tlo.methods.wasting module

Childhood wasting module

class Wasting(name=None)

This module simulates natural history, detection, and treatment of acute malnutrition in children under 5 years old.

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.

Bases: tlo.core.Module, tlo.methods.hsi_generic_first_appts.GenericFirstAppointmentsMixin

PARAMETERS:

Item	Type	Description
prev_init_any_by_agegp	LIST	initial any wasting (WHZ < -2) prevalence in 2010 by age groups
prev_init_sev_by_agegp	LIST	initial severe wasting (WHZ < -3) prevalence in 2010 by age groups
max_age_child_wasting	INT	Max age child treated for wasting
wasting_incidence_polling_freq_months	INT	Wasting incidence polling frequency in months
min_days_to_relapse	REAL	minimum days to relapse: the incidence of another wasting episode in the previous month cannot occur if recovery happened fewer than this number of days before the start of that month
base_overall_inc_rate_wasting	REAL	base overall monthly moderate wasting incidence rate (probability per child aged <0.5 years per month)
rr_inc_rate_wasting_by_agegp	LIST	relative risk of monthly moderate wasting incidence rate by age group (reference age group: <0.5 years)
rr_wasting_AGA_and_preterm	REAL	relative risk of moderate wasting incidence if born adequate for gestational age and preterm
rr_wasting_SGA_and_term	REAL	relative risk of moderate wasting incidence if born small for gestational age and term
rr_wasting_SGA_and_preterm	REAL	relative risk of moderate wasting incidence if born small for gestational age and preterm
rr_wasting_wealth_level	REAL	relative risk of moderate wasting incidence per 1 unit decrease in wealth level
min_days_duration_of_wasting	REAL	minimum limit for moderate and severe wasting duration episode (days)
duration_of_untreated_mod_wasting	REAL	duration of untreated moderate wasting (days)
duration_of_untreated_sev_wasting	REAL	duration of untreated severe wasting (days)
progression_severe_wasting_monthly_by_agegp	LIST	monthly progression rate to severe wasting by age group
prob_complications_in_SAM	REAL	probability of medical complications in a SAM episode
duration_sam_to_death	REAL	duration of SAM till death if supposed to die due to untreated SAM (days)
base_death_rate_untreated_SAM	REAL	base death rate due to untreated SAM (reference age group <0.5 months old)
rr_death_rate_by_agegp	LIST	list with relative risks of death due to untreated SAM by age group, reference group <0.5 months old
proportion_WHZ<-3_with_MUAC<115mm	REAL	proportion of individuals with severe wasting who have MUAC < 115 mm
proportion_-3<=WHZ<-2_with_MUAC<115mm	REAL	proportion of individuals with moderate wasting who have MUAC < 115 mm
proportion_-3<=WHZ<-2_with_MUAC_[115-125)mm	REAL	proportion of individuals with moderate wasting who have 115 mm ≤ MUAC < 125 mm
proportion_mam_with_MUAC_[115-125)mm_and_normal_whz	REAL	proportion of individuals with MAM who have 115 mm ≤ MUAC < 125 mm and normal/mild WHZ
proportion_mam_with_MUAC_[115-125)mm_and_-3<=WHZ<-2	REAL	proportion of individuals with MAM who have both 115 mm ≤ MUAC < 125 mm and moderate wasting
proportion_mam_with_-3<=WHZ<-2_and_normal_MUAC	REAL	proportion of individuals with MAM who have moderate wasting and normal MUAC
MUAC_distribution_WHZ<-3	LIST	mean and standard deviation of a normal distribution of MUAC measurements for WHZ < -3
MUAC_distribution_-3<=WHZ<-2	LIST	mean and standard deviation of a normal distribution of MUAC measurements for -3 <= WHZ < -2
MUAC_distribution_WHZ>=-2	LIST	mean and standard deviation of a normal distribution of MUAC measurements for WHZ >= -2
prevalence_nutritional_oedema	REAL	prevalence of nutritional oedema
proportion_WHZ<-2_with_oedema	REAL	proportion of individuals with wasting (moderate or severe) who have oedema
proportion_oedema_with_WHZ<-2	REAL	proportion of individuals with oedema who are wasted (moderately or severely)
proportion_normal_whz	REAL	proportion of children under 5 with no wasting (WHZ >= -2)
odds_ratio_health_seeking_wasting_children	REAL	Odds seeking care for wasting in children
growth_monitoring_first	INT	recommended age (in days) for first growth monitoring visit
growth_monitoring_frequency_days_agecat	LIST	growth monitoring frequency (days) for age categories
growth_monitoring_attendance_prob_agecat	LIST	probability to attend the growth monitoring for age categories
recovery_rate_with_soy_RUSF	REAL	probability of recovery from MAM following treatment with soy RUSF
recovery_rate_with_CSB++	REAL	probability of recovery from MAM following treatment with CSB++
recovery_rate_with_standard_RUTF	REAL	probability of recovery from uncomplicated SAM following treatment with standardRUTF
recovery_rate_with_inpatient_care	REAL	probability of recovery from complicated SAM following treatment via inpatient care
tx_length_weeks_SuppFeedingMAM	REAL	number of weeks the patient receives treatment in the Supplementary Feeding Programme (SFP) for MAM, including the final supply provided at discharge
tx_length_weeks_OutpatientSAM	REAL	number of weeks the patient receives treatment in the Outpatient Therapeutic Programme (OTP) for uncomplicated SAM, including the final supply provided at discharge
tx_length_weeks_InpatientSAM	REAL	number of weeks the patient receives treatment in the Inpatient Therapeutic Care (ITC) for complicated SAM—modelled to include the Rehabilitation Phase, ie to cover OTP as well
prob_death_after_SAMcare	REAL	probability of dying from SAM after receiving care if not fully recovered

PROPERTIES:

Item	Type	Description
un_ever_wasted	BOOL	ever had an episode of wasting (WHZ < -2)
un_WHZ_category	CATEGORICAL	weight-for-height Z-score category. Possible values are: [WHZ<-3, -3<=WHZ<-2, WHZ>=-2, ]
un_last_wasting_date_of_onset	DATE	date of onset of last episode of wasting
un_clinical_acute_malnutrition	CATEGORICAL	clinical acute malnutrition state based on WHZ and/or MUAC and/or nutritional oedema. Possible values are: [SAM, MAM, well, ]
un_am_nutritional_oedema	BOOL	nutritional oedema present in acute malnutrition episode
un_am_MUAC_category	CATEGORICAL	MUAC measurement categories, based on WHO cut-offs. Possible values are: [<115mm, [115-125)mm, >=125mm, ]
un_sam_with_complications	BOOL	medical complications in SAM episode
un_sam_death_date	DATE	if alive, scheduled death date from SAM if not recovers with treatment; if not alive, date of death due to SAM
un_am_recovery_date	DATE	recovery date from last acute malnutrition episode
un_am_tx_start_date	DATE	treatment start date, if currently on treatment
un_am_treatment_type	CATEGORICAL	treatment type for acute malnutrition the person is currently on; set to not_applicable if well hence no treatment required. Possible values are: [standard_RUTF, soy_RUSF, CSB++, inpatient_care, none, not_applicable, ]
un_am_discharge_date	DATE	planned discharge date from current treatment when recovery will happen if not yet recovered
un_recov_to_mam_date	DATE	date on which recovery from severe to moderate acute malnutrition (SAM to MAM) should occur
un_full_recov_date	DATE	date on which the full recovery for the person should occur
un_progression_date	DATE	date on which the progression from moderate to severe wasting for the person should occur
un_last_nonemergency_appt_date	DATE	last date of generic non-emergency first appointment
un_last_growth_monitoring_appt_date	DATE	last date of growth-monitoring appointment

Class attributes:

CAUSES_OF_DEATH : {‘Severe Acute Malnutrition’: <tlo.methods.causes.Cause object at 0x3341f3550>}

CAUSES_OF_DISABILITY : {‘Severe Acute Malnutrition’: <tlo.methods.causes.Cause object at 0x3341f3390>}

INIT_DEPENDENCIES : {‘NewbornOutcomes’, ‘HealthBurden’, ‘SymptomManager’, ‘Demography’}

METADATA : {<Metadata.USES_SYMPTOMMANAGER: 2>, <Metadata.DISEASE_MODULE: 1>, <Metadata.USES_HEALTHSYSTEM: 3>, <Metadata.USES_HEALTHBURDEN: 4>}

__annotations__ : {}

Functions (defined or overridden in class Wasting):

__init__(name=None)

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(resourcefilepath: Path | None = None)

• 1. Reads the ResourceFile

• 2. Declares the DALY weights

• 3. Registers the Symptom

initialise_population(population)

Sets the property values for the initial population. 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 the PROPERTIES dictionary above.

Parameters:

population

initialise_simulation(sim)

Prepares for simulation. Schedules: * the first annual logging event, * the first monthly incidence polling event, * the first growth monitoring for all children under 5.

Parameters:

sim

on_birth(mother_id, child_id)

Initialises properties for a newborn individual.

Parameters:

• mother_id – the mother’s id of this child

• child_id – the id of the newborn child

schedule_growth_monitoring_on_initiation()

Schedules HSI_Wasting_GrowthMonitoring for all under-5 children at simulation initiation for a random day within the age-dependent frequency.

muac_cutoff_by_WHZ(idx, whz) → None

Determines the MUAC (Mid-Upper Arm Circumference) category for each individual specified in idx, based on a shared WHZ (Weight-for-Height Z-score) category whz. The MUAC categories are: ‘<115mm’, ‘[115–125)mm’, and ‘>=125mm’.

Assigns the MUAC categories determined to the ‘un_am_MUAC_category’ property for each corresponding individual in the population DataFrame.

Parameters:

• idx – Indices of individuals in the population DataFrame to assess for MUAC category.

• whz – WHZ category shared by the individuals (‘WHZ<-3’, ‘-3<=WHZ<-2’, ‘WHZ>=-2’).

nutritional_oedema_present(idx)

Determines the presence of nutritional oedema for each individual specified in idx, based on their respective WHZ (Weight-for-Height Z-score) category.

Assigns the result (True/False) to the un_am_nutritional_oedema property for each corresponding individual in the population DataFrame.

Parameters:

idx – Indices of individuals in the population DataFrame to assess for nutritional oedema presence.

clinical_acute_malnutrition_state(person_id, pop_dataframe)

Determines * the clinical acute malnutrition status (‘well’, ‘MAM’, ‘SAM’) for the individual specified by person_id, based on their anthropometric indices (WHZ and MUAC category) and presence of nutritional oedema. * whether the individual has medical complications requiring inpatient care, applicable to SAM cases only.

Assigns for the corresponding individual in the population DataFrame:

• ‘un_clinical_acute_malnutrition’: the determined clinical acute malnutrition status (‘well’, ‘MAM’, ‘SAM’)

• ‘un_sam_with_complications’: the determined value of presence of medical complications (True/False)

For well cases * ‘un_am_treatment_type’: remains ‘not_applicable’

For non-well cases, i.e. those who developed ‘MAM’ or ‘SAM’ * ‘un_am_treatment_type’: ‘none’, i.e. they start with no treatment * ‘un_am_recovery_date’ property is reset to NaT

For the SAM cases * wasting symptom is applied * it is determined whether SAM leads to death, and if it does, the Death event is scheduled and the date of death is assigned to the ‘un_sam_death_date’ property

For non-SAM cases * the wasting symptom is cleared

param person_id:

individual’s id

param pop_dataframe:

population DataFrame

get_consumables_for_each_treatment()

Get the item_code and amount administrated for all consumables for each treatment.

length_of_untreated_wasting(whz_category)

Helper function to determine the duration of the wasting episode in days.

Parameters:

whz_category – ‘WHZ<-3’, or ‘-3<=WHZ<-2’

Returns:

duration (number of days) of wasting episode, until recovery to no wasting, progression to severe wasting, from moderate wasting; or recovery to moderate wasting or death due to SAM in cases of severe wasting

date_of_death_for_untreated_sam()

Helper function to determine date of death, assuming it occurs earlier than the progression/recovery from any wasting, moderate or severe.

Returns:

date of death

clinical_signs_acute_malnutrition(idx)

When WHZ changed, update other anthropometric indices and clinical signs (MUAC, oedema) that determine the clinical state of acute malnutrition. If SAM, update medical complications. If not SAM, clear symptoms. This will include both wasted and non-wasted children with other signs of acute malnutrition.

Parameters:

idx – index of children or person_id less than 5 years old

report_daly_values()

This must send back a pd.Series or pd.DataFrame that reports on the average daly-weights that have been experienced by persons in the previous month. Only rows for alive-persons must be returned. The names of the series of columns is taken to be the label of the cause of this disability. It will be recorded by the healthburden module as <ModuleName>_<Cause>.

Returns:

current daly values for everyone alive

wasting_clinical_symptoms(person_id) → None

Assigns clinical symptoms to the new acute malnutrition case

Parameters:

person_id

do_at_generic_first_appt(person_id: int, symptoms: List[str], individual_properties: IndividualProperties, schedule_hsi_event: HSIEventScheduler, **kwargs) → None

Handles a generic first appointment for a child under 5 years old.

If the child is not currently being treated for wasting and has not already attended a generic first appointment or growth monitoring on the same day: * Performs an acute malnutrition assessment. If acute malnutrition is detected, schedules HSI for the appropriate treatment enrolment. * Updates the ‘un_last_nonemergency_appt_date’ property for the individual in the population DataFrame.

Parameters:

• person_id – ID of the individual attending the appointment

• symptoms – list of symptoms present for the individual

• individual_properties – properties of the individual relevant to the appointment

• schedule_hsi_event – scheduler for health system interaction events

• kwargs – additional keyword arguments

do_when_am_treatment(person_id, treatment) → None

Cancels any scheduled natural outcome for the individual; outcome is now determined solely by the treatment. Processes the specified treatment, determines the outcome, and if appropriate, schedules an outcome event and/or an enrolment for a follow-up treatment.

Updates individual’s properties in the population DataFrame: * un_am_tx_start_date * un_am_discharge_date * un_sam_death_date (if applicable)

Parameters:

• person_id – ID of the individual receiving treatment

• treatment – type of treatment being applied (‘CSB++’, ‘standard_RUTF’, etc.)

class Wasting_IncidencePoll(module)

Regular event that determines new cases of wasting (WHZ < -2) to the under-5 population, and schedules individual incident cases to represent onset. It determines those who will progress to severe wasting (WHZ < -3) and schedules the event to update on properties. These are events occurring without the input of interventions, these events reflect the natural history only.

schedule to run every month :param module: the module that created this event

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

Class attributes:

AGE_GROUPS : {0: ‘0y’, 1: ‘1y’, 2: ‘2y’, 3: ‘3y’, 4: ‘4y’}

__annotations__ : {}

Functions (defined or overridden in class Wasting_IncidencePoll):

__init__(module)

schedule to run every month :param module: the module that created this event

apply(population)

Apply this event to the population. :param population: the current population

class Wasting_ProgressionToSevere_Event(module, person_id)

This Event is for the onset of severe wasting (WHZ < -3).

• Refreshes all the properties so that they pertain to this current episode of wasting

• Imposes wasting symptom

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.

• priority – a keyword-argument to set the priority (see Priority enum)

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class Wasting_ProgressionToSevere_Event):

__init__(module, person_id)

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.

• priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)

Apply this event to the given target.

Must be implemented by subclasses.

Parameters:

target – the target of the event

class Wasting_SevereAcuteMalnutritionDeath_Event(module, person_id)

This event applies the death function

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.

• priority – a keyword-argument to set the priority (see Priority enum)

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class Wasting_SevereAcuteMalnutritionDeath_Event):

__init__(module, person_id)

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.

• priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)

Apply this event to the given target.

Must be implemented by subclasses.

Parameters:

target – the target of the event

class Wasting_FullRecovery_Event(module, person_id)

This event updates the clinical signs of acute malnutrition for those cases that fully recovered, i.e. person recovers to well with all properties being set and SAM symptoms removed.

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.

• priority – a keyword-argument to set the priority (see Priority enum)

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class Wasting_FullRecovery_Event):

__init__(module, person_id)

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.

• priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)

Apply this event to the given target.

Must be implemented by subclasses.

Parameters:

target – the target of the event

class Wasting_RecoveryToMAM_Event(module, person_id)

This event updates the clinical signs of acute malnutrition and removes SAM symptoms for those cases that improved from SAM to MAM.

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.

• priority – a keyword-argument to set the priority (see Priority enum)

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class Wasting_RecoveryToMAM_Event):

__init__(module, person_id)

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.

• priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)

Apply this event to the given target.

Must be implemented by subclasses.

Parameters:

target – the target of the event

class HSI_Wasting_GrowthMonitoring(module, person_id)

Attendance is determined for the HSI. If the child attends, measurements with available equipment are performed for that child. Based on these measurements, the child can be diagnosed as well/MAM/(un)complicated SAM and eventually scheduled for the appropriate treatment. If the child (attending or not) is still under 5 at the time of the next growth monitoring, the next event is scheduled with age-dependent frequency.

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.

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

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class HSI_Wasting_GrowthMonitoring):

__init__(module, person_id)

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)

Apply this event to the population.

Must be implemented by subclasses.

did_not_run()

Called when this event is due but it is not run. Return False to prevent the event being rescheduled, or True to allow the rescheduling. This is called each time that the event is tried to be run but it cannot be.

class HSI_Wasting_SupplementaryFeedingProgramme_MAM(module, person_id)

This is the supplementary feeding programme for MAM without complications

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.

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

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class HSI_Wasting_SupplementaryFeedingProgramme_MAM):

__init__(module, person_id)

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)

Apply this event to the population.

Must be implemented by subclasses.

did_not_run()

Called when this event is due but it is not run. Return False to prevent the event being rescheduled, or True to allow the rescheduling. This is called each time that the event is tried to be run but it cannot be.

class HSI_Wasting_OutpatientTherapeuticProgramme_SAM(module, person_id)

This is the outpatient management of SAM without any medical complications

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.

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

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class HSI_Wasting_OutpatientTherapeuticProgramme_SAM):

__init__(module, person_id)

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)

Apply this event to the population.

Must be implemented by subclasses.

did_not_run()

Called when this event is due but it is not run. Return False to prevent the event being rescheduled, or True to allow the rescheduling. This is called each time that the event is tried to be run but it cannot be.

class HSI_Wasting_InpatientTherapeuticCare_ComplicatedSAM(module, person_id)

This is the inpatient management of SAM with medical complications

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.

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

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class HSI_Wasting_InpatientTherapeuticCare_ComplicatedSAM):

__init__(module, person_id)

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)

Apply this event to the population.

Must be implemented by subclasses.

did_not_run()

Called when this event is due but it is not run. Return False to prevent the event being rescheduled, or True to allow the rescheduling. This is called each time that the event is tried to be run but it cannot be.

class Wasting_LoggingEvent(module)

This Event logs the number of incident cases that have occurred since the previous logging event, the average length of wasting cases at recovery point since the previous logging, the prevalence proportions at the time of logging, and population sizes at the time of logging. At initiation only prevalence proportions and population sizes are logged.

Analysis scripts expect that the frequency of this logging event is once per year. Logs are expected to happen on the first day of each year.

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)

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

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class Wasting_LoggingEvent):

__init__(module)

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)

Apply this event to the given target.

This is a no-op; subclasses should override this method.

Parameters:

target – the target of the event