memilio.epidata.getContactData

getContactData.py

Load an age-structured contact matrix for a chosen country based on Prem et al., 2017 (DOI: https://doi.org/10.1371/journal.pcbi.1005697). The module can download the supporting ZIP from https://doi.org/10.1371/journal.pcbi.1005697.s002 (contains the MUestimates_all_locations_1.xlsx workbook) or read a defined local workbook path. By default, downloads are done in memory and no files are written.

Functions

list_available_contact_countries([contact_path])

List all country names available in the contact matrix workbook.

load_contact_matrix(country[, contact_path, ...])

Load the all-locations contact matrix for the given country.
memilio.epidata.getContactData.list_available_contact_countries(
contact_path: str | None = None,
)

List all country names available in the contact matrix workbook.

Parameters:

contact_path – Optional local path to the workbook.

Returns:

List of all country names.

memilio.epidata.getContactData.load_contact_matrix(
country: str,
contact_path: str | None = None,
reduce_to_rki_groups: bool = True,
population: Iterable[float] | None = None,
)

Load the all-locations contact matrix for the given country. If contact_path is not provided, the function downloads the MUestimates_all_locations_1.xlsx workbook from Prem et al., 2017.

Parameters:

  • country – Country name as listed in the workbook (case-insensitive).

  • contact_path – Optional path to MUestimates_all_locations_1.xlsx.

  • reduce_to_rki_groups – If True, aggregate to the six RKI age groups (0-4, 5-14, 15-34, 35-59, 60-79, 80+ years). Default True.

  • population – An iterable of 16 float values representing the population size for each original age group. Required if reduce_to_rki_groups is True.

Returns:

DataFrame indexed by age group with floats.