Electronic Partner Notification for Sexually Transmitted Infections: A Qualitative Assessment of Patient, Clinical Staff, and State Field Epidemiologist Perspectives.

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.

M-estimation for common epidemiological measures: introduction and applied examples.

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.

How do field epidemiologists learn? A protocol for a qualitative inquiry into learning in field epidemiology training programmes.

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.

Chance, ignorance, and the paradoxes of cancer: Richard Peto on developing preventative strategies under uncertainty.

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.

Losing the Public, for Better or for Worse: A Lesson from John Everett Gordon (1890-1983) and John Rodman Paul (1893-1971).

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.

Creating "boots on the ground": addressing the shortage of field epidemiologists in the Philippines through intermediate-level training programmes.

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.

Occupational Exposure to Electromagnetic Fields-Different from General Public Exposure and Laboratory Studies.

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.

Involvement and readiness of fellows from Papua New Guinea's Field Epidemiology Training Programme in the COVID-19 response, 2020-2021.

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.

Incidencia de la epidemiología en República Dominicana y ante la pandemia COVID-19

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.

Deep Learning for Epidemiologists: An Introduction to Neural Networks.

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.

[Young researchers no more young: who are we?] / I giovani ricercatori non più giovani: chi siamo?

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.

[Millennials looking for their place in epidemiology.] / I millennials alla ricerca del proprio posto nell'epidemiologia.

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.

A comparison of quasi-experimental methods with data before and after an intervention: an introduction for epidemiologists and a simulation study.

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).

Views on increased federal access to state and local National Syndromic Surveillance Program data: a nominal group technique study with state and local epidemiologists.

BACKGROUND: US public health authorities use syndromic surveillance to monitor and detect public health threats, conditions, and trends in near real-time. Nearly all US jurisdictions that conduct syndromic surveillance send their data to the National Syndromic Surveillance Program (NSSP), operated by the US. Centers for Disease Control and Prevention. However, current data sharing agreements limit federal access to state and local NSSP data to only multi-state regional aggregations. This limitation was a significant challenge for the national response to COVID-19. This study seeks to understand state and local epidemiologists' views on increased federal access to state NSSP data and identify policy opportunities for public health data modernization. METHODS: In September 2021, we used a virtual, modified nominal group technique with twenty regionally diverse epidemiologists in leadership positions and three individuals representing national public health organizations. Participants individually generated ideas on benefits, concerns, and policy opportunities relating to increased federal access to state and local NSSP data. In small groups, participants clarified and grouped the ideas into broader themes with the assistance of the research team. An web-based survey was used to evaluate and rank the themes using five-point Likert importance questions, top-3 ranking questions, and open-ended response questions. RESULTS: Participants identified five benefit themes for increased federal access to jurisdictional NSSP data, with the most important being improved cross-jurisdiction collaboration (mean Likert = 4.53) and surveillance practice (4.07). Participants identified nine concern themes, with the most important concerns being federal actors using jurisdictional data without notice (4.60) and misinterpretation of data (4.53). Participants identified eleven policy opportunities, with the most important being involving state and local partners in analysis (4.93) and developing communication protocols (4.53). CONCLUSION: These findings identify barriers and opportunities to federal-state-local collaboration critical to current data modernization efforts. Syndromic surveillance considerations warrant data-sharing caution. However, identified policy opportunities share congruence with existing legal agreements, suggesting that syndromic partners are closer to agreement than they might realize. Moreover, several policy opportunities (i.e., including state and local partners in data analysis and developing communication protocols) received consensus support and provide a promising path forward.