Parameter Categories of MultiMalModPy¶
MultiMalModPy requires users to specify three key types of parameters:
Malaria
Define and align malaria-related inputs across all models to ensure comparability.
This includes key factors influencing malaria transmission dynamics, such as seasonality, case management, and
importation.
Simulation
Specify details for each simulation experiment, including population size, number of seeds, simulation duration, and
burn-in period.
Additionally, define scenario-specific parameters that impact transmission, seasonality, case management, and other
interventions.
Framework
Configure overarching settings, such as model selection, output specifications, and directory structures for storing
inputs and results.
Cluster-specific parameters are also required to optimize simulation execution across computing environments.
Malaria Parameters¶
These parameters are primarily defined in the SimulationConfig class within the setup_sim.py script.
| Parameter | Description |
|---|---|
| seasonality | Seasonal variation in malaria transmission due to climatic factors. |
| case_management | Diagnosis and treatment for uncomplicated and severe malaria cases. |
| intervention_list | List of interventions to include. Note case management is per default included. Options i.e. ‘ccstep’ |
| importation_rate | Introduction of malaria cases from external sources (e.g., travel, migration). |
| entomology_mode | Mosquito population dynamics, biting behavior, and vector control strategies. |
| sweep_list | Creates a full factorial design of the selected sweep parameter values |
| … | … |
Parameter names with an asteriks (*) denote model-specific parameters
Simulation Parameters¶
These parameters are primarily defined in the SimulationConfig class within the setup_sim.py script.
| Parameter | Description |
|---|---|
| start_year, end_year | Start year of the monitoring period |
| burnin* | Initial period for reaching an equilibrium. |
| seed | Random seed(s) for stochastic replications. |
| pop_size* | Simulated number of individuals. |
| agebins | Age bins to simulate. |
| age_groups_aggregates | Age groups for output aggregation. |
| run_mode | Simulation execution mode, supporting testing and production configurations. |
| emodstep* | EMOD: use serialization to separate burn-in and pickup simulation, or run all together. |
| emod_calib_params* | EMOD: run simulations with alternative within-host calibration. |
| mpv* | malariasimulation parameter variation. |
| target_output_name, target_output_values |
Output type and target location for CM 0 and 15% simulations using EMOD (pop: 1,000), OpenMalaria (pop: 50,000), and malariasimulation (pop: 50,000) under seasonal and perennial profiles. |
| test | Reduces the computational demand by lowering pop_size, burn-in and seeds |
| … | … |
Parameter names with an asteriks (*) denote model-specific parameters
Framework Parameters¶
These parameters are primarily defined through the arguments provided when launching simulations
via python launch_sim.py <args>.
They are specified in the parse_launch_args function within the utility/helper.py script.
| Parameter | Description |
|---|---|
| directory | Specifies the directory for storing simulation inputs, config, and model outputs. |
| suite | Suite (collection of) of simulation experiments. |
| expname, exp_name | Name of the simulation experiment. |
| models | Specifies which models to run (one or multiple). |
| user | Creates a user-specific directory for storing experiments and simulation outputs. |
| rownum | If running from CSV, defines row of the simulation scenario to run. |
| memory_per_sim* | Memory allocation per simulation, ensuring appropriate resources. |
| time_per_sim* | Max time for each simulation to manage computational time and resources |
| analyzer_list | Type of standardized outputs to generate (i.e. select default or custom ones) |
| analyzer_script | Name of the analyzer script (default, optional for advanced users) |
| plots_to_run | Plots to generate (allows custom plots for advanced users) |
| sim_params_list | Lists the simulation parameters to be used across the models, allowing for consistent configuration of the simulation environment. |
Parameter names with an asteriks (*) denote model-specific parameters
Go to building scenarios to learn how to specify parameters, or click Next to see an example run.