repeated translation tags

config file:
# Starting with a properties file because it requires no additional dependencies

exporter.baseDirectory = ./output/
exporter.use_uuid_filenames = false
exporter.subfolders_by_id_substring = false
# number of years of history to keep in exported records, anything older than this may be filtered out
# set years_of_history = 0 to skip filtering altogether and keep the entire history
exporter.years_of_history = 10
# split records allows patients to have one record per provider organization
exporter.split_records = true
exporter.split_records.duplicate_data = false
exporter.ccda.export = true
exporter.fhir.export = true
exporter.fhir_stu3.export = false
exporter.fhir_dstu2.export = false
exporter.fhir.use_shr_extensions = false
exporter.fhir.use_us_core_ig = false
exporter.fhir.transaction_bundle = true
exporter.fhir.bulk_data = false
exporter.groups.fhir.export = false
exporter.hospital.fhir.export = true
exporter.hospital.fhir_stu3.export = false
exporter.hospital.fhir_dstu2.export = false
exporter.practitioner.fhir.export = true
exporter.practitioner.fhir_stu3.export = false
exporter.practitioner.fhir_dstu2.export = false
exporter.encoding = UTF-8
exporter.csv.export = true
# if exporter.csv.append_mode = true, then each run will add new data to any existing CSVs. if false, each run will clear out the files and start fresh
exporter.csv.append_mode = false
# if exporter.csv.folder_per_run = true, then each run will have CSVs placed into a unique subfolder. if false, each run will only use the top-level csv folder
exporter.csv.folder_per_run = true
exporter.cpcds.export = false
exporter.cpcds.append_mode = false
exporter.cpcds.folder_per_run = false
exporter.cpcds.single_payer = false
exporter.cdw.export = false
exporter.text.export = false
exporter.text.per_encounter_export = false
exporter.clinical_note.export = true
exporter.cost_access_outcomes_report = false
exporter.prevalence_report = true
exporter.custom_report = false
# note: prevalence and custom reports require a database (set below)
exporter.custom_report_queries_file = custom_queries.sql
# parameters for symptoms export
exporter.symptoms.csv.export = true
# selection mode of conditions or symptom export: 0 = conditions according to  exporter.years_of_history. other values = all conditions (entire history)
exporter.symptoms.mode = 0
# if exporter.symptoms.csv.append_mode = true, then each run will add new data to any existing CSVs. if false, each run will clear out the files and start fresh
exporter.symptoms.csv.append_mode = false
# if exporter.symptoms.csv.folder_per_run = true, then each run will have CSVs placed into a unique subfolder. if false, each run will only use the top-level csv folder
exporter.symptoms.csv.folder_per_run = false
exporter.symptoms.text.export = false

# the number of patients to generate, by default
# this can be overridden by passing a different value to the Generator constructor
generate.default_population = 1

generate.log_patients.detail = simple
# options are "none", "simple", or "detailed" (without quotes). defaults to simple if another value is used
# none = print nothing to the console during generation
# simple = print patient names once they are generated.
# detailed = print patient names, atributes, vital signs, etc..  May slow down processing

generate.timestep = 604800000
# time is in ms
# 1000 * 60 * 60 * 24 * 7 = 604800000

generate.database_type = file
# options are "file", "in-memory", or "none" (without quotes)
# file = database stored in a file at ./database.mv.db, and results are kept between runs
# in-memory = in-memory DB only, results not kept between runs
# none = no database, limits certain features but increases throughput

# default demographics is every city in the US
generate.demographics.default_file = geography/demographics.csv
generate.geography.zipcodes.default_file = geography/zipcodes.csv
generate.geography.country_code = US
generate.geography.timezones.default_file = geography/timezones.csv
generate.geography.foreign.birthplace.default_file = geography/foreign_birthplace.json

# Lookup Table Folder location
generate.lookup_tables = modules/lookup_tables/

# Set to true if you want every patient to be dead.
generate.only_dead_patients = false
# Set to true if you want every patient to be alive.
generate.only_alive_patients = True
# If both only_dead_patients and only_alive_patients are set to true,
# It they will both default back to false

# if true, tracks and prints out details of transition tables for each module upon completion
# note that this may significantly slow down processing, and is intended primarily for debugging
generate.track_detailed_transition_metrics = false

# If true, person names have numbers appended to them to make them more obviously fake
generate.append_numbers_to_person_names = true

# if true, the entire population will use veteran prevalence data
generate.veteran_population_override = false

# these should add up to 1.0
# weighting and categories are inspired by the following but there are no specific hard numbers to point to
# http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1694190/pdf/amjph00543-0042.pdf
# http://www.ncbi.nlm.nih.gov/pubmed/8122813
generate.demographics.socioeconomic.weights.income = 0.2
generate.demographics.socioeconomic.weights.education = 0.7
generate.demographics.socioeconomic.weights.occupation = 0.1

generate.demographics.socioeconomic.score.low = 0.0
generate.demographics.socioeconomic.score.middle = 0.25
generate.demographics.socioeconomic.score.high = 0.66

generate.demographics.socioeconomic.education.less_than_hs.min = 0.0
generate.demographics.socioeconomic.education.less_than_hs.max = 0.5
generate.demographics.socioeconomic.education.hs_degree.min = 0.1
generate.demographics.socioeconomic.education.hs_degree.max = 0.75
generate.demographics.socioeconomic.education.some_college.min = 0.3
generate.demographics.socioeconomic.education.some_college.max = 0.85
generate.demographics.socioeconomic.education.bs_degree.min = 0.5
generate.demographics.socioeconomic.education.bs_degree.max = 1.0

generate.demographics.socioeconomic.income.poverty = 11000
generate.demographics.socioeconomic.income.high = 75000

generate.birthweights.default_file = birthweights.csv
generate.birthweights.logging = false

# in Massachusetts, the individual insurance mandate became law in 2006
# in the US, the Affordable Care Act become law in 2010,
# and individual and employer mandates took effect in 2014.
# mandate.year will determine when individuals with an occupation score above mandate.occupation
# receive employer mandated insurance (aka "private" insurance).
# prior to mandate.year, anyone with income greater than the annual cost of an insurance plan
# will purchase the insurance.
generate.insurance.mandate.year = 2006
generate.insurance.mandate.occupation = 0.2

# Default Costs, to be used for pricing something that we don't have a specific price for
# -- $500 for procedures is completely invented
generate.costs.default_procedure_cost = 500.00
# -- $255 for medications - also invented
generate.costs.default_medication_cost = 255.00
# -- Encounters billed using avg prices from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3096340/
# -- Adjustments for initial or subsequent hospital visit and level/complexity/time of encounter
# -- not included. Assume initial, low complexity encounter (Tables 4 & 6)
generate.costs.default_encounter_cost = 125.00
# -- https://www.nytimes.com/2014/07/03/health/Vaccine-Costs-Soaring-Paying-Till-It-Hurts.html
# -- currently all vaccines cost $136.
generate.costs.default_immunization_cost = 136.00

# Providers
generate.providers.hospitals.default_file = providers/hospitals.csv
generate.providers.longterm.default_file = providers/longterm.csv
generate.providers.nursing.default_file = providers/nursing.csv
generate.providers.rehab.default_file = providers/rehab.csv
generate.providers.hospice.default_file = providers/hospice.csv
generate.providers.dialysis.default_file = providers/dialysis.csv
generate.providers.homehealth.default_file = providers/home_health_agencies.csv
generate.providers.veterans.default_file = providers/va_facilities.csv
generate.providers.urgentcare.default_file = providers/urgent_care_facilities.csv
generate.providers.primarycare.default_file = providers/primary_care_facilities.csv

# Provider selection behavior
# How patients select a provider organization:
#  nearest - select the closest provider. See generate.providers.maximum_search_distance
#  quality - select the best provider if quality is known. Otherwise nearest.
#  random  - select randomly.
#  network - select the nearest provider in your insurance network. same as random except it changes every time the patient switches insurance provider.
generate.providers.selection_behavior = nearest

# maximum distance to look for a provider for a given patient, in km
# set to 10 degrees lat/lon to support the model that veterans only seek care at VA facilities
generate.providers.maximum_search_distance = 32

# Payers
generate.payers.insurance_companies.default_file = payers/insurance_companies.csv
generate.payers.insurance_companies.medicare = Medicare
generate.payers.insurance_companies.medicaid = Medicaid
generate.payers.insurance_companies.dual_eligible = Dual Eligible

# Payer selection behavior
# How patients select a payer:
#  best_rates - select insurance with best rates for person's existing conditions and medical needs
#  random  - select randomly.
generate.payers.selection_behavior = random

# Experimental feature. Patients will miss care if true, but side-effects of missing that care
# are not handled. Additionally, the path the disease module might take may no longer make sense.
# It might assume things occurred that haven't actually happened it. Use with care.
generate.payers.loss_of_care = false

# Add a FHIR terminology service URL to enable the use of ValueSet URIs within code definitions.
# generate.terminology_service_url = https://r4.ontoserver.csiro.au/fhir

# Quit Smoking
lifecycle.quit_smoking.baseline = 0.01
lifecycle.quit_smoking.timestep_delta = -0.01
lifecycle.quit_smoking.smoking_duration_factor_per_year = 1.0

# Quit Alcoholism
lifecycle.quit_alcoholism.baseline = 0.001
lifecycle.quit_alcoholism.timestep_delta = -0.001
lifecycle.quit_alcoholism.alcoholism_duration_factor_per_year = 1.0

# Adherence
lifecycle.adherence.baseline = 0.05

# set this to true to enable randomized "death by natural causes"
# highly recommended if "only_dead_patients" is true
lifecycle.death_by_natural_causes = false

# set this to enable "death by loss of care" or missed care,
# e.g. not covered by insurance or otherwise unaffordable.
# only functional if "generate.payers.loss_of_care" is also true.
lifecycle.death_by_loss_of_care = false

# Use physiology simulations to generate some VitalSigns
physiology.generators.enabled = false

# Allow physiology module states to be executed
# If false, all Physiology state objects will immediately redirect to the state defined in
# the alt_direct_transition field
physiology.state.enabled = false

# set to true to introduce errors in height, weight and BMI observations for people
# under 20 years old
growtherrors = false
java version: 17 run with ./run_synthea -p 10 -s 111111 --exporter.fhir.export false --exporter.ccda.export true
Lots of translation tags are repeated :(
One example is in a file for a person named Jasper Hirthe, who has many repetitions of the line <translation code="49436004" codeSystem="2.16.840.1.113883.6.96" displayName="Atrial Fibrillation"/>
Is there a way to avoid having these repeated lines?
synthetichealth / synthea

repeated translation tags #992
