1,720,990 research outputs found
Discrete versus continuous domain models for disease mapping.
The main goal of disease mapping is to estimate disease risk and identify high-risk areas. Such analyses are hampered by the limited geographical resolution of the available data. Typically the available data are counts per spatial unit and the common approach is the Besag-York-Mollié (BYM) model. When precise geocodes are available, it is more natural to use Log-Gaussian Cox processes (LGCPs). In a simulation study mimicking childhood leukaemia incidence using actual residential locations of all children in the canton of Zürich, Switzerland, we compare the ability of these models to recover risk surfaces and identify high-risk areas. We then apply both approaches to actual data on childhood leukaemia incidence in the canton of Zürich during 1985-2015. We found that LGCPs outperform BYM models in almost all scenarios considered. Our findings suggest that there are important gains to be made from the use of LGCPs in spatial epidemiology
Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander cycles in London
The COVID-19 pandemic has been influencing travel behaviour in many urban areas around the world since the beginning of 2020. As a consequence, bike-sharing schemes have been affected—partly due to the change in travel demand and behaviour as well as a shift from public transit. This study estimates the varying effect of the COVID-19 pandemic on the London bike-sharing system (Santander Cycles) over the period March–December 2020. We employed a Bayesian second-order random walk time-series model to account for temporal correlation in the data. We compared the observed number of cycle hires and hire time with their respective counterfactuals (what would have been if the pandemic had not happened) to estimate the magnitude of the change caused by the pandemic. The results indicated that following a reduction in cycle hires in March and April 2020, the demand rebounded from May 2020, remaining in the expected range of what would have been if the pandemic had not occurred. This could indicate the resiliency of Santander Cycles. With respect to hire time, an important increase occurred in April, May, and June 2020, indicating that bikes were hired for longer trips, perhaps partly due to a shift from public transit.</p
Bayesian spatial modelling of childhood cancer incidence in Switzerland using exact point data: a nationwide study during 1985-2015.
BACKGROUND
The aetiology of most childhood cancers is largely unknown. Spatially varying environmental factors such as traffic-related air pollution, background radiation and agricultural pesticides might contribute to the development of childhood cancer. This study is the first investigation of the spatial disease mapping of childhood cancers using exact geocodes of place of residence.
METHODS
We included 5947 children diagnosed with cancer in Switzerland during 1985-2015 at 0-15 years of age from the Swiss Childhood Cancer Registry. We modelled cancer risk using log-Gaussian Cox processes and indirect standardisation to adjust for age and year of diagnosis. We examined whether the spatial variation of risk can be explained by modelled ambient air concentration of NO2, modelled exposure to background ionising radiation, area-based socio-economic position (SEP), linguistic region, duration in years of general cancer registration in the canton or degree of urbanisation.
RESULTS
For all childhood cancers combined, the posterior median relative risk (RR), compared to the national level, varied by location from 0.83 to 1.13 (min to max). Corresponding ranges were 0.96 to 1.09 for leukaemia, 0.90 to 1.13 for lymphoma, and 0.82 to 1.23 for central nervous system (CNS) tumours. The covariates considered explained 72% of the observed spatial variation for all cancers, 81% for leukaemia, 82% for lymphoma and 64% for CNS tumours. There was weak evidence of an association of CNS tumour incidence with modelled exposure to background ionising radiation (RR per SD difference 1.17; 0.98-1.40) and with SEP (1.6; 1.00-1.13).
CONCLUSION
Of the investigated diagnostic groups, childhood CNS tumours showed the largest spatial variation. The selected covariates only partially explained the observed variation of CNS tumours suggesting that other environmental factors also play a role
Ensemble Bayesian modelling with dynamic population to estimate excess deaths due to extreme temperatures
Extreme heat has been linked to increased mortality. Monitoring the mortality burden attributable to extreme heat is crucial to inform policies, such as heat warnings, and prevent heat-related deaths. In this study, we evaluate excess mortality during summer 2022 in Switzerland, identify vulnerable populations and estimate temperature thresholds relevant for heat adaptation policies. We use nationwide mortality and population data during 2011-2022 by age, sex, day and canton. We develop a Bayesian ensemble modelling approach with dynamic population to predict expected mortality in summer 2022 and calculate excess by comparing expected with observed mortality. We account for covariates associated with mortality such as national holidays, and spatiotemporal random effects to improve predictions. After accounting for the effect of the COVID-19 pandemic, we observed a total of 487 (95% Credible Interval: 10-935) excess deaths during summer 2022 in people older than 80 years. We illustrate that for periods of extreme heat longer than four days, the minimum excess mortality temperature threshold in the oldest age group is the 70th percentile of the temperature. Our approach highlights the importance of lower temperature thresholds during prolonged periods of extreme heat and advocates for integrating this insight in heat adaptation policies.
Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved
Area-level excess mortality in times of COVID-19 in Switzerland: geographical, socioeconomic and political determinants.
The coronavirus disease 2019 (COVID-19)-related excess mortality in Switzerland is well documented, but no study examined mortality at the small-area level. We analysed excess mortality in 2020 for 2141 Swiss municipalities using a Bayesian spatiotemporal model fitted to 2011-19 data. Areas most affected included the Ticino, the Romandie and the Northeast. Rural areas, municipalities within cross-border labour markets, of lower socioeconomic position and with less support for control measures in the popular vote on the COVID-19 Act had greater excess mortality. Particularly vulnerable municipalities require special efforts to mitigate the impact of pandemics
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Real-time forecast of heat-related excess mortality during June 2025 heatwave
It is well established that extreme heat increases the risk of mortality. During the exceptionally hot summer of 2022, an estimated 61,672 heat-related deaths occurred across 35 European countries, including approximately 3,000 excess deaths due to heatwaves in England. As the climate continues to warm, periods of extreme heat are becoming more frequent and intense.
In this report, we estimate the expected excess deaths from exposure to heat during the first heatwave of 2025 in England and Wales, specifically between 19-22 June at small geographic scales
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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