Merge pull request #208 from UCL/prep-usage

Continuous PrEP usage

src/hivpy/column_names.py

@@ -119,22 +119,29 @@
 PREP_LEN_WILLING = "prep_len_willing"           # Bool: True if an individual is willing to use injectable Lenacapavir PrEP
 PREP_VR_WILLING = "prep_vr_willing"             # Bool: True if an individual is willing to use vaginal ring PrEP
 PREP_ANY_WILLING = "prep_any_willing"           # Bool: True if an individual is willing to use at least one type of PrEP
+FAVOURED_PREP_TYPE = "favoured_prep_type"       # None | prep.PrEPType(enum): PrEP type with highest preference an individual is willing to take that is also currently available, o/w None
 PREP_ELIGIBLE = "prep_eligible"                 # Bool: True if an individual is eligible for PrEP usage
+PREP_ORAL_TESTED = "prep_oral_tested"           # Bool: True if an individual has tested explicitly to start oral PrEP (DUMMY)
+PREP_CAB_TESTED = "prep_cab_tested"             # Bool: True if an individual has tested explicitly to start injectable Cab PrEP (DUMMY)
+PREP_LEN_TESTED = "prep_len_tested"             # Bool: True if an individual has tested explicitly to start injectable Len PrEP (DUMMY)
+PREP_VR_TESTED = "prep_vr_tested"               # Bool: True if an individual has tested explicitly to start vaginal ring PrEP (DUMMY)
 PREP_TYPE = "prep_type"                         # None | prep.PrEPType(enum): Oral, Cabotegravir, Lenacapavir, or VaginalRing if PrEP is being used, o/w None
 EVER_PREP = "ever_prep"                         # Bool: True if an individual has ever been on PrEP
 FIRST_ORAL_START_DATE = "first_oral_start_date"     # None | date: start date of first ever oral PrEP usage
 FIRST_CAB_START_DATE = "first_cab_start_date"       # None | date: start date of first ever injectable Cab PrEP usage
 FIRST_LEN_START_DATE = "first_len_start_date"       # None | date: start date of first ever injectable Len PrEP usage
 FIRST_VR_START_DATE = "first_vr_start_date"         # None | date: start date of first ever vaginal ring PrEP usage
 LAST_PREP_START_DATE = "last_prep_start_date"       # None | date: start date of most recent PrEP usage
-PREP_JUST_STARTED = "prep_just_started"         # Bool: True if PrEP usage began this time step (DUMMY)
-PREP_ORAL_TESTED = "prep_oral_tested"           # Bool: True if an individual has tested explicitly to start oral PrEP (DUMMY)
-PREP_CAB_TESTED = "prep_cab_tested"             # Bool: True if an individual has tested explicitly to start injectable Cab PrEP (DUMMY)
-PREP_LEN_TESTED = "prep_len_tested"             # Bool: True if an individual has tested explicitly to start injectable Len PrEP (DUMMY)
-PREP_VR_TESTED = "prep_vr_tested"               # Bool: True if an individual has tested explicitly to start vaginal ring PrEP (DUMMY)
-
-ART_ADHERENCE = "art_adherence"                 # DUMMY
+LAST_PREP_STOP_DATE = "last_prep_stop_date"         # None | date: stop date of most recent PrEP usage
+PREP_JUST_STARTED = "prep_just_started"         # Bool: True if PrEP usage began this time step
+CONT_ON_PREP = "cont_on_prep"                   # None | timedelta: total length of continuous usage of current PrEP based on user intention (breaks due to ineligibility do not count against continuity)
+CONT_ACTIVE_ON_PREP = "cont_active_on_prep"     # None | timedelta: actual total length of continuous usage of current PrEP
+CUMULATIVE_PREP_ORAL = "cumulative_prep_oral"   # None | timedelta: total length of cumulative oral PrEP usage
+CUMULATIVE_PREP_CAB = "cumulative_prep_cab"     # None | timedelta: total length of cumulative injectable Cab PrEP usage
+CUMULATIVE_PREP_LEN = "cumulative_prep_len"     # None | timedelta: total length of cumulative injectable Len PrEP usage
+CUMULATIVE_PREP_VR = "cumulative_prep_vr"       # None | timedelta: total length of cumulative injectable vaginal ring PrEP usage
 
+ART_ADHERENCE = "art_adherence"                 # None | Float: percentage of ART intake that is adhered to
 TA_MUTATION = "tam"                             # X_MUTATION: drug resistance cols (TODO: all 24 currently DUMMIED)
 M184_MUTATION = "m184m"
 K65_MUTATION = "k65m"

src/hivpy/data/prep.yaml

@@ -23,7 +23,11 @@ prep_willing_threshold: 0.2
 prob_test_prep_start:
   Value: [0.25, 0.50, 0.75]
 prob_base_prep_start:
-  Value: [0.05, 0.10, 0.20]
-# FIXME: do we need this to be separate from prob_base_prep_start?
+  Value: [0.10, 0.30]
 prob_prep_restart:
   Value: [0.05, 0.10, 0.20]
+prob_base_prep_stop:
+  Value: [0.05, 0.15, 0.30]
+prob_base_prep_stop_nonuniform:
+  Value: [0.05, 0.15, 0.30]
+  Probability: [0.8, 0.1, 0.1]

src/hivpy/population.py

@@ -271,6 +271,17 @@ def general_func(g):
         # Use Dummy column to in order to enable transform method and avoid any risks to data
         return df.groupby(param_list, dropna=dropna)["Dummy"].transform(general_func)
 
+    def col_apply(self, param_list, func, sub_pop=None):
+        """
+        Applies a function to specific columns in the dataframe.
+        """
+        if sub_pop is not None:
+            df = self.data.loc[sub_pop]
+        else:
+            df = self.data
+        # Lambda function used to extract param column contents
+        return df.apply(lambda x: func(*[x[p] for p in param_list]), axis=1)
+
     def evolve(self, time_step: timedelta):
         """
         Advance the population by one time step.
@@ -287,7 +298,7 @@ def evolve(self, time_step: timedelta):
         if self.HIV_introduced:
             self.hiv_status.set_primary_infection(self)
             self.hiv_status.set_viral_load_groups(self)
-            self.prep.prep_willingness(self)
+            self.prep.prep_propensity(self)
             self.prep.prep_eligibility(self)
 
         if self.circumcision.vmmc_disrup_covid:
@@ -307,7 +318,7 @@ def evolve(self, time_step: timedelta):
             if (n_deaths and self.apply_death):
                 self.drop_from_population(HIV_deaths)
             self.hiv_diagnosis.update_HIV_diagnosis(self)
-            self.prep.prep_usage(self)
+            self.prep.prep_usage(self, time_step)
 
         # Some population cleanup
         self.pregnancy.reset_anc_at_birth(self)