Will Podcasting and Social Media Replace Journals and Traditional Science Communication? No, but...

The digital world in which we live is changing rapidly. The evolving media environment is having a direct impact on traditional forms of communication and knowledge translation in public health and epidemiology. Openly accessible digital media can be used to reach a broader and more diverse audience of trainees, scientists, and the lay public than can traditional forms of scientific communication. The new digital landscape for delivering content is vast, and new platforms are continuously being added. In this article, we focus on several, including Twitter and podcasting, and discuss their relevance to epidemiology and science communication. We highlight 3 key reasons why we think epidemiologists should be engaging with these mediums: 1) science communication, 2) career advancement, and 3) development of a community and public service. Other positive and negative consequences of engaging in these forms of new media are also discussed. The authors of this commentary are all engaged in social media and podcasting for scientific communication, and we reflect on our experiences with these mediums as tools to advance the field of epidemiology.

Epidemiologists Count: The Role of Diversity and Inclusion in the Field of Epidemiology.

We present interpretations of the idea that "epidemiologists count" in response to the current status of membership and diversity and inclusion efforts within the Society for Epidemiological Research (SER). We review whom epidemiologists count to describe the (mis)representation of SER membership and how categorizations of people reflect social constructions of identity and biases that exist in broader society. We argue that what epidemiologists count-how diversity and inclusion are operationalized-has real-world implications on institutional norms and how inclusive/non-inclusive environments are. Finally, we examine which epidemiologists count within the field and argue that inclusion can only be achieved when we address how resources and opportunities are distributed among epidemiologists. To improve diversity and inclusion within SER and beyond, we recommend that SER strengthen its commitment to diversity, inclusion, and equity by: 1) integrating this priority on all agendas; 2) enhancing efforts to improve self-awareness among members and accountability within the organization; 3) supporting the growth of a diversifying workforce in epidemiology; and 4) increasing the visibility of health disparities research and researchers in epidemiology.

Food for Thought: Opportunities to Improve Diversity, Inclusion, Representation, and Participation in Epidemiology.

DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998-1010) have taken on the noble and worthy cause of improving diversity, inclusion, representation, and participation across the Society for Epidemiologic Research (SER) membership-a reflection/microcosm of society. The objective of this commentary is to underscore the importance of diversity and to offer initiative ideas, which should be centered around inequity stemming from the widespread historical and contemporary maldistribution of power (e.g., decision-making) and resources (e.g., funding) within institutions and organizations. Nonexhaustive strategies could include SER becoming an opportunity and information hub that helps to fill resource gaps. It is also recommended that SER leadership learn from existing associations and scientific initiatives to improve the culture of science in general by equitably incorporating policy, systems, and environmental interventions throughout the career spectrum. Examples include the provision of tools and incentives to address explicit or implicit biases, enhance mentoring skills, and remove predictable barriers (e.g., financial). Explicitly labeling diversity/inclusion efforts should be avoided, and the initiative should be evaluated based on impact rather than intent. Our fates are interconnected, and we can all help increase diversity, inclusion, representation, and participation to improve our science in hopes of equitably improving public health.

The Society for Epidemiologic Research and the Future of Diversity and Inclusion in Epidemiology.

"The mission of the Diversity and Inclusion Committee (D&I) in the Society for Epidemiologic Research is to foster the diversity of our membership and work towards the engagement of all members, from diverse backgrounds at all stages of their careers, in the Society's activities, with the intent of enhancing discovery in public health." As a foundational step in implementing our mission, the D&I Committee conducted a survey of SER membership. Here we report on the efforts we have undertaken to expand the diversity and inclusiveness of our Society and our aspirations for future efforts in support of D&I. Early on, we established the SERvisits program to conduct outreach to institutions and students that have historically been underrepresented at SER; we hope this program continues to grow in its reach and impact. We have also taken steps to increase the inclusiveness of SER activities, for example, by engaging members on issues of D&I through symposia and workshops at SER annual meetings and through social media. DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998-1010) have demonstrated that there is substantial room for improvement with regards to diversity and inclusion within SER. We invite SER members to become involved and collaborate on this long-term goal.

Diversity and Inclusion in the Epidemiology Workforce.

Increasing participation by promoting diversity and inclusion in professional society membership has become an important topic for many scientific fields. In a recent issue of the Journal, DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998-1010) reported results from a survey conducted by the Society for Epidemiologic Research (SER) Diversity and Inclusion Committee by which several aspects of participation by sociodemographic and cultural variables among its members were measured. Here, we summarize the major findings of the survey, put the authors' results within the greater context of the epidemiology workforce, and provide suggestions on how the Committee could expand its influence by considering measuring variables related to career outcomes and trajectories. This suggestion is based on an attempt to link the interventions being facilitated by SER, the participation indices it is trying to improve, and the greater mission of SER to build sustainable career trajectories that produce the best science that will improve the health of human populations.

Beyond Diversity: Focusing on and Enhancing Inclusion in the Society for Epidemiologic Research.

Increasing diversity and inclusion among organizational membership has become a focus for many professional societies, including the Society for Epidemiologic Research (SER). In this issue of the Journal, DeVilbiss et al. (Am J Epidemiol. 2020:189(10):998-1010) assessed dimensions of diversity and inclusion within SER to provide baseline data for future evaluations of Society initiatives. In our response, we note that diversity in SER appears strong but there is lag with regard to inclusion. We also highlight some of the major weaknesses of this study that hinder efforts to accurately evaluate inclusion within SER. There is a need to more concretely define inclusion and think broadly about how measures of inclusion should be operationalized in future surveys. Additional limitations of the study include its limited generalizability to the wider SER membership and the lack of questions about barriers to inclusion in SER activities. We conclude with recommendations for SER and other professional societies based on prior literature evaluating successful diversity and inclusion efforts. We also propose a conceptual model to assist with operationalizing and directing future analyses of inclusion measures. It is essential that SER move beyond efforts around diversity to focus on measuring and enhancing inclusion.

Improving Diversity and Promoting Inclusion in the Society for Epidemiologic Research Through Choice of Conference Location.

Scientific conferences provide attendees opportunities to network, share research, learn new skills and ideas, and initiate collaborations. Conference attendance is especially important for students and early-career researchers who are establishing their research careers or looking for jobs. However, attending conferences can be expensive, and the high cost of conference attendance might hit students and early-career researchers the hardest. According to a new member survey from the Society for Epidemiologic Research, early-career members are more racially and ethnically diverse than senior members, meaning that reducing financial barriers to conference participation might be an important consideration for increasing diversity among conference attendees. In this commentary, we discuss how choice of conference location-choosing less expensive cities nearer to more Society for Epidemiologic Research members-could reduce financial and other barriers to conference attendance for all members and improve diversity and inclusion in the Society.

You're From Where, Again? A Critical Assessment of Institutional Diversity in the Society for Epidemiologic Research.

The Society for Epidemiologic Research (SER) has recently taken laudable steps toward increasing diversity, equity, and inclusion within the society, including participation in the annual meeting. In this essay, we argue that there is one critical piece of the diversity and inclusion equation that is, however, overlooked: institution. At the 2019 Annual Meeting, a mere 8 institutions accounted for a disproportionate number of both oral concurrent sessions and symposium speakers. This lack of institutional diversity, unless addressed, will hinder SER's ability to address other aspects of diversity, equity, and inclusion.

Recommendations to the Society for Epidemiologic Research for Further Promoting Diversity and Inclusion at the Annual Meeting and Beyond.

Increasing diverse engagement in the Society for Epidemiologic Research (SER) will positively impact the field of epidemiology. As the largest and longest-running epidemiologic society in North America, SER has long been a pioneer in promoting diversity and inclusion. A recent survey of SER members, however, showed there is still room for improving diversity, inclusion, representation, and participation in the Society. In this commentary, as members of both the SER and the Johns Hopkins Bloomberg School of Public Health Department of Epidemiology's Inclusion, Diversity, Equity, Anti-Racism, and Science (Epi IDEAS) Working Group, we recommend 4 goals for the SER Annual Meeting and beyond: 1) convene epidemiologic researchers with diverse backgrounds and ideas; 2) promote an inclusive environment at the SER Annual Meeting; 3) develop, compile, and disseminate best practices to honor diversity in epidemiologic research; and 4) increase prioritization of health disparities research and methods. We also suggest strategies for achieving these goals so that SER can better include, support, and elevate members from historically disadvantaged groups. While our recommendations are tailored specifically to SER, the greater epidemiologic and academic communities could benefit from adopting these goals and strategies within their professional societies and conferences.

Diversity and Political Leaning: Considerations for Epidemiology.

The positive effects of increased diversity and inclusion in scientific research and practice are well documented. In this issue, DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998-1010) present findings from a survey used to collect information to characterize diversity among epidemiologists and perceptions of inclusion in the epidemiologic profession. They capture identity across a range of personal characteristics, including race, gender, socioeconomic background, sexual orientation, religion, and political leaning. In this commentary, we assert that the inclusion of political leaning as an axis of identity alongside the others undermines the larger project of promoting diversity and inclusion in the profession and is symptomatic of the movement for "ideological diversity" in higher education. We identify why political leaning is not an appropriate metric of diversity and detail why prioritizing ideological diversity counterintuitively can work against equity building initiatives. As an alternative to ideological diversity, we propose that epidemiologists take up an existing framework for research and practice that centers the voices and perspectives of historically marginalized populations in epidemiologic work.

Sick Individuals and Sick (Microbial) Populations: Challenges in Epidemiology and the Microbiome.

The human microbiome represents a new frontier in understanding the biology of human health. While epidemiology in this area is still in its infancy, its scope will likely expand dramatically over the coming years. To rise to the challenge, we argue that epidemiology should capitalize on its population perspective as a critical complement to molecular microbiome research, allowing for the illumination of contextual mechanisms that may vary more across populations rather than among individuals. We first briefly review current research on social context and the gut microbiome, focusing specifically on socioeconomic status (SES) and race/ethnicity. Next, we reflect on the current state of microbiome epidemiology through the lens of one specific area, the association of the gut microbiome and metabolic disorders. We identify key methodological shortcomings of current epidemiological research in this area, including extensive selection bias, the use of noncompositionally robust measures, and a lack of attention to social factors as confounders or effect modifiers.

[Covid-19 and clinical-epidemiological research in Italy: proposal of a research agenda on priority topics by the Italian association of epidemiology]. / Covid-19 e ricerca clinico-epidemiologica in Italia: proposta di un'agenda di ricerca su temi prioritari da parte dell'Associazione italiana di epidemiologia.

BACKGROUND: the Covid-19 pandemic has provoked a huge of clinical and epidemiological research initiatives, especially in the most involved countries. However, this very large effort was characterized by several methodological weaknesses, both in the field of discovering effective treatments (with too many small and uncontrolled trials) and in the field of identifying preventable risks and prognostic factors (with too few large, representative and well-designed cohorts or case-control studies). OBJECTIVES: in response to the fragmented and uncoordinated research production on Covid-19, the   italian Association of Epidemiology (AIE) stimulated the formation of a working group (WG) with the aims of identifying the most important gaps in knowledge and to propose a structured research agenda of clinical and epidemiological studies considered at high priority on Covid-19, including recommendations on the preferable methodology. METHODS: the WG was composed by 25 subjects, mainly epidemiologists, statisticians, and other experts in specific fields, who have voluntarily agreed to the proposal. The agreement on a list of main research questions and on the structure of the specific documents to be produced were defined through few meetings and cycles of document exchanges. RESULTS: twelve main research questions on Covid-19 were identified, covering aetiology, prognosis, interventions, follow-up and impact on general and specific populations (children, pregnant women). For each of them, a two-page form was developed, structured in: background, main topics, methods (with recommendations on preferred study design and warnings for bias prevention) and an essential bibliography. CONCLUSIONS: this research agenda represents an initial contribution to direct clinical and epidemiological research efforts on high priority topics with a focus on methodological aspects. Further development and refinements of this agenda by Public Health Authorities are encouraged.

Epidemiology at the Heart of Population Health Science.

Epidemiology has long been concerned with understanding the causes of health and disease states so that we can improve the health of populations. Despite broad agreement on this definition of the field, we continue to debate certain core goals of epidemiology: whether epidemiology is a pragmatic science or not, which methods constitute epidemiologic methods, and what our gold-standard thinking should be to understand causation. We suggest that recognizing epidemiology as the quantitative heart of population health science can push these tensions aside and allow us to focus our science on the health of populations and on the processes that shape that health. Seeing epidemiology as the core quantitative health science has implications for the questions we ask, how we organize ourselves as a field, and how we train the next generation of epidemiologists.

The Unique Space of Epidemiology: Drawing on the Past to Project Into the Future.

Epidemiology has always filled a unique space. It lies squarely at the intersection of the social and biological sciences as well as at the intersection of knowledge generation and the translation of that knowledge into actions. Today, new data sources, new methods, and continued population health problems create opportunities and challenges for epidemiology. In this commentary, 4 areas of opportunity for epidemiology are reviewed: 1) the continued value of precise description; 2) a rigorous yet broad and practical approach to drawing conclusions about causes; 3) embracing methodological diversity; and 4) retaining a strong connection to public health practice and policy.

The Future of Observational Epidemiology: Improving Data and Design to Align With Population Health.

Improvements in data resources and computational power provide important opportunities to ensure the continued relevance and growth of observational epidemiology. To achieve that promise, rigorous statistical analyses are important but not sufficient. We must prioritize articulating relevant research questions and developing strong study designs. Relevance depends on designing observational research so it delivers actionable clinical or population health evidence. Expanding data sources, including administrative records and data from emerging technologies such as sensors, can potentially be leveraged to improve study design, statistical power, measurement, and availability of evidence on diverse populations. With these advantages, particularly evidence on the heterogeneity of treatment effects, observational research can better guide design of randomized trials. Evidence on the heterogeneity of treatment effects is also essential to extend the evidence from randomized trials beyond the narrow range of settings and populations for which trials have been conducted. Machine learning tools will likely grow in importance in observational epidemiology in coming years, although we need careful attention to the appropriate uses of prediction models. Despite the potential of these innovations, they will only be useful if embedded in theoretical frameworks motivated by applied clinical and population health questions.

A Future for Observational Epidemiology: Clarity, Credibility, Transparency.

Observational studies are ambiguous, difficult, and necessary for epidemiology. Presently, there are concerns that the evidence produced by most observational studies in epidemiology is not credible and contributes to research waste. I argue that observational epidemiology could be improved by focusing greater attention on 1) defining questions that make clear whether the inferential goal is descriptive or causal; 2) greater utilization of quantitative bias analysis and alternative research designs that aim to decrease the strength of assumptions needed to estimate causal effects; and 3) promoting, experimenting with, and perhaps institutionalizing both reproducible research standards and replication studies to evaluate the fragility of study findings in epidemiology. Greater clarity, credibility, and transparency in observational epidemiology will help to provide reliable evidence that can serve as a basis for making decisions about clinical or population-health interventions.

On Being an Epidemiologist.

This commentary addresses being an epidemiologist at a time when the field of epidemiology again faces a paradigm shift as the tools for research on human health draw increasingly on emerging technologies-various omics and new methods for collecting individual data at high intensity-and on new methods for carrying out research through administrative and health care data bases linked to biobanks. At the same time, epidemiologists in public health practice continue to face the usual array of challenges, but with the threat of global issues as well. The profession of epidemiologist is not monolithic; it embraces a broad range of activities and professional venues, reflecting the many contexts where epidemiologists do their work, the nature of the problems addressed, and the span and application of their findings. Obtaining data from people and populations comes with serious ethical obligations related to privacy and confidentiality of individuals and respect for the populations studied. Beyond generating and analyzing data, epidemiologists engage in guiding action through the evidence they have created with the ultimate goal of advancing health. This commentary addresses "mega-trends" that will affect the profession in the decades to come.

Epidemiologists of the Future: Data Collectors or Scientists?

Epidemiology is the study of epidemics. It is a biological science that includes expertise in many disciplines in social and behavioral sciences. Epidemiology is also a key component of preventive medicine and public health. Unfortunately, over recent years, academic epidemiology has lost its relationship with preventive medicine, as well as much of its focus on epidemics. The new "-omics" technologies to measure risk factors and phenotypes, and advances in genomics (e.g., host susceptibility) consistent with good epidemiology methods will likely enhance epidemiology research. There is a need based on these new technologies to modify training, especially for the first-level doctorate epidemiologist.

The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies.

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).

Challenges and Opportunities for Using Big Health Care Data to Advance Medical Science and Public Health.

Methodological advancements in epidemiology, biostatistics, and data science have strengthened the research world's ability to use data captured from electronic health records (EHRs) to address pressing medical questions, but gaps remain. We describe methods investments that are needed to curate EHR data toward research quality and to integrate complementary data sources when EHR data alone are insufficient for research goals. We highlight new methods and directions for improving the integrity of medical evidence generated from pragmatic trials, observational studies, and predictive modeling. We also discuss needed methods contributions to further ease data sharing across multisite EHR data networks. Throughout, we identify opportunities for training and for bolstering collaboration among subject matter experts, methodologists, practicing clinicians, and health system leaders to help ensure that methods problems are identified and resulting advances are translated into mainstream research practice more quickly.