An argument for renewed focus on epidemiology for public health

Reframing the environment in data-intensive health sciences

In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual shifts. First, we discuss the EXPOsOMICS project, an attempt to integrate genomic and environmental data which suggests a reframing of the boundaries between external and internal environments. Second, we explore the MEDMI platform, whose efforts to combine health, environmental and climate data instantiate a reframing and expansion of environmental exposure. Third, we illustrate how extracting epidemiological insights from extensive social data collected by the CIDACS institute yields innovative attributions of causal power to environmental factors. Identifying these shifts highlights the benefits and opportunities of new environmental data, as well as the challenges that such tools bring to understanding and fostering health. It also emphasises the constraints that data selection and accessibility pose to scientific imagination, including how researchers frame key concepts in health-related research.

Incremental Propensity Score Effects for Time-fixed Exposures

When causal inference is of primary interest, a range of target parameters can be chosen to define the causal effect, such as average treatment effects (ATEs). However, ATEs may not always align with the research question at hand. Furthermore, the assumptions needed to interpret estimates as ATEs, such as exchangeability, consistency, and positivity, are often not met. Here, we present the incremental propensity score (PS) approach to quantify the effect of shifting each person's exposure propensity by some predetermined amount. Compared with the ATE, incremental PS may better reflect the impact of certain policy interventions and do not require that positivity hold. Using the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (nuMoM2b), we quantified the relationship between total vegetable intake and the risk of preeclampsia and compared it to average treatment effect estimates. The ATE estimates suggested a reduction of between two and three preeclampsia cases per 100 pregnancies for consuming at least half a cup of vegetables per 1,000 kcal. However, positivity violations obfuscate the interpretation of these results. In contrast, shifting each woman's exposure propensity by odds ratios ranging from 0.20 to 5.0 yielded no difference in the risk of preeclampsia. Our analyses show the utility of the incremental PS effects in addressing public health questions with fewer assumptions.

A SWOT analysis of Italian medical curricular adaptations to the COVID-19 pandemic: A nationwide survey of medical school leaders

BACKGROUND

There is a growing literature on how medical education adapts to the COVID-19 pandemic. However, there is a need to examine the facilitators and barriers of these adaptations. This study explores the strengths, weaknesses, opportunities, and threats (SWOT) of how Italian medical schools adapted their curricula to the COVID -19 pandemic.

METHODS

The authors conducted an online survey of directors of medical curricula in Italy. Free-text responses to open-ended questions about curricular adaptations and reflections on these adaptations were analysed using qualitative thematic analysis.

RESULTS

Twenty out of 60 Italian medical school directors completed the survey. Strengths identified were rapid responses and a spirit of cooperation. Weaknesses included dependency on clinical facilities, teachers' limited skills to use technology, and lack of mental health support for staff. Opportunities highlighted were clear government rules, new ways of teaching and a renewed focus on underrepresented topics. Threats expressed included impaired relationships, difficulties related to online assessment, lack of IT access, and legal and insurance issues.

CONCLUSIONS

This study, in documenting the curricular adaptations of Italian medical schools during an active global pandemic, and recording the perspectives of medical education leaders, offers important lessons for the future.

A review of the applied epidemiology workforce in the United States: past, present, and future

Applied epidemiologists are key professionals within the public health workforce, fulfilling core public health science functions. The public health system in the United States has been rapidly transforming over the last decade and epidemiologists will need to develop new skill sets to be successful in the future of public health. A review of the literature was undertaken to gain a comprehensive understanding of the past and present of the applied epidemiology workforce to inform future workforce initiatives aimed at improving applied epidemiology practice. The literature search identified 48 articles related to applied epidemiologists working in the United States at the federal, state, and local levels. These articles described efforts to build, enumerate, and assess the competency of the applied epidemiology workforce in addition to putting forward opinions about it. Overall, the articles demonstrated significant prior work enumerating the applied epidemiology workforce, some prior work identifying epidemiology training needs, and few prior studies assessing competency. The functions, skill sets, and training needs of epidemiologists have changed over time and the literature provides a number of recommendations for future training. Continued assessment of the workforce literature is recommended to monitor training needs and competency for use in implementing effective workforce development activities.

Invited Commentary: Epidemiologic Methods as Applied to Epidemiology Education-Goals and Expectations to Advance and Diversify the Field

In their accompanying article, Brown and Cox (Am J Epidemiol. 2021;190(2):305-312) offer strategies for improving introductory epidemiology instruction in large undergraduate classes using a team-based instructional approach. Effective epidemiology instruction can increase the quality and effectiveness of teaching and learning in our discipline. Recent work has suggested that epidemiology education can also be targeted as a mechanism to fuel equity and progress in the field. In this commentary, I contextualize Brown and Cox's article within the literature on epidemiology instruction for undergraduates. I also explore the status of methods for measuring teaching and learning effectiveness in our field. I revisit what makes epidemiology a unique science and connect this with instructional strategies that have the potential to capitalize on these features. Lastly, I consider whether our field can improve in developing methods of measuring the effectiveness of epidemiology instruction for achieving these aims. Ultimately, as I suggest, increasing the rigor of methods for evaluating epidemiology instruction will serve to diversify, enhance, and advance our discipline.

Application of epidemiological findings to individuals

Three types of issues need to be considered in the application of epidemiology results to individuals. First, epidemiology results are subject to random error, and can be applied only to an ideal subject with average values of all variables under study, including potential confounders included in the regression models. Second, the observational nature of epidemiology makes it susceptible to systematic error, and any extrapolation to individuals would mirror the validity of the original results. Quantitative bias analysis has been proposed to assess the likelihood, direction and magnitude of bias, but this has not yet become part of the normal practice of epidemiology. Finally, external validity of the results (i.e., their application to individuals and populations other than those included in the underlying studies) needs to be addressed, including population-based factors, such as heterogeneity in exposure or disease circumstances, and individual-based factors, such as interaction of the risk factors of interest with other determinants of the disease. Similar considerations apply to the application of results of clinical trials to individual patients, although in these studies sources of systematic error are better controlled.

Worldwide epidemiology of carbon monoxide poisoning

This article presents updated information on the worldwide burden of carbon monoxide (CO) poisoning. The worldwide epidemiologic data were obtained from the Global Health Data Exchange registry, a large database of health-related data maintained by the Institute for Health Metrics and Evaluation. The worldwide cumulative incidence and mortality of CO poisoning are currently estimated at 137 cases and 4.6 deaths per million, respectively. The worldwide incidence has remained stable during the last 25 years, while both mortality and percentage of patients who died have declined by 36% and 40%, respectively. The incidence of CO poisoning does not differ between sexes, whilst mortality is double in men. The incidence shows two apparent peaks, between 0-14 years and 20-39 years. The percentage of patients who died constantly increases in parallel with aging, peaking in patients aged 80 years or older. The number of CO poisoning grows in parallel with the socio-demographic index (SDI), though more detailed analyses would be needed to confirm our findings. Mortality displays a similar trend, being approximately 2.1- and 3.6-fold higher in middle and middle-to-high than in low-to-middle SDI countries. In conclusion, while these data suggest that the worldwide burden of CO poisoning remains stable, and the number of fatal outcomes and percentage of patients who die have both consistently declined during the last 25 years, the unreliability of the primary data sources in many countries with respect to accurate diagnosis of CO poisoning means that caution is required, and that field studies, particularly in poorer countries, are required.

Worldwide asthma epidemiology: insights from the Global Health Data Exchange database

BACKGROUND

Enhanced focus on primary care provision is essential for lowering the risk of asthma exacerbation and complications, as well as for decreasing asthma-related hospitalizations and deaths. This article provides an update on current worldwide epidemiology of asthma.

METHODS

Worldwide epidemiologic information on asthma was obtained through electronic searches in the Global Health Data Exchange (GHDx) database.

RESULTS

In 2017, the incidence of asthma was 43.12 million new cases/year (0.56%), while in that same year, prevalence and mortality accounted for 272.68 million cases (3.57%) and 0.49 million deaths (0.006%), respectively. Although the number of asthma cases significantly increased during the last 25 years, disability-adjusted life years (DALYs) and deaths constantly declined. After adjustment of asthma incidence, prevalence, and DALYs for worldwide demographic variation, no significant changes could be seen during the last 25 years, while asthma mortality significantly declined during the same period. Asthma incidence peaks before the age of 5 years, whereas prevalence and DALYs peaks are observed between 0 and 14 years. DALYs also display a second peak, between 45 and 74 years. Asthma mortality increases with aging, reaching the peak after 80 years. The epidemiologic burden and mortality of asthma are constantly higher in women than in men. An inverse, highly significant correlation can be found between sociodemographic index and asthma incidence (r = -0.98) or mortality (r = -0.96).

CONCLUSION

Although the worldwide burden of asthma remains high, incidence and prevalence are not apparently translating into an escalating clinical and economic burden in terms of health loss and deaths.

Teaching on the Continuum: Epidemiology Education From High School Through Graduate School

Epidemiology education is increasingly recognized as a core science necessary for career preparation throughout the health sector, and graduate epidemiology instruction is continually being reevaluated to ensure students receive appropriate training. Recent work has also focused on the potential for epidemiology to be formally incorporated as a stand-alone discipline in undergraduate education and even integrated into wide-scale high-school science learning. As epidemiology educators, however, we face a tremendous challenge in that we should appreciate differences in students' instructional needs and goals (e.g., concepts and skills) at each educational level. In this article we propose an epidemiology learning continuum for students from high school through graduate school. We call for a student-centered instructional approach to best hone learners' grasp of concepts and skills. Furthermore, we propose scaffolded learning to help epidemiology students to develop more advanced insights and abilities as they progress in the field. This approach will not only best serve the discipline but also is well-aligned with the Association of Schools and Programs of Public Health's "Framing the Future" initiative for public health education for the 21st century.

Target Validity and the Hierarchy of Study Designs

In recent years, increasing attention has been paid to problems of external validity, specifically to methodological approaches for both quantitative generalizability and transportability of study results. However, most approaches to these issues have considered external validity separately from internal validity. Here we argue that considering either internal or external validity in isolation may be problematic. Further, we argue that a joint measure of the validity of an effect estimate with respect to a specific population of interest may be more useful: We call this proposed measure target validity. In this work, we introduce and formally define target bias as the total difference between the true causal effect in the target population and the estimated causal effect in the study sample, and target validity as target bias = 0. We illustrate this measure with a series of examples and show how this measure may help us to think more clearly about comparisons between experimental and nonexperimental research results. Specifically, we show that even perfect internal validity does not ensure that a causal effect will be unbiased in a specific target population.

The relevance of public health research for practice: A 30-year perspective

The Nordic context where public health responsibility is strongly devolved to municipalities raises specific demands on public health research. The demands for causal inference of disease aetiology and intervention efficacy is not different, but in addition there is a need for population health science that describes local prevalence, distribution and clustering of determinants. Knowledge of what interventions and policies work, for whom and under what conditions is essential, but instead of assuming context independence and demanding high external validity it is important to understand how contextual factors linked to groups and places modify both effects and implementation. More implementation studies are needed, but the infrastructure for that research in terms of theories and instruments for monitoring implementation is needed. Much of this was true also 30 years ago, but with increasing spending on both public health research and practice, the demands are increasing that major improvement of population health and health equity are actually achieved.