John Beltrami, Tamara Carree, Pilgrim Spikes, Mesfin S Mulatu, Sophia Ajoku, Erica Dunbar
{"title":"Assessment of Public Health Impact of 20 Non-Research HIV Demonstration Projects by Use of the CDC Science Impact Framework, United States, 2018-2022.","authors":"John Beltrami, Tamara Carree, Pilgrim Spikes, Mesfin S Mulatu, Sophia Ajoku, Erica Dunbar","doi":"10.1097/PHH.0000000000002205","DOIUrl":"https://doi.org/10.1097/PHH.0000000000002205","url":null,"abstract":"","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":"31 5","pages":"905"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jennifer A Lawlor, Jini Puma, Jamie N Powers, Marlayna Martinez, Danielle Varda, Jenn A Leiferman
{"title":"Shifting Connections: Assessing Changes in a Rural Social Network Addressing Adverse Childhood Experiences Over Time.","authors":"Jennifer A Lawlor, Jini Puma, Jamie N Powers, Marlayna Martinez, Danielle Varda, Jenn A Leiferman","doi":"10.1097/PHH.0000000000002143","DOIUrl":"10.1097/PHH.0000000000002143","url":null,"abstract":"<p><strong>Context: </strong>The present study was designed in the context of a movement towards using community-scale network-based approaches to address adverse childhood experiences (ACEs). Though these types of networks have become more common, assessments over time following typical network-building activities have been limited.</p><p><strong>Objective: </strong>This study focused on the question: To what extent does a rural ACEs network improve exchanges among network members following an intervention focused on improving interactions and networking among members?</p><p><strong>Design: </strong>We employed a pre-post design, assessing partnerships among organizations addressing ACEs within a single rural community with a baseline assessment and a follow-up assessment three years later.</p><p><strong>Setting: </strong>The study was conducted in the rural San Luis Valley in Colorado. It was part of a larger federally-funded, community-engaged study, entitled Supporting Trauma Awareness and Nurturing Children's Environments (STANCE).</p><p><strong>Participants: </strong>Participants for this study were representatives of organizations in the network (n = 59 in T1 and n = 58 in T2, n = 56 overlapping organizations across time points). Each participant was asked to report about their organization's partnerships in the network at two time points.</p><p><strong>Intervention: </strong>Between the baseline and follow-up assessments, an intervention to further develop the network was implemented. It included hosting a networking event among organizations working on ACEs and the development of a subcommittee of the local interagency oversight group that focused on promoting information-sharing about early childhood and ACEs among local organizations.</p><p><strong>Main outcome measures: </strong>Outcome measures included: clustering, path length, centrality and centralization, and density over time.</p><p><strong>Results: </strong>We identified changes across key network metrics, indicating that the network had increased centrality and centralization over time, decreased average path length, and increased clustering and density across three sub-networks.</p><p><strong>Conclusions: </strong>Changes identified in this network provide evidence that ACEs networks can change in response to focused network development activities.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":" ","pages":"700-708"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143504874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Availability of a Continuity of Operations Plan Toolkit for Public Health Mycobacteriology Laboratories.","authors":"Monica E Youngblood, Stephanie P Johnston","doi":"10.1097/PHH.0000000000002157","DOIUrl":"10.1097/PHH.0000000000002157","url":null,"abstract":"<p><p>Interruption of service events may result in a temporary inability to use equipment or laboratory space, compromise staffing and infrastructure, preclude maintenance or calibration of equipment, and prevent or require extensive disinfection and decontamination. A continuity of operations plan allows a mycobacteriology laboratory to shift efficiently from its regular structure to one that enables timely continuation of testing services. The Continuity of Operations Plan Toolkit for Public Health Mycobacteriology Laboratories was developed to aid continuity of operations planning for mycobacteriology laboratories that offer testing services for diagnosing tuberculosis. The toolkit includes processes for creating, modifying, or implementing mycobacteriology continuity of operations plans, including considerations for leveraging partnerships. Available within the toolkit are various templates and checklists which can be adapted to meet specific local needs. While intended for public health laboratories, the toolkit is applicable for clinical, commercial, and other laboratory types that may perform tuberculosis testing.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":" ","pages":"783-786"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leigh Reardon, Sharon E Perlman, Sarah E Dumas, Tashema Bholanath, Pui Ying Chan, Aldo Crossa, Shabitri Dasgupta, L Hannah Gould, Nafesa Kanneh, Maria Lejano, Amber Levanon Seligson, Sungwoo Lim, Nika Norvila, Kacie Seil, Tanzia Shaheen, Adrienne Solomon, R Charon Gwynn
{"title":"Creating a Probability Survey Panel for Population Health Research: The Experience of the NYC Health Panel.","authors":"Leigh Reardon, Sharon E Perlman, Sarah E Dumas, Tashema Bholanath, Pui Ying Chan, Aldo Crossa, Shabitri Dasgupta, L Hannah Gould, Nafesa Kanneh, Maria Lejano, Amber Levanon Seligson, Sungwoo Lim, Nika Norvila, Kacie Seil, Tanzia Shaheen, Adrienne Solomon, R Charon Gwynn","doi":"10.1097/PHH.0000000000002160","DOIUrl":"10.1097/PHH.0000000000002160","url":null,"abstract":"<p><strong>Context: </strong>Survey panels can allow for more efficient data collection than traditional surveillance surveys both in terms of cost and operations. Seeking an alternative way to collect timely, high-quality data, the New York City (NYC) Health Department created a probability-based survey panel.</p><p><strong>Program: </strong>The NYC Health Panel was launched in April 2020. Over its first 2 years, the Panel recruited adults (ages 18+) in NYC from address-based lists and probabilistic surveys.</p><p><strong>Implementation: </strong>Once enrolled, panelists were invited to participate in up to 10 surveys per year. Surveys could be completed online (self-administered) or via paper or phone (computer assisted telephone interview) and were offered in 5 languages. Panelists were reconsented at the start of each survey and offered an incentive at completion. Panelists were compared to the 2017-2021 5-year American Community Survey data of NYC adults to assess representativeness. Weighting was used to adjust for these differences.</p><p><strong>Evaluation: </strong>The NYC Health Department was able to successfully launch the Panel and collect survey data. In its first 2 years, the Panel enrolled approximately 13 000 adult NYC residents and conducted 18 surveys. Most surveys were completed online and in English. The Panel's size and probabilistic design allow for the creation of individual survey samples that are representative of adult NYC residents.</p><p><strong>Discussion: </strong>The NYC Health Panel is an invaluable resource in response to the COVID-19 pandemic, in assessing racial inequities, and in measuring the secondary pandemics of food insecurity, delayed primary care, and adverse mental health. It serves as a unique example of how health departments that have the necessary in-house staff resources can collect timely data.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":" ","pages":"828-835"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143992309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ghee Kheng Lim, Xuan Ci Mee, Ramzi Ibrahim, Hoang Nhat Pham, Mahmoud Abdelnabi, Girish Pathangey, George Bcharah, Christopher Kanaan, Carolyn Larsen, Chadi Ayoub, Kwan Lee
{"title":"County-Level Urbanization and Cardiovascular Death in Patients With Cancer.","authors":"Ghee Kheng Lim, Xuan Ci Mee, Ramzi Ibrahim, Hoang Nhat Pham, Mahmoud Abdelnabi, Girish Pathangey, George Bcharah, Christopher Kanaan, Carolyn Larsen, Chadi Ayoub, Kwan Lee","doi":"10.1097/PHH.0000000000002173","DOIUrl":"10.1097/PHH.0000000000002173","url":null,"abstract":"<p><strong>Context: </strong>Cardiovascular death (CVD) is a leading cause of mortality in patients with cancer, with sociodemographic factors such as urbanization influencing outcomes.</p><p><strong>Objective: </strong>To examine the impact of county-level urbanization on CVD mortality in patients with cancer in the United States from 1999 to 2020.</p><p><strong>Design: </strong>Retrospective cross-sectional analysis using CDC WONDER mortality data.</p><p><strong>Setting: </strong>US counties categorized as rural or urban based on the 2013 NCHS Urban-Rural Classification Scheme.</p><p><strong>Participants: </strong>Patients with cardiovascular disease (ICD-10: I00-I78) and comorbid cancer (ICD-10: C00-C97), spanning all U.S. counties from 1999 to 2020.</p><p><strong>Main outcome measures: </strong>Age-adjusted mortality rates (AAMRs) per 100 000 population and rural-to-urban rate ratios (RRs) with 95% confidence intervals.</p><p><strong>Results: </strong>The cumulative rural-to-urban RR for CVD in patients with cancer was 1.11 (95% CI: 1.10-1.11), increasing from 1.00 in 1999 to 1.20 in 2020 (β = 0.009, P < .001). Rural AAMRs were higher across demographic groups, including males (12.85 vs 11.62 per 100 000), females (6.08 vs 5.58), Black individuals (9.76 vs 9.64), and White individuals (8.79 vs 7.94). Rural Black populations showed a rising RR from 0.85 in 1999 to 1.04 in 2020 (β = 0.005, P = .01). Hispanic populations exhibited lower rural mortality, with a stable RR (0.93, P = 1.0). The most common CVD cause was ischemic heart disease (53.93% of rural and 55.9% of urban deaths).</p><p><strong>Conclusions: </strong>An increasing rural-to-urban disparity in CVD mortality among cancer patients highlights the role of urbanization in health inequities. Interventions targeting rural health care access and socioeconomic disparities are essential to address this growing gap.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":" ","pages":"755-762"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144040854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Khyathi Gadag, Ufuoma Ejughemre, Kristin Wilson, Whitney E Zahnd
{"title":"Addressing Social Determinants of Health in Rural Iowa Hospitals: Content Analysis of Community Health Needs Assessments.","authors":"Khyathi Gadag, Ufuoma Ejughemre, Kristin Wilson, Whitney E Zahnd","doi":"10.1097/PHH.0000000000002184","DOIUrl":"10.1097/PHH.0000000000002184","url":null,"abstract":"<p><strong>Objectives: </strong>With the shift to value-based care, social needs screening and referrals and other means of addressing the social determinants of health (SDOH) have become important ways for hospitals to address population health, which is particularly important for rural communities. Our objective was to evaluate how Iowa rural hospitals identified SDOHs in their community health needs assessment (CHNAs).</p><p><strong>Design: </strong>We conducted content analysis on the most recent CHNAs, and corresponding implementation plans of 53 rural Iowa hospitals, capturing broad social needs terms (eg, social screening, social risk) and specific SDOH terms (eg, housing, food insecurity), and hospital-community partnerships. We conducted stratified analysis by hospital-level characteristics like ownership (not-for-profit, non-federal government), type, and Accountable Care Organizations participation, and sociodemographic characteristics of each hospital's defined community area.</p><p><strong>Results: </strong>The most frequently identified SDOH were food insecurity (94.4%), transportation (92.6%), and housing insecurity (83.3%). Implementation plans primarily addressed food insecurity (53.7%), transportation (48.1%), and housing insecurity (35.2%). The most common hospital partnerships were with schools (68.5%), local organizations (53.7%), and faith-based organizations (31.5%). A lower percentage of Critical Access Hospitals and non-federal government hospitals addressed SDOH in their implementation plans compared to rural prospective payment system hospitals and non-profit hospitals, respectively. Hospitals serving counties with higher social needs showed higher assessment but lower implementation addressing these needs.</p><p><strong>Conclusion: </strong>The disparities in screening and implementation efforts by hospital type, ownership, and payment models highlight the need for tailored policy interventions and infrastructure support to enhance social needs strategies, particularly in rural contexts.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":" ","pages":"716-725"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bridging the Gap: Integrating STI and Harm Reduction Services to Combat Syndemics in the United States.","authors":"Kathleen Kelley","doi":"10.1097/PHH.0000000000002188","DOIUrl":"https://doi.org/10.1097/PHH.0000000000002188","url":null,"abstract":"","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":"31 5","pages":"899-901"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Addressing the Lack of Nutritional Interventions Tailored to the Experiences of the Homeless: A Perspective.","authors":"Aditi Tuli, Carolina Escamilla, Ben King","doi":"10.1097/PHH.0000000000002135","DOIUrl":"10.1097/PHH.0000000000002135","url":null,"abstract":"","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":" ","pages":"874-876"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial Intelligence and the Practice of Public Health.","authors":"Edward L Baker, David A Ross","doi":"10.1097/PHH.0000000000002186","DOIUrl":"https://doi.org/10.1097/PHH.0000000000002186","url":null,"abstract":"","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":"31 5","pages":"894-896"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abby Vogel, Krishna Patel, Timothy C McCall, Jason Orr, Jonathon P Leider
{"title":"The Public Health Workforce Calculator in a Post-COVID Era.","authors":"Abby Vogel, Krishna Patel, Timothy C McCall, Jason Orr, Jonathon P Leider","doi":"10.1097/PHH.0000000000002177","DOIUrl":"10.1097/PHH.0000000000002177","url":null,"abstract":"<p><strong>Context: </strong>A new tool, the Public Health Workforce Calculator (\"Workforce Calculator\"), was developed near the onset of the COVID pandemic to help agencies estimate the staffing they would need to fully implement the Foundational Public Health Services (FPHS). The data underlying the Workforce Calculator algorithm was from pre-pandemic time periods.</p><p><strong>Objective: </strong>To assess whether the Workforce Calculator continues to reliably estimate staffing need in a peri-COVID context.</p><p><strong>Design: </strong>Local health departments participated in the National Association of County and City Health Officials Profile survey, which for a random half of agencies, stratified by jurisdiction size, contained a module that asked them to estimate the FTE they would need to fully implement FPHS. For each of the 108 valid responding agencies, these data were compared with the Workforce Calculator output that the agency would have received to assess whether the Workforce Calculator was concordantly estimating staffing needs.</p><p><strong>Main outcome measure: </strong>We assessed concordance between the reported staffing needs and the Workforce Calculator's estimates, both graphically and quantitatively, using Lin's concordance correlation coefficient.</p><p><strong>Results: </strong>For most FPHS categories, the Workforce Calculator systematically underestimated the amount of staffing needed for full implementation relative to agencies' reported needs.</p><p><strong>Conclusions: </strong>Post-COVID staffing needs systematically appear more substantial than the pre-COVID data on which the Workforce Calculator was based. An update to the Workforce Calculator using post-COVID data would benefit end users.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":"31 5","pages":"836-843"},"PeriodicalIF":2.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}