1,720,970 research outputs found
Combining and comparing regional SARS-CoV-2 epidemic dynamics in Italy: Bayesian meta-analysis of compartmental models and global sensitivity analysis
Full text linkDuring autumn 2020, Italy faced a second important SARS-CoV-2 epidemic wave. We explored the time pattern of the instantaneous reproductive number, R(0)(t), and estimated the prevalence of infections by region from August to December calibrating SIRD models on COVID-19-related deaths, fixing at values from literature Infection Fatality Rate (IFR) and average infection duration. A Global Sensitivity Analysis (GSA) was performed on the regional SIRD models. Then, we used Bayesian meta-analysis and meta-regression to combine and compare the regional results and investigate their heterogeneity. The meta-analytic R(0)(t) curves were similar in the Northern and Central regions, while a less peaked curve was estimated for the South. The maximum R(0)(t) ranged from 2.15 (South) to 2.61 (North) with an increase following school reopening and a decline at the end of October. The predictive performance of the regional models, assessed through cross validation, was good, with a Mean Absolute Percentage Error of 7.2% and 10.9% when considering prediction horizons of 7 and 14 days, respectively. Average temperature, urbanization, characteristics of family medicine and healthcare system, economic dynamism, and use of public transport could partly explain the regional heterogeneity. The GSA indicated the robustness of the regional R(0)(t) curves to different assumptions on IFR. The infectious period turned out to have a key role in determining the model results, but without compromising between-region comparisons
Learning the two parameters of the Poisson–Dirichlet distribution with a forensic application
Full text linkIn forensic science, the rare type match problem arises when the matching characteristic from the suspect and the crime scene is not in the reference database; hence, it is difficult to evaluate the likelihood ratio that compares the defense and prosecution hypotheses. A recent solution consists of modeling the ordered population probabilities according to the two-parameter Poisson–Dirichlet distribution, which is a well-known Bayesian nonparametric prior, and plugging the maximum likelihood estimates of the parameters into the likelihood ratio. We demonstrate that this approximation produces a systematic bias that fully Bayesian inference avoids. Motivated by this forensic application, we consider the need to learn the posterior distribution of the parameters that governs the two-parameter Poisson–Dirichlet using two sampling methods: Markov Chain Monte Carlo and approximate Bayesian computation. These methods are evaluated in terms of accuracy and efficiency. Finally, we compare the likelihood ratio that is obtained by our proposal with the existing solution using a database of Y-chromosome haplotypes
Analisi e previsioni dell’epidemia da SARS-CoV-2 in Toscana / Analysis and future scenarios of the SARS-CoV-2 epidemic in Tuscany Region (Central Italy)
No full textOBIETTIVI: a circa due mesi dalla fine del lockdown imposto per il contenimento dell’epidemia di SARS-CoV-2, si sono valutate le dinamiche del contagio nella Regione Toscana dall’inizio dell’emergenza a fine giugno attraverso un modello compartimentale, successivamente utilizzato per produrre semplici previsioni degli andamenti epidemici per i prossimi mesi.
DATI E METODI: è stato costruito un modello compartimentale di tipo SIRD, in cui il tasso di riproduzione dell’infezione (R0) è stato assunto variabile nel tempo, tramite una funzione costante a tratti. Fissati, per motivi di identificabilità, alcuni parametri – la letalità e il tempo dal contagio alla risoluzione dell’infezione (morte o guarigione) – il modello è stato calibrato sulla serie dei decessi per malattia Covid-19 notificati nel periodo dal 09.03.2020 al 30.06.2020. L’incertezza attorno alle stime è stata quantificata attraverso un bootstrap parametrico. Il modello stimato è stato poi utilizzato per produrre proiezioni
a medio-lungo termine delle dinamiche epidemiche.
RISULTATI: la data di inizio epidemia in Toscana è stata stimata al 21.02.2020. Il valore stimato di R0(t) è andato da un iniziale 7,78 (IC95% 7,55-7,89) a un valore molto vicino a 0 tra il 27 aprile e il 17 maggio. Infine, esso è risalito, fino a raggiungere un valore medio di 0,66 (0,32-0,88) tra il 18 maggio e il 30 giugno. In corrispondenza del picco epidemico, stimato all’inizio di aprile, gli infetti notificati circolanti in regione risultavano appena il 22% di quelli predetti dal SIRD. In accordo al modello, se a partire da ottobre R 0 (t) superasse, anche di poco, l’unità, l’onda del contagio potrebbe raggiungere nuovamente livelli preoccupanti entro la prossima primavera.
CONCLUSIONI: l’andamento stimato di R0(t) suggerisce la presenza di un forte effetto delle politiche di contenimento sulla diffusione del virus in Toscana e di una minima ripresa del contagio potenzialmente attribuibile all’interruzione del lockdown. Le proiezioni a medio-lungo termine mostrano inequivocabilmente come il pericolo di una nuova ondata epidemica non sia scongiurato
A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios
Full text linkWe propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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