Exploring How Local Policies Shape Community Health Across the Bay Area
Understanding Why Policy Matters
It is critical to understand how local social and health policies influence the well-being of communities. Decisions about housing, wages, zoning, and public services directly affect health equity. As federal and state policy changes raise uncertainty, especially around safety-net programs like Medi-Cal and SNAP, local action is more important than ever.
“Laws are one of the most powerful tools we have to shape population health—yet often the least measured.”- Dr. Tracy Lam-Hine
What Is Legal Epidemiology?
Legal epidemiology is the scientific study of how laws and policies impact health outcomes.
A key method, policy surveillance, systematically collects and codes laws across jurisdictions—turning complex legal language into data that can reveal how policy variations shape health.
Despite its promise, policy surveillance remains underused in public health practice due to limited staff capacity, rapid policy turnover, and lack of standardized datasets.
Bay Area Roundtable: Exploring Opportunities
On October 14, 2025, Stanford Population Health Sciences convened leaders from Alameda, Contra Costa, Marin, San Francisco, San Mateo, Solano, and Sonoma counties for a regional Policy Surveillance Roundtable. The event brought together local health departments and researchers to explore how legal epidemiology can advance equity-focused policy work.
The discussion featured Dr. Tracy Lam-Hine from Stanford Population Health Sciences, who presented findings from a pioneering study on municipal policies related to structural racism in Bay Area charter cities.
Inside the Stanford Project
Objective: Create a quantitative, research-ready dataset of city policies in effect as of April 1, 2024.
Scope: The analysis was conducted on charter cities within seven Bay Area counties: Alameda, Contra Costa, Marin, San Francisco, San Mateo, Solano, and Sonoma. This focus was chosen because charter cities in California have greater control over local affairs compared to general law cities.
Method: Systematic coding and analysis of local ordinances, plans, and resolutions using legal epidemiology methods.
Key Findings:
The analysis yielded several key insights into the Bay Area's local policy landscape.
- Correlation with Political Leanings: The resulting policy index scores correlated qualitatively with the anecdotal political progressiveness of the cities.
- State Funding Influence: Most cities had climate and housing plans, as these are often required by the state to unlock passthrough funding. More ambitious local versions, like Vision Zero plans, were rare.
- Policy Variation by City Size: Fair chance hiring and housing laws were primarily observed in larger, more politically left-leaning cities. Conversely, some form of affordable housing policy was present in most cities.
- High Variability: Significant variation was observed across cities in policies related to elections, sanctuary status, and paid sick leave.
- Tax Rate Differences: Sales tax rates were highest in Alameda County cities and lowest in San Francisco.
Conclusion: Even progressive regions show wide variation in structural equity policies across local jurisdictions.
Beyond Legal Analysis: Toward Action
Participants agreed that policy data alone isn’t enough, real change requires political will, resources, and sustained community engagement.
Next Steps: Building Partnerships for Policy Impact
The roundtable ended with a shared commitment to:
- Evaluate the health impacts of policy changes;
- Strengthen data storytelling for policymakers;
- Develop a pipeline for student-led projects aligned with health department needs;
- Expand academic-public health partnerships to sustain local analytic capacity.
“Policy surveillance helps make invisible inequities visible and gives communities data to act.” -Roundtable participant
Get Involved
Public health departments or organizations interested in exploring legal epidemiology or policy surveillance can connect with the Stanford Population Health Sciences to learn about available tools, data resources, and collaboration opportunities.