diff --git a/docs/source/changes.rst b/docs/source/changes.rst
index 2b502e9f..728e02d7 100644
--- a/docs/source/changes.rst
+++ b/docs/source/changes.rst
@@ -15,6 +15,8 @@ all releases are available on `Anaconda.org
 - :gh:`126` enhances the plot for the channel of infections. The displayed numbers can
   be shares among all infected, among all individuals or seven days incidences per
   100,000 people.
+- :gh:`127` includes better parameters for time-variant sensitivity of rapid tests.
+- :gh:`128` ensures determinacy in the setup of a simulation.
 
 
 0.0.7 - 2021-05-12
diff --git a/src/sid/countdowns.py b/src/sid/countdowns.py
index 3aebcb24..a42ec9b1 100644
--- a/src/sid/countdowns.py
+++ b/src/sid/countdowns.py
@@ -53,8 +53,8 @@
 
 """
 
-COUNTDOWNS_WITHOUT_DRAWS = ("cd_received_rapid_test", "cd_ever_infected")
+COUNTDOWNS_WITHOUT_DRAWS = ("cd_ever_infected", "cd_received_rapid_test")
 """Tuple[str]: Countdowns which do not have draws."""
 
-COUNTDOWNS_WITH_DRAWS = tuple(set(COUNTDOWNS) - set(COUNTDOWNS_WITHOUT_DRAWS))
+COUNTDOWNS_WITH_DRAWS = tuple(sorted(set(COUNTDOWNS) - set(COUNTDOWNS_WITHOUT_DRAWS)))
 """Tuple[str]: Countdowns whose length is a random variable."""
diff --git a/src/sid/initial_conditions.py b/src/sid/initial_conditions.py
index 683cc178..7cbcfc7d 100644
--- a/src/sid/initial_conditions.py
+++ b/src/sid/initial_conditions.py
@@ -234,8 +234,9 @@ def sample_initial_distribution_of_infections_and_immunity(
         )
 
         spread_out_virus_strains = _sample_factorized_virus_strains_for_infections(
-            spread_out_infections,
-            initial_conditions["virus_shares"],
+            spread_out_infections=spread_out_infections,
+            virus_shares=initial_conditions["virus_shares"],
+            seed=next(seed),
         )
 
     else:
@@ -418,8 +419,11 @@ def _spread_out_initial_infections(
 def _sample_factorized_virus_strains_for_infections(
     spread_out_infections: pd.DataFrame,
     virus_shares: Dict[str, Any],
+    seed: int,
 ) -> pd.DataFrame:
     """Convert boolean infections to factorized virus strains."""
+    np.random.seed(seed)
+
     spread_out_virus_strains = pd.DataFrame(
         data=-1,
         index=spread_out_infections.index,