tlo.methods.stunting module

Stunting Module

Overview

The Stunting module determines the prevalence of stunting for children under 5 years old. A polling event runs every month and determines the risk of onset of non-severe stunting, progression to severe stunting or natural recovery. The Generic HSI calls do_routine_assessment_for_chronic_undernutrition for any HSI with a child under 5 years old: if they have any stunting they are provided with an intervention - HSI_Stunting_ComplementaryFeeding.

class Stunting(name=None, resourcefilepath=None)[source]

This is the disease module for Stunting

Bases: tlo.core.Module

PARAMETERS:

Item

Type

Description

prev_HAZ_distribution_age_0_5mo

LIST

Distribution of HAZ among less than 6 months of age in 2015 (mean, standard deviation)

prev_HAZ_distribution_age_6_11mo

LIST

Distribution of HAZ among 6 months and 1 year of age in 2015 (mean, standard deviation)

prev_HAZ_distribution_age_12_23mo

LIST

Distribution of HAZ among 1 year olds in 2015 (mean, standard deviation)

prev_HAZ_distribution_age_24_35mo

LIST

Distribution of HAZ among 2 year olds in 2015 (mean, standard deviation)

prev_HAZ_distribution_age_36_47mo

LIST

Distribution of HAZ among 3 year olds in 2015 (mean, standard deviation)

prev_HAZ_distribution_age_48_59mo

LIST

Distribution of HAZ among 4 year olds in 2015 (mean, standard deviation)

or_stunting_male

REAL

Odds ratio of stunting if male gender

or_stunting_preterm_and_AGA

REAL

Odds ratio of stunting if born preterm and adequate for gestational age

or_stunting_SGA_and_term

REAL

Odds ratio of stunting if born term and small for geatational age

or_stunting_SGA_and_preterm

REAL

Odds ratio of stunting if born preterm and small for gestational age

or_stunting_hhwealth_Q5

REAL

Odds ratio of stunting if household wealth is poorest Q5, ref group Q1

or_stunting_hhwealth_Q4

REAL

Odds ratio of stunting if household wealth is poorer Q4, ref group Q1

or_stunting_hhwealth_Q3

REAL

Odds ratio of stunting if household wealth is middle Q3, ref group Q1

or_stunting_hhwealth_Q2

REAL

Odds ratio of stunting if household wealth is richer Q2, ref group Q1

base_inc_rate_stunting_by_agegp

LIST

Baseline incidence rate per year of stunting by age group (1-5, 6-11, 12-23, 24-35, 36-47, 48-59mo

rr_stunting_preterm_and_AGA

REAL

Relative risk of stunting if born preterm and adequate for gestational age

rr_stunting_SGA_and_term

REAL

Relative risk of stunting if born term and small for gestational age

rr_stunting_SGA_and_preterm

REAL

Relative risk of stunting if born preterm and small for gestational age

rr_stunting_prior_wasting

REAL

Relative risk of stunting if prior wasting in the last 3 months

rr_stunting_untreated_HIV

REAL

Relative risk of stunting for untreated HIV+

rr_stunting_wealth_level

REAL

Relative risk of stunting if wealth-level is greater than 1 compared 1

rr_stunting_no_exclusive_breastfeeding

REAL

Relative risk of stunting for not exclusively breastfed babies < 6 months

rr_stunting_no_continued_breastfeeding

REAL

Relative risk of stunting for not continued breastfed infants 6-24 months

rr_stunting_per_diarrhoeal_episode

REAL

Relative risk of stunting for recent diarrhoea episode

r_progression_severe_stunting_by_agegp

LIST

Rates per year of progression to severe stunting by age group (1-5, 6-11, 12-23, 24-35, 36-47, 48-59mo

rr_progress_severe_stunting_if_prior_wasting

REAL

Relative risk of severe stunting if previously wasted

rr_progress_severe_stunting_untreated_HIV

REAL

Relative risk of severe stunting for untreated HIV+

mean_years_to_1stdev_natural_improvement_in_stunting

REAL

Mean time (in years) to a one standard deviation improvement in stunting without any treatment.

effectiveness_of_complementary_feeding_education_in_stunting_reduction

REAL

Probability of stunting being reduced by one standard deviation (category) by education about supplementary feeding (but not supplying supplementary feeding consmables).

effectiveness_of_food_supplementation_in_stunting_reduction

REAL

Probability of stunting being reduced by one standard deviation (category) by supplementary feeding.

PROPERTIES:

Item

Type

Description

un_HAZ_category

CATEGORICAL

Indicator of current stunting status - the height-for-age z-score category:”HAZ>=-2” == No Stunting (within 2 standard deviations of mean); “-3<=HAZ<-2” == Non-Severe Stunting (2-3 standard deviations from mean); “HAZ<-3 == Severe Stunting (more than 3 standard deviations from mean). Possible values are: [HAZ<-3, -3<=HAZ<-2, HAZ>=-2, ]

Class attributes:

INIT_DEPENDENCIES : {‘Wasting’, ‘NewbornOutcomes’, ‘Hiv’, ‘Diarrhoea’, ‘Demography’}

METADATA : {<Metadata.DISEASE_MODULE: 1>, <Metadata.USES_HEALTHSYSTEM: 3>}

Functions (defined or overridden in class Stunting):

__init__(name=None, resourcefilepath=None)[source]

Construct a new disease module ready to be included in a simulation.

Initialises an empty parameters dictionary and module-specific random number generator.

Parameters

name – the name to use for this module. Defaults to the concrete subclass’ name.

read_parameters(data_folder)[source]

Read parameter values from file, if required.

Must be implemented by subclasses.

Parameters

data_folder – path of a folder supplied to the Simulation containing data files. Typically modules would read a particular file within here.

initialise_population(population)[source]

Set initial prevalence of stunting according to distributions provided in parameters

initialise_simulation(sim)[source]

Prepare for simulation to start

on_birth(mother_id, child_id)[source]

Set that on birth there is no stunting

look_up_consumable_item_codes()[source]

Look up the item codes that used in the HSI in the module

do_onset(idx: Index)[source]

Represent the onset of stunting for the person_id given in idx

do_progression(idx: Index)[source]

Represent the progression to severe stunting for the person_id given in idx

do_recovery(idx: Union[list, Index])[source]

Represent the recovery from stunting for the person_id given in idx. Recovery causes the person to move ‘up’ one level: i.e. ‘HAZ<-3’ –> ‘-3<=HAZ<-2’ or ‘-3<=HAZ<-2’ –> ‘HAZ>=-2’

do_routine_assessment_for_chronic_undernutrition(person_id)[source]

This is called by the a generic HSI event for every child aged less than 5 years. It assesses stunting and schedules an HSI as needed.

do_treatment(person_id, prob_success)[source]

Represent the treatment with supplementary feeding. If treatment is successful, effect the recovery of the person immediately.

class StuntingPollingEvent(module)[source]

Regular event that controls the onset of stunting, progression to severe stunting and natural recovery.

Bases: tlo.events.RegularEvent, tlo.events.Event, tlo.events.PopulationScopeEventMixin

Functions (defined or overridden in class StuntingPollingEvent):

__init__(module)[source]

Create a new regular event.

Parameters
  • module – the module that created this event

  • frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)

apply(population)[source]
  • Determine who will be onset for stunting (among those not stunted) and effect that change;

  • Determine who will be onset for recovery (among those stunted) and effect that change.

  • Determine who will be onset for progression (among those stunted but not severely) and effect that change;

apply_model(model, mask, days_exposed_to_risk)[source]

Return the person_ids selected for an event of occur to in a given period (in days), as specified by a LinearModel that provides the annual risk of the event. * Looks-up annual probability of the event using a linear model supplied in model to a population masked with

mask

  • Converts the annual probability to a probability of the event occurring during the number of

days_exposed_to_risk * Randomly selects which individuals will have the events

class StuntingLoggingEvent(module)[source]

Logging event occurring every year

Bases: tlo.events.RegularEvent, tlo.events.Event, tlo.events.PopulationScopeEventMixin

Functions (defined or overridden in class StuntingLoggingEvent):

__init__(module)[source]

Create a new regular event.

Parameters
  • module – the module that created this event

  • frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)

apply(population)[source]

Log the current distribution of stunting classification by age

class HSI_Stunting_ComplementaryFeeding(module, person_id)[source]

HSI for complementary feeding, either with the provision of supplementary foods or with education only.

Bases: tlo.methods.healthsystem.HSI_Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class HSI_Stunting_ComplementaryFeeding):

__init__(module, person_id)[source]

Create a new event.

Note that just creating an event does not schedule it to happen; that must be done by calling Simulation.schedule_event.

Parameters

module – the module that created this event. All subclasses of Event take this as the first argument in their constructor, but may also take further keyword arguments.

apply(person_id, squeeze_factor)[source]

Apply this event to the population.

Must be implemented by subclasses.

class StuntingPropertiesOfOtherModules(name=None)[source]

For the purpose of the testing, this module generates the properties upon which the Stunting module relies

Bases: tlo.core.Module

PROPERTIES:

Item

Type

Description

hv_inf

BOOL

temporary property

hv_art

CATEGORICAL

temporary property. Possible values are: [not, on_VL_suppressed, on_not_VL_suppressed, ]

nb_low_birth_weight_status

CATEGORICAL

temporary property. Possible values are: [extremely_low_birth_weight, very_low_birth_weight, low_birth_weight, normal_birth_weight, ]

nb_size_for_gestational_age

CATEGORICAL

temporary property. Possible values are: [small_for_gestational_age, average_for_gestational_age, ]

nb_late_preterm

BOOL

temporary property

nb_early_preterm

BOOL

temporary property

nb_breastfeeding_status

CATEGORICAL

temporary property. Possible values are: [none, non_exclusive, exclusive, ]

un_ever_wasted

BOOL

temporary property

gi_number_of_episodes

INT

temporary property

Class attributes:

ALTERNATIVE_TO : {‘Diarrhoea’, ‘Wasting’, ‘Hiv’}

INIT_DEPENDENCIES : {‘Demography’}

Functions (defined or overridden in class StuntingPropertiesOfOtherModules):

__init__(name=None)[source]

Construct a new disease module ready to be included in a simulation.

Initialises an empty parameters dictionary and module-specific random number generator.

Parameters

name – the name to use for this module. Defaults to the concrete subclass’ name.

read_parameters(data_folder)[source]

Read parameter values from file, if required.

Must be implemented by subclasses.

Parameters

data_folder – path of a folder supplied to the Simulation containing data files. Typically modules would read a particular file within here.

initialise_population(population)[source]

Set our property values for the initial population.

Must be implemented by subclasses.

This method is called by the simulation when creating the initial population, and is responsible for assigning initial values, for every individual, of those properties ‘owned’ by this module, i.e. those declared in its PROPERTIES dictionary.

TODO: We probably need to declare somehow which properties we ‘read’ here, so the simulation knows what order to initialise modules in!

Parameters

population – the population of individuals

initialise_simulation(sim)[source]

Get ready for simulation start.

Must be implemented by subclasses.

This method is called just before the main simulation loop begins, and after all modules have read their parameters and the initial population has been created. It is a good place to add initial events to the event queue.

on_birth(mother, child)[source]

Initialise our properties for a newborn individual.

Must be implemented by subclasses.

This is called by the simulation whenever a new person is born.

Parameters
  • mother – the mother for this child (can be -1 if the mother is not identified).

  • child – the new child