bluuebunny/crossref_metadata_2025_split huggingface dataset:
7.Q. Workshop: Empirical insights on understanding of Othering and its impact on refugee health
Authors:   Organised by: PH-LENS (Germany),   Chair persons: Oliver Razum (Germany), Theda Borde (Germany)
Published: October 2021

Abstract

The workshop is held by the PH-LENS Research Unit Refugee Migration to Germany: a magnifying glass for broader Public Health challenges. PH-LENS is an interdisciplinary research group that blends expertise from various disciplines such as public health, medicine, psychology, sociology, statistics to examine the challenges of forced migration for Germany's health system and their effects on refugee health. Forced migration, and resulting challenges relating to refugee health, are currently treated as highly exceptional, as a singularity. This constitutes a socially as well as scientifically impoverished approach in two respects. Firstly, a singularity perspective may ultimately have adverse effects on the health of refugees because of the resulting Othering processes and further social marginalization of forced migrants. Othering serves as an essential analytical perspective in examining the relationship between minority status and health inequalities. The recourse on Othering enables to explore how refugees are positioned along with categorical distinctions and social attributions and how health inequalities arise from this ordering. Othering is a complex phenomenon based on power hierarchies that leads to social exclusion and health inequalities. The workshop explains Othering through synthesizing insights from our empirical quantitative and qualitative research, and theoretical analysis. The first presentation analyses attitudes towards refugees in Germany based on three representative studies run between 2014 and 2019. It sheds light on rejecting attitudes towards refugees that are present in the political center of Germany, and discuss how they contribute to Othering. The second presentation covers a qualitative survey concerning Othering processes from the perspective of refugees and professionals in obstetric care. Here, both rejective and benevolent processes of Othering come into play. Following on from this, we discuss whether benevolent Othering has an inclusive potential. Based on a theoretical analysis, the third presentation provides an in-depth reflection on Othering, focusing on the concept of Inclusionary Othering. By centering the discussion on Othering, the workshop seeks to shift the focus to society and the structural health care patterns that determine the intensity and extent of marginalization along categorical lines in addressing challenges of the health system.

Key messages
Othering provides an essential analytical perspective for examining the relationship between minority status and health inequalities. We show that exclusionary and inclusionary effects of Othering are relevant for Public Health but are so far under-appreciated.
Potential life years lost to COVID-19 in 17 countries during the pandemic period, up to August 2020
Authors: Achilleos S , Pagola Ugarte M , Quattrocchi A , Gabel J , Kolokotroni O , Constantinou C , Nicolaou N , Rodriguez-Llanes JM , Demetriou CA 
Published: October 2021

Abstract

Background
COVID-19 pandemic is affecting populations and regions in different ways. In this study, we assess the Potential Years of Life Lost (PYLL) to COVID-19 across different regions.

Methods
We used age-group and sex-specific weekly COVID-19 deaths (from January to August 2020) from national primary sources of 17 countries from the C-MOR consortium (Australia, Brazil, Cape Verde, Colombia, Cyprus, France, Georgia, Israel, Kazakhstan, Peru, Norway, England & Wales, Scotland, Slovenia, Sweden, Ukraine, and the United States). PYLL were calculated by summing up the numbers of deaths in each age group multiplied by the remaining years of life up to age 80. Age-standardized PYLL rates (per 100,000 population), using the World (WHO 2000-2025) Standard population as the reference population, were estimated to facilitate comparison across countries.

Results
Countries in South America displayed the highest PYLL rates (567-1,377 PYLL/100,000). Countries in Asia & Middle East (besides Kazakhstan), Australia, and some European countries (Georgia, Norway, and Slovenia) observed &lt;50 PYLL/100,000. Furthermore, the male to female PYLL rate ratio was above one in all countries [1.3 (Ukraine) - 14.4 (Cyprus)], besides Georgia (ratio = 0.5).

Conclusions
South America, and males were found to be the most affected by COVID-19. Ongoing monitoring of the COVID-19 mortality impact is essential in order to assess health system performances, control measures, and identify vulnerable populations. Differences in mortality burden among populations will help public health officials in their efforts to minimize the COVID-19 mortality burden on a local, and on a global level.

Key messages
Up to August 2020, COVID-19 was a cause of premature mortality in all the participating countries, with South America and males to be more affected. The timing of the pandemic, seasonal trends, the control measures enforced, and underlying social conditions are probable explanations for the differences observed among countries.
Estimation of Excess Deaths in Turin from COVID-19 and other causes, October to November 2020
Authors: Favaro E , Saugo C , Sandu B , DeMaria M , Gnavi R , Lefevre C , Costa G 
Published: October 2021

Abstract

Introduction
Understanding the effect of COVID-19 on mortality during this emergency and evaluating unexplained increases in deaths due to nonspecific outcomes can provide a more complete picture of this period and give better instrument to deal with the pandemy in the future.

Objective
The aim is to evaluate in the city of Turin the excess in the number of deaths from October to November 2020.

Methods
The number of excess deaths was defined as the difference between the deaths observed in the pandemic period of 2020 and the deaths expected for the years 2014-2019.

Results
There were approximately 2047 total all causes deaths in Turin October 1 to November 30 2020, representing 630 more deaths than would typically be expected at that time of year. This excess was higher between men than in women. The number of excess all cause death was higher in 80 years old, less evident between 60-79 years old and very few between under 60 years old. Regarding the place of death, the number of excess all cause death was higher in hospital or in some health institutions for old people. Regarding the causes of deaths the explanation of these excess of deaths was COVID-19 infection only for a part of deaths and there are some excess of deaths not caused by COVID-19. The cause of excess of death not COVID-19 seems to be due to cardiovascular diseases, respiratory diseases, psychiatric disorders, neurological diseases, diabetes or nephrological diseases and to other undefinited causes.

Conclusions
The results showed during pandemic an increase of mortality respect to the expected mortality. Only a part of this excess deaths is due to COVID-19 but there is a relevant percentage of excess of deaths apparentely not due to COVID-19 but probably due to other causes. A better knowledge of these phenomena could help to improve any gaps in territorial assistance and provide indications for the future management of the pandemic in Europe.

Key messages
Increase of mortality in pandemic respect to the expected mortality. There is an excess of deaths apparentely not due to COVID-19.
8.C. Round table: Round table: COVID-19: What have we learned? What are the public health challenges?
Authors:   Organised by: EUPHA,   Chair persons: Peter Allebeck (Sweden), Dineke Zeegers Paget (EUPHA)
Published: October 2021

Abstract

If there ever was a public health problem where we could learn a lot about public health research, practice, policy and communication, it is the COVID-19 pandemic. With increased knowledge about the spread, the prevention measures, treatment and vaccination, a lot of research on COVID-19 has been and is being published. Looking for COVID-19 articles on google scholar leads to over 3.6 million articles found. Nearly all research published on COVID-19 has been made publicly accessible to allow the latest research to be available for politicians, policymakers, practitioners and laymen.
The quality of the research is sometimes good, sometimes less good (see our recent viewpoints https://academic.oup.com/eurpub/issue/30/5?browseBy=volume). But with the increase in research, it becomes more difficult to find which research is old, outdated and which is new.
Furthermore, all sorts of media have covered the pandemic extensively, in many journals one can find very good reviews and articles by serious journalists, but in many cases, also rumours, guesses and fake news. On top of becoming tired of information overload, it is also more and more difficult to keep track of the development of the research. EUPHA - therefore - decided to publish a supplement to the European Journal of Public Health looking at specific health issues and specific groups that were affected by the pandemic. The supplement aims to present short summaries and updates on some key issues of public health relevance. Topics included range from environment, mental health, legal and ethical issues, health workforce, health inequalities, accountability, opening up the economy and such.
In this Round Table, we will have a number of authors from the EJPH supplement to discuss their findings and find some common grounds on what we have learned from COVID-19 and how to move forward.

Speakers/Panelists
Martin McKee LSHTM, London, UK Elena Petelos Clinic of Social and Family Medicine, Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece Julian Mamo Public Health Department, University of Malta, Valletta, Malta Ellen Kuhlmann Medizinische Hochschule Hannover, Hannover, Germany Els Maeckelberghe Wenckebach Institute for Medical Education and Training, University Medical Center Groningen, Groningen, Netherlands

Key messages
Learning from this pandemic for future planning is essential. Touching all fields affected by COVID-19 to plan for the future is necessary.
What does it mean to age in good health? An analysis of Time Use Survey data
Authors: Santos JV , Cylus J 
Published: October 2021

Abstract

Background
While there is intrinsic value of ageing in good health, there is little evidence of how the daily lives of older people differ depending on their health status.

Methods
We use Time Use Survey data from the United Kingdom to assess how people at different ages spend their time, conditional on their self-reported health.

Results
While results are preliminary, we find stark differences between people's time use dependent on their health. For example, older people who report good health are more likely than comparable older people to engage in paid work, volunteer, and participate in leisure activities.

Conclusions
There are many benefits to supporting healthy ageing. By considering how time spent differs between those in good and poor health and attributing value to that time, one can take a more holistic perspective when conducting cost-benefit analysis of policy interventions.
A liquid biopsy model to detect eventual pollutants as “one health” tool
Authors: Pepe F , Scotti G , Barbieri O , Vozzella EA , Iervolino A , Malapelle U , Troncone G 
Published: October 2021

Abstract
Environmental pollution (EP), defined as the unfavorable chemical and physical alterations of our surroundings, still represents a relevant issue of this century. In this scenario, several changes may directly or indirectly impact on human health by promoting neoplastic cell transformation due to DNA damage in human tissue. The identification of a specific molecular signature observed in people exposed to environmental contaminants could improve risk calculation of exposition. As regards, DNA methylation is considered an epigenetic modification that could play a pivotal role in the risk calculation of patients under EC exposure. This mechanism, based on the introduction of methyl groups on cytosine's in CpG islands, is carried out by methyltransferases enzymes able to activate this modification in promotor region by influencing regulation process. Several studies demonstrated that methylation pattern is drastically alterated in subjects under EC exposure. To date, several approaches for the early detection of contaminants in biological fluids are under investigation. Liquid biopsy consists in a peripheral blood withdrawn where several biomolecules [cell-free DNA (ccfDNA), circulating tumor cells (CTCs), circulating cell-free RNA (ccfRNA) and exosomes] may be isolated. Students participate to the validation of a LP assay for the evaluation of environmental determinants with the Lab Residents. They assessed the cost-efficacy and the minimally invasive approach in order to construct a reliable model to be exported for the identification of epigenetic changes in the early stage of contamination process in high risk people. The young students role was also to create an informative schedule in order to explain the role and the potential of Liquid biopsy as a non-invasive tool that could allow the analysis of nucleic biomarkers as circulating cell-free DNA (ccfDNA), a potential stable biomarkers of diverse disease conditions in humans and animals.
An overview of AI and Machine Learning methods: motivations, concepts, and examples
Authors: Assouline D , Le Pogam M-A , Pittet V 
Published: October 2021

Abstract
What is artificial intelligence? Big Data? Machine learning? It may seem very difficult to define these terms and identify their use in real life, aside from the hype surrounding them over the past ten years. All of these terms are interconnected - sometimes they intersect, often they are included in each other. The main focus of this presentation is to present ‘Machine learning' methods, which can be defined as algorithms that learn patterns (a function) about a particular phenomenon (an output variable), based on examples (training data), often without any a priori on the shape of these patterns. Therefore, they are a broad family of methods that include traditional statistical methods such as linear regression models, but which often offer more flexibility in terms of hypothesis and complex data settings. Multiple frameworks exist, based on how many examples are available (size of the training data) and the kind of modeling application one wants to perform (e.g., classification, regression, clustering). Many different families of methods exist for each modeling application, which offers a tremendous amount of different algorithms, each having advantages and drawbacks. In practice, easy-to-use libraries were developed in popular programming languages such as Python and R, offering implementations of the majority of essential algorithms.
An introduction to Random Forests for modeling tasks - theory and practice in python with public health case studies
Authors: Assouline D , Le Pogam M-A , Pittet V 
Published: October 2021

Abstract
RFs are a powerful, volatile, and easy to use method, making it an excellent benchmark method for different types of analysis, notably in the public health domain. RFs offer outstanding performance with minimal effort from the user (given its low sensitivity to its hyperparameters) and can be used for many different modeling tasks (classification, regression, clustering, outlier detection). In practice, RFs are easily applicable through libraries in Python and R languages, allowing users to benefit from their capabilities with minimal coding knowledge. In addition to their pure performance abilities, RFs have some practical advantages when compared to many classical statistical models: it does not require any normalization of the data, handles very large datasets (in population or variables) and all kinds of data types (e.g., binary, categorical, continuous); it handles outliers and is insensitive to multicollinearity within the input variables. Their main limitation is their less straightforward interpretation of the final model they build. However, they offer additional tools, such as variable importance and proximity metrics, that improve the understanding of their results and potentially provide insights that traditional models cannot. Finally, its construction based on decision trees grants it additional capabilities, notably the possibility to extract prediction intervals and to handle efficiently imbalanced data problems with a variant of the algorithm called Balanced Random Forests.
Association between economic growth, mortality and healthcare spending in 31 high-income countries
Authors: Sanmarchi F , Golinelli D , Esposito F , Toscano F , Fantini MP , Bucci A 
Published: October 2021

Abstract

Background
During the last decades, countries' healthcare spending has grown continuously, becoming a major expenditure item and threatening the overall sustainability of healthcare systems. Plenty of literature shows conflicting evidence about the relationship between economic variations and measurable health outcomes. This study aims to investigate the association between GDP, population mortality and healthcare spending in OECD high-income countries.

Methods
We conducted a cross-sectional study using panel data across 31 high-income countries from 2000 to 2017. Socioeconomic data for every year and each country were extracted from WHO and OECD Database. The association between current healthcare expenditure (CHE), GDP and mortality rate (MR) was investigated through a random-effects model. To control for possible reverse causality, we adopted a test of Granger causality for heterogeneous panel data models.

Results
The results of the random-effects model show that the MR has no statistically significant effect on CHE. We found no statistically significant association between countries' MR and GDP when the latter is the dependent variable. Our results show that an increase in GDP is associated with a significant increase of CHE (b = 0.066, p &lt; 0.001) and CHE is significantly associated with an increase in GDP (b = 3.188, p &lt; 0.001). The Granger causality analysis shows a unidirectional association between MR and CHE, with MR influencing CHE, albeit with a small statistical significance (p = 0.045). Between GDP and CHE, the causality is bidirectional, while between GDP and MR we found no causality.

Conclusions
In this study, we found a strong two-way relationship between GDP and CHE, both in the causality analysis and in the random-effect panel model. Our analysis highlights the economic multiplier effect of CHE. In the debate on the optimal allocation of resources often resulting from economic crises, this evidence should be taken into due consideration.

Key messages
Policymakers worldwide need to recognize the economic impact of healthcare spending when allocating financial resources. Spending on health leads to economic growth. In light of the current health-economy dichotomy, it is important to produce robust scientific evidence supporting healthcare spending.
Internal communication within the healthcare system during the COVID-19 pandemic in Latvia
Authors: Kursite M , Stars I , Gobina I , Springe L , Villerusa A 
Published: October 2021

Abstract

Background
Effective communication among health care providers is a key for responding to the rapidly changing health care needs, improving work efficiency, and ensuring patient safety, particularly during the crisis of the COVID-19 pandemic. This study explores the communication-related experiences of healthcare professionals during the first wave of the COVID-19 pandemic in Latvia.

Methods
Semi-structured interviews with 7 chairman of healthcare facilities, 19 general practitioners, and 15 specialists were conducted from September to December 2020. Interviews were recorded and transcribed. Thematic analysis revealed five themes related to internal communication among health care providers. The study was a component of the National research programme VPP-COVID-2020/1-0011.

Results
The 1st theme, ‘Initial chaos paralyzing the system', illustrated the disorderly format of delivering the information that created confusion and anxiety. The 2nd theme, ‘Overwhelming amount of information', revealed the challenge to process new information received daily and from various sources. The 3rd theme, ‘Decentralized decision-making' highlighted the lack of clearly communicated algorithms for specific patients' groups, leaving the decision-making to the health care providers. The 4th theme, ‘Collegial support of the peers”, emerged as a crucial coping mechanism and information channel, substituting for the lack of official information. The 5th theme, ‘Opportunity for growth', consolidated suggestions from health care professionals for improving internal communication in future.

Conclusions
Internal communication as experienced among healthcare professionals was overwhelming and insufficient at the same time. It created an environment promoting closer collaboration among different specialists and suggestions for necessary improvements.

Key messages
Understanding and perception of communication among health care providers in different healthcare system levels were central that affected the health care actions tackling the COVID-19 emergency. Effective communication within the healthcare system is critical during the pandemic. Messages should be clear, evidence-informed, and transparent for targeted action of the health care workforce.
The politics of COVID-19 on the island of Ireland
Authors: Nolan A , Burke S , Burke E , Darker C , Barry J , Dempster M , Graham C , Crowley P , O'Connell N , Scally G 
Published: October 2021

Abstract

Background
Political systems are the means through which the science of public health achieves its objectives. This is a qualitative study of public health policies for COVID-19 in Northern Ireland and the Republic of Ireland that seeks to establish if inter-jurisdictional commitments have led to co-ordination and co-operation on the island of Ireland.

Methods
10 indicators from the OxCGRT codebook directed data collection with directed qualitative content analysis supporting comprehensive reading of policy documents. Cross-case and within-case analysis of policy alignment and divergence across ten OxCGRT indicators was undertaken.

Results
Closing Schools Republic of Ireland: 12th March 2020 Northern Ireland: 23rd March 2020; Workplace Closing - Republic of Ireland: 12th and 15th March and 24th March 2020. Northern Ireland: 20th March 2020 followed by mandatory closure on 28th March 2020. Cancelling events and mass gatherings (St Patrick's Day, 17th March)-Republic of Ireland: 9th March 2020-Northern Ireland: 9th March 2020;Lockdown/Shelter-in-place policies. Republic of Ireland: 27th March 2020- Northern Ireland: 28th March 2020; Restrictions on Internal Movement Republic of Ireland: 27th March 2020 Northern Ireland: 28th March 2020. Physical Distancing Measures -Republic of Ireland: 2-metres 24th March 2020 Northern Ireland: 2 metres 23rd March 2020. Mandatory Face Masks in Enclosed Spaces-Republic of Ireland: 10th August 2020 -Northern Ireland: 10th August 2020.

Conclusions
The historical and constitutional politics of the island of Ireland is the obstacle to an all-island response to COVID-19 and this has almost certainly been compounded by Brexit. Defying the odds, however, this study has demonstrated substantial public health policy alignment brought about through ongoing dialogue and co-operation between the health administrations in each jurisdiction.

Key messages
Historical and constitutional politics of the island of Ireland is the obstacle to an all-island response to COVID-19. Even pandemics cannot overcome realpolitik.