Reduce viral load testing for PLHIV on ART

src/tlo/methods/hiv.py

@@ -338,6 +338,11 @@ def __init__(self, name=None, resourcefilepath=None, run_with_checks=False):
             Types.REAL,
             "Probability that a male will be circumcised, if HIV-negative, following testing",
         ),
+        "increase_in_prob_circ_2019": Parameter(
+            Types.REAL,
+            "increase in probability that a male will be circumcised, if HIV-negative, following testing"
+            "from 2019 onwards",
+        ),
         "prob_circ_for_child_before_2020": Parameter(
             Types.REAL,
             "Probability that a male aging <15 yrs will be circumcised before year 2020",
@@ -409,6 +414,10 @@ def __init__(self, name=None, resourcefilepath=None, run_with_checks=False):
             Types.DATA_FRAME,
             "the parameters and values changed in scenario analysis"
         ),
+        "interval_for_viral_load_measurement_months": Parameter(
+            Types.REAL,
+            " the interval for viral load monitoring in months"
+        ),
     }
 
     def read_parameters(self, data_folder):
@@ -593,6 +602,10 @@ def _build_linear_models(self):
             p["prob_circ_after_hiv_test"],
             Predictor("hv_inf").when(False, 1.0).otherwise(0.0),
             Predictor("sex").when("M", 1.0).otherwise(0.0),
+            Predictor("year",
+                      external=True,
+                      conditions_are_mutually_exclusive=True).when("<2019", 1)
+            .otherwise(p["increase_in_prob_circ_2019"])
         )
 
         # Linear model for circumcision for male and aging <15 yrs who spontaneously presents for VMMC
@@ -2414,7 +2427,8 @@ def apply(self, person_id, squeeze_factor):
                     # If person is a man, and not circumcised, then consider referring to VMMC
                     if (person["sex"] == "M") & (~person["li_is_circ"]):
                         x = self.module.lm["lm_circ"].predict(
-                            df.loc[[person_id]], self.module.rng
+                            df.loc[[person_id]], self.module.rng,
+                            year=self.sim.date.year,
                         )
                         if x:
                             self.sim.modules["HealthSystem"].schedule_hsi_event(
@@ -2873,13 +2887,15 @@ def do_at_continuation(self, person_id):
 
         df = self.sim.population.props
         person = df.loc[person_id]
+        p = self.module.parameters
 
         # default to person stopping cotrimoxazole
         df.at[person_id, "hv_on_cotrimoxazole"] = False
 
         # Viral Load Monitoring
         # NB. This does not have a direct effect on outcomes for the person.
-        _ = self.get_consumables(item_codes=self.module.item_codes_for_consumables_required['vl_measurement'])
+        if self.module.rng.random_sample(size=1) < p['dispensation_period_months'] / p['interval_for_viral_load_measurement_months']:
+            _ = self.get_consumables(item_codes=self.module.item_codes_for_consumables_required['vl_measurement'])
 
         # Check if drugs are available, and provide drugs:
         drugs_available = self.get_drugs(age_of_person=person["age_years"])