"""
This module contains functionality for diagnostic survey interventions.
"""
import random
import emod_api.interventions.utils as utils
from emod_api import schema_to_class as s2c
from emod_api.interventions.common import *
from emodpy_malaria.interventions.common import _malaria_diagnostic, add_campaign_event
[docs]def add_diagnostic_survey(
campaign,
coverage: float = 1,
repetitions: int = 1,
tsteps_btwn_repetitions: int = 365,
target: object = 'Everyone',
start_day: int = 1,
diagnostic_type: str = 'BLOOD_SMEAR_PARASITES',
diagnostic_threshold: float = 40,
measurement_sensitivity: float = 0.1,
event_name: str = "Diagnostic Survey",
node_ids: list = None,
positive_diagnosis_configs: list = None,
negative_diagnosis_configs: list = None,
received_test_event: str = 'Received_Test',
ind_property_restrictions: list = None,
disqualifying_properties: list = None,
trigger_condition_list: list = None,
listening_duration: int = -1,
triggered_campaign_delay: int = 0,
check_eligibility_at_trigger: bool = False,
expire_recent_drugs: any = None):
"""
Add an intervention to create either a scheduled or a triggered event to the
campaign using the
:py:class:`~emodpy_malaria.interventions.common.MalariaDiagnostic` class, an
individual-level class, to test individuals. Upon positive or negative
diagnosis, the list of events to occur (as defined in
**positive_diagnosis_configs** or **negative_diagnosis_configs**) is then executed.
These events can trigger other listening interventions.
Args:
camp: The :py:obj:`emod_api:emod_api.campaign` object for building,
modifying, and writing campaign configuration files.
coverage: The probability an individual receives the diagnostic.
repetitions: Number of repetitions of the survey intervention.
tsteps_btwn_repetitions: Timesteps between repetitions.
target: A dictionary targeting an age range and gender of
individuals for treatment. In the format
``{"agemin": x, "agemax": y, "gender": z}``. Default is Everyone.
start_day: The day of the simulation on which the intervention is created.
If triggered, runs on trigger, not on **start_day**.
diagnostic_type: Type of malaria diagnostic used. Default is
**BLOOD_SMEAR_PARASITES**. Available options are:
* BLOOD_SMEAR_PARASITES
* BLOOD_SMEAR_GAMETOCYTES
* PCR_PARASITES
* PCR_GAMETOCYTES
* PF_HRP2
* TRUE_INFECTION_STATUS
* TRUE_PARASITE_DENSITY
* FEVER
diagnostic_threshold: The diagnostic detection threshold based on
**diagnostic_type**:
TRUE_INFECTION_STATUS
BLOOD_SMEAR_PARASITES
In parasites/microliter, use measurement = float( 1.0 / measurementSensitivity *
Poisson(measurementSensitivity * true_parasite_density)).
BLOOD_SMEAR_GAMETOCYTES
In gametocytes/microliter, use measurement = float( 1.0 / measurementSensitivity *
Poisson(measurementSensitivity * true_gametocyte_density)).
PCR_PARASITES and PCR_GAMETOCYTES
Use the true values and an algorithm based on the paper
`Improving statistical inference on pathogen densities estimated by
quantitative molecular methods : malaria gametocytaemia as a case study
<https://doi.org/10.1186/s12859-014-0402-2>`_.
PF_HRP2
Add a new method to get the PfHRP2 value and check against
the threshold.
TRUE_PARASITE_DENSITY
Check the true parasite density against the threshold.
FEVER
Check the person's fever against the threshold.
measurement_sensitivity: Setting for **Measurement_Sensitivity** in
:py:class:`~emodpy_malaria.interventions.common.MalariaDiagnostic`.
event_name: Description of the event.
node_ids: The list of nodes to apply this intervention to (**Node_List**
parameter). If not provided, set value of NodeSetAll.
positive_diagnosis_configs: List of events to happen to an individual
who receives a positive result from test.
negative_diagnosis_configs: List of events to happen to individual who
receives a negative result from test.
received_test_event: String for individuals to broadcast upon receiving
diagnostic.
ind_property_restrictions: List of IndividualProperty key:value pairs that
individuals must have to receive the diagnostic intervention.
For example, ``[{"IndividualProperty1":"PropertyValue1"},
{"IndividualProperty2":"PropertyValue2"}]``. Default is no
restrictions.
disqualifying_properties: List of IndividualProperty key:value pairs that
cause an intervention to be aborted. For example,
``[{"IndividualProperty1":"PropertyValue1"},
{"IndividualProperty2":"PropertyValue2"}]``.
trigger_condition_list: List of events that will trigger a diagnostic survey.
listening_duration: Duration after start day to stop listening for events, as
specified in **trigger_condition_list**. Default is -1, non-stop
listening.
triggered_campaign_delay: Delay of running the intervention after receiving
a trigger from the **trigger_condition_list**.
check_eligibility_at_trigger: If triggered event is delayed, you have an
option to check individual/node's eligibility at the initial trigger
or when the event is actually distributed after delay.
expire_recent_drugs: Adds ``[{"DrugStatus:None"}]`` to
**Property_Restrictions_Within_Node** for positive test config, so
only those with that property receive drugs.
Returns:
None
"""
if ind_property_restrictions is None:
ind_property_restrictions = []
if disqualifying_properties is None:
disqualifying_properties = []
received_test_event = BroadcastEvent(campaign, Event_Trigger=received_test_event)
tested_positive = BroadcastEvent(campaign, Event_Trigger="TestedPositive")
tested_negative = BroadcastEvent(campaign, Event_Trigger="TestedNegative")
tested_positive_tether = "TestedPositive_{}".format(random.randint(1, 100000))
tested_negative_tether = "TestedNegative_{}".format(random.randint(1, 100000))
intervention_cfg = _malaria_diagnostic(
campaign,
measurement_sensitivity=measurement_sensitivity,
detection_threshold=diagnostic_threshold,
diagnostic_type=diagnostic_type)
bcast = BroadcastEvent(campaign, Event_Trigger=tested_positive_tether)
mid = MultiInterventionDistributor(campaign, Intervention_List=[tested_positive, bcast])
intervention_cfg.Positive_Diagnosis_Config = mid
intervention_cfg.Negative_Diagnosis_Config = MultiInterventionDistributor(
campaign, Intervention_List=[tested_negative, BroadcastEvent(campaign, Event_Trigger=tested_negative_tether)])
interventions = [intervention_cfg, received_test_event]
gender = "All"
age_min = 0
age_max = 9.3228e+35
if target != "Everyone" and isinstance(target, dict):
try:
age_min = target["agemin"]
age_max = target["agemax"]
if 'gender' in target:
gender = target["gender"]
target = "ExplicitAgeRangesAndGender"
else:
target = "ExplicitAgeRanges"
except KeyError:
raise KeyError("Unknown target_group parameter. Please pass in 'Everyone' or a dictionary of "
"{'agemin' : x, 'agemax' : y, 'gender': 'Female'} to target to individuals between x and "
"y years of age, and (optional) gender.\n")
if trigger_condition_list:
if listening_duration == -1:
diagnosis_config_listening_duration = -1
else:
diagnosis_config_listening_duration = listening_duration + 1
# if once triggered, you want the diagnostic survey to repeat or if there is a delay (or both)
# this creates a series of broadcast events that once triggered send out "Diagnostic_Survey_Now"
# at pre-determined intervals
if repetitions > 1 or triggered_campaign_delay > 0:
# create a trigger for each of the delays.
trigger_ind_property_restrictions = []
if check_eligibility_at_trigger:
trigger_ind_property_restrictions = ind_property_restrictions
ind_property_restrictions = []
broadcast_event = "Diagnostic_Survey_Now_{}".format(random.randint(1, 100000))
for x in range(repetitions):
tcde = TriggeredCampaignEvent(
campaign,
Start_Day=start_day + 1,
Event_Name="Diag_Survey_Now",
Node_Ids=node_ids,
Triggers=trigger_condition_list,
Duration=listening_duration,
Intervention_List=[BroadcastEvent(campaign, broadcast_event)],
Property_Restrictions=trigger_ind_property_restrictions,
Delay=triggered_campaign_delay + (x * tsteps_btwn_repetitions))
campaign.add(tcde)
trigger_condition_list = [broadcast_event]
survey_event = TriggeredCampaignEvent(
campaign,
Start_Day=start_day + 1,
Event_Name=event_name,
Node_Ids=node_ids,
Triggers=trigger_condition_list,
Target_Residents_Only=1,
Duration=listening_duration,
Demographic_Coverage=coverage,
Target_Age_Min=age_min,
Target_Age_Max=age_max,
Target_Gender=gender,
Property_Restrictions=ind_property_restrictions,
Disqualifying_Properties=disqualifying_properties,
Intervention_List=interventions)
campaign.add(survey_event)
else:
diagnosis_config_listening_duration = listening_duration
add_campaign_event(
campaign,
start_day=start_day + 1,
node_ids=node_ids,
ind_property_restrictions=ind_property_restrictions,
repetitions=repetitions,
timesteps_between_repetitions=tsteps_btwn_repetitions,
demographic_coverage=coverage,
target_age_min=age_min,
target_age_max=age_max,
target_gender=gender,
individual_intervention=interventions)
if expire_recent_drugs:
if ind_property_restrictions:
for property_restriction in ind_property_restrictions:
property_restriction["DrugStatus"] = "None"
else:
ind_property_restrictions = [{"DrugStatus": "None"}]
if positive_diagnosis_configs:
tested_positive_event = TriggeredCampaignEvent(
campaign,
Start_Day=start_day,
Event_Name=event_name + "Positive Result Action",
Node_Ids=node_ids,
Duration=diagnosis_config_listening_duration,
Property_Restrictions=ind_property_restrictions,
Triggers=[tested_positive_tether],
Intervention_List=positive_diagnosis_configs
)
campaign.add(tested_positive_event)
if negative_diagnosis_configs:
tested_negative_event = TriggeredCampaignEvent(
campaign,
Start_Day=start_day,
Event_Name=event_name + "Negative Result Action",
Node_Ids=node_ids,
Duration=diagnosis_config_listening_duration,
Triggers=[tested_negative_tether],
Intervention_List=negative_diagnosis_configs
)
campaign.add(tested_negative_event)
return