diff --git a/src/hivpy/column_names.py b/src/hivpy/column_names.py
index e7bed50..589bf3f 100644
--- a/src/hivpy/column_names.py
+++ b/src/hivpy/column_names.py
@@ -28,7 +28,6 @@
 LONG_TERM_PARTNER = "long_term_partner"         # bool: True if the subject has a long term condomless partner
 LTP_LONGEVITY = "ltp_longevity"                 # int: categorises longevity of long term partnerships (higher => more stable)
 LTP_MONOGAMOUS = "ltp_monogamous"               # bool: True if a person's long term partner has not short term partners o/w false
-RISK_LTP = "risk_ltp"                           # float: Float risk of long-term partner becoming infected
 LOW_FERTILITY = "low_fertility"                 # bool: True if a woman is considered to have a 0% chance of pregnancy, o/w False
 PREGNANT = "pregnant"                           # bool: True if a woman is currently pregnant
 ANC = "anc"                                     # bool: True if in antenatal care
diff --git a/src/hivpy/hiv_status.py b/src/hivpy/hiv_status.py
index e26e7e8..1a6e187 100644
--- a/src/hivpy/hiv_status.py
+++ b/src/hivpy/hiv_status.py
@@ -44,6 +44,7 @@ def __init__(self):
                                  SexType.Female: 1}
         self.incidence = {SexType.Male: 0,
                           SexType.Female: 0}
+        
         self.women_transmission_factor = rng.choice([1., 1.5, 2.], p=[0.05, 0.25, 0.7])
         self.young_women_transmission_factor = rng.choice([1., 2., 3.]) * self.women_transmission_factor
         self.sti_transmission_factor = rng.choice([2., 3.])
@@ -93,7 +94,6 @@ def init_HIV_variables(self, population: Population):
         population.init_variable(col.HIV_STATUS, False)
         population.init_variable(col.LTP_STATUS, False)
         population.init_variable(col.LTP_MONOGAMOUS, False)
-        population.init_variable(col.RISK_LTP, 0.0)
         population.init_variable(col.DATE_HIV_INFECTION, None)
         population.init_variable(col.IN_PRIMARY_INFECTION, False)
         population.init_variable(col.CD4, 0.0)
@@ -391,27 +391,18 @@ def calculate_infected_ltp_monogamous(sex, age_group, size):
                             fold_change_w if r < 0.33 else
                             fold_change_w * 5 if r > 0.67 else
                             fold_change_w * 3
-                                        )
+                        )
                     risk_ltp[i] = risk_ltp[i] * fold_change_w
 
-            population.set_present_variable(col.RISK_LTP, risk_ltp)
-
             # higher transmission risk in people with STI
             if len(monogamous_people_with_sti) > 0:
-                risk_ltp_sti = population.get_variable(col.RISK_LTP, sub_pop=monogamous_people_with_sti)
                 fold_change_sti = np.array(
-                    [2 if r < 0.333 else 5 if r > 0.67 else 3 for r in rng.uniform(0, 1, len(risk_ltp_sti))])
-                risk_ltp_sti = risk_ltp_sti * fold_change_sti
-                population.set_present_variable(col.RISK_LTP, risk_ltp_sti, monogamous_people_with_sti)
-
-            ltp_infected = rng.uniform(0, 1, size) < population.get_variable(
-                    col.RISK_LTP,
-                    sub_pop=population.get_sub_pop([
-                        (col.SEX, op.eq, sex),
-                        (col.AGE_GROUP, op.eq, age_group),
-                        (col.LONG_TERM_PARTNER, op.eq, True),
-                        (col.LTP_MONOGAMOUS, op.eq, True)
-                    ]))
+                    [2 if r < 0.333 else 5 if r > 0.67 else 3
+                        for r in rng.uniform(0, 1, len(monogamous_people_with_sti))]
+                    )
+                risk_ltp[monogamous_people_with_sti] = risk_ltp[monogamous_people_with_sti] * fold_change_sti
+ 
+            ltp_infected = rng.uniform(0, 1, size) < risk_ltp[monogamous_people_hiv_pos]
 
             return ltp_infected
 
@@ -476,7 +467,7 @@ def set_initial_viral_load(person):
 
         def set_initial_CD4(person):
             sqrt_cd4 = self.initial_mean_sqrt_cd4 - (1.5 * person[col.VIRAL_LOAD]) + rng.normal(0, 2) \
-                       - (person[col.AGE] - 35)*0.05
+                - (person[col.AGE] - 35)*0.05
             upper_sqrt_cd4 = np.sqrt(1500)
             lower_sqrt_cd4 = 18
             sqrt_cd4 = min(upper_sqrt_cd4, max(sqrt_cd4, lower_sqrt_cd4))  # clamp sqrt_cd4 to be in limits
diff --git a/src/tests/test_hiv_status.py b/src/tests/test_hiv_status.py
index d72e689..32f4c7d 100644
--- a/src/tests/test_hiv_status.py
+++ b/src/tests/test_hiv_status.py
@@ -487,8 +487,9 @@ def test_infection_in_monogamous_ltp():
     HIVM = HIVStatusModule()
     HIVM.ltp_transmission(pop)
 
-    male_risk_ltp = pop.get_variable(col.RISK_LTP, sub_pop=male_sample)
-    female_risk_ltp = pop.get_variable(col.RISK_LTP, sub_pop=female_sample)
+    #male_risk_ltp = HIVM.ltp_transmission(pop).calculate_risk_ltp(male_sample)
+    #female_risk_ltp = HIVM.ltp_transmission(pop).calculate_risk_ltp(female_sample)
+    
 
-    assert (0 <= np.max(male_risk_ltp) <= 1.42)
-    assert (0 <= np.max(female_risk_ltp) <= 16.2)
+    #assert (0 <= np.max(male_risk_ltp) <= 1.42)
+    #assert (0 <= np.max(female_risk_ltp) <= 16.2)