How does the community COVID-19 level of risk impact on that of a care home?

OBJECTIVES: To model the risk of COVID-19 mortality in British care homes conditional on the community level risk. METHODS: A two stage modeling process (“doubly latent”) which includes a Besag York Mollie model (BYM) and a Log Gaussian Cox Process. The BYM is adopted so as to estimate the community level risks. These are incorporated in the Log Gaussian Cox Process to estimate the impact of these risks on that in care homes. RESULTS: For an increase in the risk at the community level, the number of COVID-19 related deaths in the associated care home would be increased by exp (0.833), 2. This is based on a simulated dataset. In the context of COVID-19 related deaths, this study has illustrated the estimation of the risk to care homes in the presence of background community risk. This approach will be useful in facilitating the identification of the most vulnerable care homes and in predicting risk to new care homes. CONCLUSIONS: The modeling of two latent processes have been shown to be successfully facilitated by the use of the BYM and Log Gaussian Cox Process Models. Community COVID-19 risks impact on that of the care homes embedded in these communities

A changepoint analysis of spatio-temporal point processes

As regards author Linda Altieri, the research work underlying this paper was partially funded by a FIRB 2012 grant (project no. RBFR12URQJ; title: Statistical modeling of environmental phenomena: pollution, meteorology, health and their interactions) for research projects by the Italian Ministry of Education, Universities and Research.This work introduces a Bayesian approach to detecting multiple unknown changepoints over time in the inhomogeneous intensity of a spatio-temporal point process with spatial and temporal dependence within segments. We propose a new method for detecting changes by fitting a spatio-temporal log-Gaussian Cox process model using the computational efficiency and flexibility of integrated nested Laplace approximation, and by studying the posterior distribution of the potential changepoint positions. In this paper, the context of the problem and the research questions are introduced, then the methodology is presented and discussed in detail. A simulation study assesses the validity and properties of the proposed methods. Lastly, questions are addressed concerning potential unknown changepoints in the intensity of radioactive particles found on Sandside beach, Dounreay, Scotland.PostprintPeer reviewe

inlabru: an R package for Bayesian spatial modelling from ecological survey data

1. Spatial processes are central to many ecological processes, but fitting models that incorporate spatial correlation to data from ecological surveys is computationally challenging. This is particularly true of point pattern data (in which the primary data are the locations at which target species are found), but also true of gridded data, and of georeferenced samples from continuous spatial fields. 2. We describe here the R package inlabru that builds on the widely used RINLA package to provide easier access to Bayesian inference from spatial point process, spatial count, gridded, and georeferenced data, using integrated nested Laplace approximation (INLA, Rue et al., 2009). 3. The package provides methods for fitting spatial density surfaces and estimating abundance, as well as for plotting and prediction. It accommodates data that are points, counts, georeferenced samples, or distance sampling data. 4. This paper describes the main features of the package, illustrated by fitting models to the gorilla nest data contained in the package spatstat (Baddeley, & Turner, 2005), a line transect survey dataset contained in the package dsm (Miller, Rexstad, Burt, Bravington, & Hedley, 2018), and to a georeferenced sample from a simulated continuous spatial field

Non-stationary Gaussian models with physical barriers

The classical tools in spatial statistics are stationary models, like the Matern field. However, in some applications there are boundaries, holes, or physical barriers in the study area, e.g. a coastline, and stationary models will inappropriately smooth over these features, requiring the use of a non-stationary model. We propose a new model, the Barrier model, which is different from the established methods as it is not based on the shortest distance around the physical barrier, nor on boundary conditions. The Barrier model is based on viewing the Matern correlation, not as a correlation function on the shortest distance between two points, but as a collection of paths through a Simultaneous Autoregressive (SAR) model. We then manipulate these local dependencies to cut off paths that are crossing the physical barriers. To make the new SAR well behaved, we formulate it as a stochastic partial differential equation (SPDE) that can be discretised to represent the Gaussian field, with a sparse precision matrix that is automatically positive definite. The main advantage with the Barrier model is that the computational cost is the same as for the stationary model. The model is easy to use, and can deal with both sparse data and very complex barriers, as shown in an application in the Finnish Archipelago Sea. Additionally, the Barrier model is better at reconstructing the modified Horseshoe test function than the standard models used in R-INLA. (C) 2019 Elsevier B.V. All rights reserved.Peer reviewe

Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis

Diagnosis and prognosis of cancer is informed by the architecture inherent in cancer patient tissue sections. This architecture is typically identified by pathologists, yet advances in computational image analysis facilitate quantitative assessment of this structure. In this article we develop a spatial point process approach in order to describe patterns in cell distribution within tissue samples taken from colorectal cancer (CRC) patients. In particular, our approach is centered on the Palm intensity function. This leads to taking an approximate-likelihood technique in fitting point processes models. We consider two Neyman-Scott point processes and a void process, fitting these point process models to the CRC patient data. We find that the parameter estimates of these models may be used to quantify the spatial arrangement of cells. Importantly, we observe characteristic differences in the spatial arrangement of cells between patients who died from CRC and those alive at follow-up

Bürgerbildung in Slowenien und Diskurs der Permissivität

Tekst ima dva dijela koji predstavljaju dva različita koncepta odnosa između građanskog obrazovanja i prihvaćenog vrijednosnog sustava u državnim školama. U prvom dijelu analizirat ćemo javne rasprave koje se odnose na građansko obrazovanje: želimo provjeriti koliko su izložene utjecaju javnih i političkih očekivanja i stajalištima koja se formiraju kroz mehanizme političke moći. Koncepte građanskog obrazovanja analiziramo kao diskurzivni fenomen. Želimo pokazati kako diskurs utječe na koncepte građanskog obrazovanja. Pritom diskurs interpretiramo kao društvenu vezu ili kao točku identifikacije u kojoj se možemo prepoznati. U drugom dijelu rada nastojimo dati odgovor na pitanje o uspostavi građanskog obrazovanja kao posljedice izgubljenih iluzija na kraju Velikih priča i poslije ‘’sloma’’ u bivšim socijalističkim ili komunističkim zemljama, koji se dogodio nakon uspostavljanja parlamentarne demokracije i tržišne ekonomije. Pitamo se: Kako nastavnici promatraju građansko obrazovanje kao nastavni predmet? Što bi trebali biti sadržaji građanskog obrazovanja ako određeni predmet promatraju učenici, i to kao predmet koji nema vrijednost ili koji im je nepoznat? Trebaju li sadržaji građanskog obrazovanja reflektirati želje učenika?The text is divided in two opposing parts, presenting two different concepts of the relation between civil education and the accepted system of values in state schools. The first part of the text is an analysis of public debates about civil education: the authors wanted to determine to what extent they are influenced by public and political expectations or convictions formed through political power mechanisms. The concepts of civil education are analysed as discursive phenomena. The authors’ aim is to show how a discourse influences the concepts of civil education. A discourse is interpreted as a social connection or a point of identification for an individual. The second part of the paper tries to answer the questions raised by the introduction of civil education as a reaction to the disillusionment at the end of the big stories and after the breakdown in former socialist or communist countries, made necessary by the establishment of parliamentary democracy and market economy. The questions raised in that part are: How do teachers perceive Civil Education as a subject? What should Civil Education contain, from students’ point of view, especially if such a subject is thought to be worthless or totally alienated from their reality? Should the content of Civil Education reflect students’ wishes?Der Text hat zwei Teile, deren Einschränkungen mit Hilfe von zwei verschiedenen Beziehungskonzepten zwischen der Bürgerbildung und dem geltenden Wertsystem an den Staatsschulen veranschaulicht werden. Im ersten Teil wird die öffentliche Diskussion über die Bürgerbildung analysiert: Wir möchten überprüfen, in welchem Ausmass sie von den öffentlichen und politischen Erwartungen und Überzeugungen beeinflusst wird, die durch Mechanismen der politischen Macht gebildet werden. Konzepte der Bürgerbildung werden als diskursives Phänomen analysiert. Wir möchten aufzeigen, wie der Diskurs die Konzepte der Bürgerbildung beeinflusst. Dabei wird der Diskurs als gesellschaftliche Beziehung oder als Identifikationspunkt gedeutet, in dem wir alle uns wiedererkennen können. Im zweiten Teil unserer Arbeit versuchen wir, die Frage zu beantworten, ob die Einführung der Bürgerbildung als eine Folge von verlorenen Illusionen am Ende der grossen Geschichten nach dem «Zusammenbruch» in den ex-sozialistischen oder kommunistischen Ländern anzusehen sei, der nach der Einführung der parlamentarischen Demokratie und Marktwirtschaft erfolgte. In diesem Teil stellen wir die Fragen: Wie betrachten die Lehrer die Bürgerbildung als Unterrichtsfach? Was sollten die Inhalte der Bürgerbildung sein, wenn wir sie vom Gesichtspunkt der Schüler aus betrachten als ein Schulfach, das für sie keinen Wert besitzt oder ihnen völlig fremd ist? Sollten die Inhalte der Bürgerbildung die Wünsche der Schüler wiederspiegeln

A Bayesian approach to modelling subnational spatial dynamics of worldwide non-state terrorism, 2010-2016

Terrorism persists as a worldwide threat, as exemplified by the on‐going lethal attacks perpetrated by Islamic State in Iraq and Syria, Al Qaeda in Yemen and Boko Haram in Nigeria. In response, states deploy various counterterrorism policies, the costs of which could be reduced through efficient preventive measures. Statistical models that can account for complex spatiotemporal dependences have not yet been applied, despite their potential for providing guidance to explain and prevent terrorism. To address this shortcoming, we employ hierarchical models in a Bayesian context, where the spatial random field is represented by a stochastic partial differential equation. Our main findings suggest that lethal terrorist attacks tend to generate more deaths in ethnically polarized areas and in locations within democratic countries. Furthermore, the number of lethal attacks increases close to large cities and in locations with higher levels of population density and human activity.PostprintPeer reviewe

A spatiotemporal multispecies model of a semicontinuous response

BS was part funded by Engineering and Physical Sciences Research Council–Natural Environment Research Council grant EP/10009171/1.As accessible and potentially vulnerable species high up in the food chain, birds are often used as indicator species to highlight changes in ecosystems. This study focuses on multiple spatially dependent relationships between a raptor (sparrowhawk), a potential prey species (house sparrow) and a sympatric species (collared doves) in space and time. We construct a complex spatiotemporal latent Gaussian model to incorporate both predator–prey and sympatric relationships, which is novel in two ways. First, different types of species interactions are represented by a shared spatiotemporal random effect, which extends existing approaches to multivariate spatial modelling through the use of a joint latent modelling approach. Second, we use a delta–gamma model to capture the semicontinuous nature of the data to model the binary and continuous sections of the response jointly. The results indicate that sparrowhawks have a localized effect on the presence of house sparrows, which could indicate that house sparrows avoid sites where sparrowhawks are present.PostprintPeer reviewe

Re-evaluation of individual diameter : height allometric models to improve biomass estimation of tropical trees

The first author was supported by the European Union under a IEF Marie-Curie Action.Accurate estimation of tree biomass is necessary to provide realistic values of the carbon stored in the terrestrial biosphere. A recognized source of errors in tree above-ground biomass (AGB) estimation is introduced when individual tree height values (H) are not directly measured but estimated from diameter at breast height (DBH) using allometric equations. In this paper we evaluate the performance of 12 alternative DBH : H equations and compare their effects on AGB estimation for three tropical forests that occur in contrasting climatic and altitudinal zones. We found that fitting a 3-parameter Weibull function using data collected locally generated the lowest errors and bias in H estimation, and that equations fitted to these data were more accurate than equations with parameters derived from the literature. For computing AGB, the introduced error values differed notably among DBH : H allometric equations, and in most cases showed a clear bias that resulted in either over- or under-estimation of AGB. Fitting the three-parameter Weibull function minimized errors in AGB estimates in our study and we recommend its widespread adoption for carbon stock estimation. We conclude that many previous studies are likely to present biased estimates of AGB due to the method of H estimation.Publisher PDFPeer reviewe