HIVPiecewiseByYearandSexDiagnostic¶
The HIVPiecewiseByYearAndSexDiagnostic intervention class builds on HIVSimpleDiagnostic to configure the roll-out of an intervention over time. Unlike HIVSigmoidByYearAndSexDiagnostic, which requires the time trend to have a sigmoid shape, this intervention allows for any trend of time to be configured using piecewise or linear interpolation. The trends over time can be configured differently for males and females. Note that the term “diagnosis” is used because this builds on the diagnostic classes in EMOD. However, this intervention is typically used not like a clinical diagnostic, but more like a trend in behavior or coverage over time.
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 |
|---|---|---|---|---|---|---|
Base_Sensitivity |
float |
0 |
1 |
1 |
The sensitivity of the diagnostic. This sets the proportion of the time that individuals with the condition being tested receive a positive diagnostic test. When set to zero, then individuals who have the condition always receive a false-negative diagnostic test. |
{
"Base_Specificity": 0.95,
"Base_Sensitivity": 0.8
}
|
Base_Specificity |
float |
0 |
1 |
1 |
The specificity of the diagnostic. This sets the proportion of the time that individuals without the condition being tested receive a negative diagnostic test. When set to 1, the diagnostic always accurately reflects the lack of having the condition. When set to zero, then individuals who do not have the condition always receive a false-positive diagnostic test. |
{
"Base_Specificity": 0.95,
"Base_Sensitivity": 0.8
}
|
Cost_To_Consumer |
float |
0 |
3.40282e+38 |
1 |
The unit ‘cost’ assigned to the diagnostic. Setting Cost_To_Consumer to zero for all other interventions, and to a non-zero amount for one intervention, provides a convenient way to track the number of times the intervention has been applied in a simulation. |
{
"Cost_To_Consumer": 0.333
}
|
Days_To_Diagnosis |
float |
0 |
3.40282e+38 |
0 |
The number of days from test until diagnosis. |
{
"Days_To_Diagnosis": 0.0
}
|
Default_Value |
float |
0 |
1 |
0 |
The probability of positive diagnosis if the intervention is used before the earliest specified time in the Time_Value_Map. |
{
"Default_Value": 0
}
|
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
}
|
Enable_IsSymptomatic |
boolean |
0 |
1 |
0 |
If true (1), requires an infection to be symptomatic to return a positive test. |
{
"Enable_IsSymptomatic": 1,
"Base_Specificity": 0.85,
"Base_Sensitivity": 0.92
}
|
Event_Or_Config |
enum |
NA |
NA |
Config |
Specifies whether the current intervention (or a positive diagnosis, depending on the intervention class) distributes a nested intervention (the Config option) or an event will be broadcast which may trigger other interventions in the campaign file (the Event option). Possible values are:
|
{
"Event_Or_Config": "Config"
}
|
Female_Multiplier |
float |
0 |
3.40282e+38 |
1 |
Allows for the probabilities in the Time_Value_Map to be different for males and females, by multiplying the female probabilities by a constant value. |
{
"Female_Multiplier": 1.3
}
|
Interpolation_Order |
integer |
0 |
1 |
0 |
When set to zero, interpolation between values in the Time_Value_Map is zero-order (‘staircase’). When set to 1, interpolation between values in the Time_Value_Map is linear. The final value is held constant for all times after the last time specified in the Time_Value_Map. |
{
"Interpolation_Order": 0
}
|
Intervention_Name |
string |
NA |
NA |
NA |
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": "HIVPiecewiseByYearAndSexDiagnostic",
"Intervention_Name": "Change in health-seeking behavior"
}
}
|
Negative_Diagnosis_Event |
enum |
NA |
NA |
“” |
If an individual tests negative, this specifies an event that may trigger another intervention when the event occurs. Only used when Event_Or_Config is set to Event. See Event list for possible values. |
{
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "PreDebut"
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. 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"
}
|
Positive_Diagnosis_Config |
JSON object |
NA |
NA |
NA |
The intervention distributed to individuals if they test positive. Only used when Event_Or_Config is set to Config. |
{
"Positive_Diagnosis_Config": {
"class": "MultiInterventionDistributor",
"Intervention_List": [
{
"Cost_To_Consumer": 0.333,
"Secondary_Decay_Time_Constant": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"class": "SimpleVaccine",
"Waning_Config": {
"Box_Duration": 3650,
"Initial_Effect": 0.1,
"class": "WaningEffectBox"
}
}
]
}
}
|
Positive_Diagnosis_Event |
enum |
NA |
NA |
“” |
If the test is positive, this specifies an event that can trigger another intervention when the event occurs. Only used if Event_Or_Config is set to Event. See Event list for possible values. |
{
"Intervention_Config": {
"Base_Sensitivity": 1.0,
"Base_Specificity": 1.0,
"Cost_To_Consumer": 0.0,
"Days_To_Diagnosis": 0.0,
"Event_Or_Config": "Event",
"Positive_Diagnosis_Event": "TestedPositive_CureMeNow",
"Treatment_Fraction": 1.0,
"class": "SimpleDiagnostic"
}
}
|
Times |
array of floats |
0 |
999999 |
NA |
An array of years. |
{
"Times": [
1998,
2000,
2003,
2006,
2009
],
"Values": [
0,
0.26,
0.08,
0.14,
0.54
]
}
|
Time_Value_Map |
JSON object |
NA |
NA |
NA |
The years (times) and matching probabilities for test results. This parameter uses InterpolatedValueMap to define Times (by year) and Values for the history and expected treatment guidelines for future years. This creates 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. When queried earlier than the first listed Time, it returns the default Value. When queried in between listed Times, it either returns the Value for the most recent past time (when Interpolation_Order is 0) or linearly interpolates Values between Times (when Interpolation_Order is 1). When queried after the last Time in the list, it returns the last 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": [
1998,
2000,
2003,
2006,
2009
],
"Values": [
0,
0.26,
0.08,
0.14,
0.54
]
}
}
|
Treatment_Fraction |
float |
0 |
1 |
1 |
The fraction of positive diagnoses that are treated. |
{
"Intervention_Config": {
"Base_Sensitivity": 1.0,
"Base_Specificity": 1.0,
"Cost_To_Consumer": 0.0,
"Days_To_Diagnosis": 0.0,
"Event_Or_Config": "Event",
"Positive_Diagnosis_Event": "TestedPositive_CureMeNow",
"Treatment_Fraction": 1.0,
"class": "SimpleDiagnostic"
}
}
|
Values |
array of floats |
0 |
3.40282e+38 |
NA |
An array of values to match the defined Times. |
{
"Times": [
1998,
2000,
2003,
2006,
2009
],
"Values": [
0,
0.26,
0.08,
0.14,
0.54
]
}
|
{
"Campaign_Name": "4b_ImprovedRetention_To_BloodDraw",
"Default_Campaign_Path": "defaults/hiv_default_campaign.json",
"Use_Defaults": 1,
"Events": [
{
"class": "CampaignEventByYear",
"Event_Name": "ARTStaging: state 5 (random choice: Return for CD4 or LTFU)",
"Start_Year": 1990,
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Event_Coordinator_Config": {
"class": "StandardInterventionDistributionEventCoordinator",
"Intervention_Config": {
"class": "NodeLevelHealthTriggeredIV",
"Trigger_Condition_List": [
"ARTStaging5"
],
"Actual_IndividualIntervention_Config": {
"class": "HIVPiecewiseByYearAndSexDiagnostic",
"Disqualifying_Properties": [
"InterventionStatus:LostForever",
"InterventionStatus:OnART",
"InterventionStatus:LinkingToART",
"InterventionStatus:OnPreART",
"InterventionStatus:LinkingToPreART"
],
"New_Property_Value": "InterventionStatus:ARTStaging",
"Days_To_Diagnosis": 0,
"Default_Value": 0,
"Time_Value_Map": {
"Times": [
1990,
2020
],
"Values": [
0.85,
0.9
]
},
"Interpolation_Order": 0,
"Event_Or_Config": "Event",
"Positive_Diagnosis_Event": "ARTStaging6",
"Negative_Diagnosis_Event": "HCTUptakePostDebut9"
}
}
}
}
]
}