diseases.bv

diseases.bv

BV modules Includes: - a simple BV model for generating background prevalence of vaginal discharge - a detailed model of the vaginal microbiome including community state types (CSTs)

Classes

Name	Description
BV	Detailed bacterial vaginosis model based on community state types (CSTs).
SimpleBV	Simple bacterial vaginosis model for generating background BV prevalence.

BV

diseases.bv.BV(pars=None, name='bv', **kwargs)

Detailed bacterial vaginosis model based on community state types (CSTs).

Models BV through vaginal microbiome CST transitions (CST 1, 3, 4), with risk factors including douching, menstrual hygiene, partner concurrency, and circumcision status. Supports optional sexual transmission of BV- associated microbes.

Parameters

Name	Type	Description	Default
pars	dict	Override default parameters from `BVPars`.	`None`
name	str	Module name. Default: `'bv'`.	`'bv'`
**kwargs		Additional parameters passed to `update_pars`.	`{}`

Methods

Name	Description
clear_infection	Clear infection
compute_circumcision_impact	Compute the relative impact of circumcision on susceptibility for women.
init_post	Initialize with sim properties
init_results	Initialize results
set_circumcision	Set circumcision status
set_hygiene_states	Set vaginal hygiene states
set_male_prognoses	Set initial prognoses for newly infected males
set_prognoses	Set initial prognoses for newly infected females
sexual_transmission	Determine who gets infected on this timestep via transmission on the network
spontaneous	Determine the probability of transitioning to worse CST states
step_state	Updates for this timestep
wipe_dates	Clear all previous dates

clear_infection

diseases.bv.BV.clear_infection(uids)

Clear infection

compute_circumcision_impact

diseases.bv.BV.compute_circumcision_impact(spontaneous=True)

Compute the relative impact of circumcision on susceptibility for women. This is used for spontaneous occurence only. If sexual transmission in model, then we adjust man’s susceptibility.

init_post

diseases.bv.BV.init_post()

Initialize with sim properties

init_results

diseases.bv.BV.init_results()

Initialize results

set_circumcision

diseases.bv.BV.set_circumcision(upper_age=None)

Set circumcision status

set_hygiene_states

diseases.bv.BV.set_hygiene_states(upper_age=None)

Set vaginal hygiene states

set_male_prognoses

diseases.bv.BV.set_male_prognoses(uids)

Set initial prognoses for newly infected males

set_prognoses

diseases.bv.BV.set_prognoses(uids, new_cst=3)

Set initial prognoses for newly infected females

sexual_transmission

diseases.bv.BV.sexual_transmission()

Determine who gets infected on this timestep via transmission on the network

spontaneous

diseases.bv.BV.spontaneous(uids, cst='cst1')

Determine the probability of transitioning to worse CST states for agents in CST 1, we determine probability of transitioning to CST 3 (assuming no transition directly to CST 4) for agents in CST 3, we determine probability of transitioning to CST 4 agents in CST 4 have no further transitions

step_state

diseases.bv.BV.step_state()

Updates for this timestep

wipe_dates

diseases.bv.BV.wipe_dates(uids)

Clear all previous dates

SimpleBV

diseases.bv.SimpleBV(pars=None, name='bv', **kwargs)

Simple bacterial vaginosis model for generating background BV prevalence.

Models BV as a spontaneous condition (not sexually transmitted) using a logistic regression model with risk factors (douching, menstrual hygiene, number of partners). Includes symptomatic/asymptomatic states, care-seeking, and natural clearance or persistence.