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Parameters Reference Guide

This guide explains all parameters available in antigen-prime, organized by functional category. Parameters are configured in the src/main/resources/parameters.yml file, which overrides default values defined in the code.

Simulation Control Parameters

Basic Simulation Settings

Parameter Default Description
burnin 0 Days before logging output and fitness computation (allows system to reach equilibrium)
endDay 5000 Total number of days to simulate
deltaT 0.1 Time step size in days (0.1 = 2.4 hours per step)
printStep 10 Output frequency - write to timeseries every N days
repeatSim true Whether to repeat simulation until endDay is reached if population dies out

Usage Notes: - Use burnin > 0 to exclude initial transient dynamics from output; internal-node fitness (getAverageRisk) is also skipped during burnin, reducing computation cost - When burnin == 0 fitness computation proceeds immediately (identical to pre-burnin behavior) - Host immunity sampling (sampleHostImmunity) also respects burnin: no immunity output is written until day >= burnin, and the year column in out.histories.csv is burn-in-adjusted (year = 0.0 at end of burnin) - Smaller deltaT gives more accurate results but increases computation time - printStep affects file size - smaller values create larger output files

Output Control

Parameter Default Description
outPath "output/" Directory path for output files
outPrefix "run-" Prefix for all output filenames
reducedOutput false Output only summary and timeseries (minimal files)
detailedOutput false Include detailed host and virus files (enables checkpointing)
restartFromCheckpoint false Load population state from previous detailed output

Memory and Performance

Parameter Default Description
memoryProfiling false Enable memory usage tracking (requires classmexer.jar)

Population Structure Parameters

Metapopulation Settings

Parameter Default Description
demeCount 3 Number of geographic demes (populations)
demeNames ["north", "tropics", "south"] Names for each deme
initialNs [1000000, 1000000, 1000000] Initial population size for each deme

Migration Between Demes

Parameter Default Description
betweenDemePro 0.0005 Fraction of contacts that occur between demes

Example: With betweenDemePro = 0.0005, contacts between demes occur at 0.05% the rate of within-deme contacts.

Host Demographics

Birth and Death Rates

Parameter Default Description
birthRate 0.000091 Births per individual per day (≈30 year lifespan)
deathRate 0.000091 Deaths per individual per day (≈30 year lifespan)
swapDemography true Maintain constant population size by balancing births/deaths

Lifespan Calculation: 1/deathRate days = lifespan. Default 0.000091 = ~30 years.

Epidemiological Parameters

Transmission Dynamics

Parameter Default Description
beta 0.36 Contact rate - contacts per individual per day
nu 0.2 Recovery rate - recoveries per individual per day

Key Relationships: - Infectious period: 1/nu days (default: 5 days) - Basic reproduction number (R₀): Approximately beta/nu in naive population

Initial Conditions

Parameter Default Description
initialI 10 Number of initially infected individuals
initialDeme 2 Index of deme where infection starts (1-indexed)
initialPrR 0.5 Initial proportion of population with immunity

Transcendental Immunity (Optional)

Parameter Default Description
transcendental false Include general recovered class (non-strain-specific immunity)
immunityLoss 0.01 Rate of immunity loss (R→S per individual per day)
initialPrT 0.1 Initial fraction in general recovered class

Seasonal Transmission

Seasonal Patterns by Deme

Parameter Default Description
demeBaselines [1, 1, 1] Baseline transmission multiplier for each deme
demeAmplitudes [0.1, 0, 0.1] Seasonal amplitude for each deme
demeOffsets [0, 0, 0.5] Seasonal phase offset (fraction of year)

Seasonal Formula:

Effective beta = beta × [baseline + amplitude × cos(2π × year + 2π × offset)]

Example: Northern and southern demes have opposite seasonal patterns (offset = 0 vs 0.5).

Virus Evolution Parameters

Phenotype Models

Parameter Default Description
phenotypeSpace "geometric" Phenotype model: "geometric", "geometric3d", "geometric10d", "geometricSeq"
muPhenotype 0.005 Mutation rate per virus per day

Immune Dynamics

Parameter Default Description
waning false Allow immunity to wane over time
waningRate 0.01 Rate of losing random immune memory per day

Geometric Phenotype Parameters

Parameter Default Description
smithConversion 0.1 Multiplier to convert antigenic distance to immunity
homologousImmunity 0.05 Immunity against identical virus
initialTraitA -6 Initial virus position in dimension 1

Mutation Step Sizes

Parameter Default Description
meanStep 0.3 Mean mutation step size for non-epitope sites
sdStep 0.3 Standard deviation of mutation steps for non-epitope sites
mut2D false Allow mutations in full 360° arc (vs. 1D only)
fixedStep false Use fixed step size (ignore sdStep)

Sequence-Based Phenotype Parameters

Sequence Configuration

Parameter Default Description
startingSequence "startingSequence.fasta" FASTA file with initial virus sequence
epitopeSites "epitopeSites.txt" File listing epitope sites (1-indexed)

Mutation Parameters

Parameter Default Description
meanStepEpitope 0.3 Mean mutation step size for epitope sites
sdStepEpitope 0.3 Standard deviation for epitope mutations
transitionTransversionRatio 5.0 Bias toward transitions vs transversions
nonEpitopeAcceptance 1.0 Probability of accepting non-epitope mutations
epitopeAcceptance 1.0 Probability of accepting epitope mutations

Advanced Epitope Options

Parameter Default Description
proportionHighSites 0.2 Fraction of epitope sites with high mutation rates
meanStepEpitopeLow 0.3 Mean step size for "low" epitope sites
sdStepEpitopeLow 0.3 Standard deviation for "low" epitope sites
meanStepEpitopeHigh 0.3 Mean step size for "high" epitope sites
sdStepEpitopeHigh 0.3 Standard deviation for "high" epitope sites

DMS Integration (Optional)

Parameter Default Description
DMSFile null CSV file with Deep Mutational Scanning fitness data

DMS File Format: Must have 21 columns (site number + 20 amino acid preferences) with one row per amino acid site.

Sampling and Analysis Parameters

Virus Sampling

Parameter Default Description
tipSamplingRate 0.0002 Samples collected per deme per day
tipSamplesPerDeme 1000 Maximum samples stored per deme
tipSamplingProportional true Sample proportional to prevalence vs. uniform
treeProportion 0.1 Fraction of samples used in phylogenetic reconstruction

Diversity Analysis

Parameter Default Description
diversitySamplingCount 1000 Samples for calculating diversity statistics
netauWindow 100 Window size (days) for Ne×τ calculation
yearsFromMK 1.0 Time window for Muller-Kreitman analysis
pcaSamples false Apply PCA rotation to virus tree

Host Immunity Sampling

Parameter Default Description
sampleHostImmunity false Record host immunity throughout simulation
printHostImmunityStep 100 Frequency of immunity sampling (days)
hostImmunitySamplesPerDeme [100, 100, 100] Number of hosts sampled per deme
fitnessSampleSize 10000 Hosts sampled for fitness calculations

Memory Analysis

Parameter Default Description
immunityReconstruction false Output detailed immunity reconstruction

Parameter Configuration Tips

Common Research Scenarios

Short-term epidemic (seasonal flu):

endDay: 365
burnin: 50
beta: 0.4
nu: 0.2

Long-term evolution study:

endDay: 7300  # 20 years
burnin: 365   # 1 year
muPhenotype: 0.01

Large population study:

initialNs: [10000000, 5000000, 10000000]  # 25M total
tipSamplingRate: 0.00001  # Reduce sampling

Parameter Relationships

Memory Usage:sum(initialNs) × average immune history length Computation Time:endDay/deltaT × sum(initialNs) Output Size:endDay/printStep × sampling rates

Validation Checks

The model validates parameters on startup: - Sequence length must be multiple of 3 - Epitope sites must be ≤ sequence length / 3 - DMS data rows must match amino acid sequence length - No stop codons except at sequence end

Performance Recommendations

For faster simulations: - Increase deltaT (0.2-0.5) - Increase printStep - Reduce sampling rates - Use smaller populations

For higher accuracy: - Decrease deltaT (0.05-0.1) - Increase diversitySamplingCount - Use longer burnin periods