generate_all_households_infer_ages#

generate_all_households_infer_ages(n, n_remaining, hh_sizes, hha_by_size, hha_brackets, cm_age_brackets, cm_age_by_brackets, contact_matrices, adjusted_age_dist, ages_left_to_assign)[source]#

Generate the ages of those living in households together. First create households of people living alone, then larger households. For households larger than 1, a reference individual’s age is sampled conditional on the household size, while all other household members have their ages sampled conditional on the reference person’s age and the age mixing contact matrix in households for the population under study.

Parameters:

  • n (int) – The number of people in the population.

  • n_remaining (int) – The number of people in the population left to place in a residence.

  • hh_sizes (array) – The count of household size s at index s-1.

  • hha_by_size_counts (matrix) – A matrix in which each row contains the age distribution of the reference person for household size s at index s-1.

  • hha_brackets (dict) – The age brackets for the heads of household.

  • cm_age_brackets (dict) – The dictionary mapping age bracket keys to age bracket range matching the household contact matrix.

  • cm_age_by_brackets (dict) – The dictionary mapping age to the age bracket range it falls within matching the household contact matrix.

  • contact_matrices (dict) – The dictionary of the age-specific contact matrix for different physical contact settings.

  • ages_left_to_assign (dict) – Age count of people left to place in households larger than one person.

Returns:

An array of all households where each household is a row and the values in the row are the ages of the household members. The first age in the row is the age of the reference individual. Households are randomly shuffled by size.

Note

This method is not guaranteed to model the population age distribution well automatically. The method called inside, generate_larger_households_infer_ages uses the method ltcf_resample_age to fit Seattle, Washington populations with long term care facilities generated. For a method that matches the age distribution well for populations in general, please use generate_all_households_fixed_ages.

The following contains an example of how you may resample from an age range that is over produced and instead sample ages from an age range that is under produced in your population. This kind of customization may be necessary when your age mixing matrix and the population you are interested in modeling differ in important but subtle ways. For example, generally household age mixing matrices reflect mixing patterns for households composed of families. This means household age mixing matrices do not generally cover college or university aged individuals living together. Without this customization, this algorithm tends to under produce young adults. This method also has a tendency to underproduce the elderly, and does not explicitly model the elderly living in nursing homes. Customizations like this should be considered in context of the specific population and culture you are trying to model. In some cultures, it is common to live in non-family households, while in others family households are the most common and include multi-generational family households. If you are unsure of how to proceed with customizations please take a look at the references listed in the overview documentation for more information.