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Mudança Climática , Humanos , Epidemiologistas , Abastecimento de Alimentos , Saúde PúblicaRESUMO
The current humanitarian crises in Ukraine and Gaza, along with the chronic crises, and the climate-related disasters, have exposed the limitations of the humanitarian system. Within these contexts, humanitarian organisations frequently struggle with collecting, analysing, interpreting, and utilising health data, due to the challenging environments in which they operate and funding constraints. It is precisely in these contexts that field epidemiology plays a crucial, but often overlooked role.Field epidemiologists face unique challenges, including rapidly changing conditions, poor-quality data, and biases. Despite these difficulties, accurate epidemiological data are essential for needs assessment, guidance on interventions, and advocacy. Conventional methods often need adaptation for crisis settings, and there are still gaps in measurement.This article discusses the role of epidemiology in such contexts, noting a shortage of trained 'humanitarian epidemiologists' and specialised training as major issues.To address these needs, the Italian Association of Epidemiology organised a course in early 2024 to enhance the epidemiological skills of staff working in humanitarian crises and introduce traditional epidemiologists to crisis-specific challenges. The course covered key concepts and methods of field epidemiology, emphasising the use of secondary health data. Its positive reception underscored the demand for such specialised training.Improving public health information collection and use in humanitarian crises is an ethical and practical necessity. Indeed, investing in field epidemiology and recognising its importance can enhance humanitarian interventions and better serve vulnerable populations.
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Altruísmo , Epidemiologia , Itália/epidemiologia , Humanos , Epidemiologia/educação , Ucrânia/epidemiologia , Epidemiologistas , Socorro em Desastres/organização & administração , Desastres , Oriente Médio/epidemiologia , Sociedades Médicas , Recursos HumanosRESUMO
In Massachusetts (MA), partner notification is routinely offered for new HIV and infectious syphilis cases, but there are no formal partner notification services for gonorrhea and chlamydia. Electronic partner notification (ePN), which allows patients to anonymously notify their partners of sexually transmitted infection exposure, could fill this gap. We evaluated the acceptability of and ideal characteristics for a statewide ePN service in MA. We performed semistructured interviews with patients at a Boston area sexual health clinic and conducted focus groups with clinicians and Massachusetts Department of Public Health Field Epidemiologists (FEs). We developed a codebook and thematically analyzed interview and focus group data; 25% of interviews were double coded. We identified six main themes from our data: (1) partner notification is a relational process and (2) partner notification is situation dependent. There are three pairs of challenges and core values for an effective ePN system: (3) stigmatization versus inclusivity, (4) trust versus mistrust, and (5) privacy versus helpful information sharing. Therefore, (6) a statewide ePN platform must be customizable at each possible step. Although ePN was acceptable across all three groups, the likelihood of individual use was grounded in a patient's sociocultural context, interpersonal relationships, trust in the platform and health authorities, desire to avoid stigmatization, and privacy needs. These factors are best accommodated by a platform that adapts to users' preferences and needs. ePN presents an opportunity to link partners at risk for gonorrhea or chlamydia to clinical care that is complementary to the more labor-intensive FE role.
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Infecções por Chlamydia , Gonorreia , Infecções por HIV , Infecções Sexualmente Transmissíveis , Humanos , Gonorreia/epidemiologia , Busca de Comunicante , Epidemiologistas , Infecções por HIV/epidemiologia , Parceiros Sexuais , Infecções Sexualmente Transmissíveis/epidemiologia , Infecções por Chlamydia/epidemiologiaRESUMO
M-estimation is a statistical procedure that is particularly advantageous for some comon epidemiological analyses, including approaches to estimate an adjusted marginal risk contrast (i.e. inverse probability weighting and g-computation) and data fusion. In such settings, maximum likelihood variance estimates are not consistent. Thus, epidemiologists often resort to bootstrap to estimate the variance. In contrast, M-estimation allows for consistent variance estimates in these settings without requiring the computational complexity of the bootstrap. In this paper, we introduce M-estimation and provide four illustrative examples of implementation along with software code in multiple languages. M-estimation is a flexible and computationally efficient estimation procedure that is a powerful addition to the epidemiologist's toolbox.
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Epidemiologistas , Idioma , Humanos , Probabilidade , Software , Modelos Estatísticos , Simulação por ComputadorRESUMO
INTRODUCTION: COVID-19 underscored the importance of field epidemiology training programmes (FETPs) as countries struggled with overwhelming demands. Experts are calling for more field epidemiologists with better training. Since 1951, FETPs have been building public health capacities across the globe, yet explorations of learning in these programmes are lacking. This qualitative study will (1) describe approaches to training field epidemiologists in FETP; (2) describe strategies for learning field epidemiology among FETP trainees and (3) explain the principles and practices aligning training approaches with learning strategies in FETP. METHODS AND ANALYSIS: The research design, implementation and interpretation are collaborative efforts with FETP trainers. Data collection will include interviews with FETP trainers and trainees and participant observations of FETP training and learning events in four FETP in the Western Pacific Region. Data analysis will occur in three phases: (1) we will use the constant comparison method of Charmaz's grounded theory during open coding to identify and prioritise categories and properties in the data; (2) during focused coding, we will use constant comparison and Polkinghorne's analysis of narratives, comparing stories of prioritised categories, to fill out properties of those categories and (3) we will use Polkinghorne's narrative analysis to construct narratives that reflect domains of interest, identifying correspondence among Carr and Kemmis's practices, understandings and situations to explain principles and processes of learning in FETP. ETHICS AND DISSEMINATION: We have obtained the required ethics approvals to conduct this research at The Australian National University (2021/771) and Taiwan's Ministry of Health and Welfare (112206). Data will not be available publicly, but anonymised findings will be shared with FETP for collaborative interpretation. Ultimately, findings and interpretations will appear in peer-reviewed journals and conferences.
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Epidemiologistas , Vigilância da População , Humanos , Austrália , Saúde Pública/educação , Pesquisa QualitativaRESUMO
During the early 1980s both cancer biology and epidemiological methods were being transformed. In 1984 the leading cancer epidemiologist Richard Peto - who, in 1981, had published the landmark Causes of Cancer with Richard Doll - wrote a short chapter on "The need for ignorance in cancer research", in which the worlds of epidemiology and speculative Darwinian biology met. His reflections on how evolutionary theory related to cancer have become known as "Peto's paradox", whilst his articulation of "black box epidemiology" provided the logic of subsequent practice in the field. We reprint this sparkling and prescient example of biologically-informed epidemiological theorising at its best in this issue of the European Journal of Epidemiology, together with four commentaries that focus on different aspects of its rich content. Here were provide some contextual background to the 1984 chapter, and our own speculations regarding various paradoxes in cancer epidemiology. We suggest that one reason for the relative lack of progress in indentifying novel modifiable causes of cancer over the last 40 years may reflect such exposures being ubiquitous within environments, and discuss the lessons for epidemiology that would follow from this.
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Neoplasias , Humanos , Incerteza , Neoplasias/epidemiologia , Neoplasias/etiologia , Neoplasias/prevenção & controle , Evolução Biológica , Epidemiologistas , Tamanho CorporalRESUMO
Problem: As of 2022, only 49 graduates of the Philippines' Field Epidemiology Training Programme (FETP) were employed by the Philippine Government, emphasizing the urgent need to increase the number of practicing field epidemiologists to better equip the country for public health emergencies. Context: The FETP-Intermediate Course (IC) curriculum is based mainly on the module of the United States Centers for Disease Control and Prevention that was incorporated into the Philippine context. It consists of five 1-2-week lecture series that provide participants with the knowledge and tools necessary to conduct job-relevant field projects. Individual projects are the centrepiece of the FETP-IC, requiring trainees to investigate outbreaks, design and develop protocols, conduct field data collection, manage data, analyse data, interpret data, write reports and deliver oral presentations. Action: To address the shortage of practicing field epidemiologists in the Philippines, a subnational initiative in Northern Luzon was implemented. Outcome: Within 3 years, the two FETP-IC subnational training programmes have produced 42 applied epidemiologists who will strengthen epidemiology and surveillance in their respective localities. As of February 2023, 92 studies have been conducted, including 39 outbreak investigations, 37 data quality analysis/process improvement projects, 10 epidemiological studies and six surveillance evaluations. Discussion: By training and deploying skilled epidemiologists to local health offices and hospitals, the programme is helping to improve the capacity of the health system to respond to public health threats and protect the health of the population. The programme's emphasis on practical training and real-world experience is an effective way to build a strong and sustainable epidemiological workforce.
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Epidemiologistas , Epidemiologia , Humanos , Surtos de Doenças/prevenção & controle , Epidemiologia/educação , Filipinas , Vigilância da População/métodos , Saúde Pública , Mão de Obra em SaúdeRESUMO
The Covid-19 pandemic has laid bare a tension around scientific expertise that has major implications for the effectiveness of health systems. Critical engagement with this tension, however, is largely missing from the lessons and programs consolidating in the wake of the emergency. Lacking good frameworks for discussing the tension, the vague term "public trust" has proliferated into a buzzword that stands in for more articulate discussion. The tension between experts and the public is not new, however. It is useful to look back to the 1930s, when health experts identifying as "new epidemiologists" imagined a new modern science of epidemiology that, some believed, would resolve evident failures in public cooperation. Historical analysis of different approaches to the production and use of epidemiological knowledge in these years reveals a debate about power at the heart of epidemiology, and a critical framework for discussing the tension around epidemiological expertise in public health.
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COVID-19 , Pandemias , Humanos , Saúde Pública , Epidemiologistas , ConfiançaRESUMO
The designs of in vivo, in vitro and in silico studies do not adequately reflect the characteristics of long-term occupational EMF exposure; the higher exposure levels permitted for employees are nevertheless extrapolated on this basis. Epidemiological studies consider occupational exposure only in a very general way, if at all. There is a lack of detailed descriptive data on long-term occupational exposure over the duration of the working life. Most studies reflect exposure characteristics of the general population, exposures which are long-term, but at a comparably low level. Occupational exposure is often intermittent with high peak power followed by periods with no exposure. Furthermore, the EU EMF-Directive 2013/35/EU states a demand for occupational health surveillance, the outcome of which would be of great help to epidemiologists studying the health effects of EMF exposure. This paper thus aims to outline and specify differences between public and occupational exposure and to increase the understanding of specific aspects of occupational exposure which are important for long-term health considerations. This could lead to a future protection concept against possible hazards based on adequate descriptions of long-term exposures and also include supplementary descriptive features such as a "reset time" of biological systems and accurate dose quantities.
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Exposição Ocupacional , Saúde Ocupacional , Humanos , Campos Eletromagnéticos/efeitos adversos , EpidemiologistasRESUMO
Problem: Fellows of the Papua New Guinea Field Epidemiology Training Programme (FETP) were part of the national coronavirus disease (COVID-19) response. However, the specific activities and challenges experienced by fellows in the field were unknown. Context: The advanced FETP cohort commenced just before the COVID-19 pandemic and all fellows were involved in the response. The advanced fellows participating in this review represented a cross-section of the country's public health workforce. Action: A review was conducted to better understand the scope of activities undertaken by FETP fellows, identify the challenges experienced and assess how well the programme prepared fellows for their COVID-19 response roles. A facilitated discussion based on the World Health Organization COVID-19 intra-action review methodology and an online survey was conducted with advanced FETP fellows. Outcome: The fellows made important contributions to the national COVID-19 response by assuming leadership positions at all levels of government, leading training activities and applying core field epidemiology competencies in surveillance and response activities. The programme had prepared them well for the response, giving them the confidence and skills to undertake a diverse range of response roles. Discussion: The FETP review of the COVID-19 response in Papua New Guinea highlighted the role and influence of the fellows during the pandemic response. Fellows were able to apply core field epidemiology competencies across a range of roles. The recommendations derived from this review will be instructive for the FETP specifically and the COVID-19 response generally.
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COVID-19 , Epidemiologistas , Epidemiologia , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , Epidemiologia/educação , Pandemias , Papua Nova Guiné/epidemiologia , Vigilância da População/métodosRESUMO
Conferencia Magistral: Desafíos en la Epidemiología en el Manejo de COVID-19, presentada por el Dr. Daniel Rivera Reyes, Ministro de Salud Públlica de la República Dominicana.
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Epidemiologia , Epidemiologistas , República Dominicana , Vacinas contra COVID-19 , Monitoramento EpidemiológicoRESUMO
Deep learning methods are increasingly being applied to problems in medicine and health care. However, few epidemiologists have received formal training in these methods. To bridge this gap, this article introduces the fundamentals of deep learning from an epidemiologic perspective. Specifically, this article reviews core concepts in machine learning (e.g., overfitting, regularization, and hyperparameters); explains several fundamental deep learning architectures (convolutional neural networks, recurrent neural networks); and summarizes training, evaluation, and deployment of models. Conceptual understanding of supervised learning algorithms is the focus of the article; instructions on the training of deep learning models and applications of deep learning to causal learning are out of this article's scope. We aim to provide an accessible first step towards enabling the reader to read and assess research on the medical applications of deep learning and to familiarize readers with deep learning terminology and concepts to facilitate communication with computer scientists and machine learning engineers.
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Aprendizado Profundo , Humanos , Epidemiologistas , Redes Neurais de Computação , Algoritmos , Aprendizado de MáquinaRESUMO
To reflect on the present and the future of the "millennial" epidemiologists in Italy, the starting question is who are we? The online survey "I giovani ricercatori non più giovani: chi siamo? #GIOVANIDENTRO" was launched in 2022 and advertised at conferences of the Italian association of epidemiology to gather voices from all over Italy. Information on training, job position, attitudes and difficulties encountered in our profession and in scientific production activity has been collected and contextualized to answer the starting question and provide food for thought for the perspectives of our profession.
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Epidemiologistas , Humanos , Inquéritos e Questionários , Itália/epidemiologiaRESUMO
The "millennial" epidemiologists, born between the beginning of the 80s and the end of the 90s, are the generation that most of all, today, lives between the present and the future of this discipline. This issue of Recenti Progressi in Medicina aims to talk about what young (and no longer young) epidemiologists and public health researchers are dealing with and to reflect on the most relevant topics in our field, with an eye to the future. Starting from the profile of the "millennial" epidemiologists in Italy and the topics on which they work, the issue develops through three parts dealing with relevant topics for the present and the future of Public health. The first part deals with the important issue of finding a balance between the protection of personal data and the protection of health through a dialogue between researchers, jurists and citizens. The second part aims to clarify the issue of big data and its implications for producing health. The third part touches on four relevant topics for the perspectives of epidemiology through reflections and application examples of machine learning, integration between pharmacoepidemiology and environmental epidemiology, health prevention and promotion involving citizens and other stakeholders, and epidemiology of mental health. In a constantly changing world, challenges for those who work to produce health are not lacking, as is the determination to face them. With this issue, we hope to contribute to the awareness of who we are and our potential, to help millennials (but not only) find their place in epidemiology, today and tomorrow.
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Epidemiologia , Saúde Pública , Humanos , Itália , Epidemiologistas , FarmacoepidemiologiaRESUMO
BACKGROUND: As the interest in and use of quasi-experimental methods to evaluate impacts of health policies have dramatically increased in the epidemiological literature, we set out this study to (i) systematically compare several quasi-experimental methods that use data before and after an intervention and contrast their performance within a simulation framework while providing a brief overview of the methods; and (ii) discuss challenges that could arise from using these methods as well as directions for future research in the context of epidemiological applications. METHODS: We considered single-group designs [pre-post and interrupted time series (ITS)] and multiple-group designs [controlled interrupted time series/difference-in-differences, synthetic control methods (SCMs): traditional SCMs and generalized SCMs]. We assessed performance based on bias and root mean squared error. RESULTS: We identified settings in which each method failed to provide unbiased estimates. We found that, among the methods investigated, when data for multiple time points and for multiple control groups are available (multiple-group designs), data-adaptive methods such as the generalized SCM were generally less biased than other methods evaluated in our study. In addition, when all of the included units have been exposed to treatment (single-group designs) and data for a sufficiently long pre-intervention period are available, then the ITS performs very well, provided the underlying model is correctly specified. CONCLUSIONS: When using a quasi-experimental method using data before and after an intervention, epidemiologists should strive to use, whenever feasible, data-adaptive methods that nest alternative identifying assumptions including relaxing the parallel trend assumption (e.g. generalized SCMs).