Frontiers in Public Health

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ISSN / EISSN : 2296-2565 / 2296-2565
Current Publisher: Frontiers Media SA (10.3389)
Total articles ≅ 3,540
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, Vidya L. Purushothaman, Jiawei Li, Cortni Bardier, Matthew Nali, Neal Shah, Nick Obradovich, Joshua Yang, Tim K. Mackey
Published: 13 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.628812

Introduction: College-aged youth are active on social media yet smoking-related social media engagement in these populations has not been thoroughly investigated. We sought to conduct an exploratory infoveillance study focused on geolocated data to characterize smoking-related tweets originating from California 4-year colleges on Twitter. Methods: Tweets from 2015 to 2019 with geospatial coordinates in CA college campuses containing smoking-related keywords were collected from the Twitter API stream and manually annotated for discussions about smoking product type, sentiment, and behavior. Results: Out of all tweets detected with smoking-related behavior, 46.7% related to tobacco use, 50.0% to marijuana, and 7.3% to vaping. Of these tweets, 46.1% reported first-person use or second-hand observation of smoking behavior. Out of 962 tweets with user sentiment, the majority (67.6%) were positive, ranging from 55.0% for California State University, Long Beach to 95.8% for California State University, Los Angeles. Discussion: We detected reporting of first- and second-hand smoking behavior on CA college campuses representing possible violation of campus smoking bans. The majority of tweets expressed positive sentiment about smoking behaviors, though there was appreciable variability between college campuses. This suggests that anti-smoking outreach should be tailored to the unique student populations of these college communities. Conclusion: Among tweets about smoking from California colleges, high levels of positive sentiment suggest that the campus climate may be less receptive to anti-smoking messages or adherence to campus smoking bans. Further research should investigate the degree to which this varies by campuses over time and following implementation of bans including validating using other sources of data.
, David B. Menkes
Published: 13 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.664778

In his recent JAMA Psychiatry article “Managing Virtual Hybrid Psychiatrist-Patient Relationships in a Digital World,” Shore (1) makes a convincing case for psychiatrists to be familiar with developing technologies as they affect both the doctor-patient relationship and clinical outcomes. His scope usefully identifies administrative, operational, and clinical domains relevant to the use of various technologies, including email, text message, videoconferencing, web-based patient portals, and social networks. Conspicuously absent from Shore's argument is any consideration of research governance vital to the ethical development and application of these new technologies. He also neglects to mention another clinically promising technology; virtual reality (VR) has been studied in several psychiatric conditions (2) and is distinct in that it places patients completely within a digital, multi-modality, three-dimensional space, and enables direct interaction with that virtual environment. Clinicians need to know that VR is primarily accessed through head-mounted displays and that patient movements within the virtual space can measured by external or internal device sensors; hand-held controllers allow direct manipulation of the virtual environment which can also be measured and analyzed to provide data relevant to treatment optimization (2). The more recent availability of consumer-focused VR-devices has led to a flurry of interest and research. In psychiatry this research has thus far primarily focused on virtual versions of established therapies such as cognitive behavioral therapy (CBT) and exposure therapy (ET). These have been usefully applied to specific phobias (3) and eating disorders (4) and, more recently, trialed in schizophrenia (5). VR could also provide students and clinicians of various disciplines the opportunity to experience psychiatric patients' pathological symptoms, such as auditory and visual hallucinations. Beyond psychiatry there are important use-cases ranging from clinical use in pain detection (6) to enhanced training of various healthcare professionals (7). Extending the framework proposed by Shore, we suggest that the following considerations should apply to the developing use of VR in psychiatry. Administrative concerns include the licensing of platforms and software, and how data are collected, stored, and analyzed. Operational aspects are often more complicated; significant resources and technical expertise required to set up and effectively apply the technology, and to troubleshoot problems. Clinical evidence of VR's usefulness is accumulating with, for example, VR-exposure therapy (VR-ET) producing comparable results to conventional ET; an important advantage of VR is that it provides both therapists and patients greater control in the design and application of therapeutic environments (3). In addition to the above suggested expansion of Shore's administrative domain (1), and considering the key role research governance plays in the ethical development and application of digital technology, we propose this be regarded as a separate domain. Furthermore, trials conducted for several digital technologies are often tested on non-clinical populations and the literature therefore contains many gaps regarding effects on, for example, clinical depression, and anxiety (2). While this might be due, in part, to ethical challenges associated with testing on severe mental disorders, a focus on clinical populations will be essential to determine the therapeutic place of these technologies. It would also be important to ensure inclusion of a range of disorders and demographics in the research; otherwise clinical advances may be difficult to realize, as has occurred with the difficulties in identifying and treating female patients with autism spectrum disorder as a result of criteria being developed around male patients (8). It is therefore important that clear development, testing and reporting guidelines are developed for VR and other digital technologies used in mental health and early work by expert groups has begun to provide such guidance (9). The current reliance on proprietary software and platforms and consequent lack of open source alternatives in VR research is an important governance limitation that constrains progress in the development and application of this technology. As with other developing technologies, it is important to consider potential conflicts of interest in the promotion and use of proprietary software and hardware. Finally, as with other emerging therapeutic modalities, there is limited knowledge of the potential adverse effects associated with immersive VR interventions for mental health, and those designing clinical trials should be alert to a range of possible outcomes and considering this when reporting results. This is particularly important when considering that psychological interventions have a particularly poor track record for reporting adverse events (10). New technologies such as VR may offer a further advantage in light of current concerns about the risk of infection from face-to-face interactions and provide some relief to healthcare organizations and clinicians that have scrambled during the COVID-19 pandemic to offer virtual consultations (11). Mental health clinicians should learn from this and make sure organizations can seamlessly adapt virtual alternatives when necessary; VR can be of particular advantage due to how readily it can be adapted to automated treatment and data collection and the location where treatment is delivered (12). Ethical research governance also represents an important challenge, particularly as new technologies pose new risks in terms of privacy and confidentiality. On the other hand, new technologies can be exceptionally useful, for example allowing new data sources (such as changes in patterns of mobile phone use and geographical data and activity from smart home sensors) that can detect...
Jan Domaradzki, Dariusz Walkowiak
Published: 13 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.618608

From the very first moment coronavirus struck, medical students volunteered to support healthcare professionals' fight against the COVID-19 pandemic. To learn more about future healthcare professionals' volunteering during such an outbreak, we conducted a survey among 417 students of Poznan University of Medical Sciences. Our findings suggest that although numerous studies demonstrate that traditional, value-based volunteering is decreasing, and especially higher education students are more oriented toward their own career, in the times of the current health crisis, young peoples' involvement in volunteering has been mainly driven by altruism and the ethical imperative to serve their community, their fellow healthcare professionals and their patients. Thus, while the prime role of the volunteering was to relieve the healthcare system, it also reinforced such important medical values as altruism, public service and professional solidarity. Moreover, it proved that whilst risk is inherent to medicine, the students' volunteering is truly a moral enterprise.
Igor Silva Campos, Vinícius Ferreira Aratani, Karina Baltor Cabral, Jean Ezequiel Limongi,
Published: 13 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.586670

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. An epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature search and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on Indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1–5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte was the most vulnerable mesoregion, with 42.9 and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.
Nathalie Barth, , Sarah Anne Fraser, Martine Lagacé, Stéphane Adam, Pauline Gouttefarde, Luc Goethals, Lauren Bechard, Bienvenu Bongue, Hervé Fundenberger, et al.
Published: 12 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.589244

In February 2021, France had more than 76,000 deaths due to COVID-19 and older adults were heavily affected. Most measures taken to reduce the impact of COVID-19 (quarantine, visit ban in nursing home, etc.) significantly influenced the lives of older adults. Yet they were rarely consulted about their implementation. Exclusion of and discrimination against older adults has been accentuated during the COVID-19 pandemic. While many articles discussing COVID-19 also mention ageism, few actually incorporate the perspectives and opinions of older adults. Our research aims to assess the ageism experienced by older adults during the COVID-19 pandemic. We conducted interviews with older adults (63–92 years, mean age = 76 years) in an urban area of France. Participants reported experiencing more ageism during the COVID-19 pandemic, including hostile and benevolent ageism from older adults' families. Despite reports of experiencing ageist attitudes and behaviors from others, however, older adults also identified positive signs of intergenerational solidarity during this COVID-19 crisis.
, Anne Starker, Raimund Geene, Susanne Jordan
Published: 12 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.638242

Background: The influence of the working environment on the back health of employees is well-documented. Many companies have begun to offer employees access to services to promote back health. Factors affecting the use of these offers at the population level have received little investigation to date. The current study examined the socio-demographic factors, physical activity and health-related factors, and work-related factors associated with the use of offers of workplace health promotion for back health in Germany. Materials and Methods: In the representative population-based cross-sectional survey “German Health Update” (GEDA 2014/2015-EHIS) conducted by the Robert Koch Institute, 12,072 employees aged 18–64 years old were surveyed from November 2014 to July 2015 regarding the use of back health services in their companies. In addition to socio-demographic factors, the survey examined working hours, physical activity in leisure time, health awareness, and subjective complaints in the lower back or other chronic back problems in the last 12 months. The interaction of these factors with the utilization of back health services was tested using multiple logistic regression models. Results: Women used back health services more often than men (women: 25.5%; men: 18.1%). Female gender was associated with part-time employment (OR 0.72) and a strong to very strong level of health awareness (OR 1.40). Male gender was associated with age between 30 and 44 years (OR 1.99) and 45–64 years (OR 2.02), low socioeconomic status (OR 0.48), endurance activity of <2.5 h per week (OR 0.62), and absence of lower back pain or other chronic back conditions for the last 12 months (OR 0.48). Conclusion: The present study is the first to provide findings regarding the factors associated with the utilization of workplace health promotion to promote back health at the population level, and from the perspective of employees in Germany. The results revealed that the relevant factors for participating in offers differ for women and men. To reach more employees, workplace health promotion offers for back health should be designed specifically for each individual, considering gender and age, working hours, health awareness and behavior, and health state.
Grace E. Patterson, K. Marie McIntyre, Helen E. Clough,
Published: 12 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.630449

COVID-19 has disrupted everyday life worldwide and is the first disease event since the 1918 H1N1 Spanish influenza (flu) pandemic to demand an urgent global healthcare response. There has been much debate on whether the damage of COVID-19 is due predominantly to the pathogen itself or our response to it. We compare SARS-CoV-2 against three other major pandemics (1347 Black Death, 1520's new world smallpox outbreaks, and 1918 Spanish Flu pandemic) over the course of 700 years to unearth similarities and differences in pathogen, social and medical context, human response and behavior, and long-term social and economic impact that should be used to shape COVID-19 decision-making. We conclude that <100 years ago, pandemic disease events were still largely uncontrolled and unexplained. The extensive damage wreaked by historical pandemics on health, economy, and society was a function of pathogen characteristics and lack of public health resources. Though there remain many similarities in patterns of disease spread and response from 1300 onwards, the major risks posed by COVID-19 arise not from the pathogen, but from indirect effects of control measures on health and core societal activities. Our understanding of the epidemiology and effective treatment of this virus has rapidly improved and attention is shifting toward the identification of long-term control strategies that balance consideration of health in at risk populations, societal behavior, and economic impact. Policymakers should use lessons from previous pandemics to develop appropriate risk assessments and control plans for now-endemic COVID-19, and for future pandemics.
, Paolo Vineis
Published: 12 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.651089

The response of the scientific community to the COVID-19 pandemic has been unprecedented in size, speed and discovery output. Within months of virus emergence, the SARS-CoV-2 genomics, replication, evolution and dissemination dynamics as well as natural history, infection risk and prognostic factors and biology of the disease have been gradually deciphered. More than 250 articles on COVID-19 published in Frontiers in Public Health have contributed to these insights. We discuss here some of the key research themes and challenges that have been addressed. We provide our perspective on current research issues with surveillance data quality and limitations of epidemiological methods. We warn against the potential misuse or misleading interpretation of public data of variable quality and the use of inadequate study designs for the evaluation of effect of non-pharmaceutical interventions. We conclude by interrogating possible public health strategies for pandemic control as well as discuss the ethical responsibilities and democratic accountability of researchers in their role as experts and policy advisors.
Xia Liu,
Published: 12 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.662166

The slow-down of the Chinese economy and the depression in the global economy during the COVID-19 show that governments should provide stimulus packages. These policies should be inclusive in terms of financial gains. Using the panel data of 30 regions in China from 2006 to 2016, this paper uses the Poisson Pseudo-Maximum Likelihood (PPML) estimator to analyze the impact of inclusive finance on public health. The results show that inclusive finance has a significant positive effect on public health. The performance of the eastern region is significantly better than that of the central and western regions. When we consider the combined effect of environmental regulation, the improvement effect of inclusive finance on public health is still significant, and the coefficient increases in the eastern region. Similarly, there is also a significant improvement effect in the central and western regions. Our findings reveal that environmental regulation promotes the beneficial effect of inclusive finance. Therefore, it is important to improve the inclusive financial development mechanism and enhance environmental regulation intensity for solving public health issues. Lessons related to the COVID-19 pandemic are also discussed.
Shujuan Yang, Shaoqing Dai, Yuling Huang, Peng Jia
Published: 12 April 2021
Frontiers in Public Health, Volume 9; doi:10.3389/fpubh.2021.593176

As the supply of nucleic acid detection kits for coronavirus disease 2019 (COVID-19) is gradually approaching the demand for testing those with moderate or severe symptoms, even those with mild symptoms of the common cold in some countries, research interests in scientific communities have started to shift to those unidentified COVID-19 infections presenting mild or even no symptoms (i.e., asymptomatic COVID-19 infections). The observed rates of asymptomatic COVID-19 infections have varied from 17% in a family of six to 67% in a family of three (1, 2). Although such observational studies are subject to the limited sample size and selection bias, the emerging studies estimating the rates of unidentified COVID-19 infections may be subject to more severe biases or even errors, if we do not have a deep understanding of unidentified COVID-19 infections in the context of efforts of epidemic control and prevention on the ground. For example, a recent study simulating the dynamics of coronavirus disease 2019 (COVID-19) infection during 10–23 January 2020 revealed “a very high rate of undocumented infections: 86%” (3). However, such an estimate should be treated with caution because several flaws in fundamental definitions and assumptions in that study can significantly affect the accuracy and implications of the results. A most basic flaw is that they “divided infections into two classes: (i) documented infected individuals with symptoms severe enough to be confirmed, i.e., observed infections; and (ii) undocumented infected individuals.” In this seemingly reasonable procedure, authors mixed up three concepts, i.e., undocumented, unconfirmed, and unnoticed, which has fundamentally undermined the accuracy of that study and largely accounted for why that estimate has not been validated or even approached by any observational study so far. Such flawed definitions and assumptions would also undermine the quality of many more, if not all, forthcoming scientific studies in that direction and, more importantly, mislead general readers in understanding what has happened at the beginning of the COVID-19 pandemic in other provinces than Hubei Province of China. Therefore, they deserve some factual explanations. First, the rate of “undocumented” infections is not an estimatable concept. It would have been more appropriate to estimate the rate of “unnoticed” infections (i.e., asymptomatic infections) or “unconfirmed” infections (i.e., untested infections) (4). In particular, authors have clearly explained the first class as “observed” infections, then the second class was actually, also naturally, “unobserved” infections, which should be more rigorously defined as “unnoticed” infections or, at the very least, less rigorously defined as “unnoticed” or “unconfirmed” infections. In any case, conceptually, scientifically, or literally, the second class should have been correctly defined. Failure to do so has further led to other problematic statements and assumptions in the following. Second, observed infections were equal to “documented infected individuals with symptoms severe enough to be confirmed,” which was problematic due to lack of a clear definition of “symptoms severe enough.” Such vagueness also existed in another statement that “these undocumented infections often experience mild or limited symptoms and hence go unrecognized,” where “mild” and “limited” symptoms were not clearly defined. A reasonable guess is that authors did not have sufficient knowledge of COVID-19 symptoms at the time of conducting this study, according to the entire lack of early epidemiological studies including clinical characteristics of COVID-19 patients in the reference list of that article (5–7). Defining the epidemiology of COVID-19 on the basis of a large enough sample of infected cases (8) or their spatiobehavioral characteristics (i.e., individuals' close contact with infectors for a certain amount of time) (9), and thereby understanding the characteristics of COVID-19 (i.e., elucidating what the full spectrum of disease severity is, how transmissible the virus is, who the infectors are), is a critical step prior to any reliable scientific study examining the transmission and impact of COVID-19. This is also why very few (reliable) studies, if not entirely lacking, in this direction have been conducted outside China before March 2020. Therefore, simulating the dynamics of symptomatic and asymptomatic COVID-19 infections without considering the definitions of COVID-19 symptoms has invalidated that study to some extent. Third, the statement that “these undocumented infections often experience mild or limited symptoms and hence go unrecognized” is not true in all provinces but Hubei, where most, if not all, infections presenting mild symptoms in other provinces have visited their nearby fever clinics and been tested at the first moment possible (10–12); thus, they could not have gone unrecognized. Only some of those experiencing mild or limited symptoms prior to 23 January in Hubei Province, especially in Wuhan, may not be timely tested for COVID-19, due to insufficient capacity of conducting COVID-19 nucleic acid testing at that time; even so, most infections presenting any symptom have visited their local fever clinics and been triaged for at-home isolation or in-hospital isolation and treatment (11). Therefore, “the transmission rate due to undocumented individuals” in that study, in the simplest assumption, should be different for “unconfirmed” and “unnoticed” infections rather than a constant value for both groups of infections. This mistake could simply occur because authors failed to differentiate “unconfirmed” from “unnoticed” infections among...
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