emod_api.demographics.DemographicsTemplates module

class emod_api.demographics.DemographicsTemplates.CrudeRate(init_rate)

Bases: object

get_dtk_rate()

class emod_api.demographics.DemographicsTemplates.YearlyRate(init_rate)

Bases: emod_api.demographics.DemographicsTemplates.CrudeRate

class emod_api.demographics.DemographicsTemplates.DtkRate(init_rate)

Bases: emod_api.demographics.DemographicsTemplates.CrudeRate

emod_api.demographics.DemographicsTemplates.NoRisk()

NoRisk puts everyone at 0 risk.

emod_api.demographics.DemographicsTemplates.FullRisk(demog, description='')

FullRisk puts everyone at 100% risk.

emod_api.demographics.DemographicsTemplates.InitRiskUniform(demog, min_lim=0, max_lim=1, description='')

InitRiskUniform puts everyone at somewhere between 0% risk and 100% risk, drawn uniformly.

Parameters

• min (float) – Low end of uniform distribution. Must be >=0, <1.

• max (float) – High end of uniform distribution. Must be >=min, <=1.

• description – Why were these values chosen?

Returns

json object aka python dict that can be directly passed to Demographics::SetDefaultFromTemplate

Raises

None –

emod_api.demographics.DemographicsTemplates.InitRiskLogNormal(demog, mean=0.0, sigma=1.0)

InitRiskLogNormal puts everyone at somewhere between 0% risk and 100% risk, drawn from LogNormal.

Parameters

• mean (float) – Mean of lognormal distribution.

• sigma (float) – Sigma of lognormal distribution.

Returns

json object aka python dict that can be directly passed to Demographics::SetDefaultFromTemplate

Raises

None –

emod_api.demographics.DemographicsTemplates.InitRiskExponential(demog, mean=1.0)

InitRiskExponential puts everyone at somewhere between 0% risk and 100% risk, drawn from Exponential.

Parameters

mean (float) – Mean of exponential distribution.

Returns

json object aka python dict that can be directly passed to Demographics::SetDefaultFromTemplate

Raises

None –

emod_api.demographics.DemographicsTemplates.NoInitialPrevalence(demog)

NoInitialPrevalence disables initial prevalence; outbreak seeding must be done from an Outbreak intervention (or serialized population).

Parameters

demog – emod-api.demographics.Demographics instance.

Returns

None

Raises

None –

emod_api.demographics.DemographicsTemplates.InitPrevUniform(demog, low_prev, high_prev, description='')

emod_api.demographics.DemographicsTemplates.InitSusceptConstant(demog)

emod_api.demographics.DemographicsTemplates.EveryoneInitiallySusceptible(demog, setting=1.0)

emod_api.demographics.DemographicsTemplates.StepFunctionSusceptibility(demog, protected_setting=0.0, threshold_age=1825.0)

emod_api.demographics.DemographicsTemplates.SimpleSusceptibilityDistribution(demog, meanAgeAtInfection=2.5)

emod_api.demographics.DemographicsTemplates.DefaultSusceptibilityDistribution(demog)

emod_api.demographics.DemographicsTemplates.MortalityRateByAge(demog, age_bins, mort_rates)

Set (non-disease) mortality rates by age bins. No checks are done on input arrays.

Parameters

• age_bins – list of age bins, with ages in years.

• mort_rates – list of mortality rates, where mortality rate is daily probability of dying..

Returns

N/A.

emod_api.demographics.DemographicsTemplates.MortalityStructureNigeriaDHS(demog)

emod_api.demographics.DemographicsTemplates.get_fert_dist_from_rates(rates)

Create dictionary with DTK-compatible distributions from input vectors of fertility (crude) rates.

Parameters

rates – Array/vector of crude rates for whole population, for a range of years.

emod_api.demographics.DemographicsTemplates.get_fert_dist(path_to_csv)

This function takes a fertility csv file (by year and age bin) and populates a DTK demographics.json file, and the corresponding config file to do individual pregnancies by age and year from data.

Parameters

• demog – emod_api.demographics.Demographics instance.

• path_to_csv – absolute path to csv input file. The file should have columns for 5-year age bins

• "1950-1955". (labelled "15-19", etc. up to "45-49", and a column named "Years" with values like) –

• anywhere. (There can be extra columns and the columns can be) –

Returns

(complex) dictionary. fertility distribution, ready to be added to demographics file.

emod_api.demographics.DemographicsTemplates.InitAgeUniform(demog)

emod_api.demographics.DemographicsTemplates.AgeStructureUNWPP(demog)