Hasil untuk "Demography. Population. Vital events"

Martin Kolk, J. Tilley, Emma von Essen et al.

We examine the prevalence of gender transitions in Sweden over time and document the sociodemographic characteristics of people transitioning in different periods. Using administrative data covering the transgender population from 1973 through 2020, we analyze two common events in a gender transition: the earliest diagnosis of gender incongruence and the change of legal gender. Our research note presents three main findings. First, the measured prevalence rates of diagnoses and legal gender changes are relatively low in all periods, although they have increased substantially since the early 2010s. Second, the recent increase in transition prevalence is most pronounced among people in early adulthood; in particular, young transgender men drive an increase in overall transition rates through 2018, followed by moderate declines in 2019 and 2020. Third, transgender men and women have substantially lower socioeconomic outcomes than cisgender men and women, regardless of the age at which they transition or the historical period. They are also considerably less likely to be in a legal union or reside with children. These findings highlight the continued economic and social vulnerability of the transgender population.

Pablo Corcho-Caballero, Yago Ascasibar, Daniel Jiménez-López

Stellar population synthesis is a crucial methodology in astrophysics, enabling the interpretation of the integrated light of galaxies and stellar clusters. By combining empirical and/or theoretical libraries of the spectral energy distribution emitted by simple stellar populations (SSPs) with models of the star formation history (SFH) and chemical evolution, population synthesis facilitates the estimation of essential galaxy properties, such as total stellar mass, star formation rate, mass-weighted age and metallicity, etc. The Population Synthesis Toolkit (PST) is a Python library that offers a comprehensive and flexible framework for stellar population synthesis. Its main goal is to compute composite spectra using different galaxy evolution models and SSP libraries with ease and efficiency. It incorporates additional effects, such as cosmic redshift and dust extinction, and it computes several observable quantities derived from the spectra, including broadband photometric fluxes and equivalent widths.

Javier López-de-la-Cruz, Susana Merchán, Felipe Rivero et al.

In this paper we investigate the asymptotic behavior of some SIR models incorporating demography, bounded random transmission coefficient and a time-dependent vaccination strategy targeting the susceptible population. In this setting, we establish the existence and uniqueness of non-negative global solution of the models and derive conditions under which either the disease is eradicated or becomes endemic. In addition, the theoretical results are further illustrated by several numerical simulations.

Eleni Domzaridou, Ben Lacey, Naomi Allen et al.

Objectives To develop a resource that maps health outcomes across coding schemas in linked administrative data in UK Biobank, addressing the challenge of identifying equivalent outcomes from multiple sources. Our approach minimised the loss of clinical detail, a common limitation in such efforts, to enhance its utility for health research. Methods UK Biobank is a prospective cohort study of ~500,000 adults, recruited between 2006-10, with follow up for health outcomes through linkage with administrative health data. Clinical coding schemas include Read Version 2 (Read2) and Clinical Terms Version 3 (CTV3) from primary care, and International Classification of Diseases (ICD) 9th and 10th editions (ICD-9 and ICD-10) from secondary care, cancer registries and death records; self-reported conditions were also reported at recruitment. We reviewed existing mapping resources and, with clinical support, mapped clinical codes in different schemas to 4-digit ICD-10 to provide detailed clinical information using a single internationally-recognised schema. Results We processed data from 230,096 participants with primary care records, 442,267 with secondary care records, 40,447 with death records, and 397,063 with self-reported data. We successfully mapped to 81% of Read2 codes (N = 12,448), 93% of CTV3 (24,188), 92% of ICD-9 (3,060), and 100% of self-reported (509) to ICD-10 codes. Although existing resources frequently allowed a single code to be mapped to a single ICD-10 code (94% of the mapped codes for Read2, 58% of CTV3, and 79% of ICD-9), the remaining codes require extensive clinical review, which is ongoing. The conversion increased the granularity of health outcomes by 5.8 times from 2,006 3-digit ICD-10 codes to 11,625 4-digit ICD-10 codes. The most common ICD-10 codes included those related to musculoskeletal diseases (24%). Conclusion The increased granularity of ICD coding enhances the research potential of UK Biobank data, enabling precise outcome definitions and detailed comparisons with other healthcare datasets. The enhanced mappings revealed underrepresented and nuanced outcomes, improving subtyping of conditions, and supporting robust comparisons with external datasets using internationally recognised coding standards.

Cintami Farmawati, Siti Mumun Muniroh, Solihah Hayeesama-ae

Psychological resilience is an important factor in determining the mental well-being of migrant workers. Migrant workers are people who migrate or have migrated from one country to another who will be employed by anyone other than themselves. This study aims to determine the factors which influence the psychological resilience of migrant workers in Thailand, and how they adapt to challenges in the new environment. This study is a qualitative study. The subjects in the study were three migrant workers in Thailand. Data collection methods used were interviews, observation and documentation. Data analysis used was data reduction, data presentation, and drawing conclusions. The results of the study showed that the factors influencing the psychological resilience of migrant workers in Thailand can be grouped into two, specifically internal factors and external factors. These internal factors are spirituality, self-efficacy, optimism, self-esteem, hope, and hardiness. External factors are social and family support. Meanwhile, the description of the adaptation of migrant workers in Thailand to the challenges in the new environment can be grouped into three strategies:  social adaptation, economic adaptation and cultural adaptation.

Geeling Chau, Christopher Wang, Sabera Talukder et al.

We present a self-supervised framework that learns population-level codes for arbitrary ensembles of neural recordings at scale. We address key challenges in scaling models with neural time-series data, namely, sparse and variable electrode distribution across subjects and datasets. The Population Transformer (PopT) stacks on top of pretrained temporal embeddings and enhances downstream decoding by enabling learned aggregation of multiple spatially-sparse data channels. The pretrained PopT lowers the amount of data required for downstream decoding experiments, while increasing accuracy, even on held-out subjects and tasks. Compared to end-to-end methods, this approach is computationally lightweight, while achieving similar or better decoding performance. We further show how our framework is generalizable to multiple time-series embeddings and neural data modalities. Beyond decoding, we interpret the pretrained and fine-tuned PopT models to show how they can be used to extract neuroscience insights from large amounts of data. We release our code as well as a pretrained PopT to enable off-the-shelf improvements in multi-channel intracranial data decoding and interpretability. Code is available at https://github.com/czlwang/PopulationTransformer.

Юлия Александровна Коршунова

В данной статье рассматривается феномен стигматизации людей, живущих с ВИЧ, и его социально-экономические риски на примере студенческой молодёжи. Автором были проведены глубинные интервью среди студентов медицинских и не медицинских российских вузов и полуформализованный экспертный опрос. В результате глубинных интервью были выявлены стигматизирующие установки у студенческой молодёжи по отношению к людям с ВИЧ-позитивным статусом, а также проанализирована информированность студентов в области заболевания. В исследовательской работе проведено сравнение студентов медицинских и не медицинских направлений обучения. По итогам экспертного опроса была оценена эффективность мер по борьбе со стигматизацией ВИЧ в России: информирование населения по вопросам ВИЧ органами здравоохранения, средствами массовой информации; информирование детей в школах; проведение различных научных исследований по вопросам ВИЧ; международное сотрудничество и обмен информацией в рамках борьбы с ВИЧ; защита людей с ВИЧ от дискриминации на законодательном уровне. Эксперты оценили необходимость внедрения дополнительных мер, реализуемых в зарубежных странах. Были разработаны практические рекомендации по снижению социально-экономических рисков от стигматизации ВИЧ-инфицированных для Министерства просвещения, Министерства здравоохранения, Федерального собрания.

Namneet Sandhu, Bing Li, Danielle A Southern et al.

Introduction Coding has become burdensome to healthcare systems due to patient complexity and resource requirements. In Alberta, Intelligent Medical Objects (IMO), an interface terminology mapping product, is integrated within the new province-wide Clinical Information System, named Connect Care (CC), to support documentation by clinicians and map clinical terminologies to ICD-10. This study evaluates comparability of terminologies mapped ICD-10 codes to the ICD-10 codes in DAD. Approach We conducted a retrospective analysis by linking acute care hospital DAD with CC between April 2021 and December 2023. The primary outcome was the level of agreement between ‘hospital problem list’ of CC and DAD for ICD-10-CA codes at a 3-digit level. The number of diagnoses and rate of unspecified codes were also compared. The outcome measures were stratified by physician specialty, hospital type and location, and length-of-stay (LOS). Results A total of 498,834 unique hospital records were linked. The average level of agreement between CC and DAD at 3-digit level of ICD-10-CA code was 43.4%. The average number of diagnoses captured in CC (3.91) was slightly lower than DAD (4.06), and the average rate of unspecified codes was higher in CC (26.4%) compared to DAD (23.0%). The level of agreement varied by specialty and length-of-stay with specialties with more complex patients and longer lengths-of-stay having the lowest agreement (43% for generalists and internal medicine and 33% for LOS >3 months). Conclusion Level of agreement between CC and DAD for ICD-10 data was identified as low, indicating significant disparities between terminology mappings and the coding process.

Marta Sjeničić, Marko Milenković, Sofija Nikollić Popadić

Neformalni negovatelj je svaka osoba koja pruža negu – obično bez naknade – drugoj osobi sa hroničnom bolešću, invaliditetom ili drugom potrebom za dugotrajnom negom. Neformalni negovatelji su potpuno neprepoznati u pravnom sistemu Republike Srbije. Shodno tome, u Srbiji ne postoje zvanični podaci o broju neformalnih negovatelja. Postoje brojni aspekti neformalne brige koji predstavljaju izazov. Narušena ravnoteža između poslovnog i privatnog života može uticati na sposobnost neformalnih negovatelja da učestvuju na tržištu rada i održavaju društvene kontakte. Ovo može dalje dovesti do socijalne isključenosti i rizika od siromaštva. Konačno, zdravlje i dobrobit neformalnih negovatelja takođe mogu biti pogođeni. COVID-19 kriza dodatno je  razotkrila fundamentalne nedostatke u sistemu zbrinjavanja starijih osoba i slabosti u regulisanju pružanja neformalne nege. Koristeći ograničene raspoložive podatke o neformalnoj nezi u Srbiji, komparativne podatke i primere o položaju neformalnih negovatelja, članak nastoji da prevashodno doprinese otvaranju društvene debate o položaju neformalnih negovatelja, potencijalnoj formalizaciji njihovog položaja i ponudi preporuke za unapređenje položaja, a pre svega kada se radi o nezi starije populacije.

R. A. Wright, Dieter Mueller-Dombois

Abstract: The powerful El Niño of 1982–1983 precipitated a severe drought in the Hawai‘i Islands and was followed by an unusually dry La Niña year. Our 1983/1984 study of the early successional demography of five shrub and one tree species on volcanic cinder, Big Island of Hawai‘i, inadvertently coincided with the end of the ENSO drought. Life stage structure analyses showed a short-term dieback in the populations but then rapid population recovery. A new demographic tool, population flow diagram analysis, was developed as an aid to interpret the temporal dynamics of life stage structure. Crown size demographic depletion models were also used to describe the species’ vital statistics. The apparent dieback was shown to be a temporary dormancy response to the El Niño/La Niña-induced drought rather than a true case of dieback related to cohort senescence. As precipitation levels returned to normal the populations were rejuvenated by the revival of senescent and dormant individuals. The species showed robust demographic resilience to an unusually powerful drought. The populations of the Devastation Area appear to be members of a non-equilibrium community but there was evidence of a shift towards equilibrium. Climate change may intensify ENSO droughts in Hawai‘i and could cause longer-term diebacks of these populations and possibly their extirpation, affecting the rate and nature of primary succession on volcanic cinder ecosystems. Population viability modelling could determine if the species are likely to face extirpation from climate-change-driven alterations in the historic pattern of El Niño/La Niña events.

Omar Lenzi, K. Grossenbacher, S. Zumbach et al.

In natural populations, vital rates such as survival and reproduction are influenced by a complex interplay of abiotic conditions (e.g., environment), density dependence, and individual factors (e.g., phenotypic traits). Studies at the extremes of species distributions, particularly high elevations, offer unique insights due to the intensified effects of abiotic stressors, which can amplify both direct and indirect effects on vital rates. In this study, we focus on a high‐elevation population of the common toad (Bufo bufo) located near the upper limit of its elevational range in the Swiss Alps. This setting provides a critical context for examining how extreme abiotic conditions interact with density dependence and individual factors to influence life history traits. Utilizing 28 years of capture–mark–recapture data and individual body size measurements from nearly 2500 toads, we applied in a Bayesian statistical framework a Cormack–Jolly–Seber model for estimating male survival probabilities, and a multistate model for assessing female survival and breeding probabilities, alongside sex‐specific growth curves. Our analysis indicates that survival probabilities are significantly impacted by interactions between abiotic conditions such as the active season length and temperature at emergence from hibernation, density dependence, and individual phenotypic traits such as body size. The breeding patterns of females showed a biennial cycle, with temperature at hibernation emergence influencing the likelihood of skipping breeding events and density affecting the resumption of breeding. These results highlight the role of abiotic conditions and density in shaping physiological and reproductive strategies in a high‐stress ecological niche. Moreover, we uncovered indications of indirect effects, where both abiotic conditions and density potentially affect asymptotic growth and thus survival, mediated through changes in body size. Our findings illustrate the complex dynamics at play in high‐elevation populations and the importance of long‐term, individual‐based data in studying these processes. This study underscores the value of integrating multiple sources of variation to understand population dynamics comprehensively, particularly in understudied, extreme environments where traditional ecological models may not fully capture the nuanced interdependencies of natural systems.

Zack W. Almquist, Courtney Allen, Ihsan Kahveci

Recent developments in computing, data entry and generation, and analytic tools have changed the landscape of modern demography and health research. These changes have come to be known as computational demography, big data, and precision health in the field. This emerging interdisciplinary research comprises social scientists, physical scientists, engineers, data scientists, and disease experts. This work has changed how we use administrative data, conduct surveys, and allow for complex behavioral studies via big data (electronic trace data from mobile phones, apps, etc.). This chapter reviews this emerging field's new data sources, methods, and applications.

Ansgar Hudde, Henriette Engelhardt

<b>Objective</b>: A comprehensive and thorough investigation of the key trends in family patterns in Western Germany. <b>Methods</b>: Descriptive analyses of educational differences in marital status, cohabitation, partnerlessness, and children in the household in Western Germany from 1976 to 2019. We analyze unique data from the German Microcensus with information from more than 1.7 million individuals. <b>Results</b>: In the 1970s, men with higher education were moderately more likely to live with a partner and be married, and less likely to be divorced. The reverse was mainly the case for women. Over time, higher education levels for men and women became increasingly associated with living with a partner, being married, and living with children; lower levels of education became increasingly associated with divorce, partnerlessness, and single parenthood. Today, men with lower levels of education are least likely to live with a partner, be married, or have children in the household. Women with lower education levels are most likely to be single parents. <b>Conclusions</b>: Education is turning more and more into a generalized life resource: those with higher education are not only the winners in the labor market but are also increasingly more likely to achieve those partnership and family outcomes to which the majority of young people aspire - a stable partnership and children. <b>Contribution</b>: This 'big picture' analysis deepens our understanding of changes in family-related social inequalities in Germany. Analyses based on high-quality data have not been available for Germany and can serve as bases for future research at the granular level.

Rowena Griffiths, Laura Herbert, Ashley Akbari et al.

Introduction Critical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery. A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research. Objective To describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care. Method To demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales. Results When applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) had an emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission. Conclusion This methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways.

Piotr Teodorowski, Saiqa Ahmed, Naheed Tahir et al.

Objectives Public involvement and engagement have been growing within big data research. However, seldom heard voices such as migrant and ethnic minorities communities are often underrepresented. This study explored how Polish and South Asian communities in the United Kingdom could be better included in public involvement and engagement activities. Approach We conducted semi-structured interviews with Polish (n=20) and South Asians (n=20) to elicit their views on big data research, public involvement and engagement. We focused on Polish and South Asian communities as they represent some of the United Kingdom’s largest migrant and ethnic minority groups. Data were analysed using inductive thematic analysis. Public advisors were involved in the analysis. They and one of the researchers come from ethnic minority and offered insider insight into participants' perspectives and thus allowing us to unpick the complexity of experiences and backgrounds. Results The majority of participants were willing to become involved or engaged in big data research. However, we found there were multiple barriers to involvement, these included: language (especially for those for whom English is the second language); use of jargon by researchers; time restrictions and unfamiliarity with big data or public involvement. Some participants questioned how much migrants could be involved when they were only in the United Kingdom on a temporary basis. The participants made recommendations for how researchers can mitigate these barriers. Awareness-raising activities would allow people to expand their understanding and build their confidence when speaking about big data research in a second language. Participants spoke of the need for researchers to work more closely with local communities, especially with local gatekeepers. Conclusions The results indicate that there is no ‘right’ way to involve and engage seldom heard communities around big data research. Researchers need to engage with communities, establish trust and develop a long-lasting relationships. These partnerships should move beyond single projects and aim to benefit both researchers and seldom heard communities.

Einar Bjarki Gunnarsson, Kevin Leder, Jasmine Foo

The site frequency spectrum (SFS) is a popular summary statistic of genomic data. While the SFS of a constant-sized population undergoing neutral mutations has been extensively studied in population genetics, the rapidly growing amount of cancer genomic data has attracted interest in the spectrum of an exponentially growing population. Recent theoretical results have generally dealt with special or limiting cases, such as considering only cells with an infinite line of descent, assuming deterministic tumor growth, or taking large-time or large-population limits. In this work, we derive exact expressions for the expected SFS of a cell population that evolves according to a stochastic branching process, first for cells with an infinite line of descent and then for the total population, evaluated either at a fixed time (fixed-time spectrum) or at the stochastic time at which the population reaches a certain size (fixed-size spectrum). We find that while the rate of mutation scales the SFS of the total population linearly, the rates of cell birth and cell death change the shape of the spectrum at the small-frequency end, inducing a transition between a $1/j^2$ power-law spectrum and a $1/j$ spectrum as cell viability decreases. We show that this insight can in principle be used to estimate the ratio between the rate of cell death and cell birth, as well as the mutation rate, using the site frequency spectrum alone. Although the discussion is framed in terms of tumor dynamics, our results apply to any exponentially growing population of individuals undergoing neutral mutations.

Francesca Ronchini, Romain Serizel, Nicolas Turpault et al.

Detection and Classification Acoustic Scene and Events Challenge 2021 Task 4 uses a heterogeneous dataset that includes both recorded and synthetic soundscapes. Until recently only target sound events were considered when synthesizing the soundscapes. However, recorded soundscapes often contain a substantial amount of non-target events that may affect the performance. In this paper, we focus on the impact of these non-target events in the synthetic soundscapes. Firstly, we investigate to what extent using non-target events alternatively during the training or validation phase (or none of them) helps the system to correctly detect target events. Secondly, we analyze to what extend adjusting the signal-to-noise ratio between target and non-target events at training improves the sound event detection performance. The results show that using both target and non-target events for only one of the phases (validation or training) helps the system to properly detect sound events, outperforming the baseline (which uses non-target events in both phases). The paper also reports the results of a preliminary study on evaluating the system on clips that contain only non-target events. This opens questions for future work on non-target subset and acoustic similarity between target and non-target events which might confuse the system.

Nélida Redondo, Agustín Benencia

Se presentan resultados de una investigación amplia sobre las trayectorias finales de la vida y los servicios sociosanitarios en domicilio en el Área Metropolitana de la Ciudad de Buenos Aires*. La investigación longitudinal prospectiva produjo datos primarios sobre la composición y el gasto en salud de los hogares de mayores con morbilidades crónicas avanzadas que recibieron asistencia en domicilio durante el período agosto 2014-diciembre 2015. El fallecimiento o la sobrevivencia mostraron asociación estadística con el tipo de hogar en el que las personas residían, así como con los gastos familiares. El aumento del grado de dependencia también se asoció estadísticamente con los gastos. La investigación proporciona información sobre los cuidadores familiares, destacándose que a medida que aumenta la edad de éstos aumenta la participación masculina en el cuidado y ofrece evidencia empírica para orientar las políticas de cuidados de larga duración en América latina, incluyendo en ellos los cuidados paliativos.

José Leonardo Montealegre Quijano, Julián Alonso Garzón Quiroga

En 2018, la Organización Mundial de la Salud informó que los accidentes de tránsito se han convertido en un problema de salud pública, con muertes anuales estimadas en 1.2 millones de personas. En Colombia, constituyen la segunda causa de muerte en la población, sólo después de las derivadas de enfermedades crónicas. En la ciudad de Ibagué, seis de cada 100000 habitantes mueren en las calles al año. En este trabajo estudiamos los puntos críticos de accidentabilidad de la ciudad, y encontramos como las causas principales las fallas mecánicas, así como las imprudencias y el estado de embriaguez de los conductores; asimismo, la inapropiada toma de decisiones y el desconocimiento de la forma de acceder a una glorieta (round point) se constituyen en un común denominador de accidentalidad.

Viet Dac Lai, Franck Dernoncourt, Thien Huu Nguyen

Current event detection models under super-vised learning settings fail to transfer to newevent types. Few-shot learning has not beenexplored in event detection even though it al-lows a model to perform well with high gener-alization on new event types. In this work, weformulate event detection as a few-shot learn-ing problem to enable to extend event detec-tion to new event types. We propose two novelloss factors that matching examples in the sup-port set to provide more training signals to themodel. Moreover, these training signals can beapplied in many metric-based few-shot learn-ing models. Our extensive experiments on theACE-2005 dataset (under a few-shot learningsetting) show that the proposed method can im-prove the performance of few-shot learning