Immigrant community integration in world cities

Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis

Introduction

Dementia is an umbrella term indicating a group of diseases that affect the cognitive sphere. Dementia is not a mere individual health issue, since its interference with the ability to carry out daily activities entails a series of collateral problems, comprising exclusion of patients from civil rights and welfare, unpaid caregiving work, mostly performed by women, and an additional burden on the public healthcare systems. Thus, gender and wealth inequalities (both among individuals and among countries) tend to amplify the social impact of such a disease. Since at present there is no cure for dementia but only drug treatments to slow down its progress and mitigate the symptoms, it is essential to work on prevention and early diagnosis, identifying the risk factors that increase the probability of its onset. The complex and multifactorial etiology of dementia, resulting from an interplay between genetics and environmental factors, can benefit from a multidisciplinary approach that follows the "One Health" guidelines of the World Health Organization.

Methods

In this work, we apply methods of Artificial Intelligence and complex systems physics to investigate the possibility to predict dementia prevalence throughout world countries from a set of variables concerning individual health, food consumption, substance use and abuse, healthcare system efficiency. The analysis uses publicly available indicator values at a country level, referred to a time window of 26 years.

Results

Employing methods based on eXplainable Artificial Intelligence (XAI) and complex networks, we identify a group of lifestyle factors, mostly concerning nutrition, that contribute the most to dementia incidence prediction.

Discussion

The proposed approach provides a methodological basis to develop quantitative tools for action patterns against such a disease, which involves issues deeply related with sustainable, such as good health and resposible food consumption.

Aging effects in Schelling segregation model

The Schelling model has become a paradigm in social sciences to explain the emergence of residential spatial segregation, even in the presence of high tolerance to mixed neighborhoods by the side of citizens. In particular, we consider a noisy constrained version of the Schelling model, in which agents maximize its satisfaction, related to the composition of the local neighborhood, by infinite-range movements towards satisfying vacancies. We add to it an aging effect by making the probability of agents to move inversely proportional to the time they have been satisfied in their present location. This mechanism simulates the development of an emotional attachment to a location where an agent has been satisfied for a while. The introduction of aging has several major impacts on the model statics and dynamics: the phase transition between a segregated and a mixed phase of the original model disappears, and we observe segregated states with a high level of agent satisfaction even for high values of tolerance. In addition, the new segregated phase is dynamically characterized by a slow power-law coarsening process similar to a glassy-like dynamics.

Geolocation of multiple sociolinguistic markers in Buenos Aires

Analysis of language geography is increasingly being used for studying spatial patterns of social dynamics. This trend is fueled by social media platforms such as Twitter which provide access to large amounts of natural language data combined with geolocation and user metadata enabling reconstruction of detailed spatial patterns of language use. Most studies are performed on large spatial scales associated with countries and regions, where language dynamics are often dominated by the effects of geographic and administrative borders. Extending to smaller, urban scales, however, allows visualization of spatial patterns of language use determined by social dynamics within the city, providing valuable information for a range of social topics from demographic studies to urban planning. So far, few studies have been made in this domain, due, in part, to the challenges in developing algorithms that accurately classify linguistic features. Here we extend urban-scale geographical analysis of language use beyond lexical meaning to include other sociolinguistic markers that identify language style, dialect and social groups. Some features, which have not been explored with social-media data on the urban scale, can be used to target a range of social phenomena. Our study focuses on Twitter use in Buenos Aires and our approach classifies tweets based on contrasting sets of tokens manually selected to target precise linguistic features. We perform statistical analyses of eleven categories of language use to quantify the presence of spatial patterns and the extent to which they are socially driven. We then perform the first comparative analysis assessing how the patterns and strength of social drivers vary with category. Finally, we derive plausible explanations for the patterns by comparing them with independently generated maps of geosocial context. Identifying these connections is a key aspect of the social-dynamics analysis which has so far received insufficient attention.

Associations of socioeconomic status indicators and migrant status with risk of a low vegetable and fruit consumption in children

Background

It is important to provide insight in potential target groups for interventions to reduce socioeconomic inequalities in children's vegetable/fruit consumption. In earlier studies often single indicators of socioeconomic status (SES) or migrant status have been used. However, SES is a multidimensional concept and different indicators may measure different SES dimensions. Our objective is to explore multiple associations of SES indicators and migrant status with risk of a low vegetable/fruit consumption in a large multi-ethnic and socioeconomically diverse sample of children.

Methods

We included 5,010 parents of 4- to 12-year-olds from a Dutch public health survey administered in 2018. Cross-sectional associations of parental education, material deprivation, perceived financial difficulties, neighbourhood socioeconomic status (NSES) and migrant status with low (≤4 days a week) vegetable and fruit consumption in children were assessed using multilevel multivariable logistic regression models. Results are displayed as odds ratios (OR) with 95% confidence intervals (CI).

Results

Of the 4- to 12-year-olds, 22.1% had a low vegetable consumption and 11.9% a low fruit consumption. Low (OR 2.51; 95%CI: 2.05, 3.07) and intermediate (OR 1.83; 95%CI: 1.54, 2.17) parental education, material deprivation (OR 1.45; 95%CI: 1.19, 1.76), low NSES (OR 1.28; 95%CI: 1.04, 1.58) and a non-Western migrant status (OR 1.94; 95%CI: 1.66, 2.26) were associated with a higher risk of a low vegetable consumption. Low (OR 1.68; 95%CI: 1.31, 2.17) and intermediate (OR 1.39; 95%CI: 1.12, 1.72) parental education and material deprivation (OR 1.63; 95%CI: 11.27, 2.08) were also associated with a higher risk of a low fruit consumption.

Conclusion

Our findings indicate associations of multiple SES indicators and migrant status with a higher risk of a low vegetable/fruit consumption in children and thus help to identify potential target groups.

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Vegetable and fruit consumptions on 4 days or less a week is reported for respectively 22.1% and 11.9% of children.

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Children's vegetable but not fruit consumption differs between neighbourhoods.

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A non-Western migrant status and a low socio-economic status of the neighbourhood are associated with low vegetable consumption.

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Low/intermediate education and material deprivation are associated with low vegetable and fruit consumption.

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This study provides clues to potential entry points for reducing inequalities in vegetable and fruit consumption.

Knowledge translation in health and wellness research focusing on immigrants in Canada

INTRODUCTION Knowledge translation (KT) is a relatively new concept referring to transfers of knowledge into practice in collaboration with multiple sectors that work for the health and wellness of society. Knowledge translation is crucial to identifying and addressing the health needs of immigrants. AIM To scope the evidence on KT research engaging immigrants in the host country regarding the health and wellness of immigrants. METHODS This study followed a scoping review approach suggested by Arksey O'Malley. We identified relevant studies from both academic and grey literature using structured criteria, charted the data from the selected studies, collated, summarised and report the results. RESULTS Analysis of the eligible studies found two types of KT research: integrated KT and end-of-grant KT. Meeting or discussion with community-level knowledge-users were common KT activities among immigrants, but they were involved in the entire research process only if they were hired as members of research teams. Most KT research among immigrants explored cancer screening and used a community-based participatory action research approach. Barriers and enablers usually came from researchers rather than from the community. There was little practice of evaluation and defined frameworks to conduct KT research among immigrants in Canada. CONCLUSION This study can help the researchers and other stakeholders of health and wellness of the immigrant population to identify appropriate KT research activities for immigrants and where KT research is required to facilitate the transfer of research knowledge into action.

Size Matters: Digital Social Networks and Language Change

Social networks play a role in language variation and change, and the social network theory has offered a powerful tool in modeling innovation diffusion. Networks are characterized by ties of varying strength which influence how novel information is accessed. It is widely held that weak-ties promote change, whereas strong ties lead to norm-enforcing communities that resist change. However, the model is primarily suited to investigate small ego networks, and its predictive power remains to be tested in large digital networks of mobile individuals. This article revisits the social network model in sociolinguistics and investigates network size as a crucial component in the theory. We specifically concentrate on whether the distinction between weak and strong ties levels in large networks over 100 nodes. The article presents two computational methods that can handle large and messy social media data and render them usable for analyzing networks, thus expanding the empirical and methodological basis from small-scale ethnographic observations. The first method aims to uncover broad quantitative patterns in data and utilizes a cohort-based approach to network size. The second is an algorithm-based approach that uses mutual interaction parameters on Twitter. Our results gained from both methods suggest that network size plays a role, and that the distinction between weak ties and slightly stronger ties levels out once the network size grows beyond roughly 120 nodes. This finding is closely similar to the findings in other fields of the study of social networks and calls for new research avenues in computational sociolinguistics.

Refugees Welcome? Online Hate Speech and Sentiments in Twitter in Spain during the Reception of the Boat Aquarius

High-profile events can trigger expressions of hate speech online, which in turn modifies attitudes and offline behavior towards stigmatized groups. This paper addresses the first path of this process using manual and computational methods to analyze the stream of Twitter messages in Spanish around the boat Aquarius (n = 24,254) before and after the announcement of the Spanish government to welcome the boat in June 2018, a milestone for asylum seekers acceptance in the EU and an event that was highly covered by media. It was observed that most of the messages were related to a few topics and had a generally positive sentiment, although a significant part of messages expressed rejection or hate—often supported by stereotypes and lies—towards refugees and migrants and towards politicians. These expressions grew after the announcement of hosting the boat, although the general sentiment of the messages became more positive. We discuss the theoretical, practical, and methodological implications of the study, and acknowledge limitations referred to the examined timeframe and to the preliminary condition of the conclusions.

Immigration as a Divisive Topic: Clusters and Content Diffusion in the Italian Twitter Debate

In this work, we apply network science to analyse almost 6 M tweets about the debate around immigration in Italy, collected between 2018 and 2019, when many related events captured media outlets’ attention. Our aim was to better understand the dynamics underlying the interactions on social media on such a delicate and divisive topic, which are the actors that are leading the discussion, and whose messages have the highest chance to reach out the majority of the accounts that are following the debate. The debate on Twitter is represented with networks; we provide a characterisation of the main clusters by looking at the highest in-degree nodes in each one and by analysing the text of the tweets of all the users. We find a strongly segregated network which shows an explicit interplay with the Italian political and social landscape, that however seems to be disconnected from the actual geographical distribution and relocation of migrants. In addition, quite surprisingly, the influencers and political leaders that apparently lead the debate, do not necessarily belong to the clusters that include the majority of nodes: we find evidence of the existence of a ‘silent majority’ that is more connected to accounts who expose a more positive stance toward migrants, while leaders whose stance is negative attract apparently more attention. Finally, we see that the community structure clearly affects the diffusion of content (URLs) by identifying the presence of both local and global trends of diffusion, and that communities tend to display segregation regardless of their political and cultural background. In particular, we observe that messages that spread widely in the two largest clusters, whose most popular members are also notoriously at the opposite sides of the political spectrum, have a very low chance to get visibility into other clusters.

Geographical fragmentation of the global network of Twitter communications

Understanding the geography of society represents a challenge for social and economic sciences. The recent availability of data from social media enables the observation of societies at a global scale. In this paper, we study the geographical structure of the Twitter communication network at the global scale. We find a complex structure where self-organized patches with clear cultural, historical, and administrative boundaries are manifested and first-world economies centralize information flows. These patches unveil world regions that are socially closer to each other with direct implications for processes of collective learning and identity creation.

Estimation of socioeconomic attributes from location information

Timely estimation of the distribution of socioeconomic attributes and their movement is crucial for academic as well as administrative and marketing purposes. In this study, assuming personal attributes affect human behavior and movement, we predict these attributes from location information. First, we predict the socioeconomic characteristics of individuals by supervised learning methods, i.e., logistic Lasso regression, Gaussian Naive Bayes, random forest, XGBoost, LightGBM, and support vector machine, using survey data we collected of personal attributes and frequency of visits to specific facilities, to test our conjecture. We find that gender, a crucial attribute, is as highly predictable from locations as from other sources such as social networking services, as done by existing studies. Second, we apply the model trained with the survey data to actual GPS log data to check the performance of our approach in a real-world setting. Though our approach does not perform as well as for the survey data, the results suggest that we can infer gender from a GPS log.

Health and well-being literacy initiatives focusing on immigrant communities: an environmental scan protocol to identify "what works and what does not"

INTRODUCTION

Most of the major cities in the developed western countries are characterized by an increasing multiculturalism brought by the immigrant population. The immigrant communities face challenges in the new environment with their health and wellness related unmet needs. It is imperative to find sustainable ways to empower these diverse communities to champion their health and wellness. Community-based health and wellness literacy initiatives (CBHWLI) focusing on immigrant communities can be an important step towards citizen empowerment in this regard. The aim of the present environmental scan is to identify the key factors that might impact a CBHWLI in immigrant communities in Canada in order to facilitate the process in practice and identify the competencies and training required for its implementation.

METHODS

This study will gather information from existing literature and online sources as well as will capture expert and lay perspectives on the factors that can impact the effectiveness and sustainability of CBHWLIs through conducting a comprehensive environmental scan: (i) a systematic scoping review of published literature and grey literature, (ii) a comprehensive Internet search, (iii) key informant interviews, and (iv) community consultation. Specific methodological and analytical frameworks will guide each step.

ETHICS AND DISSEMINATION

This study is the first step in establishing a practical base for developing CBHWLI implementation research. Once the initial findings have been generated, the second step will involve inviting experts to provide their input. We first plan to disseminate the results of our scoping review and Internet scan through meetings with key stakeholders, to be followed by journal publications and conference or workshop presentations. Ethical approval is not required for the scoping review or Internet scan; however, approval to conduct interviews with key informants and community consultations in the second stage of the study will be sought from the Conjoint Health Research Ethics Board.

Knowledge mobilisation in bridging community-practice-academia-policy through meaningful engagement: systematic integrative review protocol focusing on studies conducted on health and wellness among immigrant communities

INTRODUCTION

Though the importance of knowledge mobilisation has been established globally in health and wellness research, a certain degree of ambiguity remains regarding the meaning and extent of knowledge mobilisation activities and how they have been implemented. In this study, we aim to explore the different descriptions of knowledge mobilisation and the diverse ways mobilisation activities have been realised by different researchers working for the betterment of health and wellness of immigrant communities in their host countries.

METHODS AND ANALYSIS

We aimed to conduct an integrative review to organise the available literature describing knowledge mobilisation pertaining to health and wellness in immigrant communities. We will employ a comprehensive search, using appropriate search-terms, to identify relevant literature and will qualitatively synthesise the information toward fulfilling our objectives. Specific methodological and analytical frameworks related to the integrative review process will guide each step of the process. A librarian designed the systematic search of the academic and grey literature from database inception to December 2019. The databases include MEDLINE (Ovid), Embase, PsycINFO, PubMed, CINAHL and SocINDEX. For grey literature, we will conduct searches in AHS Insite, Google, Google Scholar, OAISter and government websites. A two-stage (title-abstract and full-text) screening will be conducted, including single-citation tracking and hand search of reference lists.

ETHICS AND DISSEMINATION

Ethical approval is not required for this review. We first plan to disseminate the results of our systematic review protocol through meetings with key stakeholders, followed by appropriate publications and presentations at applicable platforms. We also have opted for an integrated knowledge translation or community-engaged knowledge mobilisation approach where we have engaged with community-based citizen researchers from the inception of our research.

Community engagement with immigrant communities involving health and wellness research: a systematic review protocol towards developing a taxonomy of community engagement definitions, frameworks, and methods

INTRODUCTION

The importance of community engagement has been established globally in health and wellness research. A certain degree of ambiguity remains, however, regarding the meaning of community engagement, which term has been used for various purposes and implemented in various forms. In this study, we aimed to explore the different definitions of community engagement, discuss the various objectives that have been proposed and uncover the diverse ways this concept has been implemented among researchers working for the betterment of the health and wellness of immigrant communities in host countries.

METHODS AND ANALYSIS

Taxonomy is a process for classifying complex and multifaceted matters using logical conceptual domains and dimensions for clearer way of contextualising. We will develop a taxonomy to organise the available literature on community engagement in immigrant health and wellness research in a way that captures user knowledge and understanding of its various meanings and processes. Specific methodological and analytical frameworks for systematic review and taxonomy development will guide each step. We will conduct a comprehensive systematic search in relevant databases, from inception to December 2019, using appropriate keywords followed by snowball search (single-citation tracking, reference lists). Papers will be included if they fall within predefined inclusion criteria (seen as most likely informative on elements pertaining to community engagement) and are written in English, regardless of design (conceptual, qualitative and quantitative). Two reviewers will independently employ two-stage screening (title-abstract screening followed by screening of the full text to determine inclusion). Finally, information that helps to develop taxonomy of the concept and practice of community engagement will be abstracted and used towards taxonomy development, where different levels of stakeholder research team members will be involved.

ETHICS AND DISSEMINATION

Ethical approval is not required for this systematic review. We have opted for an integrated knowledge translation or a community-engaged knowledge mobilisation approach where we are engaged with community-based citizen researchers from the inception of our programme. We plan to disseminate the results of our review through meetings with key stakeholders, followed by journal publications and presentations at applicable platforms.

Migrant mobility flows characterized with digital data

Monitoring migration flows is crucial to respond to humanitarian crisis and to design efficient policies. This information usually comes from surveys and border controls, but timely accessibility and methodological concerns reduce its usefulness. Here, we propose a method to detect migration flows worldwide using geolocated Twitter data. We focus on the migration crisis in Venezuela and show that the calculated flows are consistent with official statistics at country level. Our method is versatile and far-reaching, as it can be used to study different features of migration as preferred routes, settlement areas, mobility through several countries, spatial integration in cities, etc. It provides finer geographical and temporal resolutions, allowing the exploration of issues not contemplated in official records. It is our hope that these new sources of information can complement official ones, helping authorities and humanitarian organizations to better assess when and where to intervene on the ground.

Entropy as a Measure of Attractiveness and Socioeconomic Complexity in Rio de Janeiro Metropolitan Area

Defining and measuring spatial inequalities across the urban environment remains a complex and elusive task which has been facilitated by the increasing availability of large geolocated databases. In this study, we rely on a mobile phone dataset and an entropy-based metric to measure the attractiveness of a location in the Rio de Janeiro Metropolitan Area (Brazil) as the diversity of visitors’ location of residence. The results show that the attractiveness of a given location measured by entropy is an important descriptor of the socioeconomic status of the location, and can thus be used as a proxy for complex socioeconomic indicators.

Human migration: the big data perspective

How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and ideas. The first phase includes the journey, and we study migration flows and stocks, providing examples where big data can have an impact. The second phase discusses the stay, i.e. migrant integration in the destination country. We explore various data sets and models that can be used to quantify and understand migrant integration, with the final aim of providing the basis for the construction of a novel multi-level integration index. The last phase is related to the effects of migration on the source countries and the return of migrants.

Monitoring of the Venezuelan exodus through Facebook's advertising platform

Venezuela is going through the worst economical, political and social crisis in its modern history. Basic products like food or medicine are scarce and hyperinflation is combined with economic depression. This situation is creating an unprecedented refugee and migrant crisis in the region. Governments and international agencies have not been able to consistently leverage reliable information using traditional methods. Therefore, to organize and deploy any kind of humanitarian response, it is crucial to evaluate new methodologies to measure the number and location of Venezuelan refugees and migrants across Latin America. In this paper, we propose to use Facebook's advertising platform as an additional data source for monitoring the ongoing crisis. We estimate and validate national and sub-national numbers of refugees and migrants and break-down their socio-economic profiles to further understand the complexity of the phenomenon. Although limitations exist, we believe that the presented methodology can be of value for real-time assessment of refugee and migrant crises world-wide.

The future of cystic fibrosis care: a global perspective

The past six decades have seen remarkable improvements in health outcomes for people with cystic fibrosis, which was once a fatal disease of infants and young children. However, although life expectancy for people with cystic fibrosis has increased substantially, the disease continues to limit survival and quality of life, and results in a large burden of care for people with cystic fibrosis and their families. Furthermore, epidemiological studies in the past two decades have shown that cystic fibrosis occurs and is more frequent than was previously thought in populations of non-European descent, and the disease is now recognised in many regions of the world. The Lancet Respiratory Medicine Commission on the future of cystic fibrosis care was established at a time of great change in the clinical care of people with the disease, with a growing population of adult patients, widespread genetic testing supporting the diagnosis of cystic fibrosis, and the development of therapies targeting defects in the cystic fibrosis transmembrane conductance regulator (CFTR), which are likely to affect the natural trajectory of the disease. The aim of the Commission was to bring to the attention of patients, health-care professionals, researchers, funders, service providers, and policy makers the various challenges associated with the changing landscape of cystic fibrosis care and the opportunities available for progress, providing a blueprint for the future of cystic fibrosis care. The discovery of the CFTR gene in the late 1980s triggered a surge of basic research that enhanced understanding of the pathophysiology and the genotype-phenotype relationships of this clinically variable disease. Until recently, available treatments could only control symptoms and restrict the complications of cystic fibrosis, but advances in CFTR modulator therapies to address the basic defect of cystic fibrosis have been remarkable and the field is evolving rapidly. However, CFTR modulators approved for use to date are highly expensive, which has prompted questions about the affordability of new treatments and served to emphasise the considerable gap in health outcomes for patients with cystic fibrosis between high-income countries, and low-income and middle-income countries (LMICs). Advances in clinical care have been multifaceted and include earlier diagnosis through the implementation of newborn screening programmes, formalised airway clearance therapy, and reduced malnutrition through the use of effective pancreatic enzyme replacement and a high-energy, high-protein diet. Centre-based care has become the norm in high-income countries, allowing patients to benefit from the skills of expert members of multidisciplinary teams. Pharmacological interventions to address respiratory manifestations now include drugs that target airway mucus and airway surface liquid hydration, and antimicrobial therapies such as antibiotic eradication treatment in early-stage infections and protocols for maintenance therapy of chronic infections. Despite the recent breakthrough with CFTR modulators for cystic fibrosis, the development of novel mucolytic, anti-inflammatory, and anti-infective therapies is likely to remain important, especially for patients with more advanced stages of lung disease. As the median age of patients with cystic fibrosis increases, with a rapid increase in the population of adults living with the disease, complications of cystic fibrosis are becoming increasingly common. Steps need to be taken to ensure that enough highly qualified professionals are present in cystic fibrosis centres to meet the needs of ageing patients, and new technologies need to be adopted to support communication between patients and health-care providers. In considering the future of cystic fibrosis care, the Commission focused on five key areas, which are discussed in this report: the changing epidemiology of cystic fibrosis (section 1); future challenges of clinical care and its delivery (section 2); the building of cystic fibrosis care globally (section 3); novel therapeutics (section 4); and patient engagement (section 5). In panel 1, we summarise key messages of the Commission. The challenges faced by all stakeholders in building and developing cystic fibrosis care globally are substantial, but many opportunities exist for improved care and health outcomes for patients in countries with established cystic fibrosis care programmes, and in LMICs where integrated multidisciplinary care is not available and resources are lacking at present. A concerted effort is needed to ensure that all patients with cystic fibrosis have access to high-quality health care in the future.

Mapping the Americanization of English in space and time

As global political preeminence gradually shifted from the United Kingdom to the United States, so did the capacity to culturally influence the rest of the world. In this work, we analyze how the world-wide varieties of written English are evolving. We study both the spatial and temporal variations of vocabulary and spelling of English using a large corpus of geolocated tweets and the Google Books datasets corresponding to books published in the US and the UK. The advantage of our approach is that we can address both standard written language (Google Books) and the more colloquial forms of microblogging messages (Twitter). We find that American English is the dominant form of English outside the UK and that its influence is felt even within the UK borders. Finally, we analyze how this trend has evolved over time and the impact that some cultural events have had in shaping it.