PURPOSE: Alzheimer's disease and related dementias (ADRD) are a significant public health concern characterized by memory decline that, over time, leads to loss of independence. This study reports ADRD diagnosis rates among Medicare beneficiaries aged ≥ 65 years in rural America. METHODS: We conducted a descriptive analysis of Medicare Fee-for-Service (FFS) and Medicare Advantage enrollees using administrative Medicare data from 2020. Combining data from Medicare FFS and Medicare Advantage produces a more complete and representative sample of older adults than previous studies that used FFS data alone. Nonmetropolitan counties were used to define rural. Rural ADRD diagnosis rates, stratified by age, sex, race/ethnicity, and Census region, were adjusted using the 2000 Census population standard. FINDINGS: The study population consisted of 54 million Medicare data Fee-for-Service (FFS) and Medicare Advantage enrollees aged ≥ 65; 5.3 million beneficiaries were diagnosed with ADRD, and 16.2% (n = 861,337) of beneficiaries diagnosed with ADRD resided in rural America. The age-adjusted ADRD diagnosis rate was slightly lower in rural America (9.6 per 100 beneficiaries) than in the United States (10.0 per 100 beneficiaries). The South Census region had the highest rural ADRD diagnosis rates. CONCLUSION: These findings underscore the need for targeted interventions and support mechanisms to address the growing burden of ADRD in rural communities.

Public health policy interventions are associated with many important public health achievements. To provide public health practitioners and decision makers with practical approaches for examining and employing evidence-based public health (EBPH) policy interventions, we describe the characteristics and benefits that distinguish EBPH policy interventions from programmatic interventions. These characteristics include focusing on health at a population level, focusing on upstream drivers of health, and involving less individual action than programmatic interventions. The benefits of EBPH policy interventions include more sustained effects on health than many programs and an enhanced ability to address health inequities. Early childhood education and universal preschool provide a case example that illustrates the distinction between EBPH policy and programmatic interventions. This review serves as the foundation for 3 concepts that support the effective use of public health policy interventions: applying core component thinking to understand the population health effects of EBPH policy interventions; understanding the influence of existing policies, policy supports, and the context in which a particular policy is implemented on the effectiveness of that policy; and employing a systems thinking approach to identify leverage points where policy implementation can have a meaningful effect.

A growing body of literature uses the concept of core components to better understand small-scale programmatic interventions. Instead of interventions being viewed as unitary "black boxes," interventions are viewed as configurations of core components, which are the parts of interventions that carry their causal potential and therefore need to be reproduced with fidelity to produce the intended effect. To date, the concept of core components has not been as widely applied to public health policy interventions as it has to programmatic interventions. The purpose of this topical review is to familiarize public health practitioners and policy makers with the concept of core components as applied to public health policy interventions. Raising the profile of core component thinking can foster mindful adaptation and implementation of public health policy interventions while encouraging further research to enhance the supporting evidence base. We present 3 types of multilevel interactions in which the core components of a public health policy intervention produce effects at the population level by (1) seeking to directly affect individual behavior, (2) facilitating adoption of programmatic interventions by intermediaries, and (3) encouraging intermediaries to take action that can shape changes in upstream drivers of population health. Changing the unit of analysis from whole policies to core components can provide a basis for understanding how policies work and for facilitating novel evidence-generating strategies and rapid evidence reviews that can inform future adaptation efforts.

BACKGROUND AND OBJECTIVES: Although acute respiratory illness (ARI) is a leading cause of hospitalization among young children, few data are available about cost of hospitalization in middle-income countries. We estimated direct and indirect costs associated with severe ARI resulting in hospitalization among children aged <10 years in El Salvador and Panama through the societal perspective. METHODS: During 2012 and 2013, we surveyed caregivers of children hospitalized with ARI about their direct medical (i.e. outpatient consultation, medications, hospital fees), non-medical (transportation, childcare), and indirect costs (lost wages) at discharge and 7 days after discharge. We multiplied subsidized hospital bed cost derived from administrative data by hospitalization days to estimate provider costs. RESULTS: Overall, 638 children were enrolled with a median age of 12 months (IQR 6-23). Their median length of hospitalization was 4 days (IQR 3-6). In El Salvador, caregivers incurred a median of US$38 (IQR 22-72) in direct and indirect costs per illness episode, while the median government-paid hospitalization cost was US$118 (IQR 59-384) generating an overall societal cost of US$219 (IQR 101-416) per severe ARI episode. In Panama, caregivers incurred a median of US$75 (IQR 39-135) iin direct and indirect costs, and the health-care system paid US$280 (IQR 150-420) per hospitalization producing an overall societal cost of US$393 (IQR 258-552). CONCLUSIONS: The cost of severe ARI to caregivers and the health care system was substantive. Our estimates will inform models to estimate national costs of severe ARI and cost-benefit of prevention and treatment strategies.

BACKGROUND: In many Latin American countries, official influenza reports are neither timely nor complete, and surveillance of influenza-like illness (ILI) remains thin in consistency and precision. Public participation with mobile technology may offer new ways of identifying nonmedically attended cases and reduce reporting delays, but no published studies to date have assessed the viability of ILI surveillance with mobile tools in Latin America. We implemented and assessed an ILI-tailored mobile health (mHealth) participatory reporting system. OBJECTIVE: The objectives of this study were to evaluate the quality and characteristics of electronically collected data, the user acceptability of the symptom reporting platform, and the costs of running the system and of identifying ILI cases, and to use the collected data to characterize cases of reported ILI. METHODS: We recruited the heads of 189 households comprising 584 persons during randomly selected home visits in Guatemala. From August 2016 to March 2017, participants used text messages or an app to report symptoms of ILI at home, the ages of the ILI cases, if medical attention was sought, and if medicines were bought in pharmacies. We sent weekly reminders to participants and compensated those who sent reports with phone credit. We assessed the simplicity, flexibility, acceptability, stability, timeliness, and data quality of the system. RESULTS: Nearly half of the participants (47.1%, 89/189) sent one or more reports. We received 468 reports, 83.5% (391/468) via text message and 16.4% (77/468) via app. Nine-tenths of the reports (93.6%, 438/468) were received within 48 hours of the transmission of reminders. Over a quarter of the reports (26.5%, 124/468) indicated that at least someone at home had ILI symptoms. We identified 202 ILI cases and collected age information from almost three-fifths (58.4%, 118/202): 20 were aged between 0 and 5 years, 95 were aged between 6 and 64 years, and three were aged 65 years or older. Medications were purchased from pharmacies, without medical consultation, in 33.1% (41/124) of reported cases. Medical attention was sought in 27.4% (34/124) of reported cases. The cost of identifying an ILI case was US $6.00. We found a positive correlation (Pearson correlation coefficient=.8) between reported ILI and official surveillance data for noninfluenza viruses from weeks 41 (2016) to 13 (2017). CONCLUSIONS: Our system has the potential to serve as a practical complement to respiratory virus surveillance in Guatemala. Its strongest attributes are simplicity, flexibility, and timeliness. The biggest challenge was low enrollment caused by people's fear of victimization and lack of phone credit. Authorities in Central America could test similar methods to improve the timeliness, and extend the breadth, of disease surveillance. It may allow them to rapidly detect localized or unusual circulation of acute respiratory illness and trigger appropriate public health actions.