Jonathon P. Leider

Introduction: USAspending.gov represents an important potential source of expenditure data, covering trillions of federal outlays. However, this valuable data source has not commonly been used by researchers due to notable challenges acquiring, processing, or validating data. Our study examines the potential utility of USAspending.gov data to characterize federal health investments pre- and peri-COVID. Methods: We retrieved all HHS federal award data from USAspending.gov for fiscal years 2018-2025. Substantial processing and cleaning was performed, with resulting data used to assess overall and sub-agency trends, and examine sociodemographic correlates of HHS spending changes. Results: Total inflation-adjusted HHS spending rose from $1.6 trillion in FY18 to a pandemic peak of $2.0 trillion in FY20, before declining sharply to a low of $1.9 trillion in FY22-FY24. Spending for CMS increased substantially. Non-CMS spending, overall and at health departments, declined to levels below pre-Covid amounts as of FY25, driven by post-pandemic award cancellations and budget reductions. Conclusion: Data utility was constrained due to substantial work needed to prepare data for analysis. Sharply diverging spending trends within HHS for CMS versus non-CMS programs may have important policy implications in coming years.

Context: Persistent workforce shortages have challenged the public health workforce. During COVID-19 response, the federal government launched Public Health AmeriCorps (PHA) to embed AmeriCorps members in public health systems. Minnesota Public Health Corps (MNPHC), a PHA initiative, focused on placing members in Minnesota public health agencies to strengthen capacity. Objective: The objective of this study was to strengthen the evidence base for public health workforce development by evaluating the relationship between MNPHC participation on members' “career capital,” and subdomains of “Knowing How,” “Knowing Why,” and “Knowing Whom,” through a mixed-methods approach, addressing a key gap in program evaluation and guiding future strategies. Design: Single-group, pre-post observational, explanatory mixed-methods design. Setting: Public health agencies with at least one MNPHC member. Participants: MNPHC members. Main Outcome Measures: Career capital. Results: Participants demonstrated significant gains in overall career capital (scale of 1–7) after service, with mean scores increasing from 5.4 preservice to 6.1 postservice ( P < .001). In the “Knowing How” domain (scale of 1–7), scores rose from a preservice mean of 5.4–6.1 postservice ( P < .001), supported by 2237 qualitative references from 94 members. The “Knowing Why” domain (scale of 1–7) showed an increase from 5.6 to 6.1 ( P < .001), with 315 qualitative references from 74 members. In the “Knowing Whom” domain (scale of 1–7), scores improved from 5.2 to 5.9 ( P < .001), with 171 qualitative references from 65 members. Conclusions: Quantitative results showed a difference in members' career capital from preservice to postservice; the qualitative data support and contextualize the quantitative findings. An integrated interpretation supports an inference that participants' career development was both statistically and experientially significant, with applied skill-building acting as a potential driver of broader gains.

Context: Public health systems face persistent workforce shortages. Career pathway models like the Minnesota Public Health Corps (MNPHC) aim to strengthen public health capacity while supporting early-career professionals' entry into the field. Objective: To explore how MNPHC participation influences members' career development, focusing on the cultivation of public health career capital. Design: This descriptive qualitative study analyzed administrative data submitted by MNPHC members during the 2023–2024 service year, including project plans, weekly logs, service stories, and career surveys. A hybrid thematic analysis combined deductive coding grounded in career capital theory with inductive identification of emergent themes. Reflexive, team-based approaches enhanced rigor and minimized researcher bias. Setting: Public health agencies with at least one MNPHC member. Participants: MNPHC members. Main Outcome Measures: Career capital. Results: Participants developed career capital across 3 domains: Knowing Why (637 references: values, career engagement), Knowing How (4486 references: skills, knowledge/credentials, barriers, facilitators), and Knowing Whom (424 references: networks, supportive ties, barriers). Although members gained skills, identity, and networks, they also faced challenges such as role ambiguity and inconsistent supervision. Viewed together, the domains are mutually reinforcing, highlighting that workforce initiatives should integrate training, mentorship, and professional identity as codesigned elements of career pathways. Conclusions: MNPHC participation supports early-career professionals' development of career capital across skills, identity, and networks. By fostering competencies, confidence, and professional connections, the program highlights the value of intentionally designed service-learning models that align learning, mentorship, and developmental goals. Such investments can strengthen workforce preparation, retention, and advancement.

Objectives. To characterize the national landscape of student loan debt for state and local public health staff and consider the potential roles of loan forgiveness and repayment in workforce development. Methods. This study analyzed data from the nationally representative 2024 Public Health Workforce Interests and Needs Survey, which had 57 000 respondents in the United States. We calculated descriptive statistics and performed an interval regression to assess correlates of student loan balance. Results. More than 40% of the workforce has a student loan balance: $48 000 on average, among those with any debt. Differences are observed by age, race/ethnicity, and level of academic degree. Conclusions. As in other fields, governmental public health is experiencing high rates of turnover while having difficulty with recruitment. Lack of competitive pay and benefits makes it difficult to find and retain staff who may have a public service inclination but also have bills to pay. High on that list of bills, for many, are student loans. Public Health Implications. Loan forgiveness and repayment represent important policy tools to address the ongoing workforce shortage and may be adversely affected by recent federal legislation. (Am J Public Health. Published online ahead of print January 22, 2026:e1-e7. https://doi.org/10.2105/AJPH.2025.308290).

Context: The Public Health Workforce Interests and Needs Survey (PH WINS) was fielded in 2014, 2017, and 2021. In the last 10 years, it has provided participating health departments and the field with data to improve recruitment and retention, strengthen workforce development efforts, guide strategic planning, and raise critical funds to improve public health infrastructure. It captures individual perspectives on engagement and satisfaction, intention to leave, training needs, and workplace infrastructure. This article describes the methods used for the 2024 administration of PH WINS. PH WINS 2024: PH WINS 2024 was fielded to a nationally representative sample of staff in State Health Agency Central Offices (SHA-CO) and local health departments (LHDs) from September 9, 2024, to January 17, 2025. The instrument was revised to improve the actionability of the results, reduce respondents’ cognitive burden, and align with existing standards or survey questions. PH WINS 2024 had 12 sampling frames, compared with the 3 in previous years: SHAs, members of the Big Cities Health Coalition (BCHC), and LHDs in each of the 10 Health and Human Services (HHS) Regions. All participating agencies were surveyed using a census approach. Participation: Overall, staff lists for 48 SHAs, 1,178 LHDs were collected, and the survey was sent to 159 627 individuals. PH WINS received a total of 56 595 responses, a 37% of eligible respondents. The SHA frame received responses from 29% of eligible respondents, BCHC members received 33%, and all other LHDs received 51%. The nationally representative SHA-CO frame included a total of 18 110 individuals, and the nationally representative LHD frame included 38 485 individuals from all 1178 LHDs. For the first time, the national sample of LHDs included small LHDs. Reflections: With the 2024 administration of PH WINS, all state and local public health departments in the United States had the opportunity to participate, yielding a nationally representative sample of small LHDs for the first time. State and local health department leaders should be empowered to use the results for workforce development and other planning. Questions were modified to become more action-oriented, rigorous, and stable over time to maximize the utility of PH WINS for years to come. Given the changing public health landscape associated with new outbreaks, disasters, and the political environment, these changes are critical.

Context: Large local health departments (LHDs) serve diverse, high-need communities and are uniquely positioned to influence public health policy and practice locally, regionally, and nationally. Objective: The purpose of this study is to investigate policy engagement as a reported training need in the 2024 Public Health Workforce Interests and Needs Survey within large LHDs, highlighting gaps and opportunities to strengthen policy capacity. Design: Cross-sectional analysis of 2024 Public Health Workforce Interests and Needs Survey data using descriptive statistics and weighted logistic regression. Setting: Large LHDs, serving populations of 250 000 or more, across the US. Participants: Study sample included 24 121 responses from individuals working in large LHDs. Main Outcome Measures: Descriptive and regression-based statistics for training needs, self-identified skill-building interests, and predictors of reporting a policy engagement training need. Results: Nearly 40% of staff at large LHDs reported a training need in policy engagement, the only domain to show an increase in need since 2021. Women had significantly higher odds of reporting a policy training need (odds ratios [OR] = 1.67; P < .001), as did supervisors (OR = 2.09; P < .001) and managers (OR = 1.78; P < .001) compared to nonsupervisors, while those with master’s (OR = 0.64; P < .001) or doctoral degrees (OR = 0.40; P < .001) had lower odds compared to bachelor’s-level staff. Conclusions: Large LHDs are well positioned to advance public health policy given their scale and connection to local communities. Targeting policy engagement training to workforce segments with the highest reported need offers a strategic opportunity to strengthen policy capacity across the US public health workforce.

Context: High turnover rates in the public health workforce pose ongoing challenges to maintain essential services and institutional knowledge. Recent studies indicate that job dissatisfaction, burnout, and structural barriers have intensified following the COVID-19 pandemic. While prior studies have identified key predictors of turnover intention, the potential of machine learning (ML) to improve predictive accuracy and guide targeted interventions remains underexplored. Objective: This study applied ML techniques to examine the predictors of turnover intent and to simulate the impact of workplace satisfaction improvements among state health agency employees. Methods: We used data from 4 waves of the nationally representative Public Health Workforce Interests and Needs Survey: 2014, 2017, 2021, and 2024. Focusing on state health agency central office staff, we trained 3 ML models—Lasso Regression, Random Forest, and Gradient Boosting—to predict intent to leave one’s organization within the next year. Models were trained separately by year using cross-sectional data and evaluated. Variable importance was assessed, and a simulation was conducted to evaluate the potential reduction in predicted turnover following targeted improvements in job satisfaction, organizational satisfaction, and pay satisfaction. Results: All models demonstrated strong performance, with area under the receiver operating characteristic curve values ranging from 0.78 to 0.85. Job satisfaction consistently emerged as the most important predictor across all models and years, followed by organizational and pay satisfaction. Lasso Regression generally achieved the highest sensitivity and accuracy. Simulation results showed that modest improvements in satisfaction variables could substantially reduce predicted turnover intent, particularly among early- and mid-career staff. Conclusion: This study highlights the value of ML for identifying key predictors of turnover intention. Findings reinforce the importance of job satisfaction, organizational climate, and compensation in retaining public health staff. ML-driven tools can support more proactive, data-informed retention strategies in the governmental public health system.

This study examines entry pathways, motivations, and workforce characteristics of employees aged 35 years and under using data from the 2024 Public Health Workforce Interests and Needs Survey. The survey received 56 595 responses, including 12 839 from the 35 and underage group who completed tailored questions on entry and career motivations. Compared with older colleagues, a larger proportion of younger staff hold a public health degree (36% vs 17%) and work in public health sciences roles (54% vs 37%). Most entered the state and local government public health workforce from other jobs, with 60% coming from outside the public health field. Although many intend to remain in governmental public health long term, advancement barriers contribute to anticipated early departures. These findings suggest opportunities to strengthen and expand pathways into governmental public health, as well as leadership development strategies to retain this skilled and mission-driven segment of the workforce.

Introduction: Conceptualization of the COVID-19 response burden on the state and local government public health workforce is complicated as it continuously evolved and called upon nearly every aspect of the workforce. This study aims to catalog the scale of COVID-19 response among the state and local public health workforce by assessing the role of overtime in the delivery of public health services during pandemic response and shifts in agency size and program area distribution since the height of the pandemic. Methods: This study uses detailed state and local workforce survey data from the Public Health Workforce Interests and Needs Survey 2021 and 2024 administrations. The analytic sample includes the 72.2% of employees that served in a COVID-19 response role at any time during the pandemic (n = 30 914; N = 136 591) and 214 state and local agencies that participated in both years (n = 65 144 unduplicated responses). Results: In total, overtime equated for the equivalent of 25 000 FTE COVID-19 response employees, one-quarter (25%) of the total FTE COVID-19 response workforce. Of the 214 agencies that participated in both the Public Health Workforce Interests and Needs Survey 2021 and 2024, 41% of agencies (88) saw decreases in staff size overall between those 2 points in time. Shifts in primary program area between 2021 and 2024 are largely driven by changes in the proportion of non-full-time permanent employees. Conclusion: This analysis magnifies the strain on the existing capacity of the public health workforce during the COVID-19 pandemic. These challenges stem from a chronically underfunded and understaffed workforce that was not prepared for surge capacity beyond existing employees. Given that many state and local public health agencies are smaller post-pandemic, it is reasonable to conclude that without large infrastructural changes, the workforce would likely face the same challenges if another pandemic-like crisis were to occur.

Objective: To assess perceptions of effective communication training needs among US state and local government public health employees and examine variations across generations and other worker characteristics. Design: Cross-sectional survey analysis using data from the 2024 Public Health Workforce Interests and Needs Survey. Setting: State health agencies and local health departments across 48 states in the US. Participants: A total of 56 595 state and local government public health employees (37% response rate) representing 4 generations: Baby boomers (16%), Gen X (39%), millennials (38%), and Gen Z (7%). Main Outcome Measures: Training needs for effective communication, defined as the combination of ability to communicate effectively across audiences and ability to communicate persuasively. Training needs were identified when respondents rated skills as moderately or very important but reported being unable to perform or at beginner level. Results: Overall, 11% of respondents identified a training need for effective communication, including 7% with gaps in communicating effectively with different audiences and 9% in persuasive communication. Gen Z staff ranked persuasive communication as their top training need regardless of skill level. Logistic regression revealed that Communications and Policy staff (adjusted odds ratio 1.46, 95% CI 1.21-1.76) and Environmental Health staff (adjusted odds ratio 1.20, 95% CI 1.04-1.37) had higher odds of prioritizing communication training. Women and older generations were less likely to prioritize communication training compared to men and Gen Z, respectively. Conclusions: Although effective communication was identified as a training need, respondents did not consistently identify effective communication as their top perceived training need. Given the importance of communication to effective public health practice, training interventions should be tailored to different generations, roles, and programmatic areas.