Add and update measles modifications

covid_data/disease_measles.yml

@@ -1,28 +1,26 @@
 name: Measles
-infection_rate: 0.1
+infection_rate: 0.02
 mortality:
-  - [4.5, 0.001]     # Mortality rate for children under 5 years old
-  - [14.5, 0.02]     # Mortality rate for children aged 5-14 years
-  - [24.5, 0.1]      # Mortality rate for individuals aged 15-24 years
-  - [34.5, 0.3]      # Mortality rate for individuals aged 25-34 years
-  - [44.5, 0.5]      # Mortality rate for individuals aged 35-44 years
-  - [54.5, 1.0]      # Mortality rate for individuals aged 45-54 years
-  - [64.5, 5.0]      # Mortality rate for individuals aged 55-64 years
-  - [74.5, 10.0]     # Mortality rate for individuals aged 65-74 years
-  - [84.5, 20.0]     # Mortality rate for individuals aged 75-84 years
-  - [999, 50.0]      # Mortality rate for individuals aged 85 and older
+  - [4.5, 0.83]     # Mortality rate for children under 5 years old
+  - [14.5, 0.47]    # Mortality rate for children aged 5-14 years
+  - [24.5, 0.5]     # Mortality rate for individuals aged 15-24 years
+  - [34.5, 0.66]    # Mortality rate for individuals aged 25-34 years
+  - [44.5, 0.66]    # Mortality rate for individuals aged 35-44 years
+  - [54.5, 0.67]    # Mortality rate for individuals aged 45-54 years
+  - [64.5, 0.7]     # Mortality rate for individuals aged 55-64 years
+  - [74.5, 0.72]    # Mortality rate for individuals aged 65-74 years
+  - [84.5, 0.78]    # Mortality rate for individuals aged 75-84 years
 
 hospitalised:
-  - [4.5, 0.01]     # Hospitalisation rate for children under 5 years old
-  - [14.5, 0.02]    # Hospitalisation rate for children aged 5-14 years
-  - [24.5, 0.03]    # Hospitalisation rate for individuals aged 15-24 years
-  - [34.5, 0.04]    # Hospitalisation rate for individuals aged 25-34 years
-  - [44.5, 0.05]    # Hospitalisation rate for individuals aged 35-44 years
-  - [54.5, 0.06]    # Hospitalisation rate for individuals aged 45-54 years
-  - [64.5, 0.08]    # Hospitalisation rate for individuals aged 55-64 yearsgit
-  - [74.5, 0.1]     # Hospitalisation rate for individuals aged 65-74 years
-  - [84.5, 0.15]    # Hospitalisation rate for individuals aged 75-84 years
-  - [999, 0.2]      # Hospitalisation rate for individuals aged 85 and older
+  - [4.5, 0.89]     # Hospitalisation rate for children under 5 years old
+  - [14.5, 0.82]    # Hospitalisation rate for children aged 5-14 years
+  - [24.5, 0.87]    # Hospitalisation rate for individuals aged 15-24 years
+  - [34.5, 0.96]    # Hospitalisation rate for individuals aged 25-34 years
+  - [44.5, 0.85]    # Hospitalisation rate for individuals aged 35-44 years
+  - [54.5, 0.72]    # Hospitalisation rate for individuals aged 45-54 years
+  - [64.5, 0.77]    # Hospitalisation rate for individuals aged 55-64 yearsgit
+  - [74.5, 0.83]    # Hospitalisation rate for individuals aged 65-74 years
+  - [84.5, 0.89]    # Hospitalisation rate for individuals aged 75-84 years
 
 mortality_period: 7.0           # Measles mortality typically occurs 7 to 10 days after symptom onset due to complications like pneumonia or encephalitis.
 recovery_period: 21.0           # Measles recovery lasts about 2 to 3 weeks from symptom onset as individuals gradually recover.
@@ -33,9 +31,9 @@ immunity_duration: 9125.0       # Natural immunity after measles recovery is usu
 immunity_fraction: 0.8          # The initial fraction of the population that is immune to measles due to vaccination or prior infection.
 genotypes:
   D4:
-    infection_rate: 0.12
+    infection_rate: 0.02
   B3:
-    infection_rate: 0.15
+    infection_rate: 0.04
   H1:
-    infection_rate: 0.19
-
+    infection_rate: 0.07
+

covid_data/vaccinations.yml

@@ -3,13 +3,7 @@ vaccine_effect_time: 21 # time between receiving vaccine and immunity conferred
 vaccine_immunity_duration: 287 # average time that vaccines give immunity to persons.
 antivax_fraction: 0.05
 
-1/12/2020:
-  vaccines_per_day: 500 # Total no. of vaccines handed out daily.
-  vaccine_age_limit: 70 # age limit for preferred category.
-  no_symptoms: 0.6 # relative probability that vaccination reduces COVID infection to mild and asymptomatic, given that infection does take place.
-  no_transmission: 0.5 # relative probability that vaccination prevents COVID altogether.
-
-1/2/2021:
+1/3/2024:
   vaccines_per_day: 1200
   vaccine_age_limit: 60
   no_symptoms: 0.8 # Source: Israel study on Delta - https://twitter.com/segal_eran/status/1418260295550742528
@@ -20,14 +14,3 @@ antivax_fraction: 0.05
     no_symptoms: 0.75
     no_transmission: 0.6
 
-1/3/2021:
-  vaccines_per_day: 1800
-  vaccine_age_limit: 16
-  booster:
-    boosters_per_day: 50
-
-1/4/2021:
-  no_symptoms: 0.8 # Source: Israel study on Delta - https://twitter.com/segal_eran/status/1418260295550742528
-  no_transmission: 0.4
-  booster:
-    boosters_per_day: 500

dump_nearest_locations.py

@@ -59,7 +59,7 @@
     print("age distribution in system:", e.ages, file=sys.stderr)
 
     e.disease = read_disease_yml.read_disease_yml(
-        "{}/disease_covid19.yml".format(data_dir)
+        "{}/disease_measles.yml".format(data_dir)
     )
 
     building_file = "{}/{}_buildings.csv".format(data_dir, location)

facs/base/person.py

@@ -36,8 +36,8 @@
     vac_data = yaml.safe_load(f)
     antivax_chance = vac_data["antivax_fraction"]
 
-immune_duration = read_disease_yml("covid_data/disease_covid19.yml").immunity_duration
-immunity_fraction = read_disease_yml("covid_data/disease_covid19.yml").immunity_fraction
+immune_duration = read_disease_yml("covid_data/disease_measles.yml").immunity_duration
+immunity_fraction = read_disease_yml("covid_data/disease_measles.yml").immunity_fraction
 
 
 @dataclass

run.py

@@ -33,14 +33,14 @@ def parse_arguments() -> dict:
         "-m",
         "--measures_yml",
         action="store",
-        default="measures_uk",
+        default="measures_lt",
         help="Input YML file containing interventions.",
     )
     parser.add_argument(
         "-d",
         "--disease_yml",
         action="store",
-        default="disease_covid19",
+        default="disease_measles",
         help="Input YML file containing disease specification.",
     )
     parser.add_argument(

validate.py

@@ -15,7 +15,7 @@
 def load_output_data(out_dir):
     """Load the output data from the FACS model."""
 
-    filename = f"{out_dir}/out.csv"
+    filename = f"{out_dir}/klaipeda-measures_lt.csv"
     facs_output = pd.read_csv(filename, sep=",", encoding="latin1")
 
     return facs_output
@@ -35,7 +35,7 @@ def validate():
 
     d_sim = load_output_data(sys.argv[1])
     d_adm = load_admissions_data(sys.argv[1])
-    start_date = datetime.strptime("1/3/2020", "%d/%m/%Y")
+    start_date = datetime.strptime("2/7/2023", "%d/%m/%Y")
 
     # Validation data preprocessing.
     d_adm["date"] = pd.to_datetime(d_adm["date"], format="%d/%m/%Y")
@@ -48,12 +48,14 @@ def validate():
     for _, row in d_adm.iterrows():
         day = int(row["days"])
         adm = int(row["admissions"])
-        adm_sim = d_sim.loc[d_sim["#time"] == day]["num hospitalisations today"].values[
-            0
-        ]
-        validation_table["days"].append(day)
-        validation_table["admissions"].append(adm)
-        validation_table["admissions sim"].append(adm_sim)
+        print(f"Checking for day: {day}")  # Debugging statement
+        if not d_sim.loc[d_sim["#time"] == day].empty:
+            adm_sim = d_sim.loc[d_sim["#time"] == day]["num hospitalisations today"].values[0]
+            validation_table["days"].append(day)
+            validation_table["admissions"].append(adm)
+            validation_table["admissions sim"].append(adm_sim)
+        else:
+            print(f"No matching record for day {day} in simulation output.")  # Debugging statement
 
     # conversion from dict to DF.
     d_val = pd.DataFrame.from_dict(validation_table)