Community Voices and Whole-Genome Sequencing for Tuberculosis: Storytelling and the Importance of Listening.

One of the primary public health functions of a tuberculosis (TB) program is to arrest the spread of infection. Traditionally, TB programs have relied on epidemiological information, gathered through contact tracing, to infer that transmission has occurred between people. The ability of drawing such inferences is extensively context dependent. Where epidemiological information has been strong, such as 2 cases of TB occurring sequentially within a single household, confidence in such inferences is high; conversely, public health authorities have been less certain about the significance of TB cases merely occurring in the same wider social group or geographic area. Many current laboratory tests for TB used globally may be sufficient to confirm a diagnosis and guide appropriate therapy but still be insufficiently precise for distinguishing two strains reliably. In short, drawing inferences regarding a chain of transmissions has always been as much art as science.

Intervención participativa comunitaria: necesidades de salud de las personas mayores durante el período de la pandemia por COVID-19 / Community participatory intervention: health needs of older people during the COVID-19 pandemic period

Objetivo. Proponer una intervención participativa comunitaria según las necesidades de salud percibida por las personas mayores del Programa de Salud Cardiovascular de un centro de salud familiar y comunitaria de una comuna de Santiago de Chile durante el período de la pandemia de la COVID-19. Métodos. Se utilizó una metodología participativa de la comunidad, la cual se desarrolló en dos fases: diagnóstico participativo comunitario y desarrollo de la propuesta participativa de una intervención en salud comunitaria. Resultados. Desde el diagnóstico participativo comunitario, los participantes eligieron el desarrollo de un programa educativo fundamentado en las necesidades de salud, además de la entrega de material educativo sobre estilos de vida saludable y recomendaciones para tener un buen control de sus enfermedades. Conclusión. Desde el diagnóstico y planificación participativa, es posible intervenir en pro de las necesidades de las personas, familias y comunidades y capacitarlas en el manejo de su propia salud. (AU)

Aim. To propose a community participatory intervention according to the health needs perceived by elderly people in the Family and Community Health Centre Cardiovascular Health programme of a Santiago de Chile commune during the COVID-19 pandemic. Methods. A community participatory methodology was used, which was developed over two phases: community participatory diagnosis and development of a participatory proposal for a community health intervention. Results. From the community participatory diagnosis, participants opted for development of an educational programme based on health needs, in addition to the delivery of educational material related to healthy lifestyles and recommendations for robust control of their diseases. Conclusion. From diagnosis and participatory planning, it is possible to intervene in favour of the needs of individuals, families and communities and train them in managing their own health. (AU)

Alfabetización en salud: proceso de aprendizaje significativo personal y comunitario / Health literacy: meaningful personal and community learning process

El aprendizaje y la salud son dos elementos vinculados entre sí. El hecho de cuidar de la salud requiere del aprendizaje de conocimientos, habilidades, comportamientos y actitudes que se desarrollan a lo largo de nuestra vida. Los aprendizajes relacionados con la salud comportan estilos de vida más saludables, la mejora del bienestar, la calidad de vida y la salud de la comunidad. El aprendizaje significativo transforma las vidas, abriendo nuevas oportunidades, posibilitando nuevas competencias y formando nuevas redes sociales. Este artículo pretende reflexionar sobre la relación entre elementos de la alfabetización en salud y el proceso de aprendizaje significativo. (AU)

Learning and health are both interrelated aspects. The act of looking after health requires learning knowledge, skills, behaviors, and attitudes that develop throughout our lives. Health-related learning leads to healthier lifestyles, improved well-being, better quality of life and community health. Significant learning transforms lives, paving the way towards new opportunities, enabling new skills and forming new social networks. This paper aims to reflect on the relationship between aspects of health literacy and the meaningful learning process. (AU)

A reproducible ensemble machine learning approach to forecast dengue outbreaks.

Dengue fever, a prevalent and rapidly spreading arboviral disease, poses substantial public health and economic challenges in tropical and sub-tropical regions worldwide. Predicting infectious disease outbreaks on a countrywide scale is complex due to spatiotemporal variations in dengue incidence across administrative areas. To address this, we propose a machine learning ensemble model for forecasting the dengue incidence rate (DIR) in Brazil, with a focus on the population under 19 years old. The model integrates spatial and temporal information, providing one-month-ahead DIR estimates at the state level. Comparative analyses with a dummy model and ablation studies demonstrate the ensemble model's qualitative and quantitative efficacy across the 27 Brazilian Federal Units. Furthermore, we showcase the transferability of this approach to Peru, another Latin American country with differing epidemiological characteristics. This timely forecast system can aid local governments in implementing targeted control measures. The study advances climate services for health by identifying factors triggering dengue outbreaks in Brazil and Peru, emphasizing collaborative efforts with intergovernmental organizations and public health institutions. The innovation lies not only in the algorithms themselves but in their application to a domain marked by data scarcity and operational scalability challenges. We bridge the gap by integrating well-curated ground data with advanced analytical methods, addressing a significant deficiency in current practices. The successful transfer of the model to Peru and its consistent performance during the 2019 outbreak in Brazil showcase its scalability and practical application. While acknowledging limitations in handling extreme values, especially in regions with low DIR, our approach excels where accurate predictions are critical. The study not only contributes to advancing DIR forecasting but also represents a paradigm shift in integrating advanced analytics into public health operational frameworks. This work, driven by a collaborative spirit involving intergovernmental organizations and public health institutions, sets a precedent for interdisciplinary collaboration in addressing global health challenges. It not only enhances our understanding of factors triggering dengue outbreaks but also serves as a template for the effective implementation of advanced analytical methods in public health.

Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic.

The substance use disorder epidemic has emerged as a serious public health crisis, presenting complex challenges. Visual analytics offers a unique approach to address this complexity and facilitate effective interventions. This paper details the development of an innovative visual analytics dashboard, aimed at enhancing our understanding of the substance use disorder epidemic. By employing record linkage techniques, we integrate diverse data sources to provide a comprehensive view of the epidemic. Adherence to responsive, open, and user-centered design principles ensures the dashboard's usefulness and usability. Our approach to data and design encourages collaboration among various stakeholders, including researchers, politicians, and healthcare practitioners. Through illustrative outputs, we demonstrate how the dashboard can deepen our understanding of the epidemic, support intervention strategies, and evaluate the effectiveness of implemented measures. The paper concludes with a discussion of the dashboard's use cases and limitations.

Unleashing the global potential of public health: A framework for future pandemic response.

Public health emergencies, especially pandemics, need to be managed globally, and on several levels, emphasizing the importance of leadership, communication, and synchronization of measures, data, and management plans in contrast to the management of the Coronavirus-19 pandemic, which illustrated diverse strategies employed by various nations. This paper aims to review and discuss whether globalized diseases in a globalized world should be managed by globalized public health. Using a systematic literature search, followed by a non-systematic literature review, selected studies were grouped into topics, and analyzed, using content analysis to enhance the conclusive results. The results present a roadmap towards a re-envisioned framework highlighting key areas of focus: data-driven decision-making, robust technology infrastructure, global cooperation, and ongoing public health education, as part of a coordinated global response. This article reveals the weaknesses of current pandemic management systems and recommends new steps to further strengthen the management of future pandemics.

A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts.

How likely is it to become infected by SARS-CoV-2 after being exposed? Almost everyone wondered about this question during the COVID-19 pandemic. Contact-tracing apps1,2 recorded measurements of proximity3 and duration between nearby smartphones. Contacts-individuals exposed to confirmed cases-were notified according to public health policies such as the 2 m, 15 min guideline4,5, despite limited evidence supporting this threshold. Here we analysed 7 million contacts notified by the National Health Service COVID-19 app6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had risk similar to that of shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. Whereas most exposures were short (median 0.7 h, interquartile range 0.4-1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4-28). Households accounted for about 6% of contacts but 40% of transmissions. With sufficient preparation, privacy-preserving yet precise analyses of risk that would inform public health measures, based on digital contact tracing, could be performed within weeks of the emergence of a new pathogen.

Retention of Community Health Workers in the Public Health Workforce: Public Health Workforce Interests and Needs Survey, 2017 and 2021.

Objectives. To investigate the organizational factors contributing to the intent of community health workers (CHWs) to quit their jobs in local and state health departments in the United States. Methods. We used the 2017 (n = 844) and 2021 (n = 1014) Public Health Workforce Interests and Needs Survey data sets to predict CHWs' intent to leave with Stata 17 balanced repeated replication survey estimations. Results. CHWs dissatisfied with organizational support, pay, or job security had high probabilities of reporting an intent to leave (50%, P < .01; 39%, P < .01; and 42%, P < .01, respectively) relative to satisfied or neutral workers (24%, P < .01; 21%, P < .01; and 26%, P < .01, respectively). Conclusions. Improving organizational support, pay satisfaction, and job security satisfaction in public health agencies can significantly improve CHW retention, potentially lowering overall organizational costs, enhancing organizational morale, and promoting community health. Public Health Implications. Our findings shed light on actionable ways to improve CHW retention, including assessing training needs; prioritizing diversity, equity, and inclusion; and improving communication between management and workers. (Am J Public Health. 2024;114(1):44-47. https://doi.org/10.2105/AJPH.2023.307462).

Standard Occupational Classification Codes: Gaps in Federal Data on the Public Health Workforce.

Objectives. To determine whether US Department of Labor standard occupational classification (SOC) codes can be used for public health workforce research. Methods. We reviewed past attempts at SOC matching for public health occupations and then used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to match the actual job titles for 26 516 respondents to the 2021 Public Health Workforce Interests and Needs Survey (PH WINS) with SOC codes, grouped by respondents' choice of job category in PH WINS. We assessed the accuracy of the NIOCCS matches and excluded matches under a cutpoint using the Youden Index. We assessed the percentage of SOC matches with insufficient information and diversity of SOC matches per PH WINS category using the Herfindahl-Hirschman Index. Results. Several key public health occupations do not have a SOC code, including disease intervention specialist, public health nurse, policy analyst, program manager, grants or contracts specialist, and peer counselor. Conclusions. Without valid SOC matches and detailed data on local and state government health departments, the US Department of Labor's data cannot be used for public health workforce enumeration. (Am J Public Health. 2024;114(1):48-56. https://doi.org/10.2105/AJPH.2023.307463).

Historical narratives about the COVID-19 pandemic are motivationally biased.

How people recall the SARS-CoV-2 pandemic is likely to prove crucial in future societal debates on pandemic preparedness and appropriate political action. Beyond simple forgetting, previous research suggests that recall may be distorted by strong motivations and anchoring perceptions on the current situation1-6. Here, using 4 studies across 11 countries (total n = 10,776), we show that recall of perceived risk, trust in institutions and protective behaviours depended strongly on current evaluations. Although both vaccinated and unvaccinated individuals were affected by this bias, people who identified strongly with their vaccination status-whether vaccinated or unvaccinated-tended to exhibit greater and, notably, opposite distortions of recall. Biased recall was not reduced by providing information about common recall errors or small monetary incentives for accurate recall, but was partially reduced by high incentives. Thus, it seems that motivation and identity influence the direction in which the recall of the past is distorted. Biased recall was further related to the evaluation of past political action and future behavioural intent, including adhering to regulations during a future pandemic or punishing politicians and scientists. Together, the findings indicate that historical narratives about the COVID-19 pandemic are motivationally biased, sustain societal polarization and affect preparation for future pandemics. Consequently, future measures must look beyond immediate public-health implications to the longer-term consequences for societal cohesion and trust.

A global research agenda on public health and social measures during emergencies.

The importance of strong coordination for research on public health and social measures was highlighted at the Seventy-fourth World Health Assembly in 2021. This article describes efforts undertaken by the World Health Organization (WHO) to develop a global research agenda on the use of public health and social measures during health emergencies. This work includes a multistep process that started with a global technical consultation convened by WHO in September 2021. The consultation included experts from around the world and from a wide range of disciplines, such as public health, education, tourism, finance and social sciences, and aimed to identify research and implementation approaches based on lessons learnt during the coronavirus disease 2019 pandemic. To prepare for future epidemics and pandemics, it is essential to adopt a more robust, comparable and systematic research approach to public health and social measures. Such comprehensive approach will better inform agile, balanced and context-specific implementation decisions during future emergencies. This article describes the methods used to develop global research priorities for public health and social measures and the next steps needed.

La soixante-quatorzième Assemblée mondiale de la Santé en 2021 a souligné l'importance d'une coordination solide pour la recherche sur la santé publique et les mesures sociales. Le présent article décrit les efforts entrepris par l'Organisation mondiale de la santé (OMS) pour élaborer un programme de recherche mondial sur l'utilisation des mesures de santé publique et des mesures sociales lors de situations d'urgence sanitaire. Ce travail comprend un processus en plusieurs étapes qui a commencé par une consultation technique mondiale organisée par l'OMS en septembre 2021. La consultation a réuni des experts du monde entier issus d'un large éventail de disciplines telles que la santé publique, l'éducation, le tourisme, la finance et les sciences sociales. Elle visait à identifier des approches de recherche et de mise en œuvre fondées sur les enseignements tirés de la pandémie de maladie à coronavirus de 2019. Pour se préparer aux futures épidémies et pandémies, il est essentiel d'adopter une approche de recherche plus solide, comparable et systématique en matière de santé publique et de mesures sociales. Cette approche globale permettra de mieux éclairer les décisions de mise en œuvre agiles, équilibrées et adaptées au contexte lors des futures situations d'urgence. Le présent article décrit les méthodes appliquées pour définir les priorités mondiales de recherche en matière de santé publique et de mesures sociales, ainsi que les prochaines étapes à franchir.

En la 74.ª Asamblea Mundial de la Salud, celebrada en 2021, se destacó la importancia de una sólida coordinación en la investigación sobre salud pública y medidas sociales. Este artículo describe los esfuerzos que ha emprendido la Organización Mundial de la Salud (OMS) para desarrollar un programa mundial de investigación sobre el uso de medidas sociales y de salud pública durante las emergencias sanitarias. Este trabajo incluye un proceso de varios pasos que comenzó con una consulta técnica mundial que convocó la OMS en septiembre de 2021. La consulta incluyó a expertos de todo el mundo y de una gran variedad de disciplinas, como la salud pública, la educación, el turismo, las finanzas y las ciencias sociales, y tuvo como objetivo identificar enfoques de investigación y aplicación basados en las lecciones aprendidas durante la pandemia de la enfermedad por coronavirus de 2019. Para prepararse ante futuras epidemias y pandemias, es esencial adoptar un enfoque de investigación más sólido, comparable y sistemático en materia de salud pública y medidas sociales. Este enfoque integral informará mejor las decisiones de aplicación ágiles, equilibradas y adaptadas al contexto durante futuras emergencias. En este artículo se describen los métodos utilizados para elaborar las prioridades mundiales de investigación sobre salud pública y medidas sociales, así como los próximos pasos necesarios.

Priorities for research to support local authority action on health and climate change: a study in England.

BACKGROUND: Evidence is needed to support local action to reduce the adverse health impacts of climate change and maximise the health co-benefits of climate action. Focused on England, the study identifies priority areas for research to inform local decision making. METHODS: Firstly, potential priority areas for research were identified from a brief review of UK policy documents, and feedback invited from public and policy stakeholders. This included a survey of Directors of Public Health (DsPH) in England, the local government officers responsible for public health. Secondly, rapid reviews of research evidence examined whether there was UK evidence relating to the priorities identified in the survey. RESULTS: The brief policy review pointed to the importance of evidence in two broad areas: (i) community engagement in local level action on the health impacts of climate change and (ii) the economic (cost) implications of such action. The DsPH survey (n = 57) confirmed these priorities. With respect to community engagement, public understanding of climate change's health impacts and the public acceptability of local climate actions were identified as key evidence gaps. With respect to economic implications, the gaps related to evidence on the health and non-health-related costs and benefits of climate action and the short, medium and longer-term budgetary implications of such action, particularly with respect to investments in the built environment. Across both areas, the need for evidence relating to impacts across income groups was highlighted, a point also emphasised by the public involvement panel. The rapid reviews confirmed these evidence gaps (relating to public understanding, public acceptability, economic evaluation and social inequalities). In addition, public and policy stakeholders pointed to other barriers to action, including financial pressures, noting that better evidence is insufficient to enable effective local action. CONCLUSIONS: There is limited evidence to inform health-centred local action on climate change. More evidence is required on public perspectives on, and the economic dimensions of, local climate action. Investment in locally focused research is urgently needed if local governments are to develop and implement evidence-based policies to protect public health from climate change and maximise the health co-benefits of local action.

Fotovoz de activos en Cornellà de Llobregat, una experiencia de los profesionales sanitarios para conocer la comunidad / Photovoice of Cornellà de Llobregat assets, an experience for healthcare professionals to get to know the community

Introducción. La prescripción social es el proceso de recomendación de activos beneficiosos para la salud y bienestar. Para ello es necesario conocer los activos de la comunidad de trabajo. El fotovoz es una técnica de investigación participativa que permite conocer una comunidad con la fotografía.Objetivos. Elaborar un fotovoz con los activos de salud de la comunidad.Métodos. Se formó a profesionales y se hizo un paseo comunitario para identificar y fotografiar activos de la comunidad. Se hizo una puesta en común de las fotografías recogidas y una selección. Se creó un fotovoz que se expuso en el centro.Resultados. Un total de 17 profesionales sanitarios hicieron 91 fotografías a activos. Se hizo una selección y se llevó a cabo una discusión, y como resultado, se creó un fotovoz con 16 activos.Conclusión. El fotovoz es un proceso participativo basado en la comunidad que permite mejorar el conocimiento que los profesionales sanitarios tienen sobre los recursos de salud disponibles en su entorno y hacer una prescripción social. (AU)

Introduction. Social prescribing is the process of recommending assets beneficial to health and well-being. To do this, it is necessary to get to know the assets of the working community. Photovoice is a participatory research technique that enables getting to know a community with photography.Objectives. Prepare a Photovoice with community health assets.Methods. Professionals were trained and a community walk was held to identify and photograph community assets. A sharing the photographs collected and made a selection. A Photovoice was created and exhibited in the centre.Results. A total of 17 healthcare professionals took 91 asset photographs. A selection was made and a discussion held. As a result a photovoice was created with 16 assets.Conclusion. PhotoVoice is a community-based participatory process that enables improving health professionals' knowledge of the health resources available in their setting and enables social prescribing. (AU)

Design and Implementation of an Innovative, Rapid Data-Monitoring Strategy for Public Health Emergencies: Pilot of the United States School COVID-19 Mitigation Strategies Project.

During the COVID-19 pandemic, an urgent need existed for near-real-time data collection to better understand how individual beliefs and behaviors, state and local policies, and organizational practices influenced health outcomes. We describe the processes, methods, and lessons learned during the development and pilot testing of an innovative rapid data collection process we developed to inform decision-making during the COVID-19 public health emergency. We used a fully integrated mixed-methods approach to develop a structured process for triangulating quantitative and qualitative data from traditional (cross-sectional surveys, focus groups) and nontraditional (social media listening) sources. Respondents included students, parents, teachers, and key school personnel (eg, nurses, administrators, mental health providers). During the pilot phase (February-June 2021), data from 12 cross-sectional and sector-based surveys (n = 20 302 participants), 28 crowdsourced surveys (n = 26 820 participants), 10 focus groups (n = 64 participants), and 11 social media platforms (n = 432 754 503 responses) were triangulated with other data to support COVID-19 mitigation in schools. We disseminated findings through internal dashboards, triangulation reports, and policy briefs. This pilot demonstrated that triangulating traditional and nontraditional data sources can provide rapid data about barriers and facilitators to mitigation implementation during an evolving public health emergency. Such a rapid feedback and continuous improvement model can be tailored to strengthen response efforts. This approach emphasizes the value of nimble data modernization efforts to respond in real time to public health emergencies.

Child Mental Health Status in Flint, Michigan: A Worsening Health Inequity, 2018-2022.

Objectives. To determine the burden of mental health disorders among children enrolled in Michigan's Flint Registry in the context of a local public health crisis and a nationally declared pediatric mental health crisis. Methods. This survey-based study included 1203 children aged 3 to 17 years whose caregivers enrolled them in the Flint Registry between December 2018 and March 2020 and who completed a follow-up survey between October 2020 and March 2022. The baseline and follow-up surveys included caregiver reports of childhood anxiety and depression and overall mental health wellness. Results. At enrollment, Flint Registry caregivers reported significantly higher rates of anxiety and depression among their children than caregivers reported nationally (12.9% vs 9.4% and 8.2% vs 4.4%; P < .001). Flint Registry caregivers also reported declines in their children's overall mental health wellness at follow-up, t(1472) = -4.17; P < .001. Conclusions. Our findings reveal a disparate burden of pediatric mental health disorders and exemplify the health inequities vulnerable populations face. Public Health Implications. More proactive and preventive steps should be taken to lessen this burden, especially in chronically disadvantaged communities that experience public health crises. (Am J Public Health. 2023;113(12):1318-1321. https://doi.org/10.2105/AJPH.2023.307406).