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Get a bird's eye view of intersectional strategies to prevent ACEs, suicide, overdose, and mental health concerns.

Learn how health agencies can strengthen their overdose prevention programs through business improvement.

Learn about how five jurisdictions approached self-measured blood pressure monitoring programs to reduce hypertension and uncover systemic barriers to care.

Learn how health departments can focus their infectious disease prevention efforts in this brief.

This resource highlights state-based program initiatives tailored to improving hypertensive disorders of pregnancy outcomes.

State firearm survey data can inform firearm injury prevention strategies—read recommendations for developing state firearm surveys and applying findings.

Learn key lessons from the DREAM Learning Community about addressing structural racism and driving systemic change, which can help achieve optimal health for all.

Defining Disease Forecasting and Modeling Disease forecasting, generated by disease models, helps the public health workforce understand potential future outbreaks. Learn more about disease forecasts and models. Disease forecasting is important in describing potential future outbreaks that will affect the population and demand for health services in a given geographic area. Forecasts pull input from various sources (e.g., disease models, demographic, mobility, and intervention impact data). Individual forecasts can also be part of an ensemble forecast to improve accuracy. Forecasts can cover any length of time, but most target a window of several weeks to a few months. A subset of forecasts, known as nowcasts, seek to estimate present conditions, or those expected to occur imminently. Disease models are mathematical tools that are foundational components of disease forecasts. They estimate quantifiable factors that are impossible or impractical to directly measure, (e.g., future hospitalizations from a given disease, or its infection count in a population). Although models can be useful for specific questions, they do not give as complete a picture as a forecast. There are four major disease model types: Mechanistic. Attempts to simulate biological and/or social processes of transmission based on assumptions from prior or experimental data. Statistical. Relies on past data (such as infections or death) to predict future trends and can incorporate some assumptions about intervention application and uptake. Quality and quantity of past data can be a major limitation, and some models may suggest biological improbabilities. Agent. Simulates individual risks and behaviors in a population. These are highly complex, computationally very expensive to develop and run and require vast amounts of data and strong assumptions. Ensemble. Like their forecasting counterparts, they compile models and outputs, mitigating the risk of relying on one data point. While raising the overall confidence in output, they require coordination of many models to be built and simulated, which can be complex and costly unless the models already exist (such as for COVID-19 case counts). Forecasts and Models Work Together While disease forecasts and models are often conflated, they are discrete concepts. Forecasts offer a general prediction, whereas models are the mathematical pieces forecasters use to create them. Weather forecasts are commonplace, and their weekly predictions are often reasonably accurate. In contrast, predicting a big storm’s individual factors (e.g., rainfall, wind speed, lightning strikes) fall to the job of models. Together, those models help meteorologists better understand the weather and generate a forecast. In a public health context, disease forecasting informs public health officials, health care providers, and policymakers about potential risks and guide decision-making regarding preventive measures, resource allocation, and response strategies. Meanwhile, disease models aim to simulate the behavior of infectious diseases under different scenarios, allowing researchers to explore and evaluate various factors that influence disease transmission. Considerations for Decision-Making Decision-makers should consider scope and limitations of forecasts and models. They may consider adding inputs—such as projections for economic and long-term impacts. Examples include economic impacts of school closures, costs of more staffing ahead of an outbreak, and supply chain shortage forecasts for personal protective equipment (PPE). Decision-makers at all levels should consider using modeling to answer more specific, practical questions rather than predicting overall trends. Forecasts can cover different geographic scales. Public health leaders will need granular, local data to most effectively inform decision-making and communications. Novel conditions and pathogens may not have readily available data to inform models or forecasts, which will affect their predictive ability. Health officials must effectively communicate these limitations to decision-makers and the public. Examples of Forecasts and Models CDC’s COVID-19 Forecast for Hospitalizations (ensemble forecast) shows the number of daily COVID-19 hospitalizations reported in the United States from the prior two months and projected daily COVID-19 hospitalizations over the coming four weeks. Information sources are independent teams meeting submission and data quality requirements. CDC’s FluSight (ensemble forecast) has many contributing teams and models that predicts the upcoming weekly laboratory confirmed influenza hospital admissions both nationally and by state. Johns Hopkins University’s Center for Systems Science and Engineering county-level risk model for COVID-19 in the United States. This model leverages epidemiological data, mobile phone data, demographic and socioeconomic information, and behavioral metrics. The Global Epidemic and Mobility Framework simulates the global spread of infectious diseases by mathematically representing infection dynamics, population geographies, and population mobility patterns. Additional Resources Disease modeling for public health: added value, challenges, and institutional constraints Predictive Models for Forecasting Public Health Scenarios: Practical Experiences Applied during the First Wave of the COVID-19 Pandemic Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples Technology to advance infectious disease forecasting for outbreak management CDC-RFA-OT18-1802 2018-2024 article yes

Overdose Data to Action (OD2A) Case Study: New York State’s Power of Voice Program

Leveraging Medicaid to Support Community Health Workers astho, association of state and territorial health officials, community health workers, health equity, medicaid coverage, chw workforce, social service, public health, health care system, improve health, individual and community, mental health, achieving health equity, social determinants of health, underserved communities, united states, health disparities, medicaid program, state Medicaid, advance health equity, highest level of health, people of color, community they serve, improve access, people living, increased health Vanessa Finisse, Madison Hluchan How to leverage Medicaid to support community health workers. Community health workers (CHWs) are pivotal in advancing health equity and improving population health, especially for marginalized communities. Today, there is increasing federal investment to better integrate CHWs into the health care system, spurred by post-COVID-19 federal legislation. While the benefits of CHW integration are well-documented, sustainable funding remains a challenge. This brief, developed in partnership with the Center for Health Care Strategies (CHCS), explores Medicaid coverage for CHW-led services and highlights opportunities for state and territorial health agencies (S/THAs) to collaborate with Medicaid to support CHWs. Key Considerations Medicaid-Funded CHW-Led Services Medicaid authorities can finance CHW-led services, such as state plan amendments (SPAs), section 1115 demonstrations (1115 waivers), and managed care flexibilities. States can pick a pathway depending on their goals, timeline, and administrative capacity. As compared to SPAs, 1115 waivers provide states with more flexibility to waive federal Medicaid rules to test innovative approaches (see Table 1). website yes

Engaging Communities Is a Critical Tobacco Control Strategy Community Engagement Tobacco Control, Menthol Cigarette Disparities, Tobacco Control Learning Collaborative, Culturally Tailored Tobacco Interventions, Flavored Tobacco Product Legislation, United States, Flavored Tobacco Product, Health Equity, Youth and Young Adults, Tobacco Free, Cigarettes Smoked, Community Partners, Young People, Community Health, Youth Tobacco Survey, Flavored E-Cigarettes, Smoking Cessation, Tobacco Industry, Smoking Behavior, Study Showed, African American, Smoking Rates, Tobacco Marketing, Minority Populations, Hispanic Black, ASTHO, Association of State and Territorial Health Officials Charla Sutton, Matta Sannoh, Josh Berry, Kenny Ray, Ashley Hebert, Iman Byfield For decades, the tobacco industry has disproportionately targeted communities of color increasing rates of menthol cigarette use and tobacco-related health disparities. By prioritizing community efforts, health agencies can confront these disparities by fostering trust, inclusivity, and cultural responsiveness. Funded by CDC’s Office of Smoking and Health (OSH) and in partnership with The Center for Black Health & Equity (The Center), ASTHO initiated the Increasing State Menthol Capacity Learning Collaborative consisting of eight state tobacco use prevention teams each paired with a local community-based organization. The program fosters strong linkages between state commercial tobacco control programs and community-based partners to reduce menthol and flavored product use. The Role of Community Engagement Community-based initiatives are pivotal in tobacco control efforts, as they enable stakeholders to: Understand history, context, culture, and geography. Underserved communities possess a keen awareness of the origins of their problems and how decision-making processes affect them. Embrace community voices. “No one asked us” is the most common feeling communities most impacted by a problem share when decision-makers act without including them. Build organizational capacity that sustains change, creates credibility with decision-makers, and empowers communities to meet challenges head-on and garner support for their initiatives. Barriers to effective community engagement include insufficient training, funding, communication, and planning, plus disorganization, under-acknowledged communities, over-committed leaders, and inability to change course. Learning Collaborative at a Glance Eight state health teams (IN, MN, NY, PA, RI, MI, WA, WI)—each paired with a community-facing organization—kicked off the Increasing State Menthol Capacity Learning Collaborative in January 2023 with a shared vision and plan to reduce menthol and flavored product use. The Collaborative worked to: (1) improve capacity to identify and implement strategies to prevent menthol and other flavored tobacco product use, (2) strengthen collaboration between state commercial tobacco control programs and community-based partners, (3) tailor interventions to those most affected, and (4) understand the role of policy interventions and/or systems change and culturally-appropriate cessation strategies. ASTHO, OSH, and The Center provided peer-to-peer learning, technical assistance, and networking opportunities to help project teams draw from the group’s various resources, expertise, and experiences. For example, each state team participated in five virtual, expert-led learning sessions, which provided training on SMARTIE goals, equity-centered community engagement strategies, and effective communication messages for policies that restrict or eliminate the sale of flavored tobacco products. In addition, technical assistance provided the project teams guidance on their established workplan objectives and helped them navigate community-specific challenges. Menthol Capacity Building Strategies Each team worked to address health inequities of their chosen target population with culturally-tailored actions in one of three strategies: (1) Policy, Systems, and Environmental Change, (2) Menthol Cessation, or (3) Counter Marketing/Public Education. Teams focused on African Americans (nearly two-thirds of whom start by using tobacco with menthol), youth, Latinx, immigrant populations, and the LGBTQ+ community. Each team curated state-specific infographics, factsheets, webpages, and media campaigns to examine the role of policy in reducing menthol and flavored tobacco product use. Others engaged legislators or held educational events. Key Takeaways and Next Steps Community Engagement and the Menthol Landscape: Despite challenges, preemption should not stop community engagement work. While state or federal laws and regulations may change, the communities most impacted—and their voices, experiences, and advocacy efforts—remain and are essential in driving meaningful change. Ongoing awareness of the disproportionate impact of menthol and other flavored tobacco products on marginalized communities underscore a continuous need for community engagement and policies that prioritize health equity. Partnering for Influence and Advocacy: Community engagement fosters awareness of the unique challenges that marginalized populations face, ensuring that initiatives are tailored accordingly. In the face of preemption and other regulatory challenges, community voices are critical for national change. Mobilizing Support through Collaboration: Partnerships between state agencies and local organizations allow capacity building and resource sharing. Such partnerships help mobilize broader support with both constituents and legislators, share best practices/lessons learned, and collectively address challenges. Funding Local Initiatives: Effective community engagement often requires financial resources. Examples include facilitating quality meetings as needed, developing educational tools for community dissemination, using paid and social media, and obtaining individuals to implement key activities (e.g., employees or subject matter experts). The collaborative’s participants further encourage: Sustaining and strengthening partnerships with community-based organizations, state health agencies, and national partners to leverage stakeholder expertise and insights. Investing in ongoing capacity building efforts to equip communities with the knowledge, skills, and resources to address tobacco-related challenges effectively (e.g., training, resource sharing, offering technical assistance, and funding community-led initiatives). Engaging with policymakers, community leaders, and others to raise awareness about the negative impact of menthol and other tobacco products. Advocate for evidence-based policies (e.g., e-cigarette flavor restriction) at the local and state level to inform national discussion. Sharing lessons learned—both successes and challenges—with others. website yes

Implementing Levels of Maternal Care Improves Access to Risk-Appropriate Care Lexa Giragosian Levels of maternal care support risk-appropriate care for pregnant and birthing populations. Risk-appropriate care (RAC) is a strategy to ensure that pregnant women and infants with high risk of complications receive care at facilities with personnel who offer services at the required level of specialized care. States can use the process of perinatal regionalization to create coordinated care systems based on levels of maternal care to support RAC access. Implementing and strengthening maternal RAC systems can improve health outcomes for pregnant and birthing populations and reduce the incidence of severe maternal morbidity and mortality. Wanda Barfield - Brief - Implementing Levels of Maternal Care Improves Access to RAC website yes

This brief examines the ways states can support certification for community health workers.

Strengthening Maternal and Infant Health Data in the U.S. Territories ASTHO, association of state and territorial health officials, maternal and infant health data, U.S. territories, public health, surveillance programs, pregnancy risk assessment monitoring system, improving the health, live births, health problems, reproductive health, federal government, toggle the centers for disease control and prevention cdc, risk assessment monitoring system, assessment monitoring system prams, pregnancy risk assessment monitoring, maternal and infant health, information collected, table of contents, population based, health status, supreme court, prams data, toggle the table, risk factors, prenatal care, collecting information Stephany Strahle The U.S. territories—Puerto Rico (PR), U.S. Virgin Islands (USVI), Guam, Commonwealth of the Northern Mariana Islands (CNMI), and American Samoa—are largely excluded from most statistical data systems in the United States. This gap leaves island health leaders, national partners, and federal agencies without the surveillance necessary to inform timely and robust public health programs and policies. This is also seen in critical maternal and child health surveillance programs like the Pregnancy Risk Assessment Monitoring System (PRAMS), Maternal Mortality Review Committees, and the Pregnancy Mortality Surveillance System, which either do not include or only recently included territories in their scope of coverage. This incomplete information creates challenges in identifying the aspects health systems need to address to reduce adverse maternal and infant health outcomes. Applying a life course perspective to maternal and infant health data reveals gaps in public health systems that impact outcomes before, during, and after birth. PRAMS provides vital insights into these lived experiences and pregnant people’s interactions with health care services. PRAMS data can also be linked to other administrative datasets, such as Medicaid, child welfare services, and Community Healthy Start programs, to provide a broader understanding of determinants of health across the life course for both the birthing parent and their child. With the breadth of contextual experiences that PRAMS captures in its data and the potential for data linkage projects to explore outcomes and their contributing factors, U.S. territories can leverage this wealth of information to assess the needs of their pregnant communities and their children. Despite its development in 1987, PRAMS has been implemented in only two territories, PR and CNMI, within the past decade. This brief highlights the work of these two islands and the potential to gain further insights into maternal and infant health outcomes using data linkage methods. Island Expansion of Maternal and Infant Health Surveillance Using PRAMS Since beginning PRAMS data collection in 2017, PR has made considerable strides in providing their communities with comprehensive reports on various topics. In 2021, one in eight live births was preterm in PR—the U.S. average is one in 10 live births. This outcome is one example of a potential research area in PR that could leverage PRAMS linkages to clinical administrative data sources to investigate contributing factors. In a special project conducted from 2016 to 2018, PRAMS served as an avenue for assessment of Zika awareness among pregnant people and their partners. Moreover, PRAMS informed numerous reports and educational materials on topics ranging from dental care to lactation and opioid use during pregnancy. Linking PRAMS to other administrative datasets could illuminate more information about health care utilization and access among pregnant people in PR. Although limited research exists on maternal and infant health outcomes in CNMI, available evidence reveals disparities in preterm birth among the territory’s indigenous Chamorro and Carolinian communities and Asian and Pacific Islander groups. Since CNMI started administering PRAMS in 2021, strong relationships with entities outside the territory (e.g., the Hawaii Department of Health) have facilitated PRAMS implementation by helping navigate Internal Review Board regulations and applications—both of which are necessary to conduct PRAMS collection and potential research using PRAMS data, like data linkage projects. Moreover, the CNMI PRAMS team’s deep familiarity with their communities could help identify local administrative data sources that, when linked to PRAMS, capture priority areas for improved health care and social service delivery. Considerations for Future Maternal and Infant Health Data Exploration With the existing gaps in surveillance data available for maternal and infant health, this recent implementation of PRAMS and the potential for data linkages to other data sources could provide enhanced insights for U.S. territories. The following considerations can inform best practices to optimize this data. Building Partnerships to Support a Linked Maternal and Infant Health Data Network To build capacity for further data exploration, building partnerships with other agencies and PRAMS jurisdictions can facilitate the information-sharing necessary to navigate data use agreements and other considerations before successfully linking data. Leveraging these connections can also supply more avenues to administer educational tools about PRAMS and perinatal services, linking their pregnant populations to the services they need. A robust web of partnerships can create a network of linked data capturing the life course perspective to inform high-quality programs for the ongoing care of pregnant people and their infants. Leveraging Community Input and Data on Social Determinants of Health Territories are uniquely positioned to leverage closer community ties to examine how data linkages can inform initiatives that improve experiences surrounding pregnancy and the life course after birth. As with PR, integrating the voices of pregnant people, their families, and the people providing their care into their advisory committees allows for better identification of what communities need. Active engagement ensures agencies can be efficient with their linkage efforts by tailoring their projects to high-priority maternal and infant health outcomes. Moreover, to foster community awareness about PRAMS and possible linked data sources, territories could create dashboards such as those created by Washington D.C.’s PRAMS program to provide a comprehensive and interactive view of the data. Data on social determinants of health collected through PRAMS—such as insurance coverage throughout pregnancy and postpartum as well as access to social support and a wide range of services—can also be leveraged for potential data linkage to identify inequities in health outcomes and the delivery of care. website yes

Hypertension disorders in pregnancy are the leading cause of maternal death, but state and territorial health agencies can address hypertension in pregnancy and reduce maternal morbidity and mortality.

Linking Datasets to Address Racial Equity in Maternal and Child Health Outcomes astho, association of state and territorial health officials, data sources, people of color, centers for disease control, racial inequities, advance racial equity, maternal morbidity, maternal death, maternal health, child health, participate in prams, risk assessment monitoring system, disease control and prevention, maternal and child, morbidity and mortality, pregnancy risk assessment monitoring, pregnancy related death, racial justice, linked data, achieve health equity, advancing health equity, racial equity, maternal and child health, maternal mortality and morbidity, racial disparities, health equity, data linkages, vital records, pregnancy risk assessment monitoring system Stephany Strahle ASTHO | Strategies for promoting racial equity in maternal and infant health through data linkages. Racial disparities in maternal and child health outcomes impact populations across the United States. Having robust data to understand these disparities may inform more comprehensive initiatives and policies that address the impacts and root causes of inequities. Looking at administrative datasets, such as hospital discharges and vital records, allows health professionals to monitor inequities by racial and ethnic communities. Often not captured in these data, however, is the complex interaction of social determinants—such as access to social support, racial discrimination, insurance coverage throughout pregnancy and postpartum, and access to paid family and medical leave—and their impact on health outcomes. Public health surveillance systems monitor these outcomes and aim to answer questions on a broad range of contextual experiences. These systems can be combined with administrative data through data linkage, “a process that matches records representing the same person or entity derived from different data sources in order to generate new and more comprehensive datasets.” These linkages can help identify areas for patient-centered outcomes research and inform policy recommendation and programs that address maternal and child health disparities across racial and ethnic groups. State Approaches to Data Linkages Linking Vital Records with Income Data California In a recent working paper on maternal and infant health inequities in California, researchers linked administrative vital records with parental income data. This research found that “infant and maternal health in Black families at the top of the income distribution is markedly worse than that of White families at the bottom of the income distribution.” Linking vital records, a source that typically does not capture income information, with data sources that do, provided a novel and robust dataset illuminating the exacerbated disparities experienced by racial and ethnic minorities at all income levels. Using PRAMS to Monitor Health Outcomes The Pregnancy Risk Assessment Monitoring System (PRAMS) allows jurisdictions to monitor various maternal and infant health indicators before, during, and after pregnancy. As one of the few public health surveillance systems collecting data on race-related experiences and discrimination, it also provides a better understanding of disparities among racial and ethnic groups. As part of ASTHO’s Linking PRAMS and Clinical Outcomes Data Multi-Jurisdiction Learning Community, two state teams from Massachusetts and Georgia used data linkage of PRAMS to explore racial disparities in maternal and child health outcomes. Massachusetts The Division of Maternal and Child Health Research and Analysis at the Massachusetts Department of Public Health linked PRAMS data with the Pregnancy to Early Life Longitudinal Data System (PELL), a data system linking birth files to hospital discharge records that can be later used to link hospital-based service records, data on early intervention services, and other data documenting maternal and infant health experiences beyond birth. Previously, both PRAMS and PELL data informed Massachusetts’s 2022 report from the Special Commission on Racial Inequities in Maternal Health, which provided policy-related recommendations on doula workforce development and equitable implementation of paid family and medical leave within the state. Sarah Stone, PhD, MPH, the director of the Massachusetts Office of Data Translation, notes that linking PRAMS, which provides insights into the social determinants shaping people’s experiences during pregnancy, with the more administrative data included in PELL can further inform additional evidence-based initiatives to address inequities in maternal mortality and severe maternal morbidity. Georgia At the Maternal and Child Health Section of the Division of Epidemiology in the Georgia Department of Public Health, linkages between PRAMS and Georgia Vital Record data can provide insight into the observed differences in health outcomes among the state’s diverse population. Jenna Self, MPH, Georgia’s PRAMS project director and health surveys team lead, explains that “the linkages will help explore the association between maternal postpartum behaviors and negative infant health outcomes (e.g., mortality, hospitalization, emergency department visits) with the goal of understanding the health disparities” to inform future equity-focused initiatives. The development of a linked data environment will allow the Georgia Department of Public Health to ask and answer previously time and resource prohibitive questions. Recommendations Data linkage can be a powerful tool to create enhanced datasets that better inform state initiatives to improve racial equity in maternal and infant health outcomes. To use data linkages that identify areas needing equitable public health efforts, states should: Build and strengthen cross-collaborative relationships within and between various state agencies owning the datasets to facilitate data sharing. Consider the racial equity impacts of performing data linkages by exploring research questions that lead to more evidence-based decision-making. Understanding the linked data using a racial equity lens can better inform equitable policy recommendations and programmatic planning. Examine which data sources, when linked, could fill in gaps of understanding and provide a wealth of information to identify disparities and point to specific gaps in quality health care. Brief - Linking Datasets to Address Racial Equity in Maternal and Child Health Outcomes - Special Thanks website yes

The Pennsylvania Department of Health adapted its National Electronic Disease Surveillance System to allow providers to report STI treatment more efficiently.

Support for programs and policies that encourage positive mental health in early childhood and provides support for parents and caregivers to have the best chance to improve mental health across the life course.

PrEP is a powerful tool to reduce new HIV infections; expanding access to PrEP is a priority within the federal Ending the HIV Epidemic in the U.S. initiative. One way to increase access to PrEP is by allowing pharmacists to prescribe and dispense it.

This ASTHOBrief addresses the financial challenges facing pregnant people in rural areas.