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BACKGROUND:Female biomedical scientists tend to publish fewer articles as last author than their male colleagues and accrue fewer citations per publication. We seek to understand whether epidemiology follows this pattern. METHODS:We gathered aggregate information on the current gender distribution of epidemiology departments (n = 29 of 71 surveyed), societies (n = 4 of 8), and journal editorial boards (n = 6 of 6) using two online surveys and publicly available online information. Bibliometric data from 4,149 articles published between 2008 and 2012 in six high-impact epidemiology journals were drawn from Web of Science and PubMed. RESULTS:We observed a higher prevalence of female than male doctoral students and epidemiology faculty, particularly at lower faculty ranks. A total of 54% of society members were female. Among editorial boards, all current and emeritus editors-in-chief were male and board membership was largely male (64%). Females were more likely to be first authors, but less likely to be last authors. There were no differences in accrued citations at the 50th percentile by first or last author gender. However, articles with male first and last authors tend to accrue more citations (5.7 citations, 95% CI2.1, 9.4), mostly driven by the most highly cited articles. This disparity is not fully explained by potential confounders, including seniority. CONCLUSIONS:We found a greater number of female epidemiologists in early-career positions and further evidence of potential gender disparity in publication metrics in epidemiology. If epidemiology continues to be practiced by a majority of women, it remains to be seen if these patterns will change over time.

We conducted interviews with state epidemiologists involved in the state-level COVID-19 response to understand the challenges and opportunities that state epidemiologists and state health departments faced during COVID-19 and consider the implications for future pandemic responses. As part of a broader study on policymaking during COVID-19, we analyzed 12 qualitative interviews with state-epidemiologists from 11 US states regarding the challenges and opportunities they experienced during the COVID-19 response. Interviewees described the unprecedented demands COVID-19 placed on them, including increased workloads as well as political and public scrutiny. Decades of under-funding and constraints posed particular challenges for meeting these demands and compromised state responses. Emergency funding contributed to ameliorating some challenges. However, state health departments were unable to absorb the funds quickly, which created added pressure for employees. The emergency funding also did not resolve longstanding resource deficits. State health departments were not equipped to meet the demands of a comprehensive COVID-19 response, and increased funding failed to address shortfalls. Effective future pandemic responses will require sustained investment and adequate support to manage on-going and surge capacity needs. Increased public interest and skepticism complicated the COVID-19 response, and additional measures are needed to address these factors.

Objectives: The Council of State and Territorial Epidemiologists (CSTE) has periodically assessed the epidemiological capacity of states since 2001, but the data do not reflect the total US epidemiology capacity. CSTE partnered with the Big Cities Health Coalition (BCHC) in 2017 to assess epidemiology capacity in large urban health departments. We described the epidemiology workforce capacity of large urban health departments in the United States and determined gaps in capacity among BCHC health departments. Methods: BCHC, in partnership with CSTE, modified the 2017 State Epidemiology Capacity Assessment for its 30 member departments. Topics in the assessment included epidemiology leadership, staffing, funding, capacity to perform 4 epidemiology-related Essential Public Health Services, salary ranges, hiring requirements, use of competencies, training needs, and job vacancies. Results: The 27 (90%) BCHC-member health departments that completed the assessment employed 1091 full-time equivalent epidemiologists. All or nearly all health departments provided epidemiology services for programs in infectious disease (n = 27), maternal and child health (n = 27), preparedness (n = 27), chronic diseases (n = 25), vital statistics (n = 25), and environmental health (n = 23). On average, funding for epidemiology activities came from local (47%), state (24%), and federal (27%) sources. Health departments reported needing a 40% increase from the current number of epidemiologists to achieve ideal epidemiology capacity. Twenty-five health departments reported substantial-to-full capacity to monitor health problems, 21 to diagnose health problems, 11 to conduct evaluations, and 9 to perform applied research. Conclusions: Strategies to meet 21st century challenges and increase substantial-to-full epidemiological capacity include seeking funds from nongovernmental sources, partnering with schools and programs of public health, and identifying creative solutions to hiring and retaining epidemiologists.

Objectives: To better understand the current status and challenges of the state public health department workforce, the Council of State and Territorial Epidemiologists (CSTE) assessed the number and functions of applied public health epidemiologists at state health departments in the United States. Methods: In 2017, CSTE emailed unique online assessment links to state epidemiologists in the 50 states and the District of Columbia (N = 51). The response rate was 100%. CSTE analyzed quantitative data (27 questions) on funding, the number of current and needed epidemiologists, recruitment, retention, perceived capacity, and training. CSTE coded qualitative data in response to an open-ended question that asked about the most important problems state epidemiologists face. Results: Most funding for epidemiologic activities came from the federal government (mean, 77%). State epidemiologists reported needing 1199 additional epidemiologists to achieve ideal capacity but noted challenges in recruiting qualified staff members. Respondents cited opportunities for promotion (n = 45, 88%), salary (n = 41, 80%), restrictions on merit raises (n = 36, 70%), and losses to the private or government sector (n = 33, 65%) as problems for retention. Of 4 Essential Public Health Services measured, most state epidemiologists reported substantial-to-full capacity to monitor health status (n = 43, 84%) and diagnose and investigate community health problems (n = 47, 92%); fewer respondents reported substantial-to-full capacity to conduct evaluations (n = 20, 39%) and research (n = 11, 22%). Conclusions: Reliance on federal funding negatively affects employee retention, core capacity, and readiness at state health departments. Creative solutions for providing stable funding, developing greater flexibility to respond to emerging threats, and enhancing capacity in evaluation and applied research are needed.

Background Implementation science experts define champions as “supporting, marketing, and driving through an implementation, overcoming indifference or resistance that the intervention may provoke in an organization.” Many hospitals use designated clinical champions—often called “hand hygiene (HH) champions”—typically to improve hand hygiene compliance. We conducted an ethnographic examination of how infection control teams in the Veterans Health Administration (VHA) use the term “HH champion” and how they define the role. Methods An ethnographic study was conducted with infection control teams and frontline staff directly involved with hand hygiene across 10 geographically dispersed VHA facilities in the USA. Individual and group semi-structured interviews were conducted with hospital epidemiologists, infection preventionists, multi-drug-resistant organism (MDRO) program coordinators, and quality improvement specialists and frontline staff from June 2014 to September 2017. The team coded the transcripts using thematic content analysis content based on a codebook composed of inductive and deductive themes. Results A total of 173 healthcare workers participated in interviews from the 10 VHA facilities. All hand hygiene programs at each facility used the term HH champion to define a core element of their hand hygiene programs. While most described the role of HH champions as providing peer-to-peer coaching, delivering formal and informal education, and promoting hand hygiene, a majority also included hand hygiene surveillance. This conflation of implementation strategies led to contradictory responsibilities for HH champions. Participants described additional barriers to the role of HH champions, including competing priorities, staffing hierarchies, and turnover in the role. Conclusions Healthcare systems should consider narrowly defining the role of the HH champion as a dedicated individual whose mission is to overcome resistance and improve hand hygiene compliance—and differentiate it from the role of a “compliance auditor.” Returning to the traditional application of the implementation strategy may lead to overall improvements in hand hygiene and reduction of the transmission of healthcare-acquired infections.

The quality of medical research importantly depends, among other aspects, on a valid statistical planning of the study, analysis of the data, and reporting of the results, which is usually guaranteed by a biostatistician. However, there are several related professions next to the biostatistician, for example epidemiologists, medical informaticians and bioinformaticians. For medical experts, it is often not clear what the differences between these professions are and how the specific role of a biostatistician can be described. For physicians involved in medical research, this is problematic because false expectations often lead to frustration on both sides. Therefore, the aim of this article is to outline the tasks and responsibilities of biostatisticians in clinical trials as well as in other fields of application in medical research.

Background Zika virus (ZIKV) is an emerging mosquito-borne arbovirus that can produce serious public health consequences. In 2016, ZIKV caused an epidemic in many countries around the world, including the United States. ZIKV surveillance and vector control is essential to combating future epidemics. However, challenges relating to the timely publication of case reports significantly limit the effectiveness of current surveillance methods. In many countries with poor infrastructure, established systems for case reporting often do not exist. Previous studies investigating the H1N1 pandemic, general influenza and the recent Ebola outbreak have demonstrated that time- and geo-tagged Twitter data, which is immediately available, can be utilized to overcome these limitations. Methods In this study, we employed a recently developed system called Cloudberry to filter a random sample of Twitter data to investigate the feasibility of using such data for ZIKV epidemic tracking on a national and state (Florida) level. Two auto-regressive models were calibrated using weekly ZIKV case counts and zika tweets in order to estimate weekly ZIKV cases 1 week in advance. Results While models tended to over-predict at low case counts and under-predict at extreme high counts, a comparison of predicted versus observed weekly ZIKV case counts following model calibration demonstrated overall reasonable predictive accuracy, with an R 2 of 0.74 for the Florida model and 0.70 for the U.S. model. Time-series analysis of predicted and observed ZIKV cases following internal cross-validation exhibited very similar patterns, demonstrating reasonable model performance. Spatially, the distribution of cumulative ZIKV case counts (local- & travel-related) and zika tweets across all 50 U.S. states showed a high correlation ( r  = 0.73) after adjusting for population. Conclusions This study demonstrates the value of utilizing Twitter data for the purposes of disease surveillance. This is of high value to epidemiologist and public health officials charged with protecting the public during future outbreaks.

The demands of professional tennis, including physical and psychological aspects, contribute to the frequency of retirements at elite levels of the sport. The aim of this study was to analyze epidemiological patterns and risk factors associated with retirements in previous ATP and WTA Tour tournaments. A retrospective cohort study was conducted. This study focused on previous ATP and WTA Tour tournaments. The ATP database encompassed 584,806 matches, while the WTA database included 267,380 matches. To assess retirements, potential risk factors such as playing surface, tournament category, match round, and player age were analyzed. Incidence rates were calculated for the period between 1978–2019 for men and 1994–2018 for women. The overall incidence rate was 1.56 (95%CI: 1.54, 1.59) and 1.36 (95%CI: 1.33, 1.39) retirements per 1000 games played in male and female competitions, respectively. Retirements increased over the years. Higher incidence rates were observed on hard (1.59 [95%CI: 1.56, 1.63] and 1.39 [95%CI: 1.34, 1.44]) and clay (1.60 [95%CI: 1.57, 1.63] and 1.36 [95%CI: 1.32, 1.41]) compared to grass courts (0.79 [95%CI: 0.65, 0.94] and 1.06 [95%CI: 0.88, 1.27]). Risk factors differed by gender, with tournament category significant in males (IRR: 1.23 [95%CI: 1.19, 1.28] in ITF vs ATP) and match round in females (IRR: 0.92 [95%CI: 0.88, 0.98] in preliminary vs final). This study provides valuable insights for coaches, players, support teams, and epidemiologists regarding retirements and associated risk factors in previous ATP and WTA Tour tournaments, contributing to injury prevention strategies.

Population-based serological surveys are a key tool in epidemiology to characterize the level of population immunity and reconstruct the past circulation of pathogens. A variety of serocatalytic models have been developed to estimate the force of infection (FOI) (i.e., the rate at which susceptible individuals become infected) from age-stratified seroprevalence data. However, few tool currently exists to easily implement, combine, and compare these models. Here, we introduce an R package, Rsero , that implements a series of serocatalytic models and estimates the FOI from age-stratified seroprevalence data using Bayesian methods. The package also contains a series of features to perform model comparison and visualise model fit. We introduce new serocatalytic models of successive outbreaks and extend existing models of seroreversion to any transmission model. The different features of the package are illustrated with simulated and real-life data. We show we can identify the correct epidemiological scenario and recover model parameters in different epidemiological settings. We also show how the package can support serosurvey study design in a variety of epidemic situations. This package provides a standard framework to epidemiologists and modellers to study the dynamics of past pathogen circulation from cross-sectional serological survey data.

Anders Tegnell talks to Nature about the nation’s ‘trust-based’ approach to tackling the pandemic. The epidemiologist behind Sweden’s controversial coronavirus strategy Anders Tegnell talks to Nature about the nation’s ‘trust-based’ approach to tackling the pandemic. Anders Tegnell attends a press conference in Solna, Sweden