Hasil untuk "Demography. Population. Vital events"

Federica Becca, Albert Esteve

BACKGROUND: It is common for young adults in Mexico to coreside with own parents or other extended family members when forming the first partnership or becoming a parent/single parent. This practice has scarcely been studied in the literature and yet plays a very relevant role in understanding transitions to adulthood in the Latin American context. OBJECTIVE: This study explores whether young Mexicans realize family transitions (first partnership, parenthood, and single motherhood) within an extended household (‘family-anchored’ transitions), emphasizing the role of family support during life course transitions and its stability across cohorts. METHODS: Leveraging longitudinal data from the 2017 Retrospective Demographic Survey (EDER) for cohorts born between 1962 and 1987 (N = 13,020), we analyze whether family transitions (first partnership, first parenthood within partnership, and first single motherhood) involve a shift from a nuclear to an extended household. Using multivariate logistic regressions, we assess the socioeconomic and demographic profile associated with family-anchored transitions. RESULTS: Around 42% of women and 32% of men anchor their transition to first partnership and single motherhood in an extended household. Younger adults from recent cohorts, low-SES families, and with lower education have higher odds of experiencing family-anchored transitions to first partnership and parenthood, whereas anchored transitions to single motherhood is more likely for women from younger cohorts and high-SES backgrounds. CONTRIBUTION: This research contributes to the understanding of the critical role of family support during vulnerable life stages in Mexico, and how anchoring family transitions in extended households represents a common strategy across Mexican society.

Hollie Henderson, Sally Bridges, Maria Bryant et al.

Introduction Priority setting with patients, public and professionals is essential for research utilising routinely collected data, as this ensures data are being used in the public interest. However, it is challenging to identify research priorities that are relevant to a wide range of local stakeholders and can be addressed with routinely collected data. Objectives To describe and present the results of a priority setting exercise aiming to identify research priorities for Born in Bradford for All (BiB4All), a routine data linkage cohort of mothers and babies born in Bradford, a city in the north of England. Methods We developed a two-hour online workshop to engage a range of stakeholders across Bradford, including parents, early years practitioners, commissioners, and service providers. The workshop method combined elements of existing priority setting approaches to ensure priorities were identified in an inclusive, timely and deliberative way, and supported stakeholders to develop their understanding of using linked routine data for research. Results The workshop identified seventeen important and urgent research priorities around child and maternal health for research with locally linked routine data. Key topic areas included maternal and infant mental health, the long-term impact of the Covid-19 pandemic on maternal and child health outcomes, inequalities in access to services, and infant feeding experiences. Conclusions The identified research priorities have been shared widely amongst interested networks and have shaped the BiB4All research agenda, demonstrating the feasibility of the stakeholder engagement method. They also have important implications for policy and practice. For policy, they provide an understanding of the key issues faced by local communities, which can steer policy priorities and investment in evidence generation. For practice, involvement in the workshop has generated a greater understanding of how local service data can be used for research and to inform improvements to service delivery.

Haochen Li, Di Geng

Events describe the state changes of entities. In a document, multiple events are connected by various relations (e.g., Coreference, Temporal, Causal, and Subevent). Therefore, obtaining the connections between events through Event-Event Relation Extraction (ERE) is critical to understand natural language. There are two main problems in the current ERE works: a. Only embeddings of the event triggers are used for event feature representation, ignoring event arguments (e.g., time, place, person, etc.) and their structure within the event. b. The interconnection between relations (e.g., temporal and causal relations usually interact with each other ) is ignored. To solve the above problems, this paper proposes a jointly multiple ERE framework called GraphERE based on Graph-enhanced Event Embeddings. First, we enrich the event embeddings with event argument and structure features by using static AMR graphs and IE graphs; Then, to jointly extract multiple event relations, we use Node Transformer and construct Task-specific Dynamic Event Graphs for each type of relation. Finally, we used a multi-task learning strategy to train the whole framework. Experimental results on the latest MAVEN-ERE dataset validate that GraphERE significantly outperforms existing methods. Further analyses indicate the effectiveness of the graph-enhanced event embeddings and the joint extraction strategy.

Maria Zafeiri, Georgios Evangelidis, Emmanouil Psarakis

In this paper, an event-based tracker is presented. Inspired by recent advances in asynchronous processing of individual events, we develop a direct matching scheme that aligns spatial distributions of events at different times. More specifically, we adopt the Enhanced Correlation Coefficient (ECC) criterion and propose a tracking algorithm that computes a 2D motion warp per single event, called event-ECC (eECC). The complete tracking of a feature along time is cast as a \emph{single} iterative continuous optimization problem, whereby every single iteration is executed per event. The computational burden of event-wise processing is alleviated through a lightweight version that benefits from incremental processing and updating scheme. We test the proposed algorithm on publicly available datasets and we report improvements in tracking accuracy and feature age over state-of-the-art event-based asynchronous trackers.

Olawale F. Ayilara, Robert W. Platt, Matt Dahl et al.

Introduction Administrative health records (AHRs) are used to conduct population-based post-market drug safety and comparative effectiveness studies to inform healthcare decision making. However, the cost of data extraction, and the challenges associated with privacy and securing approvals can make it challenging for researchers to conduct methodological research in a timely manner using real data. Generating synthetic AHRs that reasonably represent the real-world data are beneficial for developing analytic methods and training analysts to rapidly implement study protocols. We generated synthetic AHRs using two methods and compared these synthetic AHRs to real-world AHRs. We described the challenges associated with using synthetic AHRs for real-world study. Methods The real-world AHRs comprised prescription drug records for individuals with healthcare insurance coverage in the Population Research Data Repository (PRDR) from Manitoba, Canada for the 10-year period from 2008 to 2017. Synthetic data were generated using the Observational Medical Dataset Simulator II (OSIM2) and a modification (ModOSIM). Synthetic and real-world data were described using frequencies and percentages. Agreement of prescription drug use measures in PRDR, OSIM2 and ModOSIM was estimated with the concordance coefficient. Results The PRDR cohort included 169,586,633 drug records and 1,395 drug types for 1,604,734 individuals. Synthetic data for 1,000,000 individuals were generated using OSIM2 and ModOSIM. Sex and age group distributions were similar in the real-world and synthetic AHRs. However, there were significant differences in the number of drug records and number of unique drugs per person for OSIM2 and ModOSIM when compared with PRDR. For the average number of days of drug use, concordance with the PRDR was 16% (95% confidence interval [CI]: 12%-19%) for OSIM2 and 88% (95% CI: 87%-90%) for ModOSIM. Conclusions ModOSIM data were more similar to PRDR than OSIM2 data on many measures. Synthetic AHRs consistent with those found in real-world settings can be generated using ModOSIM. Synthetic data will benefit rapid implementation of methodological studies and data analyst training.

Rudolf Frühwirth, Winfried Mitaroff

The paper addresses general aspects of experimental data analysis, dealing with the separation of ``signal vs. background''. It consists of two parts. Part I is a tutorial on statistical event classification, Bayesian inference, and test optimization. Aspects of the base data sample if being created by Poisson processes are discussed, and a method for estimating the unknown numbers of signal and background events is presented. Data quality of the selected events sample is assessed by the expected purity and background contamination. Part II contains a rigorous statistical analysis of the methods discussed in Part I. Both Bayesian and frequentist estimators of the unknown signal/background content are investigated. The estimates and their stochastic uncertainties are calculated for various conjugate priors in the Bayesian case, and for three choices of the virtual parent population in the frequentist case.

Alexander Shmakov, Alejandro Yankelevich, Jianming Bian et al.

The complex events observed at the NOvA long-baseline neutrino oscillation experiment contain vital information for understanding the most elusive particles in the standard model. The NOvA detectors observe interactions of neutrinos from the NuMI beam at Fermilab. Associating the particles produced in these interaction events to their source particles, a process known as reconstruction, is critical for accurately measuring key parameters of the standard model. Events may contain several particles, each producing sparse high-dimensional spatial observations, and current methods are limited to evaluating individual particles. To accurately label these numerous, high-dimensional observations, we present a novel neural network architecture that combines the spatial learning enabled by convolutions with the contextual learning enabled by attention. This joint approach, TransformerCVN, simultaneously classifies each event and reconstructs every individual particle's identity. TransformerCVN classifies events with 90\% accuracy and improves the reconstruction of individual particles by 6\% over baseline methods which lack the integrated architecture of TransformerCVN. In addition, this architecture enables us to perform several interpretability studies which provide insights into the network's predictions and show that TransformerCVN discovers several fundamental principles that stem from the standard model.

Arman Oganisian, Anthony Girard, Jon A. Steingrimsson et al.

Observational studies of recurrent event rates are common in biomedical statistics. Broadly, the goal is to estimate differences in event rates under two treatments within a defined target population over a specified followup window. Estimation with observational data is challenging because, while membership in the target population is defined in terms of eligibility criteria, treatment is rarely observed exactly at the time of eligibility. Ad-hoc solutions to this timing misalignment can induce bias by incorrectly attributing prior event counts and person-time to treatment. Even if eligibility and treatment are aligned, a terminal event process (e.g. death) often stops the recurrent event process of interest. In practice, both processes can be censored so that events are not observed over the entire followup window. Our approach addresses misalignment by casting it as a time-varying treatment problem: some patients are on treatment at eligibility while others are off treatment but may switch to treatment at a specified time - if they survive long enough. We define and identify an average causal effect estimand under right-censoring. Estimation is done using a g-computation procedure with a joint semiparametric Bayesian model for the death and recurrent event processes. We apply the method to contrast hospitalization rates among patients with different opioid treatments using Medicare insurance claims data.

Laura Schummers, Kimberlyn McGrail, Elizabeth K Darling et al.

Background The shifting landscape of abortion care from a hospital-only to a distributed service including primary care has implications for how to identify abortion cohorts for research and surveillance. The objectives of this study were to 1) create an improved approach to define abortion cohorts using linked administrative data sets and 2) evaluate the performance of this approach for abortion surveillance compared with standard approaches. Methods We applied four principles to identify induced abortion cohorts when some services are delivered beyond hospital settings; 1) exclude early pregnancy losses and postpartum procedures; 2) use multiple data sources; 3) define episodes of care; 4) apply a hierarchical algorithm to determine abortion date to a population-based cohort of all abortion events in Ontario (Canada) from January 1, 2018-March 15, 2020. We calculated risk differences (RD, with 95% confidence intervals) comparing the proportion of medication vs. surgical, first vs. second trimester, and complication incidence applying these principles vs. standard approaches. Results Hospital-only data (versus multiple data sources) underestimated the frequency of medication abortion (16.1% vs. 31.4%; RD -15.3% [-14.3, -16.3]) and first-trimester abortion (82.1% vs. 94.5%; RD -12.8 [-11.4, 13.4]) and overestimated incidence of abortion complication (2.9% vs. 0.69%; RD 2.2% [1.8, 2.7]). An unlinked (versus linked) approach underestimated the frequency of abortion complications (0.19% vs 0.69%, -RD 0.50% [-0.44 - -0.56]). Including (versus excluding) abortions following early pregnancy loss or delivery events increased the estimated incidence of abortion complications (1.29% vs. 0.69%, RD 0.60% [0.51-0.69]. Conclusion New methods are required to accurately identify abortion cohorts for surveillance or research. When legal or regulatory approaches to medication abortion evolve to enable abortion in primary care or office-based settings, hospital-based surveillance systems will become incomplete and biased; to continue valid and complete abortion surveillance, methods must be adjusted to ensure complete capture of procedures across all settings.

V. E. Irekponor, M. Abdul-Rahman, M. Agunbiade et al.

About half of the world population already live in urban areas. It is projected that by 2050, approximately 70% of the world population will live in cities. In addition to this, most developing countries do not have reliable population census figures, and periodic population censuses are extremely resource expensive. In Africa's most populous country, Nigeria, for instance, the last decennial census was conducted in 2006. The relevance of near-accurate population figures at the local levels cannot be overemphasized for a broad range of applications by government agencies and non-governmental organizations, including the planning and delivery of services, estimating populations at risk of hazards or infectious diseases, and disaster relief operations. Using GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) high-resolution spatially disaggregated population data estimates, this study proposed a framework for aggregating population figures at micro levels within a larger geographic jurisdiction. Python, QGIS, and machine learning techniques were used for data visualization, spatial analysis, and zonal statistics. Lagos Island, Nigeria was used as a case study to demonstrate how to obtain a more precise population estimate at the lowest administrative jurisdiction and eliminate ambiguity caused by antithetical parameters in the calculations. We also demonstrated how the framework can be used as a benchmark for estimating the carrying capacities of urban basic services like healthcare, housing, sanitary facilities, education, water etc. The proposed framework would help urban planners and government agencies to plan and manage cities better using more accurate data.

Matheus Menezes dos Santos, Bernardo Lanza Queiroz, Ana Paula de Andrade Verona

Abstract Multidimensional discussion about transition to adulthood is an incipient theme in Latin America. This paper seeks to describe and characterize the process of change in the transition of men and women in the region between the 1960s and 2010's. Using census data from IPUMS-International for 15 Latin American countries, we calculate the mean ages at transition to adulthood, at entering the labor market, at first union, and at first birth. We concluded there was a process of postponing transition to adulthood, although much stronger for males than for females, which we attribute to the events linked to the transition of each group. With these results, we hope to encourage further research into transition to adulthood in Latin America.

Ugo Bardi

Most scenarios for the world’s human population predict continued growth into the 22nd century, while some indicate that it could stabilize or begin to fall before 2100. Almost always, decline is seen as not being faster than the preceding growth. Different scenarios are obtained if we consider the human population as a complex system, subject to the general rules that govern complex systems, in particular their tendency to show rapid changes which – in the case of populations – may take the shape of true collapses (defined here as “Seneca Collapses”). The present survey examines a small number of examples of rapid population collapses in the human and in the animal domains. While not pretending to be exhaustive, the data presented here show that biological populations do show rapid “Seneca-style” collapses. So, it is possible that the same phenomenon could occur for the world’s human population.

Julia Bertino Moreira, Janine Hadassa Oliveira Marques de Borba

Resumo O presente artigo se propõe a debater um novo conceito no campo de estudos migratórios – as migrações de crise –, o qual traz à luz os processos, motivos e fatores vivenciados por populações afetadas por crises e que podem contribuir para processos migratórios de indivíduos, famílias e comunidades como um todo. Introduzindo diversas categorias correlatas – como a eventualidade, a imobilidade (ou enclausuramento) e a não escolha –, adota-se um direcionamento metodológico e conceitual que aponta para as crises como propulsoras das migrações. Dessa maneira, busca-se tensionar a ideia de que as migrações geram crises aos Estados-nação receptores de movimentos significativos de pessoas – a qual notavelmente se consolida pela disseminação do termo “crise migratória”, em especial, nos discursos políticos e midiáticos correntes. A delimitação do novo conceito proposto e da sua metodologia de estudo pautou-se pela revisão bibliográfica da literatura especializada na área, com foco em pesquisas recentes sobre as migrações de crise e suas implicações tanto na esfera local como na internacional. Ao final do texto, levantamos os desafios e as contribuições de tal conceito, envolvendo debates centrais no campo das migrações, inobstante questões teórico-metodológicas

Giacomo D'Amico, Tomislav Terzić, Jelena Strišković et al.

Signal estimation in the presence of background noise is a common problem in several scientific disciplines. An 'On/Off' measurement is performed when the background itself is not known, being estimated from a background control sample. The 'frequentist' and Bayesian approaches for signal estimation in On/Off measurements are reviewed and compared, focusing on the weakness of the former and on the advantages of the latter in correctly addressing the Poissonian nature of the problem. In this work, we devise a novel reconstruction method, dubbed BASiL (Bayesian Analysis including Single-event Likelihoods), for estimating the signal rate based on the Bayesian formalism. It uses information on event-by-event individual parameters and their distribution for the signal and background population. Events are thereby weighted according to their likelihood of being a signal or a background event and background suppression can be achieved without performing fixed fiducial cuts. Throughout the work, we maintain a general notation, that allows to apply the method generically, and provide a performance test using real data and simulations of observations with the MAGIC telescopes, as demonstration of the performance for Cherenkov telescopes. BASiL allows to estimate the signal more precisely, avoiding loss of exposure due to signal extraction cuts. We expect its applicability to be straightforward in similar cases.

Charline Smadi

We introduce a model of parasite infection in a cell population, where cells can be infected, either at birth through maternal transmission, from a contact with the parasites reservoir, or because of the parasites released in the cell medium after the lyses of infected cells. Inside the cells and between infection events, the quantity of parasites evolves as a general non linear branching process. We study the long time behaviour of the infection.

Wei-hsin Yu, Yuko Hara

<b>Background</b>: Most research linking jobs to marriage formation focuses on how job contexts and prospects affect singles' paces of entering marriage. Direct evidence on whether job traits shape singles' desire for marriage and actions toward forming a union remains scarce. <b>Objective</b>: We examine how changes in a range of job characteristics correspond to alterations in never-married people's intention to marry and actions taken to meet romantic partners in Japan, a country with increasing inequality in job quality and declining marriage rates. <b>Methods</b>: We use longitudinal data from the Japan Life Course Panel Survey to fit fixed-effects models, which take into account unobserved heterogeneity among people with differing jobs. <b>Results</b>: We find that rises in job insecurity and workplace staffing shortages weaken, whereas increases in income and job autonomy strengthen, men's intention to marry. Moreover, men with a low marriage desire are especially likely to withdraw from partner-seeking activities when they have low-income jobs or face great deadline pressure at work. Job prospects and quality are generally less important to women's desire for marriage or partner-seeking actions. Nevertheless, being in workplaces where teamwork is prevalent, which could enhance singles' exposure to married and older coworkers, raises both women's intention to marry and their probability of using a formal method, such as employing a marriage agency, to find a partner. <b>Conclusions</b>: For Japanese men, our results offer support for the argument that economic stagnation and deterioration of job quality are conducive to later and fewer marriages. The findings for women, however, are more consistent with the narrative focusing on values and social influences. <b>Contribution</b>: This study enriches our understanding of singles' considerations of marriage and partner search and provides highly rigorous evidence on the roles of job conditions.

Agatha C. H. de Mattos, Gavin McArdle, Michela Bertolotto

Over a billion people live in slums in settlements that are often located in ecologically sensitive areas and hence highly vulnerable. This is a problem in many parts of the world, but it is more prominent in low-income countries, where in 2014 on average 65% of the urban population lived in slums. As a result, building resilient communities requires quantifying the population living in these deprived areas and improving their living conditions. However, most of the data about slums comes from census data, which is only available at aggregate levels and often excludes these settlements. Consequently, researchers have looked at alternative approaches. These approaches, however, commonly rely on expensive high-resolution satellite imagery and field-surveys, which hinders their large-scale applicability. In this paper, we investigate a cost-effective methodology to estimate the slum population by assessing the quality of gridded population data. We evaluate the accuracy of the WorldPOP and LandScan population layers against ground-truth data composed of 1,703 georeferenced polygons that were mapped as deprived areas and which had their population surveyed during the 2010 Brazilian census. While the LandScan data did not produce satisfactory results for most polygons, the WorldPOP estimates were less than 20% off for 67% of the polygons and the overall error for the totality of the studied area was only -5.9%. This small error margin demonstrates that population layers with a resolution of at least a 100m, such as WorldPOP's, can be useful tools to estimate the population living in slums.

Maria Gabriela Navarro, Dante Minniti, Rodrigo Contreras Ramos

The VVV microlensing search has recently surveyed the region of the Galactic plane at b=0 within -10.00 < l < 10.44 deg. in the near-infrared (IR), discovering hundreds of microlensing events. In this paper we explore the microlensing events with background sources that might be located in the far disk of the Galaxy, beyond the bulge. We discuss the possible configurations for the microlensing lenses and sources located at different places within the Galactic plane. Then we search for these events using the local red clump centroids of the VVV near-IR color-magnitude diagrams. According to the estimated distances and proper motions, N=20 events may have sources located in the far disk. The candidates for far-disk sources show on average longer timescales (tE= 49.3 +- 7.9 days) than the mean of the timescale distribution for the bulge red clump sources (tE= 36.4 +- 1.1 days). We conclude that the population of microlensing events in the region -10.00 < l < 10.44, -0.46 < b < 0.65 deg. contains a non-negligible number of events with candidate far-disk sources (~ 11 %). Our results are relevant in view of the future microlensing plans with the Roman Space Telescope (formerly WFIRST) in the near-IR.

Benjamin Ackerman, Catherine R. Lesko, Juned Siddique et al.

Randomized trials are considered the gold standard for estimating causal effects. Trial findings are often used to inform policy and programming efforts, yet their results may not generalize well to a relevant target population due to potential differences in effect moderators between the trial and population. Statistical methods have been developed to improve generalizability by combining trials and population data, and weighting the trial to resemble the population on baseline covariates.Large-scale surveys in fields such as health and education with complex survey designs are a logical source for population data; however, there is currently no best practice for incorporating survey weights when generalizing trial findings to a complex survey. We propose and investigate ways to incorporate survey weights in this context. We examine the performance of our proposed estimator in simulations by comparing its performance to estimators that ignore the complex survey design.We then apply the methods to generalize findings from two trials - a lifestyle intervention for blood pressure reduction and a web-based intervention to treat substance use disorders - to their respective target populations using population data from complex surveys. The work highlights the importance in properly accounting for the complex survey design when generalizing trial findings to a population represented by a complex survey sample.

Samuel Vézina, Alain Bélanger

<b>Background</b>: In most developed countries the demographic regime is characterised by low fertility, high immigration, and population ageing. This regime impacts on the size of the labour force population, the ethno-cultural composition, and potential productivity. <b>Objective</b>: We examine the prospective impacts of two sociodemographic changes, namely increasing education and increasing immigration levels, on the size and skills of the workforce aged 25 to 64 years old for the time period 2011-2061. <b>Methods</b>: We use microsimulation models to project the population of Austria and Canada by age, sex, and several other socioeconomic and ethno-cultural dimensions. Using 'what-if' scenarios, we measure the impact of different immigration rates and immigrant selection patterns on the size and average literacy skills of the projected workforce. We also examine the potential effects of different assumptions about future educational attainment on the projection outcomes. <b>Results</b>: The results show that the volume of immigration heavily influences the expansion of the workforce .In terms of education among the general population, the rise in educational attainment is positively correlated with higher skill levels. However, increased immigration can override the effect that increasing education levels have on advancing workforce skills. <b>Contribution</b>: This paper shows the extent to which Austria and Canada have adopted diametrically opposed strategies regarding the future development of their workforces. Assuming that current policy goals hold true in the coming decades, Austria is likely to rely on a higher-skilled but declining (in size) workforce, whereas Canada will rely on a fast-growing but less-skilled and more culturally diversified workforce.