ReferenceTrackingEventCoordinatorTrackingConfig#
The ReferenceTrackingEventCoordinatorTrackingConfig coordinator class defines a particular prevalence of an individual-level attribute that should be present in a population over time, and a corresponding intervention that will cause individuals to acquire that attribute. The coordinator tracks the actual prevalence of that attribute against the desired prevalence; it will poll the population of nodes it has been assigned to determine how many people have the attribute. When coverage is less than the desired prevalence, it will distribute enough of the designated intervention to reach the desired prevalence. This coordinator is similar to the ReferenceTrackingEventCoordinator, but allows an attribute in the population to be polled, not only the intervention itself having been received. This allows for tracking overall coverage when, potentially, multiple routes exist for individuals to have acquired the same target attribute.
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 |
---|---|---|---|---|---|---|
End_Year |
float |
1900 |
2200 |
2200 |
The final date at which this set of targeted coverages should be applied (expiration). |
{
"End_Year": 1965
}
|
Intervention_Config |
json object |
NA |
NA |
NA |
The nested JSON of the actual intervention to be distributed by this event coordinator. |
{
"Intervention_Config": {
"class": "MaleCircumcision",
"Cost_To_Consumer": 10,
"Circumcision_Reduced_Acquire": 0.6,
"Distributed_Event_Trigger": "VMMC_1"
}
}
|
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. |
{
"Node_Property_Restrictions": [
{
"Place": "URBAN",
"Risk": "MED"
},
{
"Place": "RURAL",
"Risk": "LOW"
}
]
}
|
Property_Restrictions |
array of json objects |
[] |
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. |
{
"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. |
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Demographic |
enum |
NA |
NA |
Everyone |
The target demographic group. Possible values are:
|
{
"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:
|
{
"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": {
"Intervention_Name": "MyVaccine",
"Is_Equal_To": 0,
"class": "HasIntervention"
}
}
|
Time_Value_Map |
json object |
NA |
NA |
NA |
The years (times) and matching values of coverages. This parameter uses InterpolatedValueMap to create a JSON structure containing one array of Times and one for Values, which allows for a time-variable probability that can take on any shape over time. When queried at a simulation year corresponding to one of the listed Times, it returns the corresponding Value. The Times and Values must be of equal length, and can consist of a single value. Times must monotonically increase. |
{
"Time_Value_Map": {
"Times": [
1960,
1961,
1962,
1963,
1964
],
"Values": [
0.25,
0.375,
0.4,
0.4375,
0.46875
]
}
}
|
Tracking_Config |
json object |
NA |
NA |
NA |
Defines the attribute to be tracked within the targeted group; the intervention will be distributed to people without the attribute, if coverage is below the target level the time of polling. |
{
"Tracking_Config": {
"Intervention_Name": "MaleCircumcision",
"Is_Equal_To": 1,
"class": "HasIntervention"
}
}
|
Update_Period |
float |
1 |
3650 |
365 |
The time between distribution updates. |
{
"Update_Period": 30
}
|
Example: Use Tracking_Config to look at men who are not circumcised (by any route, not only via the MaleCircumcision intervention); if coverage is below the target level at the time of polling, apply the MaleCircumcision intervention to uncircumcised men to reach the target coverage.
{
"Use_Defaults": 1,
"Events": [{
"class": "CampaignEventByYear",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Year": 1960,
"Event_Coordinator_Config": {
"class": "ReferenceTrackingEventCoordinatorTrackingConfig",
"Target_Demographic": "ExplicitGender",
"Target_Gender": "Male",
"Update_Period": 182,
"End_Year": 1965,
"Time_Value_Map": {
"Times": [1960, 1961, 1962, 1963, 1964],
"Values": [
0.25,
0.375,
0.4,
0.4375,
0.46875
],
},
"Tracking_Config": {
"class": "IsCircumcised",
"Is_Equal_To": 1,
},
"Intervention_Config": {
"class": "MaleCircumcision",
"Cost_To_Consumer": 10.0,
"Circumcision_Reduced_Acquire": 0.6,
"Distributed_Event_Trigger": "VMMC_1"
}
}
}]
}