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. You can use 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 malaria simulation type.

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	Type	Min	Max	Default	Example	Description
Author	string	NA	NA	NA	example	The person who created the demographics file. Files generated by COMPS will include this value, but it is not used by EMOD simulations.
DateCreated	string	NA	NA	NA	example	The date the demographics file was created. Files generated by COMPS will include this value, but it is not used by EMOD simulations.
IdReference	string	NA	NA	NA	example	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	json object	NA	NA	NA	example	The structure that contains the metadata for the demographics file.
NodeCount	integer	1	Depends on available memory	NA	example	The number of nodes to expect in the input files. This parameter is required.
Resolution	integer	NA	NA	NA	example	The spatial resolution of the demographics file. Files generated by COMPS will include this value, but it is not used by EMOD simulations.
Tool	string	NA	NA	NA	example	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.

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	Type	Min	Max	Default	Example	Description
Age_Bin_Edges_In_Years	array	NA	NA	NA	example	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 model-targeted-interventions for more information.
IndividualProperties	array of objects	NA	NA	[]	example	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.
Initial_Distribution	array of floats	0	1	1	example, example	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	array of objects	NA	NA	NA	example	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.
Property	enum	NA	NA	NA	example, example	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: Age_Bin Assign individuals to age bins. Use with Age_Bin_Edges_In_Years. Cannot be used with NodeProperties. Accessibility Tag individuals or nodes based on their accessibility. Geographic Tag individuals or nodes based on geographic characteristics. HasActiveTB Tag individuals or nodes based on active TB status. Typically used only with HIV ART staging interventions. InterventionStatus Tag individuals or nodes based on intervention status, so that receiving an intervention can affect how other interventions are distributed. Use with Disqualifying_Properties and New_Property_Value in the campaign file. Place Tag individuals or nodes based on place. Risk Tag individuals or nodes based on disease risk. QualityofCare Tag individuals or nodes based on the quality of medical care.
Transitions	array	NA	NA	NA	example	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.
Values	array of strings	NA	NA	NA	example, example	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.

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	Type	Min	Max	Default	Example	Description
Airport	boolean	0	1	0	example	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.
Altitude	float	-3.40282e+038	3.40282e+038	0	example	The altitude, in meters, for the node. Required, but only used when Climate_Model is set to CLIMATE_KOPPEN.
BirthRate	double	0	1	0.00008715	example	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).
InfectivityReservoirEndTime	float	InfectivityReservoirStartTime	3.40282e+038	3.40282e+038	example	The ending of the exogeneous reservoir of infectivity. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1).
InfectivityReservoirSize	float	0	3.40282e+038	0	example	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).
InfectivityReservoirStartTime	float	0	3.40282e+038	0	example	The beginning of the exogeneous reservoir of infectivity. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1).
InitialPopulation	integer	0	2147480000	1000	example	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).
InitialVectorsPerSpecies	json object	0	2.15e+09	10,000	example	The number of vectors per species that will be populated into the node at the beginning of the simulation. Population responds to habitat availability that can be scaled by LarvalHabitatMultiplier. Vector_Sampling_Type in the configuration file must be set to TRACK_ALL_VECTORS or SAMPLE_IND_VECTORS.
LarvalHabitatMultiplier	float or nested json object	NA	NA	NA	example, example, example	The value by which to scale the larval habitat availability specified in the configuration file with Larval_Habitat_Types across all habitat types, for specific habitat types, or for specific mosquito species within each habitat type.
Latitude	float	3.40282e+038	-3.40282e+038	-1	example	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.
Longitude	float	-3.40282e+38	3.40282e+38	-1	example	Longitude of the node in decimal degrees. This can be used for several things, including defining the size of grid cells.
NodeAttributes	json object	NA	NA	NA	example	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.
Region	boolean	0	1	0	example	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.
Seaport	boolean	0	1	0	example	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.

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	Type	Min	Max	Default	Example	Description
IndividualAttributes	json object	NA	NA	NA	example	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.
PercentageChildren	float	0	1	NA	example	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.

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	Type	Min	Max	Default	Example	Description
AgeDistribution1	float	-3.4e+38	3.4e+38	0.000118	example	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. 0: Age, in days, to assign to all individuals. 1: Minimum age, in days, for a uniform distribution. 2: Mean age, in days, for a Gaussian distribution. 3: Exponential decay rate. 4: Mean age, in days, for a Poisson distribution. 5: Mu (the mean of the natural log) for a log normal distribution. 6: Proportion of individuals in the second, user-defined age bin vs. the first age bin (1 day) for a bimodal distribution. Must be between 0 and 1. 7: Scale parameter for a Weibull distribution. Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_SIMPLE (see Population dynamics parameters).
AgeDistribution2	float	-3.4e+38	3.4e+38	0	example	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. 0: NA, set to 0. 1: Maximum age, in days, for a uniform distribution. 2: Standard deviation in age, in days, for a Gaussian distribution. 3: NA, set to 0. 4: NA, set to 0. 5: Sigma (the standard deviation of the natural log) for a log normal distribution. 6: The age, in days, of individuals in the second age bin for a bimodal distribution. 7: Shape parameter for a Weibull distribution. Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_SIMPLE (see Population dynamics parameters).
AgeDistributionFlag	integer	0	7	3	example	The type of distribution to use for age. Possible values are: 0 (Constant, everyone in the population is the same age.) 1 (Uniform, ages are randomly drawn between a minimum and maximum value.) 2 (Gaussian) 3 (Exponential) 4 (Poisson) 5 (Log normal) 6 (Bimodal, non-continuous with some individuals 1 day old and others a user-defined age.) 7 (Weibull) Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_SIMPLE (see Population dynamics parameters).
MigrationHeterogeneityDistribution1	float	-3.4e+38	3.4e+38	1	example	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. 0: Migration heterogeneity value to assign. 1: Minimum migration heterogeneity for a uniform distribution. 2: Mean migration heterogeneity for a Gaussian distribution. 3: Exponential decay rate. 4: Mean migration heterogeneity for a Poisson distribution. 5: Mu (the mean of the natural log) for a log normal distribution. 6: Proportion of individuals in the second, user-defined migration heterogeneity bin vs. the first migration heterogeneity bin (value of 1 ) for a bimodal distribution. Must be between 0 and 1. 7: Scale parameter for a Weibull distribution. Enable_Migration_Heterogeneity in the configuration file must be set to 1 (see Migration parameters).
MigrationHeterogeneityDistribution2	float	-3.4e+38	3.4e+38	0	example	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. 0: NA, set to 0. 1: Maximum migration heterogeneity for a uniform distribution. 2: Standard deviation in migration heterogeneity for a Gaussian distribution. 3: NA, set to 0. 4: NA, set to 0. 5: Sigma (the standard deviation of the natural log) for a log normal distribution. 6: The migration heterogeniety of individuals in the second migration heterogeniety bin for a bimodal distribution. 7: Shape parameter for a Weibull distribution. Enable_Migration_Heterogeneity in the configuration file must be set to 1 (see Migration parameters).
MigrationHeterogeneityDistributionFlag	integer	0	7	0	example	The type of distribution to use for migration heterogeneity. Possible values are: 0 (Constant, everyone in the population has the same migration value.) 1 (Uniform, migration values are randomly drawn between a minimum and maximum value.) 2 (Gaussian) 3 (Exponential) 4 (Poisson) 5 (Log normal) 6 (Bimodal, non-continuous with some individuals with a migration heterogeniety of 1 and others a user-defined value.) 7 (Weibull) Enable_Migration_Heterogeneity in the configuration file must be set to 1 (see Migration parameters).
PrevalenceDistribution1	float	-3.4e+38	3.4e+38	1	example	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. 0: Prevalence value to assign. 1: Minimum prevalence for a uniform distribution. 2: Mean prevalence for a Gaussian distribution. 3: Exponential decay rate. 4: Mean prevalence for a Poisson distribution. 5: Mu (the mean of the natural log) for a log normal distribution. 6: Proportion of individuals in the second, user-defined prevalence bin vs. the first prevalence bin (value of 1) for a bimodal distribution. Must be between 0 and 1. 7: Scale parameter for a Weibull distribution.
PrevalenceDistribution2	float	-3.4e+38	3.4e+38	0	example	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. 0: NA, set to 0. 1: Maximum prevalence for a uniform distribution. 2: Standard deviation in prevalence for a Gaussian distribution. 3: NA, set to 0. 4: NA, set to 0. 5: Sigma (the standard deviation of the natural log) for a log normal distribution. 6: The prevalence for individuals in the second prevalence bin for a bimodal distribution. 7: Shape parameter for a Weibull distribution.
PrevalenceDistributionFlag	integer	0	7	0	example	The type of distribution to use for prevalence. Possible values are: 0 (Constant, everyone in the population has the same prevalence.) 1 (Uniform, prevalence is randomly drawn between a minimum and maximum value.) 2 (Gaussian) 3 (Exponential) 4 (Poisson) 5 (Log normal) 6 (Bimodal, non-continuous with some individuals having a prevalence of 1 and others a user-defined prevalence.) 7 (Weibull)
RiskDistribution1	float	-3.4e+38	3.4e+38	0	example	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. 0: Risk value to assign. 1: Minimum risk for a uniform distribution. 2: Mean risk for a Gaussian distribution. 3: Exponential decay rate. 4: Mean risk for a Poisson distribution. 5: Mu (the mean of the natural log) for a log normal distribution. 6: Proportion of individuals in the second, user-defined risk bin vs. the first risk bin (value of 1) for a bimodal distribution. Must be between 0 and 1. 7: Scale parameter for a Weibull distribution.
RiskDistribution2	float	-3.4e+38	3.4e+38	0	example	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. 0: NA, set to 0. 1: Maximum risk for a uniform distribution. 2: Standard deviation in risk for a Gaussian distribution. 3: NA, set to 0. 4: NA, set to 0. 5: Sigma (the standard deviation of the natural log) for a log normal distribution. 6: The risk of individuals in the second risk bin for a bimodal distribution. 7: Shape parameter for a Weibull distribution.
RiskDistributionFlag	integer	0	7	0	example	The type of distribution to use for risk. Possible values are: 0 (Constant, everyone in the population has the same risk.) 1 (Uniform, risk is randomly drawn between a minimum and maximum value.) 2 (Gaussian) 3 (Exponential) 4 (Poisson) 5 (Log normal) 6 (Bimodal, non-continuous with some individuals with a risk of 1 and others a user-defined risk.) 7 (Weibull) Enable_Demographics_Risk must be set to 1 (see Population dynamics parameters).
InnateImmuneDistribution1	float	-3.4e+38	3.4e+38	0	example	The first value in the innate immune coefficient distribution, the meaning of which depends upon the value set in InnateImmuneDistributionFlag. The table below shows the flag value and corresponding distribution value. 0: Innate immune coefficient value to assign. 1: Minimum innate immune coefficient for a uniform distribution. 2: Mean innate immune coefficient for a Gaussian distribution. 3: Exponential decay rate. 4: Mean innate immune coefficient for a Poisson distribution. 5: Mu (the mean of the natural log) for a log normal distribution. 6: Proportion of individuals in the second, user-defined innate immune coefficient bin vs. the first innate immune coefficient bin (value of 1) for a bimodal distribution. Must be between 0 and 1. 7: Scale parameter for a Weibull distribution.
InnateImmuneDistribution2	float	-3.4e+38	3.4e+38	0	example	The second value in the distribution, the meaning of which depends upon the value set in InnateImmuneDistributionFlag. The table below shows the flag value and corresponding distribution value. 0: NA, set to 0. 1: Maximum innate immune coefficient for a uniform distribution. 2: Standard deviation in innate immune coefficient for a Gaussian distribution. 3: NA, set to 0. 4: NA, set to 0. 5: Sigma (the standard deviation of the natural log) for a log normal distribution. 6: The innate immune coefficient for individuals in the second innate immune coefficient bin for a bimodal distribution. 7: Shape parameter for a Weibull distribution.
InnateImmuneDistributionFlag	integer	0	7	0	example	The type of distribution to use for innate immune coefficient. Possible values are: 0 (Constant, everyone in the population has the same innate immune coefficient.) 1 (Uniform, innate immune coefficient is randomly drawn between a minimum and maximum value.) 2 (Gaussian) 3 (Exponential) 4 (Poisson) 5 (Log normal) 6 (Bimodal, non-continuous with some individuals having a innate immune coefficient of 1 and others a user-defined innate immune coefficient.) 7 (Weibull)
SusceptibilityDistribution1	float	-3.4e+38	3.40282e+38	0	example	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. 0: Probability of full susceptibility. 1: Minimum probability of susceptibility for a uniform distribution. 6: Proportion of individuals in the second, user-defined susceptibility bin vs. the first susceptibility bin (value of 1) for a bimodal distribution. Must be between 0 and 1. 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).
SusceptibilityDistribution2	float	-3.4e+38	3.40282e+38	0	example	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. 0: NA, set to 0. 1: Maximum susceptibility for a uniform distribution. 6: The susceptibility values of individuals in the second susceptibility bin for a bimodal distribution. 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).
SusceptibilityDistributionFlag	integer	0	7	0	example	The type of distribution to use for determining an individual's probability of full susceptibility. Possible values are: 0 (Constant, everyone in the population has the same probability of susceptibility.) 1 (Uniform, the probability of susceptibility is randomly drawn between a minimum and maximum value.) 6 (Bimodal, non-continuous with some individuals' probability of susceptibility at 1 and others with a user-defined probability.) 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).

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	Type	Min	Max	Default	Example	Description
AgeDistribution	json object	NA	NA	NA	example	The structure defining a complex age distribution. Age_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
AxisNames	array of strings	NA	NA	NA	example	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: MortalityDistribution ["gender", "age"] Death_Rate_Dependence in the configuration file must be set to NONDISEASE_MORTALITY_BY_AGE_AND_GENDER (see Mortality and survival parameters). MortalityDistributionMale ["age", "year"] Death_Rate_Dependence must be set to NONDISEASE_MORTALITY_BY_YEAR_AND_AGE_FOR_EACH_GENDER (see Mortality and survival parameters). MortalityDistributionFemale ["age", "year"] Death_Rate_Dependence must be set to NONDISEASE_MORTALITY_BY_YEAR_AND_AGE_FOR_EACH_GENDER (see Mortality and survival parameters). FertilityDistribution Two options are available: * ["urban", "age"] Birth_Rate_Dependence in the configuratIon file must be set to INDIVIDUAL_PREGNANCIES_BY_URBAN_AND_AGE (see Population dynamics parameters). * ["age", "year"] Birth_Rate_Dependence must be set to INDIVIDUAL_PREGNANCIES_BY_AGE_AND_YEAR (see Population dynamics parameters). ImmunityDistribution ["age"] AgeDistribution No axes. ["age"] is the only value accepted for all malaria-specific distributions: MSP_mean_antibody_distribution MSP_variance_antibody_distribution nonspec_mean_antibody_distribution nonspec_variance_antibody_distribution PfEMP1_mean_antibody_distribution PfEMP1_variance_antibody_distribution
AxisScaleFactors	array of floats	3.40282e+038	-3.40282e+038	1	example	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.
AxisUnits	array of strings	NA	NA	NA	example	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.
DistributionValues	array of floats	0	1	1	example	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).
FertilityDistribution	json object	NA	NA	NA	example	The distribution of the fertility rate in the population. Enable_Birth in the configuration file must be set to 1 (see Population dynamics parameters).
ImmunityDistribution	json object	NA	NA	NA	example	The structure defining a complex immunity distribution. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX (see Immunity parameters).
MortalityDistribution	json object	NA	NA	NA	example	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.
MSP_mean_antibody_distribution	json object	NA	NA	NA	example	The mean of the fraction of the antigenic variants of the anti-MSP antibody that the immune system has been exposed to, binned by age using PopulationGroups. ResultValues are bounded between 0 and 1, typically increasing with age. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
MSP_variance_antibody_distribution	json object	NA	NA	NA	example	The variance of the fraction of the antigenic variants of the anti-MSP antibody that the immune system has been exposed to, binned by age using PopulationGroups. ResultValues are bounded between 0 and 1, typically increasing with age. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
nonspec_mean_antibody_distribution	json object	NA	NA	NA	example	The mean of the fraction of the antigenic variants of non-specific malaria antibodies that the immune system has been exposed to, binned by age using PopulationGroups. ResultValues are bounded between 0 and 1, typically increasing with age. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
nonspec_variance_antibody_distribution	json object	NA	NA	NA	example	The variance of the fraction of the antigenic variants of non-specific malaria antibodies that the immune system has been exposed to, binned by age using PopulationGroups. ResultValues are bounded between 0 and 1, typically increasing with age. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
NumDistributionAxes	integer	1	NA	NA	example	The number of axes to use for a complex distribution. EMOD does not use this value; it is only informational.
NumPopulationGroups	array of integers	NA	NA	NA	example	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.
PfEMP1_mean_antibody_distribution	json object	NA	NA	NA	example	The mean of the fraction of the antigenic variants of the PfEMP1 antibody that the immune system has been exposed to, binned by age using PopulationGroups. ResultValues are bounded between 0 and 1, typically increasing with age. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
PfEMP1_variance_antibody_distribution	json object	NA	NA	NA	example	The variance of the fraction of the antigenic variants of the PfEMP1 antibody that the immune system has been exposed to, binned by age using PopulationGroups. ResultValues are bounded between 0 and 1, typically increasing with age. Immunity_Initialization_Distribution_Type in the configuration file must be set to DISTRIBUTION_COMPLEX.
PopulationGroups	matrix of integers	NA	NA	NA	example	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.
ResultScaleFactor	float	-3.40282e+038	3.40282e+038	1	example	The scale factor used to convert ResultUnits to number of births, deaths, or another variable per individual per day.
ResultUnits	string	NA	NA	NA	example	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.
ResultValues	array of floats	NA	NA	NA	example, example	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.
SusceptibilityDistribution	json object	NA	NA	NA	example	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).