CommunityHealthWorkerEventCoordinator#

The CommunityHealthWorkerEventCoordinator coordinator class is used to model a health care worker’s ability to distribute interventions to the nodes and individual in their coverage area. This coordinator distributes a limited number of interventions per day, and can create a backlog of individuals or nodes requiring the intervention. For example, individual-level interventions could be distribution of drugs and node-level interventions could be spraying houses with insecticide.

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

Amount_In_Shipment

integer

1

2147480000.0

2147480000.0

The number of interventions (such as vaccine doses) that a health worker or clinic receives in a shipment. Interventions can only be distributed if they are in stock; stock is updated every Days_Between_Shipments with the Amount_In_Shipment.

 
{
  "Amount_In_Shipment": 10
}

Days_Between_Shipments

float

1

3.40282e+38

3.40E+38

The number of days to wait before a clinic or health worker receives a new shipment of interventions (such as vaccine doses). Interventions can only be distributed if they are in stock; stock is updated every Days_Between_Shipments with the Amount_In_Shipment.

 
{
  "Days_Between_Shipments": 30
}

Demographic_Coverage

float

0

1

1

The fraction of individuals in the target demographic that will receive this intervention.

 
{
  "Demographic_Coverage": 1
}

Duration

float

0

3.40282e+38

3.40E+38

The number of days for an event coordinator to be active before it expires.

 
{
  "Duration": 65
}

Initial_Amount_Constant

float

0

3.40282E+38

-1

The initial amount to use for all health workers when Initial_Amount_Distribution is set to CONSTANT_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "CONSTANT_DISTRIBUTION",
  "Initial_Amount_Constant": 8
}

Initial_Amount_Distribution

enum

NA

NA

NOT_INITIALIZED

The distribution type to use for assigning the initial amount of interventions in stock. 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 Initial_Amount_Constant.

UNIFORM_DISTRIBUTION

Use a uniform distribution with a given minimum and maximum. Set Initial_Amount_Max and Initial_Amount_Min.

GAUSSIAN_DISTRIBUTION

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

EXPONENTIAL_DISTRIBUTION

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

WEIBULL_DISTRIBUTION

Use a Weibull distribution with a given shape and scale. Set Initial_Amount_Kappa and Initial_Amount_Lambda.

LOG_NORMAL_DISTRIBUTION

Use a log-normal distribution with a given mean and standard deviation of the natural log. Set Initial_Amount_Log_Normal_Mu and Initial_Amount_Log_Normal_Sigma.

POISSON_DISTRIBUTION

Use a Poisson distribution with a given mean. Set Initial_Amount_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 Initial_Amount_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 Initial_Amount_Mean_1, Initial_Amount_Mean_2, and Initial_Amount_Proportion_1. This distribution does not use the parameters set for EXPONENTIAL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Initial_Amount_Mean_1": 4,
  "Initial_Amount_Mean_2": 12,
  "Initial_Amount_Proportion_1": 0.2
}

Initial_Amount_Exponential

float

0

3.40282E+38

-1

The mean of the initial amount of intervention in stock when Initial_Amount_Distribution is set to EXPONENTIAL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "EXPONENTIAL_DISTRIBUTION",
  "Initial_Amount_Exponential": 4.25
}

Initial_Amount_Gaussian_Mean

float

0

3.40282E+38

-1

The mean of the initial amount of intervention in stock when Initial_Amount_Distribution is set to GAUSSIAN_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "GAUSSIAN_DISTRIBUTION",
  "Initial_Amount_Gaussian_Mean": 8,
  "Initial_Amount_Gaussian_Std_Dev": 1.5
}

Initial_Amount_Gaussian_Std_Dev

float

1.17549E-38

3.40282E+38

-1

The standard deviation of the initial amount of intervention in stock when Initial_Amount_Distribution is set to GAUSSIAN_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "GAUSSIAN_DISTRIBUTION",
  "Initial_Amount_Gaussian_Mean": 8,
  "Initial_Amount_Gaussian_Std_Dev": 1.5
}

Initial_Amount_Kappa

float

1.17549E-38

3.40282E+38

-1

The shape value for the initial amount of intervention in stock when Initial_Amount_Distribution is set to WEIBULL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "WEIBULL_DISTRIBUTION",
  "Initial_Amount_Kappa": 0.9,
  "Initial_Amount_Lambda": 1.5
}

Initial_Amount_Lambda

float

1.17549E-38

3.40282E+38

-1

The scale value for the initial amount of intervention in stock when Initial_Amount_Distribution is set to WEIBULL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "WEIBULL_DISTRIBUTION",
  "Initial_Amount_Kappa": 0.9,
  "Initial_Amount_Lambda": 1.5
}

Initial_Amount_Log_Normal_Mu

float

-3.40282e+38

1.70141e+38

3.40282E+38

The mean of the natural log of the initial amount of intervention in stock when Initial_Amount_Distribution is set to LOG_NORMAL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "LOG_NORMAL_DISTRIBUTION",
  "Initial_Amount_Log_Normal_Mu": 9,
  "Initial_Amount_Log_Normal_Sigma": 2
}

Initial_Amount_Log_Normal_Sigma

float

-3.40282e+38

3.40282E+38

1

The standard deviation of the natural log of the initial amount of intervention in stock when Initial_Amount_Distribution is set to LOG_NORMAL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "LOG_NORMAL_DISTRIBUTION",
  "Initial_Amount_Log_Normal_Mu": 9,
  "Initial_Amount_Log_Normal_Sigma": 2
}

Initial_Amount_Max

float

0

3.40282E+38

1

The maximum initial amount of intervention in stock when Initial_Amount_Distribution is set to UNIFORM_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "UNIFORM_DISTRIBUTION",
  "Initial_Amount_Max": 7,
  "Initial_Amount_Min": 2
}

Initial_Amount_Mean_1

float

1.17549E-38

3.40282E+38

-1

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

 
{
  "Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Initial_Amount_Mean_1": 4,
  "Initial_Amount_Mean_2": 12,
  "Initial_Amount_Proportion_1": 0.2
}

Initial_Amount_Mean_2

float

1.17549E-38

3.40282E+38

-1

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

 
{
  "Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Initial_Amount_Mean_1": 4,
  "Initial_Amount_Mean_2": 12,
  "Initial_Amount_Proportion_1": 0.2
}

Initial_Amount_Min

float

0

3.40282e+38

0

The minimum of initial amount of intervention in stock when Initial_Amount_Distribution is set to UNIFORM_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "UNIFORM_DISTRIBUTION",
  "Initial_Amount_Max": 10,
  "Initial_Amount_Min": 5
}

Initial_Amount_Peak_2_Value

float

0

3.40282E+38

-1

The initial amount in stock to assign to the remaining health workers when Initial_Amount_Distribution is set to DUAL_CONSTANT_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
  "Initial_Amount_Proportion_0": 0.25,
  "Initial_Amount_Peak_2_Value": 5
}

Initial_Amount_Poisson_Mean

float

0

3.40282E+38

-1

The mean of the initial amount of intervention in stock when Initial_Amount_Distribution is set to the POISSON_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "POISSON_DISTRIBUTION",
  "Initial_Amount_Poisson_Mean": 5
}

Initial_Amount_Proportion_0

float

0

1

-1

The proportion of health workers to assign a value of zero stock when Initial_Amount_Distribution is set to DUAL_CONSTANT_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
  "Initial_Amount_Proportion_0": 0.25,
  "Initial_Amount_Peak_2_Value": 5
}

Initial_Amount_Proportion_1

float

0

1

-1

The proportion of health workers in the first exponential distribution when Initial_Amount_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION.

 
{
  "Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
  "Initial_Amount_Mean_1": 4,
  "Initial_Amount_Mean_2": 12,
  "Initial_Amount_Proportion_1": 0.2
}

Intervention_Config

json object

NA

NA

NA

The nested JSON of the actual intervention to be distributed by this event coordinator.

 
{
  "Intervention_Config": {
    "class": "BroadcastEvent",
    "Broadcast_Event": "EventFromIntervention"
  }
}

Max_Distributed_Per_Day

integer

1

2147480000.0

2147480000.0

The maximum number of interventions (such as vaccine doses) that can be distributed by health workers or clinics in a given day.

 
{
  "Max_Distributed_Per_Day": 1
}

Max_Stock

integer

0

2147480000.0

2147480000.0

The maximum number of interventions (such as vaccine doses) that can be stored by a health worker or clinic. If the amount of interventions in a new shipment and current stock exceeds this value, only the number of interventions specified by this value will be stored.

 
{
  "Max_Stock": 12
}

Node_Property_Restrictions

array of json objects

NA

NA

NA

A list of the NodeProperty key:value pairs, as defined in the demographics file, that nodes must have to be targeted by the intervention. See NodeProperties and IndividualProperties parameters for more information.

You can specify AND and OR combinations of key:value pairs with this parameter.

The following example restricts the intervention to nodes that are urban and medium risk or rural and low risk.

{
  "Node_Property_Restrictions": [
    {
      "Place": "URBAN",
      "Risk": "MED"
    },
    {
      "Place": "RURAL",
      "Risk": "LOW"
    }
  ]
}

Property_Restrictions

array of json objects

NA

NA

NA

A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information.

To specify AND and OR combinations of key:value pairs, use Property_Restrictions_Within_Node. You cannot use both of these parameters in the same event coordinator.

 
{
  "Property_Restrictions": [
    "Risk:HIGH"
  ]
}

Property_Restrictions_Within_Node

array of json objects

NA

NA

NA

A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information.

This parameter allows you to specify AND and OR combinations of key:value pairs. You may specify individual property restrictions using either this parameter or Property_Restrictions, but not both.

The following example restricts the intervention to individuals who are urban and high risk or urban and medium risk.

{
  "Property_Restrictions_Within_Node": [
    {
      "Risk": "HIGH",
      "Geographic": "URBAN"
    },
    {
      "Risk": "MEDIUM",
      "Geographic": "URBAN"
    }
  ]
}

Target_Age_Max

float

0

9.3228e+35

9.3228e+35

The upper end of ages targeted for an intervention, in years.

 
{
  "Target_Age_Max": 20,
  "Target_Age_Min": 10,
  "Target_Demographic": "ExplicitAgeRanges"
}

Target_Age_Min

float

0

9.3228e+35

0

The lower end of ages targeted for an intervention, in years. Used when Target_Demographic is set to ExplicitAgeRanges or ExplicitAgeRangesAndGender.

 
{
  "Target_Age_Max": 20,
  "Target_Age_Min": 10,
  "Target_Demographic": "ExplicitAgeRanges"
}

Target_Demographic

enum

NA

NA

Everyone

The target demographic group. Possible values are:

  • Everyone

  • ExplicitAgeRanges

  • ExplicitAgeRangesAndGender

  • ExplicitGender

  • ExplicitDiseaseState

 
{
  "Target_Age_Max": 20,
  "Target_Age_Min": 10,
  "Target_Demographic": "ExplicitAgeRanges"
}

Target_Gender

enum

NA

NA

All

Specifies the gender restriction for the intervention. Possible values are:

  • Male

  • Female

  • All

 
{
  "Target_Gender": "Male"
}

Target_Residents_Only

boolean

0

1

0

When set to true (1), the intervention is only distributed to individuals that began the simulation in the node (i.e. those that claim the node as their residence).

 
{
  "Target_Residents_Only": 1
}

Targeting_Config

json object

NA

NA

NA

Be more selective of individuals by using the Targeting_Config classes.

 
{
  "Targeting_Config": {
    "class": "HasIntervention",
    "Is_Equal_To": 0,
    "Intervention_Name": "MyVaccine"
  }
}

Trigger_Condition_List

array of strings

NA

NA

NA

The list of events that are of interest to the community health worker (CHW). If one of these events occurs, the individual or node is put into a queue to receive the CHW’s intervention. The CHW processes the queue when the event coordinator is updated. See Event list for possible values.

 
{
  "Trigger_Condition_List": [
    "ListenForEvent"
  ]
}

Waiting_Period

float

0

3.40282e+38

3.40E+38

The number of days a person or node can be in the queue waiting to get the intervention from the community health worker (CHW). If a person or node is in the queue, they will not be re-added to the queue if the event that would add them to the queue occurs. This allows them to maintain their priority, however they could be removed from the queue due to this waiting period.

 
{
  "Waiting_Period": 15
}

{
  "Events": [
    {
      "class": "CampaignEvent",
      "Start_Day": 1,
      "Nodeset_Config": {
        "class": "NodeSetNodeList",
        "Node_List": [
          2,
          3,
          4
        ]
      },
      "Event_Coordinator_Config": {
        "class": "CommunityHealthWorkerEventCoordinator",
        "Duration": 400,
        "Distribution_Rate": 25,
        "Waiting_Period": 10,
        "Days_Between_Shipments": 25,
        "Amount_In_Shipment": 250,
        "Max_Stock": 1000,
        "Initial_Amount_Distribution": "CONSTANT_DISTRIBUTION",
        "Initial_Amount_Constant": 500,
        "Target_Demographic": "Everyone",
        "Demographic_Coverage": 1.0,
        "Property_Restrictions": [],
        "Target_Residents_Only": 0,
        "Trigger_Condition_List": [
          "NewInfectionEvent"
        ],
        "Intervention_Config": {
          "class": "SimpleVaccine",
          "Cost_To_Consumer": 10.0,
          "Vaccine_Take": 1,
          "Vaccine_Type": "AcquisitionBlocking",
          "Waning_Config": {
            "class": "WaningEffectBox",
            "Initial_Effect": 1,
            "Box_Duration": 200
          }
        }
      }
    }
  ]
}