Mathematical Population Studies最新文献

{"title":"Methods and applications in spatial demography","authors":"S. Matthews","doi":"10.1080/08898480.2019.1653058","DOIUrl":"https://doi.org/10.1080/08898480.2019.1653058","url":null,"abstract":"The two thematic issues 26(4) and 27(1) of Mathematical Population Studies deal with “methods and applications in spatial demography.” The five articles they contain, and which are listed below, show how population studies can be informed through an integration of appropriate spatial theory, data, and methods. In the editorial to appear in the next issue, 27(1), I will provide a summary of each article and discuss its contribution to this very lively field. I would like to thank the authors, the journal, and Taylor and Francis for these issues, which I had the pleasure of organizing. We wish you a pleasant reading.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"26 1","pages":"183 - 184"},"PeriodicalIF":1.8,"publicationDate":"2019-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1653058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47249999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In memoriam: Jennifer Buher Kane (1979–2019)","authors":"S. Matthews","doi":"10.1080/08898480.2019.1669363","DOIUrl":"https://doi.org/10.1080/08898480.2019.1669363","url":null,"abstract":"","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"26 1","pages":"185 - 185"},"PeriodicalIF":1.8,"publicationDate":"2019-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1669363","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44556794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian inference for a susceptible-exposed-infected-recovered epidemic model with data augmentation","authors":"Chouaib Beldjoudi, T. Kernane, Hamid El Maroufy","doi":"10.1080/08898480.2019.1656491","DOIUrl":"https://doi.org/10.1080/08898480.2019.1656491","url":null,"abstract":"ABSTRACT A Bayesian data-augmentation method allows estimating the parameters in a susceptible-exposed-infected-recovered (SEIR) epidemic model, which is formulated as a continuous-time Markov process and approximated by a diffusion process using the convergence of the master equation. The estimation was carried out with latent data points between every pair of observations simulated through the Euler-Maruyama scheme, which involves imputing the missing data in addition to the model parameters. The missing data and parameters are treated as random variables, and a Markov-chain Monte-Carlo algorithm updates the missing data and the parameter values. Numerical simulations show the effectiveness of the proposed Markov-chain Monte-Carlo algorithm.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"232 - 258"},"PeriodicalIF":1.8,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1656491","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43385656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connecting Continuum of Care point-in-time homeless counts to United States Census areal units","authors":"Zack W. Almquist, Nathaniel E. Helwig, Yun You","doi":"10.1080/08898480.2019.1636574","DOIUrl":"https://doi.org/10.1080/08898480.2019.1636574","url":null,"abstract":"ABSTRACT In 2007, the Department of Housing and Urban Development initiated a point-in-time count of the homeless across the United States. The counts are administered by the Continuum of Care Program, which provides spatial and temporal data for the homeless population over the last decade. Unfortunately, this administrative spatial unit does not align with the more common areal units defined by the United States Census Bureau, which limits usability of these data. To unify these two areal units, spatial disaggregation, matching, and imputation allow for aligning Continuum of Care data with county data. The resulting county-level homeless counts for the years 2005 to 2017 are provided as an R package. The county-level data display more spatial precision and more temporal variation than the Continuum of Care-level data. Nonparametric regression analyses reveal that the spatiotemporal variation in the data can be well approximated by additive spatial and temporal effects at both the county and Continuum of Care level.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"46 - 58"},"PeriodicalIF":1.8,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1636574","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42686396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population model with immigration in continuous space","authors":"E. Chernousova, O. Hryniv, S. Molchanov","doi":"10.1080/08898480.2019.1626189","DOIUrl":"https://doi.org/10.1080/08898480.2019.1626189","url":null,"abstract":"ABSTRACT In a population model in continuous space, individuals evolve independently as branching random walks subject to immigration. If the underlying branching mechanism is subcritical, the model has a unique steady state for each value of the immigration intensity. Convergence to the equilibrium is exponentially fast. The resulting dynamics are Lyapunov stable in that their qualitative behavior does not change under suitable perturbations of the main parameters of the model.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"199 - 215"},"PeriodicalIF":1.8,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1626189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42375749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved chain-ratio type estimator for population total in double sampling","authors":"Saurav Guha, Hukum Chandra","doi":"10.1080/08898480.2019.1626635","DOIUrl":"https://doi.org/10.1080/08898480.2019.1626635","url":null,"abstract":"ABSTRACT Chain-ratio estimators are often used to improve the efficiency of the estimation of the population total or the mean using two auxiliary variables, available in two different phases. An improved chain-ratio estimator for the population total based on double sampling is proposed when auxiliary information is available for the first variable and not available for the second variable. The bias and the mean square error of this estimator are obtained for a large sample. Empirical evaluations using both model-based and design-based simulations show that the proposed estimator performs better than the ratio, the regression, and the difference estimators.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"216 - 231"},"PeriodicalIF":1.8,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1626635","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48595379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time to extinction and stationary distribution of a stochastic susceptible-infected-recovered-susceptible model with vaccination under Markov switching","authors":"Xiaoni Li, Xining Li, Qimin Zhang","doi":"10.1080/08898480.2019.1626633","DOIUrl":"https://doi.org/10.1080/08898480.2019.1626633","url":null,"abstract":"ABSTRACT A stochastic susceptible-infected-recovered-susceptible model with vaccination includes stochastic variation in its parameters. Sufficient conditions for the extinction and the existence of the stationary distribution of the population are proved.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"259 - 274"},"PeriodicalIF":1.8,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1626633","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45208367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatially varying relationships between risk factors and child diarrhea in West Africa, 2008-2013","authors":"Gillian Dunn, Glen D. Johnson, D. Balk, Grace Sembajwe","doi":"10.1080/08898480.2019.1592638","DOIUrl":"https://doi.org/10.1080/08898480.2019.1592638","url":null,"abstract":"ABSTRACT Diarrhea is a major contributor to child morbidity and mortality in West Africa. Non-spatial regression and geographically weighted Poisson regression applied to data from 10 Demographic and Health Surveys conducted in West Africa from 2008 to 2013 show that water source, toilet type, mother’s education, latitude, temperature, rainfall, altitude, and population density influence the risk of diarrhea. The risk associated with these factors is dependent on location and may be higher or lower than the rest of the study area. Areas with increased relative risk for diarrhea include several urban centers, low-elevation areas (coastal and along rivers), remote areas such as western Mali, and conflict zones (northeast Nigeria).","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"27 1","pages":"8 - 33"},"PeriodicalIF":1.8,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1592638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47205859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Big data in policy making","authors":"Biagio Aragona, R. De Rosa","doi":"10.1080/08898480.2017.1418113","DOIUrl":"https://doi.org/10.1080/08898480.2017.1418113","url":null,"abstract":"ABSTRACT A review of studies based on big data shows that big data advantageously complete surveys and censuses, nurture policy making, and highlight effects of a given policy in real time.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"26 1","pages":"107 - 113"},"PeriodicalIF":1.8,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2017.1418113","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45676558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methods for big data in social sciences","authors":"Enrica Amaturo, Biagio Aragona","doi":"10.1080/08898480.2019.1597577","DOIUrl":"https://doi.org/10.1080/08898480.2019.1597577","url":null,"abstract":"The diffusion of digital technologies and social networks has multiplied the forms of digital data that can be employed for social research. The main two forms are native digital data, which are produced in social networks, search engines, or blogging, and digitized data, which are analog data transformed into digital (Rogers, 2013). Big data are originally produced in the Internet. They allow for analyzing behaviors without interfering with individuals (Webb et al., 1966). An example is the data used in web platforms analytics, such as Google Correlate, whose purpose is to reveal the co-occurrences associated with a keyword searched through the Google search engine. This tool helped to predict the flu epidemic in the US, well before the US Centre for Disease Control and Prevention (Ginsberg et al., 2009). This example demonstrates that digital web platforms enable innovations in data analysis. Another example of native digital data is the data voluntarily uploaded on social networks, blogs, and websites. These are mainly textual or visual (images and videos), often unstructured. A third example is transactional data and the Internet of things. Transactions made through digital devices, such as smart-phones, scanners, tablets, and cards with chips (credit cards, shopping cards) produce data with some structure. These data comprise metadata (date, time, duration, or expenditures) associated with transactions. The objects connected to the Internet (the Internet of things), such as sensors for health monitoring, house automation, and driving aid, usually produce structured data, which can be organized and analyzed. Digitized data previously existed in analog form, for example images, videos, and scanned or digitally photographed documents uploaded on the web, such as museum collections or libraries available on-line. Digital humanities have converted this material into digital form. Another example is the surveys assisted by computers, where the data are inserted into digital databases. Web surveys now are conducted through the Internet (by e-mail) (Amaturo and Aragona, 2016), and allow for reaching a large sample with a small budget.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"26 1","pages":"65 - 68"},"PeriodicalIF":1.8,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1597577","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41950429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}