Defunding Sexual Healthcare: A Topological Investigation of Resource Accessibility

TL;DR

This paper uses topological data analysis to investigate spatial inequalities in access to reproductive healthcare facilities in California, highlighting the impact of funding restrictions on resource distribution.

Contribution

It introduces a novel application of topological data analysis to assess healthcare accessibility disparities caused by policy changes.

Findings

Identifies regions with limited access to reproductive health services.

Shows how topological methods reveal gaps in healthcare coverage.

Demonstrates potential future access issues under current policies.

Abstract

Government actions, such as the Medina v. Planned Parenthood South Atlantic Supreme Court ruling and the passage of the Big Beautiful Bill Act, have aimed to restrict or prohibit Medicaid funding for Planned Parenthood Healthcare Centers (PPHCs) at both the state and national levels. These funding cuts are particularly harmful in states like California, which has a large population of Medicaid users. This analysis focuses on the distribution of Planned Parenthood clinics and Federally Qualified Health Centers (FQHCs), which offer essential reproductive healthcare services including, but not limited to, abortions, birth control, HIV services, pregnancy testing and planning, STD testing and treatment, and cancer screenings. While expanded funding for FQHCs has been proposed as a solution, it fails to address the locational accessibility of Medicaid-funded health centers that provide sexual and reproductive care. To assess this issue, we analyze the proximity of data points representing California's PPHC and FQHC locations. Topological Data Analysis (TDA)-an approach that examines the shape and structure of data -- is used to detect disparities in reproductive and sexual healthcare coverage. To conduct data collection and visualization, we utilize R and Python. We apply an n-closest neighbor algorithm to examine distances between facilities and assess changes in travel time required to reach healthcare sites. We apply persistent homology to analyze current gaps across multiple scales in healthcare coverage and compare them to potential future gaps. Our findings aim to identify areas where access to care is most vulnerable and demonstrate how TDA can be used to analyze spatial inequalities in public health.