
array of floats |
0 |
1 |
1 |
An array of values between 0 and 1 listed in ascending order that defines a complex age distribution. Each value represents the proportion of the population below that age and the difference between two successive values is the proportion of the population in the age bin defined in ResultValues. Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX (see Population dynamics parameters). |
The following example shows at age distribution in which 25% of individuals are under age 5, 50% are between 5 and 20, and 25% are between 20 and 35. {
"IndividualAttributes": {
"AgeDistribution": {
"ResultUnits": "years",
"ResultScaleFactor": 365,
"AxisScaleFactors": 1,
"DistributionValues": [
0,
0.25,
0.75,
1
],
"ResultValues": [
0,
5,
20,
35
]
}
}
}
|
FertilityDistribution |
json object |
NA |
NA |
NA |
The distribution of the fertility rate in the population. Enable_Birth in the configuration file must be set to 1 (see Population dynamics parameters). |
{
"IndividualAttributes": {
"FertilityDistribution": {
"NumDistributionAxes": 2,
"AxisNames": [
"urban",
"XXX"
],
"AxisUnits": [
"rural=0, urban=1",
"years"
],
"AxisScaleFactors": [
1,
365
],
"NumPopulationGroups": [
2,
9
],
"PopulationGroups": [
[
0,
1
],
[
0,
15,
20,
25,
30,
35,
40,
45,
49
]
],
"ResultUnits": "annual births per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
0,
28.4,
190.3,
222.4,
155.4,
68,
21.9,
3.6,
0
],
[
0,
28.4,
190.3,
222.4,
155.4,
68,
21.9,
3.6,
0
]
]
}
}
}
|
ImmunityDistribution |
json object |
NA |
NA |
NA |
The structure defining a complex immunity distribution. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX (see Immunity parameters). |
{
"IndividualAttributes": {
"ImmunityDistribution": {
"AxisNames": [
"age"
],
"AxisUnits": [
"years"
],
"AxisScaleFactors": [
365
],
"NumPopulationGroups": [
1
],
"PopulationGroups": [
[
0
]
],
"ResultScaleFactor": 3.6952,
"ResultValues": [
[
0
]
]
}
}
}
|
MortalityDistribution |
json object |
NA |
NA |
NA |
The distribution of non-disease mortality for a population. Death_Rate_Dependence in the configuration file must be set to NONDISEASE_MORTALITY_BY_AGE_AND_GENDER or NONDISEASE_MORTALITY_BY_YEAR_AND_AGE_FOR_EACH_GENDER (see Mortality and survival parameters). Warning Mortality is sampled every 30 days. To correctly attribute neonatal deaths to days 0-30, you must indicate that the threshold for the first age group in PopulationGroups is less than 30 days. |
{
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisScaleFactors": [
1,
1
],
"NumDistributionAxes": 2,
"NumPopulationGroups": [
2,
4
],
"PopulationGroups": [
[
0,
1
],
[
0.0,
29.99,
365,
1826
]
],
"ResultScaleFactor": 1,
"ResultValues": [
[
0.0016,
0.000107,
6.3e-05,
100.0
],
[
0.0016,
0.000107,
6.3e-05,
100.0
]
]
}
}
}
|
NumDistributionAxes |
integer |
1 |
NA |
NA |
The number of axes to use for a complex distribution. EMOD does not use this value; it is only informational. |
{
"IndividualAttributes": {
"MortalityDistribution": {
"NumDistributionAxes": 2,
"AxisNames": [
"gender",
"age"
],
"AxisScaleFactors": [
1,
365
]
}
}
}
|
NumPopulationGroups |
array of integers |
NA |
NA |
NA |
An array of population groupings for each independent variable for a complex distribution. This variable defines the number of columns for each row in the population group table. The number of values in the array is often two, representing the values for gender and number of age bins. EMOD does not use this value; it is only informational. |
{
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisUnits": [
"male=0,female=1",
"years"
],
"AxisScaleFactors": [
1,
365
],
"NumPopulationGroups": [
2,
1
],
"PopulationGroups": [
[
0,
1
],
[
0
]
],
"ResultUnits": "annual deaths per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
0
],
[
0
]
]
}
}
}
|
PopulationGroups |
matrix of integers |
NA |
NA |
NA |
An array in which each row represents one of the distribution axes and contains the values that the independent variable can take. The values must be listed in ascending order and each defines the left edge of the bin. Warning Mortality is sampled every 30 days. To correctly attribute neonatal deaths to days 0-30, you must indicate that the threshold for the first age group in PopulationGroups is less than 30 days. |
The following example configures relatively high infant mortality and lower mortality at ages 10 and 40, with everyone dead by age 120. {
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisUnits": [
"male=0,female=1",
"years"
],
"AxisScaleFactors": [
1,
365
],
"NumPopulationGroups": [
2,
1
],
"PopulationGroups": [
[
0,
1
],
[
0,
10,
40,
120
]
],
"ResultUnits": "annual deaths per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
51.6,
3.7,
5.3,
1000
],
[
60.1,
4.1,
4.8,
1000
]
]
}
}
}
|
ResultScaleFactor |
float |
-3.40282e+038 |
3.40282e+038 |
1 |
The scale factor used to convert ResultUnits to number of births, deaths, or another variable per individual per day. |
{
"IndividualAttributes": {
"AgeDistribution": {
"AxisScaleFactors": 1,
"DistributionValues": [
0.99,
1.0
],
"ResultScaleFactor": 365,
"ResultUnits": "years",
"ResultValues": [
0.0027,
0.0027
]
}
}
}
|
ResultUnits |
string |
NA |
NA |
NA |
A string that indicates the units used for the ResultValues parameter of a complex distribution. EMOD does not use this value; it is only informational. The values here are scaled by the value in ResultScaleFactor before being passed to EMOD as a daily rate. |
{
"IndividualAttributes": {
"MortalityDistribution": {
"NumPopulationGroups": [
2,
1
],
"PopulationGroups": [
[
0,
1
],
[
0
]
],
"ResultUnits": "annual deaths per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
0
],
[
0
]
]
}
}
}
|
ResultValues |
array of floats |
NA |
NA |
NA |
An array in which each row represents one of the distribution axes and contains the dependent variable values. The units are configurable; the values are scaled by the value in ResultScaleFactor before being passed to EMOD in units of days. For age distributions, it lists in ascending order the ages at which to bin the population. The corresponding values in DistributionValues represent the proportion of the population that is below that age. If the first member of the array is non-zero, the first bin is defined as those with that exact value (EMOD does not assume the bins start at zero). For all other distributions, an array in which each row represents the values for a combination of axes. For example, a mortality distribution that includes both gender and age axes will have a row for males and a row for females that each contain the mortality rate at various ages set in PopulationGroups. |
The following example shows an age distribution in which 10% of individuals are newborn, 25% are under age 5, 50% are between 5 and 20, and 25% are between 20 and 35. {
"IndividualAttributes": {
"AgeDistribution": {
"DistributionValues": [
0.1,
0.25,
0.75,
1
],
"ResultValues": [
0,
5,
20,
35
]
}
}
}
The following example configures relatively high infant mortality and lower mortality at ages 10 and 40, with everyone dead by age 120. {
"IndividualAttributes": {
"MortalityDistribution": {
"AxisNames": [
"gender",
"age"
],
"AxisUnits": [
"male=0,female=1",
"years"
],
"AxisScaleFactors": [
1,
365
],
"NumPopulationGroups": [
2,
1
],
"PopulationGroups": [
[
0,
1
],
[
0,
10,
40,
120
]
],
"ResultUnits": "annual deaths per 1000 individuals",
"ResultScaleFactor": 2.739726027397e-06,
"ResultValues": [
[
51.6,
3.7,
5.3,
1000
],
[
60.1,
4.1,
4.8,
1000
]
]
}
}
}
|
SusceptibilityDistribution |
json object |
NA |
NA |
NA |
The structure defining a complex immunity/susceptibility distribution. Susceptibility_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX (see Immunity parameters). |
{
"IndividualAttributes": {
"SusceptibilityDistribution": {
"AxisNames": [
"age"
],
"AxisScaleFactors": [
365
],
"AxisUnits": [
"years"
],
"NumPopulationGroups": [
1
],
"PopulationGroups": [
[
0
]
],
"ResultScaleFactor": 3.6952,
"ResultValues": [
[
0
]
]
}
}
}
|
Society#
The Society section defines the behavioral-based parameters of a relationship type in the STI and HIV models, such as rates of partnership formation, partner preference, relationship duration, or concurrent partnerships. It must contain the four sets of relationship type parameters and the Concurrency_Configuration section. Note that the name used for each relationship type is only a guide; EMOD does not include specific logic for each type and the settings for each depend only upon the parameters you provide.
The section for each relationship type must include the Relationship_Parameters, Pair_Formation_Parameters, and Concurrency_Parameters sections. These sections define the settings for the specific relationship type they are nested under.
The Concurrency_Configuration section defines how the simultaneous relationship parameters are used across all relationship types.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
COMMERCIAL |
json object |
NA |
NA |
NA |
The structure that defines basic relationship, pair formation, and concurrency parameters for transactional relationships involving commercial sex work (CSW). |
{
"Society": {
"COMMERCIAL": {
"Relationship_Parameters": {
"Condom_Usage_Probability": {
"Min": 0.02,
"Max": 0.65,
"Mid": 2000,
"Rate": 1.5
}
},
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.05
},
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 20,
"Max_Simultaneous_Relationships_Male": 20
}
}
}
}
}
|
Concurrency_Configuration |
json object |
NA |
NA |
NA |
The structure that determines how concurrent relationships are formed, for all relationship types. To apply to all individuals regardless of individual property values, nest parameters under NONE. To apply only to individuals with certain property values, nest parameters under the property value. |
The following example sets extra-relational flags independently to everyone regardless of individual properties. {
"Society": {
"Concurrency_Configuration": {
"Probability_Person_Is_Behavioral_Super_Spreader": 0,
"Individual_Property_Name": "NONE",
"NONE": {
"Extra_Relational_Flag_Type": "Independent"
}
}
}
}
The following example sets different extra-relational flag types to low-risk and high-risk groups. {
"Society": {
"Concurrency_Configuration": {
"Individual_Property_Name": "Risk",
"LOW": {
"Extra_Relational_Flag_Type": "Independent"
},
"HIGH": {
"Extra_Relational_Flag_Type": "Correlated"
}
}
}
}
|
INFORMAL |
json object |
NA |
NA |
NA |
The structure that defines basic relationship, pair formation, and concurrency parameters for longer-term non-marital relationships. |
{
"Society": {
"INFORMAL": {
"Relationship_Parameters": {
"Condom_Usage_Probability": {
"Min": 0.0125,
"Max": 0.45,
"Mid": 2000,
"Rate": 1.5
}
},
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.01
},
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 3
}
}
}
}
}
|
MARITAL |
json object |
NA |
NA |
NA |
The structure that defines basic relationship, pair formation, and concurrency parameters for marital relationships. |
{
"Society": {
"MARITAL": {
"Relationship_Parameters": {
"Condom_Usage_Probability": {
"Min": 0.002,
"Max": 0.05,
"Mid": 2000,
"Rate": 1.5
}
},
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.006
},
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 1,
"Max_Simultaneous_Relationships_Male": 1
}
}
}
}
}
|
Pair_Formation_Parameters |
json object |
NA |
NA |
NA |
Structure that defines all relationship formation parameters for the relationship type specified. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Extra_Relational_Rate_Ratio_Male": 4,
"Extra_Relational_Rate_Ratio_Female": 2
}
}
}
}
|
Society |
json object |
NA |
NA |
NA |
The structure that defines the behavioral-based parameters of a relationship type. Under this structure, include the following and assign JSON objects to each:
|
{
"Society": {
"Concurrency_Configuration": {
"NONE": {
"Extra_Relational_Flag_Type": "Correlated",
"Correlated_Relationship_Type_Order": [
"TRANSITORY",
"INFORMAL",
"MARITAL",
"COMMERCIAL"
]
}
},
"MARITAL": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "INDIVIDUAL_PROPERTY",
"Property_Name": "Risk",
"Axes": [
"LOW",
"HIGH"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.8275185967686474,
0.17248140323135264
],
[
0.17248140323135264,
0.8275185967686474
]
]
}
}
},
"INFORMAL": {},
"TRANSITORY": {},
"COMMERCIAL": {}
}
}
|
TRANSITORY |
json object |
NA |
NA |
NA |
The structure that defines basic relationship, pair formation, and concurrency parameters for brief relationships lasting one night, weekend, or week. |
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Condom_Usage_Probability": {
"Min": 0.0125,
"Max": 0.45,
"Mid": 2000,
"Rate": 1.5
}
},
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.01
},
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 3
}
}
}
}
}
|
Concurrency_Configuration#
The Concurrency_Configuration section is at the same level as each relationship type section and defines how the simultaneous relationship parameters are used across all relationship types. For example, how flags that allow an individual to seek out different types of extra-relational partnerships are distributed.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Correlated_Relationship_Type_Order |
array of strings |
NA |
NA |
NA |
The relationship types listed in order of the correlated probabilities. The array must contain all relationship types and Extra_Relational_Flag_Type must be set to Correlated. |
{
"Society": {
"Concurrency_Configuration": {
"NONE": {
"Extra_Relational_Flag_Type": "Correlated",
"Correlated_Relationship_Type_Order": [
"TRANSITORY",
"INFORMAL",
"MARITAL",
"COMMERCIAL"
]
}
}
}
}
|
Extra_Relational_Flag_Type |
enum |
NA |
NA |
Independent |
The manner in which extra-relational flags are distributed. Individuals cannot seek additional concurrent relationships unless they have a flag for the relationship type they are currently in. Possible values are Correlated or Independent. When independent flags are enabled, all flags are distributed randomly and an individual is unlikely to receive all extra-relational flags. When correlated flags are enabled, flags are distributed for each relationship type in the order listed, with the first flags distributed randomly and each subsequent flag distributed only among individuals who have the prior flag. The probability of receiving a flag is defined in Prob_Extra_Relationship_Male and Prob_Extra_Relationship_Female in Concurrency_Parameters. |
In the following example, the extra-transitory flag is randomly distributed, the extra-informal flag is provided only to those who possess the extra-transitory flag, and so on. {
"Society": {
"Concurrency_Configuration": {
"NONE": {
"Extra_Relational_Flag_Type": "Correlated",
"Correlated_Relationship_Type_Order": [
"TRANSITORY",
"INFORMAL",
"MARITAL",
"COMMERCIAL"
]
}
}
}
}
|
Individual_Property_Name |
string |
NA |
NA |
NA |
The individual property used to create groups of people for configuring relationship concurrency settings. The property name must be defined in the IndividualProperties section. If the concurrency settings do not vary based on individual properties, set to NONE. |
The following example configures different concurrency settings for high and low risk individuals. {
"Society": {
"Concurrency_Configuration": {
"Probability_Person_Is_Behavioral_Super_Spreader": 0,
"Individual_Property_Name": "Risk",
"LOW": {
"Extra_Relational_Flag_Type": "Independent"
},
"HIGH": {
"Extra_Relational_Flag_Type": "Correlated"
}
}
}
}
The following example configures the same concurrency settings for all individuals. {
"Society": {
"Concurrency_Configuration": {
"Individual_Property_Name": "NONE",
"NONE": {
"Max_Simultaneous_Relationships_Female": 4,
"Max_Simultaneous_Relationships_Male": 4,
"Prob_Extra_Relationship_Female": 1,
"Prob_Extra_Relationship_Male": 1
}
}
}
}
|
Probability_Person_Is_Behavioral_Super_Spreader |
float |
0 |
1 |
0.001 |
The probability that an individual is a behavioral super spreader, where they are allowed multiple relationships of all types. |
{
"Social": {
"Concurrency_Configuration": {
"Probability_Person_Is_Behavioral_Super_Spreader": 0.25,
"Individual_Property_Name": "NONE",
"NONE": {
"Extra_Relational_Flag_Type": "Independent"
}
}
}
}
|
Relationship_Parameters#
The Relationship_Parameters section defines basic attributes such as relationship duration, what happens if one member of a relationship migrates, and condom usage.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Coital_Act_Rate |
float |
FLT_EPSILON |
20 |
0.33 |
The probability of a coital act occurring at each time step. |
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Coital_Act_Rate": 1
}
}
}
}
|
Condom_Usage_Probability |
json object |
NA |
NA |
NA |
The structure that determines the probability of condom usage over time in a relationship type. The probability follows a sigmoidal curve, as defined by the following parameters:
|
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Condom_Usage_Probability": {
"Min": 0.0125,
"Max": 0.3,
"Mid": 2001,
"Rate": 1.5
}
}
}
}
}
|
Duration_Weibull_Heterogeneity |
float |
0 |
100 |
1 |
Inverse of the Weibull shape (1/kappa) parameter of relationship duration in years. |
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Duration_Weibull_Heterogeneity": 0.1,
"Duration_Weibull_Scale": 1051025.709
}
}
}
}
|
Duration_Weibull_Scale |
float |
0 |
3.40282e+038 |
1 |
Weibull scale parameter of relationship duration in years. |
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Duration_Weibull_Heterogeneity": 0.1,
"Duration_Weibull_Scale": 1051025.709
}
}
}
}
|
Max |
float |
0 |
1 |
1 |
The maximum asymptote (unit of probability) for sigmoidal curve. This parameter is included in the sigmoid utility class, which is currently used with the HIV sim type for the Formation_Rate_Sigmoid and Condom_Usage_Probability parameters. |
{
"Max": 0.3,
"Mid": 2019,
"Min": 0.0125,
"Rate": 1.5
}
|
Mid |
float |
0 |
3.40282e+038 |
2000 |
The year of the inflection point for sigmoidal curve. This parameter is included in the sigmoid utility class, which is currently used with the HIV sim type for the Formation_Rate_Sigmoid and Condom_Usage_Probability parameters. |
{
"Min": 0.0125,
"Max": 0.3,
"Mid": 2019,
"Rate": 1.5
}
|
Migration_Actions |
array of enums |
NA |
NA |
NA |
A list of what relationship action to take when one member of the relationship migrates to another node. The order in which they are listed corresponds to the probability values in Migration_Actions_Distributions. Migration_Model in the configuration file must be set to FIXED_RATE_MIGRATION. Possible values are:
|
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Migration_Actions": [
"TERMINATE",
"PAUSE",
"MIGRATE"
],
"Migration_Actions_Distribution": [
0.7,
0.2,
0.1
]
}
}
}
}
|
Migration_Actions_Distribution |
array of floats |
0 |
1 |
NA |
A list of the proportion of relationships that take a given action when one member of the relationship migrates. The sum of all values must be 1 and the order of the list corresponds to the order in Migration_Actions. Migration_Model in the configuration file must be set to FIXED_RATE_MIGRATION. |
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Migration_Actions": [
"TERMINATE",
"PAUSE",
"MIGRATE"
],
"Migration_Actions_Distribution": [
0.7,
0.2,
0.1
]
}
}
}
}
|
Min |
float |
0 |
1 |
1 |
The minimum asymptote (unit of probability) for sigmoidal curve. This parameter is included in the sigmoid utility class, which is currently used with the HIV sim type for the Formation_Rate_Sigmoid and Condom_Usage_Probability parameters. |
{
"Min": 0.0125,
"Max": 0.3,
"Mid": 2019,
"Rate": 1.5
}
|
Rate |
float |
-100 |
100 |
1 |
The rate (probability/year) proportional to the slope at the inflection point of sigmoidal curve. This parameter is included in the sigmoid utility class, which is currently used with the HIV sim type for the Formation_Rate_Sigmoid and Condom_Usage_Probability parameters. |
{
"Max": 0.3,
"Mid": 2019,
"Min": 0.0125,
"Rate": 1.5
}
|
Relationship_Parameters |
json object |
NA |
NA |
NA |
The structure that determines basic aspects of the relationship, such as duration, condom usage, or how to handle migration. |
{
"Society": {
"TRANSITORY": {
"Relationship_Parameters": {
"Migration_Actions": [
"TERMINATE",
"PAUSE",
"MIGRATE"
],
"Migration_Actions_Distribution": [
0.7,
0.2,
0.1
]
}
}
}
}
|
Pair_Formation_Parameters#
The Pair_Formation_Parameters section defines the rate at which new relationships are formed and partnership preference using the main pair forming algorithm that finds potential partners based on their age and the Joint_Probabilities matrix.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Age_of_First_Bin_Edge_Female |
integer |
0 |
100 |
1 |
The maximum age for the first age bin when dividing the female population into age bins for pair formation. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Number_Age_Bins_Male": 25,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 10,
"Age_of_First_Bin_Edge_Female": 20
}
}
}
}
|
Age_of_First_Bin_Edge_Male |
integer |
0 |
100 |
1 |
The maximum age for the first age bin when dividing the male population into age bins for pair formation. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Number_Age_Bins_Male": 25,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 10,
"Age_of_First_Bin_Edge_Female": 20
}
}
}
}
|
Assortivity |
json object |
NA |
NA |
NA |
The object that defines how people will preferentially form pairs based on their membership in different groups. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "INDIVIDUAL_PROPERTY",
"Property_Name": "Risk",
"Axes": [
"LOW",
"HIGH"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.8275185967686474,
0.17248140323135264
],
[
0.17248140323135264,
0.8275185967686474
]
]
}
}
}
}
}
|
Extra_Relational_Rate_Ratio_Female |
integer |
1 |
3.40282e+038 |
1 |
For women, the rate ratio for having extra-relational sex for this relationship type, where the ratio is the event over the period of time defined in Update_Period. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Update_Period": 7.0,
"Extra_Relational_Rate_Ratio_Male": 4,
"Extra_Relational_Rate_Ratio_Female": 2
}
}
}
}
|
Extra_Relational_Rate_Ratio_Male |
integer |
1 |
3.40282e+038 |
1 |
For males, the rate ratio for having extra-relational sex for this relationship type, where the ratio is the event over the period of time defined in Update_Period. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Update_Period": 7.0,
"Extra_Relational_Rate_Ratio_Male": 4,
"Extra_Relational_Rate_Ratio_Female": 2
}
}
}
}
|
Formation_Rate_Constant |
float |
0 |
1 |
0.001 |
If Formation_Rate_Type is set to CONSTANT, the number of new relationships per day for this relationship type. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0013,
"Update_Period": 7.0,
"Extra_Relational_Rate_Ratio_Male": 5,
"Extra_Relational_Rate_Ratio_Female": 2
}
}
}
}
|
Formation_Rate_Interpolated_Values |
json object |
NA |
NA |
NA |
The structure that contains two arrays of floats specifying Times and Values arrays that will be interpolated to provide the formation rate when Formation_Rate_Type is set to INTERPOLATED_VALUES. The years listed in Times must be in ascending order; the first year must be prior to the current year and if the last year is prior to the current year, the last value in Values will be used for the formation rate. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Type": "INTERPOLATED_VALUES",
"Formation_Rate_Interpolated_Values": {
"Times": [
1980,
2000,
2020
],
"Values": [
0.2,
0.8,
0.4
]
}
}
}
}
}
|
Formation_Rate_Sigmoid |
json object |
NA |
NA |
NA |
The structure that determines the shape of the sigmoidal curve for pair formation when Formation_Rate_Type is set to SIGMOID_VARIABLE_WIDTH_HEIGHT. Include the following parameters:
|
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Type": "SIGMOID_VARIABLE_WIDTH_HEIGHT",
"Formation_Rate_Sigmoid": {
"Min": 0.6,
"Max": 0.9,
"Mid": 2010,
"Rate": 3
}
}
}
}
}
|
Formation_Rate_Type |
enum |
NA |
NA |
CONSTANT |
The type of functional form that describes that pair formation rate. Possible values are:
|
{
"Society": {
"MARITAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Type": "CONSTANT",
"Formation_Rate_Constant": 0.002739726
}
}
}
}
|
Joint_Probabilities |
matrix of floats |
0 |
3.40282e+038, |
0 |
The relative preference of members of one age bin to form relationships with members of another age bin. The columns represent female bins and rows represent male bins. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0027398,
"Update_Period": 7.0,
"Number_Age_Bins_Male": 2,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 50,
"Age_of_First_Bin_Edge_Female": 50,
"Years_Between_Bin_Edges_Male": 35,
"Years_Between_Bin_Edges_Female": 35,
"Joint_Probabilities": [
[
0,
1
],
[
1,
0
]
]
}
}
}
}
|
Number_Age_Bins_Female |
integer |
1 |
1000 |
1 |
The number of age bins to divide the female population into for pair formation. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0027398,
"Update_Period": 7.0,
"Number_Age_Bins_Male": 2,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 50,
"Age_of_First_Bin_Edge_Female": 50,
"Years_Between_Bin_Edges_Male": 35,
"Years_Between_Bin_Edges_Female": 35,
"Joint_Probabilities": [
[
0,
1
],
[
1,
0
]
]
}
}
}
}
|
Number_Age_Bins_Male |
integer |
1 |
1000 |
1 |
The number of age bins to divide the male population into for pair formation. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0027398,
"Update_Period": 7.0,
"Number_Age_Bins_Male": 2,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 50,
"Age_of_First_Bin_Edge_Female": 50,
"Years_Between_Bin_Edges_Male": 35,
"Years_Between_Bin_Edges_Female": 35,
"Joint_Probabilities": [
[
0,
1
],
[
1,
0
]
]
}
}
}
}
|
Update_Period |
float |
0 |
3.40282e+38 |
0 |
The period, in days, to wait before an individual is eligible to seek out new relationships. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0013,
"Update_Period": 7.0,
"Extra_Relational_Rate_Ratio_Male": 5,
"Extra_Relational_Rate_Ratio_Female": 2
}
}
}
}
|
Years_Between_Bin_Edges_Female |
float |
0.1 |
100 |
1 |
For the female population, the number of years covered in each age bin. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0027398,
"Update_Period": 7.0,
"Number_Age_Bins_Male": 2,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 50,
"Age_of_First_Bin_Edge_Female": 50,
"Years_Between_Bin_Edges_Male": 35,
"Years_Between_Bin_Edges_Female": 35,
"Joint_Probabilities": [
[
0,
1
],
[
1,
0
]
]
}
}
}
}
|
Years_Between_Bin_Edges_Male |
integer |
0.1 |
100 |
1 |
For the male population, the number of years covered in each age bin. |
{
"Society": {
"INFORMAL": {
"Pair_Formation_Parameters": {
"Formation_Rate_Constant": 0.0027398,
"Update_Period": 7.0,
"Number_Age_Bins_Male": 2,
"Number_Age_Bins_Female": 2,
"Age_of_First_Bin_Edge_Male": 50,
"Age_of_First_Bin_Edge_Female": 50,
"Years_Between_Bin_Edges_Male": 35,
"Years_Between_Bin_Edges_Female": 35,
"Joint_Probabilities": [
[
0,
1
],
[
1,
0
]
]
}
}
}
}
|
Assortivity#
The Assortivity section refines who partners with whom. After the main pair forming algorithm reduces the set of potential partners to a subset based on age, Assortivity allows for selection based on other criteria.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Axes |
array of strings |
NA |
NA |
NA |
The axes defined in Group to use for the weighting matrix for pair formation. The order of the array defines the order of the weighting matrix. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "INDIVIDUAL_PROPERTY",
"Property_Name": "Risk",
"Axes": [
"LOW",
"HIGH"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.8275185967686474,
0.17248140323135264
],
[
0.17248140323135264,
0.8275185967686474
]
]
}
}
}
}
}
|
Group |
enum |
NA |
NA |
NO_GROUP |
The group that individuals may belong to that is used for weighting assortivity for pair formation. Possible values are:
|
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "INDIVIDUAL_PROPERTY",
"Property_Name": "Risk",
"Axes": [
"LOW",
"HIGH"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.8275185967686474,
0.17248140323135264
],
[
0.17248140323135264,
0.8275185967686474
]
]
}
}
}
}
}
|
Property_Name |
string |
NA |
NA |
NA |
If Group is set to INDIVIDUAL_PROPERTY, the name of the individual property as defined in the IndividualProperties section. |
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "INDIVIDUAL_PROPERTY",
"Property_Name": "Risk",
"Axes": [
"LOW",
"HIGH"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.8275185967686474,
0.17248140323135264
],
[
0.17248140323135264,
0.8275185967686474
]
]
}
}
}
}
}
|
Start_Year |
float |
1900 |
2200 |
1900 |
The year to start using the assortivity weighting matrix. The value must be prior to the current year or Group will be set to NO_GROUP. Used only when the Group value is one of the following:
|
{
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "HIV_INFECTION_STATUS",
"Start_Year": 1990,
"Axes": [
"True",
"FALSE"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.75,
0.25
],
[
0.4,
0.6
]
]
}
}
}
}
}
|
Weighting_Matrix_RowMale_ColumnFemale |
matrix of floats |
0 |
1 |
0 |
The weights to apply to pair formation rates for individuals belonging to the groups defined in Axes. Rows are indexed by the male attribute and columns by the female attribute as defined in Axes. A single row or column cannot be all zeros. The matrix must be square with the number of dimensions defined by the number of entries in Axes. |
The following example shows that males who are negative for STI coinfection are 3 times more likely to form relationships with females who are negative and, likewise, individuals positive for STI coinfection are more likely to form relationships with others of the same status. {
"Society": {
"TRANSITORY": {
"Pair_Formation_Parameters": {
"Assortivity": {
"Group": "STI_COINFECTION_STATUS",
"Start_Year": 1990,
"Axes": [
"FALSE",
"TRUE"
],
"Weighting_Matrix_RowMale_ColumnFemale": [
[
0.75,
0.25
],
[
0.4,
0.6
]
]
}
}
}
}
}
|
Concurrency_Parameters#
The Concurrency_Configuration section at the top level of the Society section defines the simultaneous relationship parameters for super spreader probabilities, whether simultaneous relationships type probabilities are independent or correlated, and, if correlated, the order of the relationship types. If you want to base concurrency on IndividualProperties settings, you can list the relevant properties in Individual_Property_Name, using “NONE” if the properties are irrelevant for concurrency.
Under each relationship type, the Concurrency_Parameters section defines simultaneous relationship parameters for that relationship type. In this section, all parameters should be nested under the name of the individual property relevant for setting concurrency. Again, if the properties are irrelevant, use “NONE”.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Concurrency_Parameters |
json object |
NA |
NA |
NA |
The structure that determines how concurrent relationships are formed, for a specific relationship type. This parameter is nested under a parameter for one of the supported relationship types. To apply to all individuals regardless of individual property values, nest parameters under NONE. To apply only to individuals with certain property values, nest parameters under the property value as set in Concurrency_Configuration. |
The following example sets concurrency for transitory relationships regardless of individual properties. {
"Society": {
"TRANSITORY": {
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 2,
"Max_Simultaneous_Relationships_Male": 2,
"Prob_Extra_Relationship_Female": 0.3,
"Prob_Extra_Relationship_Male": 0.3
}
}
}
}
}
The following example sets different concurrency parameters for low-risk and high-risk individuals in transitory relationships. {
"Society": {
"Concurrency_Configuration": {
"Individual_Property_Name": "Risk",
"LOW": {
"Extra_Relational_Flag_Type": "Independent"
},
"HIGH": {
"Extra_Relational_Flag_Type": "Correlated"
}
},
"TRANSITORY": {
"Concurrency_Parameters": {
"LOW": {
"Max_Simultaneous_Relationships_Female": 2,
"Max_Simultaneous_Relationships_Male": 2,
"Prob_Extra_Relationship_Female": 0.3,
"Prob_Extra_Relationship_Male": 0.3
},
"HIGH": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 5,
"Prob_Extra_Relationship_Female": 0.5,
"Prob_Extra_Relationship_Male": 0.7
}
}
}
}
}
|
Max_Simultaneous_Relationships_Female |
integer |
0 |
63 |
1 |
For females, the maximum number of concurrent relationships. The individual sets the value at initialization and whenever they change relationship type. |
{
"Society": {
"INFORMAL": {
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 3,
"Prob_Extra_Relationship_Female": 0.8,
"Prob_Extra_Relationship_Male": 0.8
}
}
}
}
}
|
Max_Simultaneous_Relationships_Male |
integer |
0 |
63 |
1 |
For males, the maximum number of concurrent relationships. |
{
"Society": {
"INFORMAL": {
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 3,
"Prob_Extra_Relationship_Female": 0.8,
"Prob_Extra_Relationship_Male": 0.8
}
}
}
}
}
|
Prob_Extra_Relationship_Female |
float |
0 |
1 |
0 |
The probability of a female receiving a flag that allows her to seek additional relationships while currently in another relationship. |
{
"Society": {
"INFORMAL": {
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 3,
"Prob_Extra_Relationship_Female": 0.8,
"Prob_Extra_Relationship_Male": 0.8
}
}
}
}
}
|
Prob_Extra_Relationship_Male |
float |
0 |
1 |
0 |
The probability of a male receiving a flag that allows him to seek additional relationships while currently in another relationship. |
{
"Society": {
"INFORMAL": {
"Concurrency_Parameters": {
"NONE": {
"Max_Simultaneous_Relationships_Female": 3,
"Max_Simultaneous_Relationships_Male": 3,
"Prob_Extra_Relationship_Female": 0.8,
"Prob_Extra_Relationship_Male": 0.8
}
}
}
}
}
|