Modernizing Data Systems in Environmental Public Health

Modernizing Data Systems in Environmental Public Health: A Blueprint for Action

Table 4 (continued)

SOURCE TYPE

SUBCATEGORY (IF APPLICABLE) Local Nonprof- its and Non -

DESCRIPTION

REAL-WORLD EXAMPLES

KEY CONSIDERATIONS Trusted in local contexts; often issue- driven, with deep community ties but limited scalability. High research quality; dependent on funding cycles and time-limited studies. Rich qualitative insight; requires strong community trust and labor- intensive data collection. Directly actionable and operationally relevant; accessibility depends on data infrastructure and staff training

Community-Based Sources

Community organizations that conduct studies or advocacy tied to health and the environment.

• GreenRoots (Massachusetts): Heat and flooding risk mapping.

governmental Organizations

Academic- Community Partnerships

Collaborations between universities and local communities to co-produce data and research. Community-driven assessments using interviews, focus groups, or neighborhood audits. Data from within an agency’s operations—collected via inspections, apps, permitting, and surveys.

• Flint Water Study: Exposed lead via resident sampling.

Hyperlocal Surveys and Reports

• Boston Chinatown Heat Study: Tracked temperature variation with handheld sensors and resident input. • Mobile food safety inspections • Environmental health management system dashboards • Public complaints and heat-related illness reports

Internal Systems

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