BitingRisk

The BitingRisk class allows you to adjust the relative risk that the person is bitten by a vector. As an intervention, it allows you to target specific groups at specific times during the simulation.

The relative biting rate can be initially set by setting Enable_Demographic_Risk to 1 and then configuring IndividualAttributes, RiskDistributionFlag, RiskDistributionParam1, and RiskDistributionParam2. This will give each new person their own relative risk.

The relative biting rate can be thought of as having two parts: the relative risk value and the age dependent value. Age dependence is set using the Age_Dependent_Biting_Risk_Type parameter. These two values (from age dependence and relative risk) are multiplied to get the resulting rate, which is then used to control how much contagion is deposited from an infectious individual and the probability that an infection is acquired.

This intervention expires. To reset it, distribute another BitingRisk intervention that sets it back to the original value. Note that this is a relative biting rate. For example, giving everyone a value of 10 is the same as giving everyone a value of 1. This intervention is used to indicate some individuals are more likely to be bitten than others.

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.

The table below describes all possible parameters with which this class can be configured. The JSON example that follows shows one potential configuration.

Parameter

Data type

Minimum

Maximum

Default

Description

Example

Disqualifying_Properties

array of strings

NA

NA

[]

A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time.

 
{
  "Disqualifying_Properties": [
    "InterventionStatus:LostForever"
  ]
}

Dont_Allow_Duplicates

boolean

0

1

0

If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes.

 
{
  "Dont_Allow_Duplicates": 0
}

Intervention_Name

string

NA

NA

BitingRisk

The optional name used to refer to this intervention as a means to differentiate it from others that use the same class.

 
{
  "Intervention_Config": {
    "class": "BitingRisk",
    "Intervention_Name": "Relative biting risk with bednet usage"
  }
}

New_Property_Value

string

NA

NA

“”

An optional IndividualProperty key:value pair that will be assigned when the intervention is applied. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one.

 
{
  "New_Property_Value": "InterventionStatus:None"
}

Risk_Constant

float

0

3.40282E+38

6

The risk to use for all individuals when Risk_Distribution is set to CONSTANT_DISTRIBUTION.

 
{
  "Risk_Distribution": "CONSTANT_DISTRIBUTION",
  "Risk_Constant": 8
}

Risk_Distribution

enum

NA

NA

NOT_INITIALIZED

The distribution type to use for assigning the relative risk of being bitten by a mosquito to each individual. Each assigned value is a random draw from the distribution.

Possible values are:

NOT_INITIALIZED

No distribution set.

CONSTANT_DISTRIBUTION

Use the same value for each individual. Set Risk_Constant.

UNIFORM_DISTRIBUTION

Use a uniform distribution with a given minimum and maximum. Set Risk_Max and Risk_Min.

GAUSSIAN_DISTRIBUTION

The distribution is Gaussian (or normal). Values are resampled to ensure >= 0. Set Risk_Gaussian_Mean and Risk_Gaussian_Std_Dev.

EXPONENTIAL_DISTRIBUTION

The distribution is exponential with a given mean. Set Risk_Exponential.

WEIBULL_DISTRIBUTION

Use a Weibull distribution with a given shape and scale. Set Risk_Kappa and Risk_Lambda.

LOG_NORMAL_DISTRIBUTION

Use a log-normal distribution with a given mean and width. Set Risk_Log_Normal_Mean and Risk_Log_Normal_Width.

POISSON_DISTRIBUTION

Use a Poisson distribution with a given mean. Set Risk_Poisson_Mean.

DUAL_CONSTANT_DISTRIBUTION

Use a distribution where some individuals are set to a value of zero and the rest to a given value. Set Risk_Proportion_0 and Peak_2_Value. This distribution does not use the parameters set for CONSTANT_DISTRIBUTION.

DUAL_EXPONENTIAL_DISTRIBUTION

Use two exponential distributions with given means. Set Risk_Mean_1, Risk_Mean_2, and Risk_Proportion_1. This distribution does not use the parameters set for EXPONENTIAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "WEIBULL_DISTRIBUTION",
  "Risk_Kappa": 0.9,
  "Risk_Lambda": 1.5
}

Risk_Exponential

float

0

3.40282E+38

-1

The mean of the biting risk when Risk_Distribution is set to EXPONENTIAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "EXPONENTIAL_DISTRIBUTION",
  "Risk_Exponential": 4.25
}

Risk_Gaussian_Mean

float

0

3.40282E+38

-1

The mean of the biting risk when Risk_Distribution is set to GAUSSIAN_DISTRIBUTION.

 
{
  "Risk_Distribution": "GAUSSIAN_DISTRIBUTION",
  "Risk_Gaussian_Mean": 8,
  "Risk_Gaussian_Std_Dev": 1.5
}

Risk_Gaussian_Std_Dev

float

1.17549E-38

3.40282E+38

-1

The standard deviation of the biting risk when Risk_Distribution is set to GAUSSIAN_DISTRIBUTION.

 
{
  "Risk_Distribution": "GAUSSIAN_DISTRIBUTION",
  "Risk_Gaussian_Mean": 8,
  "Risk_Gaussian_Std_Dev": 1.5
}

Risk_Kappa

float

1.17549E-38

3.40282E+38

-1

The shape value for the biting risk when Risk_Distribution is set to WEIBULL_DISTRIBUTION.

 
{
  "Risk_Distribution": "WEIBULL_DISTRIBUTION",
  "Risk_Kappa": 0.9,
  "Risk_Lambda": 1.5
}

Risk_Lambda

float

1.17549E-38

3.40282E+38

-1

The scale value for the biting risk when Risk_Distribution is set to WEIBULL_DISTRIBUTION.

 
{
  "Risk_Distribution": "WEIBULL_DISTRIBUTION",
  "Risk_Kappa": 0.9,
  "Risk_Lambda": 1.5
}

Risk_Log_Normal_Mu

float

-3.40282e+38

1.70141e+38

3.40282E+38

The mean of the biting risk when Risk_Distribution is set to LOG_NORMAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "LOG_NORMAL_DISTRIBUTION",
  "Risk_Log_Normal_Mu": 9,
  "Risk_Log_Normal_Sigma": 2
}

Risk_Log_Normal_Sigma

float

-3.40282e+38

1.70141e+38

3.40282E+38

The width of the biting risk when Risk_Distribution is set to LOG_NORMAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "LOG_NORMAL_DISTRIBUTION",
  "Risk_Log_Normal_Mu": 9,
  "Risk_Log_Normal_Sigma": 2
}

Risk_Max

float

0

3.40282E+38

-1

The maximum biting risk when Risk_Distribution is set to UNIFORM_DISTRIBUTION.

 
{
  "Risk_Distribution": "UNIFORM_DISTRIBUTION",
  "Risk_Min": 2,
  "Risk_Max": 7
}

Risk_Mean_1

float

1.17549E-38

3.40282E+38

-1

The mean of the first exponential distribution when Risk_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Risk_Mean_1": 4,
  "Risk_Mean_2": 12,
  "Risk_Proportion_1": 0.2
}

Risk_Mean_2

float

1.17549E-38

3.40282E+38

-1

The mean of the second exponential distribution when Risk_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Risk_Mean_1": 4,
  "Risk_Mean_2": 12,
  "Risk_Proportion_1": 0.2
}

Risk_Min

float

0

3.40282E+38

-1

The minimum biting risk when Risk_Distribution is set to UNIFORM_DISTRIBUTION.

 
{
  "Risk_Distribution": "UNIFORM_DISTRIBUTION",
  "Risk_Min": 2,
  "Risk_Max": 7
}

Risk_Peak_2_Value

float

0

3.40282E+38

-1

The biting risk value to assign to the remaining individuals when Risk_Distribution is set to DUAL_CONSTANT_DISTRIBUTION.

 
{
  "Risk_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
  "Risk_Proportion_0": 0.25,
  "Risk_Peak_2_Value": 5
}

Risk_Poisson_Mean

float

0

3.40282E+38

-1

The mean of the biting risk when Risk_Distribution is set to POISSON_DISTRIBUTION.

 
{
  "Risk_Distribution": "POISSON_DISTRIBUTION",
  "Risk_Poisson_Mean": 5
}

Risk_Proportion_0

float

0

1

-1

The proportion of individuals to assign a value of zero biting risk when Risk_Distribution is set to DUAL_CONSTANT_DISTRIBUTION.

 
{
  "Risk_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
  "Risk_Proportion_0": 0.25,
  "Risk_Peak_2_Value": 5
}

Risk_Proportion_1

float

0

1

-1

The proportion of individuals in the first exponential distribution when Risk_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION.

 
{
  "Risk_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Risk_Mean_1": 4,
  "Risk_Mean_2": 12,
  "Risk_Proportion_1": 0.2
}

{
  "Intervention_Config": {
    "class": "BitingRisk",
    "Risk_Distribution": "CONSTANT_DISTRIBUTION",
    "Risk_Constant": 0.1
  }
}