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States Partner Across Sectors to Address Lead Poisoning Kayley Humm, Kerry Wyss, Ali Aslam Learn in this brief how three states are using partnerships to improve lead testing and reduce cases of lead poisoning. ASTHO partnered with the National Center for Healthy Housing (NCHH) to provide technical assistance and capacity-building support for lead poisoning prevention efforts in three state health agencies: Maryland Department of Health, North Dakota Department of Health and Human Services, and Arkansas Department of Health. This brief highlights each agency’s strategies for collaborating across sectors along with accomplishments for strengthening lead poisoning prevention capacity in each jurisdiction. Many of these strategies align with those used in a health in all polices (HiAP) approach to lead poisoning prevention. State Examples Maryland Department of Health Maryland adopted a collaborative approach to prevent lead poisoning. The Maryland Department of Health (MDH) has an established lead poisoning prevention program that partners with the Maryland Department of the Environment. The Department of the Environment oversees the childhood lead registry and case management, while MDH focuses on lead testing regulations and Medicaid services. This partnership has been implemented across the 24 local health departments in the state. Maryland enhanced lead case management by providing staff support and tackling complex cases that require additional assistance. In addition to supporting an increase in lead case management activities and lead awareness, ASTHO funding also helped strengthen collaboration and coordination among local health departments, state agencies, and local health care providers. The MDH Environmental Health Bureau also improved efficiency by moving data from the lead registry to MDH for lead surveillance and case management. They also developed and launched sub-county lead testing data as part of their Environmental Public Health Tracking public portal. These activities align with HiAP strategies of developing and structuring cross-sector relationships, coordinating funding and investments, and synchronizing communications. North Dakota Department of Health and Human Services The North Dakota Department of Health and Human Services (NDHHS) made significant strides in building up the state lead program, which recently transitioned from the department of environmental quality to NDHHS. With support from ASTHO and NCHH, NDHHS developed a lead prevention website with a data dashboard, developed a lead screening questionnaire, and built collaborative partnerships. The activities in North Dakota align with the HiAP strategies of developing and structuring cross-sector relationships, synchronizing communications, and integrating research, evaluation, and data systems. Building collaborative partnerships is a key initiative for the NDHHS lead program. Already developed partnerships include stakeholders such as Health Tracks and WIC. Health Tracks developed a newsletter article for their provider network so physicians can stay up to date and aware of the lead program transition and lead testing changes, and WIC will host informational lunch and learns to raise awareness about lead testing within their network. North Dakota is also prioritizing building partnerships with tribal communities. A tribal communications plan was developed with the goal of establishing an effective communication plan between the state of North Dakota and each tribal government for lead-related events. Anticipated outcomes from the communication plan include testing for blood lead levels, conducting environmental assessments on tribal lands, and seeing if a tribal member or government is interested in hosting a lead screening event. Progress has been made with the Standing Rock Sioux Tribe, Turtle Mountain band of Chippewa, and NDHHS is hopeful to establish intertribal meetings with all four governmental tribal representatives. Arkansas Department of Health The Arkansas Department of Health established its lead program in 2011 to support abatement of lead-based paint in residential and commercial properties. With support from ASTHO and NCHH, Arkansas has been using a data-driven approach to gain a more comprehensive understanding of lead exposure burden in the state. These activities align with the HiAP strategy of incorporating health data into decision-making and integrating research, evaluation, and data systems. The Arkansas Department of Health conducts periodic audits on its data system to support access to timely and accurate data. To improve data quality and frequency of blood lead testing reports, the health department is establishing incentive programs to encourage facilities to report cases of elevated blood lead. In addition to conducting outreach to its partners, the Arkansas Department of Health has been working to improve lead case data access and data quality through data mining efforts, case report matching, and migration to a new lead surveillance system. Arkansas has been working to modernize the current reporting system to facilitate automation and promote overall efficiency of data analysis and case identification. Conclusion The collaborative efforts of Maryland, North Dakota, and Arkansas highlight the importance of multi-sector partnerships and data sharing in addressing lead poisoning prevention and align with many of the strategies used in a HiAP approach. Each state implemented tailored strategies that sought to grow collaboration in its unique context. These initiatives highlight the importance of cross-sector collaboration in public health initiatives and may serve as valuable models for other jurisdictions. article yes

Learn how boundary spanning leadership can help develop more robust and productive public health workplaces.

Disease Forecasting and Modeling Data for Public Health Action Disease Forecasting Benefits Public Health Planning Disease forecasting and modeling help prepare public health departments for future infectious disease outbreaks and epidemics. Disease forecasting and modeling data can be powerful tools for state and local health agencies (S/THAs) that respond to outbreaks, develop appropriate policies, and ensure interventions have maximum impact. Actions for which decision-makers can leverage such data include: Surveillance. Forecasts and modeling help public health agencies anticipate the spread of disease or outbreaks. This advance warning allows public health officials to inform public health recommendations, preparation, and response. Communication. Disease forecasts help relate the risk of disease outbreaks to various audiences accurately and quickly, which, in turn, can inform messages on important preventive measures and encourages compliance with recommended interventions. Resource allocation. Modeling data can help decision-makers better allocate resources by predicting where and when disease outbreaks are likely to intensify and create the greatest need. Evaluation. Forecasts and modeling can help make evaluating the effectiveness of public health policies and interventions more efficient by comparing predicted outcomes with observed data and adjusting as needed. Considerations Informed by S/THA Forecasting Jurisdictions with forecasting experience identified key indicators to monitor as part of outbreak forecasting, which fall into three main categories: Epidemic spread indicators (e.g., symptom monitoring, morbidity and mortality data, percent positivity, regional pictures of transmission). Health care system capacity (e.g., essential and/or surge personnel, available beds, ventilator usage, and supply of personal protective equipment. Public health capacity for testing capacity and contact tracing. Further considerations for S/THAs: Know your strengths. Identify the unique skillsets among partners in public health, academia, and the private sector and consider how they foster reciprocal relationships. Recognize capacity/expertise gaps. Consider leveraging partnerships for specific types of analytics expertise while exploring internal capacity building opportunities (e.g., job shadowing and resource-sharing programs on workflows and methodologies). Engage legal and compliance teams. Ensure policy and practice are aligned among partners. Explore data access/sharing pipelines. Connect public, private, academic partners, and their audiences. Start small. Identify discrete forecasting and modeling projects to demonstrate success. Identify decision-makers’ needs. Provide quick access to analyses, metrics, dashboards. Michigan Used Models and Forecasting for Hep C Cases In response to Hepatitis C virus (HCV) in young adults from 2010-2018, the Michigan Department of Health and Human Services (MDHHS) simulated how HCV treatment could significantly reduce HCV prevalence among young people who inject drugs, especially for those both previously or currently injecting drugs. MDHHS used several novel predictors to paint a local picture of probable HCV diagnoses among residents up to age 40. These predictors included measures related to a variety of population characteristics (e.g., access to transportation, college education, presence of non-family households) and public health indicators (e.g., heroin treatment admissions, newborns with neonatal abstinence syndrome, and sexually-transmitted infections). MDHHS also leveraged county-level assessments of HCV vulnerability to identify locations for new syringe services programs in the state. MDHHS has recognized several modeling and analytics use cases that benefitted their work during responses to HCV and COVID-19: Short-term forecasts (i.e., weeks) helped predict likely transmission patterns and potential ranges of projections. Longer-term forecasts (i.e., months) explored scenarios based on new recommendations and policy changes. Retrospective counterfactuals evaluated the impact of policies or other changes by examining “what-if” situations. MDHHS is considering using forecasts and models for COVID-19, influenza epidemics, tuberculosis vulnerability, and C. auris spread. Resource constraints require decision-makers and public health practitioners to consider how they are using available resources for the highest return on investment. Models generated momentum to respond to threats and evaluate whether interventions were successful. CDC-RFA-OT18-1802 2018-2024 article yes

Case study: geospatial AI applied to public health in Essex County for disease mapping, resource allocation, and health equity.

Analysis of how AI could transform public health planning—including forecasting and resource allocation—while raising equity concerns.

Framework for integrating health equity considerations into AI design and deployment for public health applications.

Research on harnessing AI/ML to enhance public health surveillance: pathogen detection, outbreak forecasting, and data integration.

Review of AI applications in disease surveillance: real-time monitoring, predictive analytics, and early outbreak detection systems.

Government standard for securing public-facing AI services: risk assessment, procurement controls, and security requirements.

Study of public use of a generalist LLM chatbot for health queries: patterns, accuracy, and implications for health communication.

Overview of geospatial AI and its applications in GIS for public health mapping, environmental analysis, and decision support.

Framework for designing AI evaluations that matter: linking AI system assessment to real-world outcomes and stakeholder needs.

Los Angeles AI Roadmap: city strategy for responsible AI adoption across departments, public services, and civic engagement.

Webinar on AI applications in health policy and systems research, exploring the shift from experimentation to real-world implementation.

Content analysis of social determinants of health accelerator plans using AI/NLP to identify themes and equity gaps at scale.

Empirical study using LLMs and prompt engineering to generate health awareness messages, evaluating quality for public health communication.

Blended online course from Digital Bridge giving community health workers foundational AI literacy for public health and service delivery.

Substack newsletter on AI applications in public health—policy implications and emerging tools for public health practitioners.

CDC blog on AI in medicine and public health: imaging, big data, and ethical challenges post-pandemic. Rasooly & Khoury, March 2022.

Washington County, OR AI acceptable use policy: guidelines for responsible generative AI use, data protection, and human review of AI outputs.