emodpy_malaria.demographics.MalariaDemographics module

This module contains the classes and functions for creating demographics files for malaria simulations. For more information on EMOD demographics files, see Demographics file.

class emodpy_malaria.demographics.MalariaDemographics.MalariaDemographics(nodes, idref='Gridded world grump2.5arcmin', base_file=None, init_prev=0.0, include_biting_heterogeneity=True)

Bases: Demographics

This class is derived from emod_api:emod_api.demographics.Demographics.Demographics and sets certain defaults for malaria in construction.

Args:

nodes: The number of nodes to create. idref: Method describing how the latitude and longitude values are created

for each of the nodes in a simulation. “Gridded world” values use a grid overlaid across the globe at some arcsec resolution. You may also generate the grid using another tool or coordinate system. For more information, see Metadata.

base_file: A basic demographics file used as a starting point for

creating more complicated demographics files. For example, using a single node file to create a multi-node file for spatial simulations.

init_prev: The initial malaria prevalence of the population. Defaults to 0%. include_biting_heterogeneity: variable biting rates. Defaults to on.

Returns:

None

set_risk_lowmedium()

Set initial risk for low-medium transmission settings per: https://wiki.idmod.org/display/MAL/Heterogeneous+biting+risk+in+simulations+vs+data.

set_risk_high()

Set initial risk for high transmission settings per: https://wiki.idmod.org/display/MAL/Heterogeneous+biting+risk+in+simulations+vs+data.

add_larval_habitat_multiplier(schema, hab_type, multiplier, species='ALL_SPECIES', node_id=0)

Add LarvalHabitatMultiplier to node(s).

Args:

schema: Path to schema.json. hab_type: Habitat type. multiplier: Multiplier or Factor. species: Specific species (defaults to ALL). node_id: Nodes for this LHM. Defaults to all.

Returns:

Nothing.

add_initial_vectors_per_species(init_vector_species, node_ids=None)

Add an InitialVectorsForSpecies configuration for all nodes or just a set of nodes.

Args:

init_vector_species: Dictionary of vector species (strings) to initial populations. There is no

checking for coherence of species named in other input settings.

node_ids: Array of node ids. Defaults to None for all nodes.

Returns:

N/A.

add_initial_vectors_per_species_from_csv(csv_path)

Add initial vector species population to ‘demographics’ nodes from a csv file.

Args:

csv_path: Path to CSV file with the initial vector species populations for each node.

Returns:

N/A.

set_innate_immune_distribution(distribution_flag: int = 0, param1: float = 0.0, param2: float = 0.0)

Set the innate immune distribution for individuals in all nodes.

Args:

distribution_flag: Integer flag to select the distribution type.

0 (Constant, everyone in the population has the same innate immune coefficient.) 1 (Uniform, innate immune coefficient is randomly drawn between a minimum and maximum value.) 2 (Gaussian) 3 (Exponential) 4 (Poisson) 5 (Log normal) 6 (Bimodal, non-continuous with some individuals having a innate immune coefficient of 1 and others a user-defined innate immune coefficient.) 7 (Weibull)

param1: First parameter for the distribution (meaning depends on distribution type).

0, Innate immune coefficient value to assign. 1, Minimum innate immune coefficient for a uniform distribution. 2, Mean innate immune coefficient for a Gaussian distribution. 3, Exponential decay rate. 4, Mean innate immune coefficient for a Poisson distribution. 5, Mu (the mean of the natural log) for a log normal distribution. 6, “”Proportion of individuals in the second, user-defined innate immune coefficient bin vs. the first innate immune coefficient bin (value of 1) for a bimodal distribution. Must be between 0 and 1.”” 7, Scale parameter for a Weibull distribution.

param2: Second parameter for the distribution (meaning depends on distribution type).

0, NA, set to 0. 1, Maximum innate immune coefficient for a uniform distribution. 2, Standard deviation in innate immune coefficient for a Gaussian distribution. 3, NA, set to 0. 4, NA, set to 0. 5, Sigma (the standard deviation of the natural log) for a log normal distribution. 6, The innate immune coefficient for individuals in the second innate immune coefficient bin for a bimodal distribution. 7, Shape parameter for a Weibull distribution.

Returns:

Nothing

emodpy_malaria.demographics.MalariaDemographics.from_template_node(lat=0, lon=0, pop=1000000.0, name=1, forced_id=1, init_prev=0.2, include_biting_heterogeneity=True)

Create a single-node MalariaDemographics instance from the parameters you supply.

Args:

lat: Latitude of the centroid of the node to create. lon: Longitude of the centroid of the node to create. pop: Human population of the node. name: The name of the node. This may be a characteristic of the

node, such as “rural” or “urban”, or an identifying integer.

forced_id: The node ID for the single node. init_prev: The initial malaria prevalence of the node.

Returns:

A MalariaDemographics instance.

emodpy_malaria.demographics.MalariaDemographics.from_pop_csv(pop_filename_in, pop_filename_out='spatial_gridded_pop_dir', site='No_Site')

Create a multi-node MalariaDemographics instance from a CSV file describing a population.

Args:

pop_filename_in: The path to the demographics file to ingest. pop_filename_out: The path to the file to output. site: A string to identify the country, village, or trial site.

Returns:

A MalariaDemographics instance

emodpy_malaria.demographics.MalariaDemographics.from_csv(input_file, res=0.008333333333333333, id_ref='from_csv', init_prev=0.0, include_biting_heterogeneity=True)

Create a multi-node MalariaDemographics instance from a CSV file describing a population.

Args:

input_file: The path to the csv file to ingest. res: Resolution. id_ref: A string to identify the file, needs to match other input files. init_prev: The initial malaria prevalence of the population. Defaults to 0%. include_biting_heterogeneity: variable biting rates. Defaults to on.

Returns:

A MalariaDemographics instance

emodpy_malaria.demographics.MalariaDemographics.from_params(tot_pop=1000000.0, num_nodes=100, frac_rural=0.3, id_ref='from_params')

Creates nodes with following logic: First node is the urban node, which contains tot_pop * (1-frac_rural) of the population, the rest of the nodes splip the left-over population with less and less people in each node.

Create a multi-node MalariaDemographics instance as a synthetic population based on a few parameters.

Args:

tot_pop: The total human population in the node. num_nodes: The number of nodes to create. frac_rural: The fraction of the population that will be distributed between

nodes 2 and higher

id_ref: Method describing how the latitude and longitude values are created

for each of the nodes in a simulation. “Gridded world” values use a grid overlaid across the globe at some arcsec resolution. You may also generate the grid using another tool or coordinate system. For more information, see Metadata.

Returns:

A MalariaDemographics instance.