New analysis functionality for the maternal and newborn health modules (intervention analysis)

src/tlo/methods/newborn_outcomes.py

@@ -523,28 +523,23 @@ def apply_risk_of_congenital_anomaly(self, child_id):
 
         if self.rng.random_sample() < params['prob_congenital_heart_anomaly']:
             self.congeintal_anomalies.set(child_id, 'heart')
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'congenital_heart_anomaly'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['congenital_heart_anomaly'] += 1
 
         if self.rng.random_sample() < params['prob_limb_musc_skeletal_anomaly']:
             self.congeintal_anomalies.set(child_id, 'limb_musc_skeletal')
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'limb_or_musculoskeletal_anomaly'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['limb_or_musculoskeletal_anomaly'] += 1
 
         if self.rng.random_sample() < params['prob_urogenital_anomaly']:
             self.congeintal_anomalies.set(child_id, 'urogenital')
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'urogenital_anomaly'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['urogenital_anomaly'] += 1
 
         if self.rng.random_sample() < params['prob_digestive_anomaly']:
             self.congeintal_anomalies.set(child_id, 'digestive')
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'digestive_anomaly'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['digestive_anomaly'] += 1
 
         if self.rng.random_sample() < params['prob_other_anomaly']:
             self.congeintal_anomalies.set(child_id, 'other')
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'other_anomaly'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['other_anomaly'] += 1
 
     def apply_risk_of_neonatal_infection_and_sepsis(self, child_id):
         """
@@ -558,9 +553,7 @@ def apply_risk_of_neonatal_infection_and_sepsis(self, child_id):
         # The linear model calculates the individuals probability of early_onset_neonatal_sepsis
         if self.eval(self.nb_linear_models['early_onset_neonatal_sepsis'], child_id):
             df.at[child_id, 'nb_early_onset_neonatal_sepsis'] = True
-
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'early_onset_sepsis'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['early_onset_sepsis'] += 1
 
     def apply_risk_of_encephalopathy(self, child_id, timing):
         """
@@ -592,8 +585,7 @@ def apply_risk_of_encephalopathy(self, child_id, timing):
             else:
                 df.at[child_id, 'nb_encephalopathy'] = 'severe_enceph'
 
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': f'{df.at[child_id, "nb_encephalopathy"]}'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter[f'{df.at[child_id, "nb_encephalopathy"]}'] += 1
 
             # Check all encephalopathy cases receive a grade
             if df.at[child_id, 'nb_encephalopathy'] == 'none':
@@ -616,9 +608,7 @@ def apply_risk_of_preterm_respiratory_distress_syndrome(self, child_id):
         # Use the linear model to calculate individual risk and make changes
         if self.eval(self.nb_linear_models['rds_preterm'], child_id):
             df.at[child_id, 'nb_preterm_respiratory_distress'] = True
-
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'respiratory_distress_syndrome'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['respiratory_distress_syndrome'] += 1
 
     def apply_risk_of_not_breathing_at_birth(self, child_id):
         """
@@ -638,9 +628,7 @@ def apply_risk_of_not_breathing_at_birth(self, child_id):
         # explicitly modelled
         elif self.rng.random_sample() < params['prob_failure_to_transition']:
             df.at[child_id, 'nb_not_breathing_at_birth'] = True
-
-            logger.info(key='newborn_complication', data={'newborn': child_id,
-                                                          'type': 'not_breathing_at_birth'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['not_breathing_at_birth'] += 1
 
     def scheduled_week_one_postnatal_event(self, individual_id):
         """
@@ -912,8 +900,11 @@ def kangaroo_mother_care(self, hsi_event):
         if (df.at[person_id, 'nb_low_birth_weight_status'] != 'normal_birth_weight') or \
            (df.at[person_id, 'nb_low_birth_weight_status'] != 'macrosomia'):
 
+            kmc_delivered = pregnancy_helper_functions.check_int_deliverable(
+            self, int_name='kmc', hsi_event=hsi_event, q_param=[params['prob_kmc_available']])
+
             # Check KMC can be delivered
-            if self.rng.random_sample() < params['prob_kmc_available']:
+            if kmc_delivered:
                 # Store treatment as a property of the newborn used to apply treatment effect
                 df.at[person_id, 'nb_kangaroo_mother_care'] = True
 
@@ -964,42 +955,38 @@ def assessment_and_treatment_newborn_sepsis(self, hsi_event, facility_type):
         """
         df = self.sim.population.props
         person_id = int(hsi_event.target)
+        l_params = self.sim.modules['Labour'].current_parameters
+        pnc_location = 'hc' if facility_type == '1a' else 'hp'
 
         # We assume that only hospitals are able to deliver full supportive care for neonatal sepsis, full supportive
         # care evokes a stronger treatment effect than injectable antibiotics alone
 
         if df.at[person_id, 'nb_early_onset_neonatal_sepsis'] or df.at[person_id, 'pn_sepsis_late_neonatal'] or\
            df.at[person_id, 'pn_sepsis_early_neonatal']:
 
-            # Run HCW check
-            sf_check = pregnancy_helper_functions.check_emonc_signal_function_will_run(self.sim.modules['Labour'],
-                                                                                       sf='iv_abx',
-                                                                                       hsi_event=hsi_event)
             if facility_type != '1a':
 
-                # check consumables
-                avail = pregnancy_helper_functions.return_cons_avail(
-                    self, hsi_event,
+                neo_sepsis_treatment_delivered = pregnancy_helper_functions.check_int_deliverable(
+                    self, int_name='neo_sepsis_treatment_supp_care', hsi_event=hsi_event,
+                    q_param=[l_params['prob_hcw_avail_iv_abx'], l_params[f'mean_hcw_competence_{pnc_location}']],
                     cons=self.item_codes_nb_consumables['sepsis_supportive_care_core'],
-                    opt_cons=self.item_codes_nb_consumables['sepsis_supportive_care_optional'])
+                    opt_cons=self.item_codes_nb_consumables['sepsis_supportive_care_optional'],
+                    equipment={'Drip stand', 'Infusion pump'})
 
-                # Then, if the consumables are available, treatment for sepsis is delivered
-                if avail and sf_check:
+                if neo_sepsis_treatment_delivered:
                     df.at[person_id, 'nb_supp_care_neonatal_sepsis'] = True
-                    pregnancy_helper_functions.log_met_need(self, 'neo_sep_supportive_care', hsi_event)
-                    hsi_event.add_equipment({'Drip stand', 'Infusion pump'})
 
             # The same pattern is then followed for health centre care
             else:
-                avail = pregnancy_helper_functions.return_cons_avail(
-                    self, hsi_event,
+                neo_sepsis_treatment_delivered = pregnancy_helper_functions.check_int_deliverable(
+                    self, int_name='neo_sepsis_treatment_abx', hsi_event=hsi_event,
+                    q_param=[l_params['prob_hcw_avail_iv_abx'], l_params[f'mean_hcw_competence_{pnc_location}']],
                     cons=self.item_codes_nb_consumables['sepsis_abx'],
-                    opt_cons=self.item_codes_nb_consumables['iv_drug_equipment'])
+                    opt_cons=self.item_codes_nb_consumables['iv_drug_equipment'],
+                    equipment={'Drip stand', 'Infusion pump'})
 
-                if avail and sf_check:
+                if neo_sepsis_treatment_delivered:
                     df.at[person_id, 'nb_inj_abx_neonatal_sepsis'] = True
-                    pregnancy_helper_functions.log_met_need(self, 'neo_sep_abx', hsi_event)
-                    hsi_event.add_equipment({'Drip stand', 'Infusion pump', 'Oxygen cylinder, with regulator'})
 
     def link_twins(self, child_one, child_two, mother_id):
         """
@@ -1021,6 +1008,7 @@ def link_twins(self, child_one, child_two, mother_id):
                       'date_of_delivery': self.sim.date}
 
         logger.info(key='twin_birth', data=twin_birth, description='A record of each birth of twin pairs')
+        self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['twin_birth'] += 1
 
         # Finally we log the second live birth and add another to the womans parity
         df.at[mother_id, 'la_parity'] += 1
@@ -1157,14 +1145,14 @@ def on_birth(self, mother_id, child_id):
         if (df.at[child_id, 'nb_low_birth_weight_status'] == 'low_birth_weight') or\
             (df.at[child_id, 'nb_low_birth_weight_status'] == 'very_low_birth_weight') or\
            (df.at[child_id, 'nb_low_birth_weight_status'] == 'extremely_low_birth_weight'):
-            logger.info(key='newborn_complication', data={'newborn': child_id, 'type': 'low_birth_weight'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['low_birth_weight'] += 1
 
         elif df.at[child_id, 'nb_low_birth_weight_status'] == 'macrosomia':
-            logger.info(key='newborn_complication', data={'newborn': child_id, 'type': 'macrosomia'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['macrosomia'] += 1
 
         df.at[child_id, 'nb_size_for_gestational_age'] = mni[mother_id]['birth_size']
         if df.at[child_id, 'nb_size_for_gestational_age'] == 'small_for_gestational_age':
-            logger.info(key='newborn_complication', data={'newborn': child_id, 'type': 'small_for_gestational_age'})
+            self.sim.modules['PregnancySupervisor'].mnh_outcome_counter['small_for_gestational_age'] += 1
 
         df.at[child_id, 'nb_early_init_breastfeeding'] = False
         df.at[child_id, 'nb_breastfeeding_status'] = 'none'