Pairwise interaction point processes for modelling bivariate spatial point patterns in the presence of interaction uncertainty

Current ecological research seeks to understand the mechanisms that sustain biodiversity and allow a large number of species to coexist. Coexistence concerns inter-individual interactions. Consequently, there is an interest in identifying and quantifying interactions within and between species as reflected in the spatial pattern formed by the individuals. This study analyses the spatial pattern formed by the locations of plants in a community with high biodiversity from Western Australia. We fit a pairwise interaction Gibbs marked point process to the data using a Bayesian approach and quantify the inhibitory interactions within and between the two species. We quantitatively discriminate between competing models corresponding to different inter-specific and intraspecific interactions via posterior model probabilities. The analysis provides evidence that the intraspecific interactions for the two species of the genus Banksia are generally similar to those between the two species providing some evidence for mechanisms that sustain biodiversity.Publisher PDFPeer reviewe

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

Area Interaction Point Processes for Bivariate Point Patterns in a Bayesian Context

In this paper we consider bivariate point patterns which may contain both attractive and inhibitive interactions. The two subpatterns may depend on each other with both intra- and interspecific interactions possible. We use area interaction point processes for quantifying both attractive and inhibitive interactions in contrast to pairwise interaction point processes, typically model regular point patterns. The ability to permit both attraction and repulsion is a valuable feature and allows for the modelling of different forms of interactions in a given community. The differentiation between intra- and interspecific interactions in one model accounts for the fact that the presence of a second species may "mask" or "magnify" existing intraspecific interactions. A Bayesian approach has been applied for estimating interaction parameters and for discriminating between eight competing research hypotheses. For the particular application to modelling the interactions of species in a highly biodiverse forest, this study reveals posterior support for an interspecific interaction of attraction between the two species considered and may serve to inform forest rehabilitation schemes relating to this forest. Overall, knowledge of the interactions of key species in any given forest would be invaluable to reforestation efforts if this forest is later ravaged by wildfires

The relationship between women’s empowerment and household food and nutrition security in Pakistan

Women’s empowerment is considered to play a crucial role in food and nutrition security. We aimed to explore the relationship between women’s empowerment and food and nutrition security, in rural Pakistan. Methods: To estimate women’s empowerment, we developed a Rural Women Composite Empowerment Index incorporating nine domains. For indicators of food and nutritional data we used data of 1879 rural households from Pakistan Rural Household Panel Survey (PRHPS). Food insecurity was measured through a caloric intake approach; nutrition insecurity was measured through recommended nutrient intake (RNI). Using the Rural Women’s Composite Empowerment Index (RWCEI), we employed multi-level mixed-effect regression analysis. Results: The domains of traveling safely (21%), time allocated to tasks (20%), and (lack of) domestic violence (19%) were the most significant domains in defining empowerment of rural woman. The prevalence of food and nutrition insecurity were 33% and 50% respectively. Regression analysis found a positive and significant relationship between women’s empowerment and food and nutrition security–the proportion of household who were food and nutritionally secure in empowered households was 70% and 98% respectively. Conclusions: Developing programmes and policies to improve the range of domains of women’s empowerment requires a focussed policy agenda, bringing together policy makers from a number of different sectors including education, economy, communications, technology and agriculture. Women’s empowerment has the potential to make positive changes not only in food and nutrition security, but in all aspects of family health and wellbeing

Analysis of the impact of COVID-19 on Scotland’s care-homes from March 2020 to October 2021:national linked data cohort analysis

Background: The impact of the COVID-19 pandemic on long-term care residents remains of wide interest, but most analyses focus on the initial wave of infections. Objective: To examine change over time in: (1) The size, duration, classification and pattern of care-home outbreaks of COVID-19 and associated mortality; (2) Characteristics associated with an outbreak.Design: Retrospective observational cohort study using routinely-collected dataSetting: All adult care-homes in Scotland (1,092 homes, 41,299 places)Methods: Analysis was undertaken at care-home level, over three periods. Period (P)1 01/03/2020-31/08/2020; P2 01/09/2020-31/05/2021 &amp; P3 01/06/2021-31/10/2021. Outcomes were the presence and characteristics of outbreaks and mortality within the care-home. Cluster analysis was used to compare the pattern of outbreaks. Logistic regression examined care-home characteristics associated with outbreaks. Results: In total 296 (27.1%) care-homes had one outbreak, 220 (20.1%) had two, 91 (8.3%) had three, and 68 (6.2%) had four or more. There were 1,313 outbreaks involving residents: 431 outbreaks in P1, 559 in P2 and 323 in P3. The COVID-19 mortality rate per 1,000 beds fell from 45.8 in P1, to 29.3 in P2, and 3.5 in P3. Larger care-homes were much more likely to have an outbreak, but associations between size and outbreaks were weaker in later periods. Conclusions: COVID-19 mitigation measures appear to have been beneficial, although the impact on residents remained severe until early 2021. Care-home residents, staff, relatives and providers are critical groups for consideration and involvement in future pandemic planning.Keywords Long-term care, COVID-19, epidemiology, care-homes, data linkage<br/

Fees, flows and imaginaries: exploring the destination choices arising from intra-national student mobility

Are intra-national student flows driven by the same forces as international student mobility? This paper addresses this question by analysing cross-border student mobility in the UK. The paper identifies four principles that one might expect to drive the destination choices of students from Scotland enrolling in English universities. Following a statistical analysis of student destination choices, it is argued that cross-border moves from Scotland to England are stimulated by some of the same global forces as international student mobility (such as a desire to accumulate cultural capital), but in terms of destination choice the imaginaries held by Scottish students of ‘good’ places to study in England to accumulate cultural capital are constructed differently from the imaginaries of international students

Public attitudes to, and perceived impacts of 20mph (32 km/h) speed limits in Edinburgh:An exploratory study using the Speed Limits Perceptions Survey (SLiPS)

The ‘Is 20 plenty for health?’ study is funded by a National Institute for Health Research (NIHR) Public Health Research (PHR) grant 15/82/12.Between 2016 and 2018 a policy was implemented to increase the proportion of 20mph (32km/h) streets in Edinburgh, UK from approximately 50% to 80%, providing the opportunity to evaluate how behaviour and public perceptions change over time. This is important as negative public responses have been reported to limit the implementation of transport policies and may reduce the effectiveness of the policy. The Speed Limits Perception Survey (SLiPS) was developed to assess changes in public perceptions from baseline to 6 and 12 months post-implementation. We collected 3,485 individual responses to the survey, 64.6% (n = 2,253) of which included complete perceptions data. Using exploratory factor analysis, the following perception factors were identified: i) Detraction and resistance, ii) Support, iii) Rule following, iv) Child safety, and v) Walking safety. Following the 20mph implementation at 6–12 months: Support (ii) and Rule following (iii) had increased; Detraction and resistance (i) had decreased; and Child safety (iv) and Walking safety (v) had not changed significantly. These findings indicate that the public in Edinburgh became more positive towards the policy once it was implemented. However, more extensive policy or ongoing communication of the safety benefits of 20mph limits are needed to increase perceptions of safety that might lead to increased walking and cycling. Future research should aim to understand how those implementing speed limit interventions can positively influence public perceptions and how public perceptions about speed limits influence behaviour.Publisher PDFPeer reviewe

"Are we working (too) comfortably?”:Understanding the nature of and factors associated with sedentary behaviour when working in the home environment

Home working has increased due to COVID-19, but little is known about how this change has impacted the health risk behaviour of elevated sedentary time. The aim of this cross-sectional exploratory study was to assess occupational sitting behaviour when working at home, and use the Capability Opportunity Motivation-Behaviour (COM-B) model to identify influences on this behaviour. University staff (n = 267; 69% female; 92% white) who were predominantly working from home completed a questionnaire to assess sitting time, sitting breaks, demographic and occupational characteristics, and a 7-item COM-B questionnaire and open-ended questions to assess influences on time spent sitting whilst working from home. Data were analysed descriptively, a repeated measures ANOVA was used to determine differences in the COM-B items, and binary logistic regression was used to examine predictors of sitting time. Staff spent on average 89.5% (SD = 17.1) of their time sitting whilst working at home, and took an average of 1.36 (1.38) sitting breaks per hour. There were significant and meaningful differences in the influence of the COM factors on ability and willingness to reduce sitting behaviour (p < .0001; η(p)(2) = .38), and the open-ended responses added further context. The included variables accounted for 20.7% of variance in sitting behaviour, with age, sitting breaks, motivation-automatic, and opportunity-physical contributing significantly. Working from home leads to elevated levels of sitting, and the COM-B provides a useful model to identify key influences on ability and willingness to reduce sitting. Strategies incorporating regular breaks, habit formation/reversal, and restructuring the physical environment may be beneficial

Trend shifts in road traffic collisions - An application of Hidden Markov Models and Generalised Additive Models to assess the impact of the 20mph speed limit policy in Edinburgh

Empirical study of road traffic collision (RTCs) rates is challenging at small geographies due to the relative rarity of collisions and the need to account for secular and seasonal trends. In this paper, we demonstrate the successful application of Hidden Markov Models (HMMs) and Generalised Additive Models (GAMs) to describe RTCs time series using monthly data from the city of Edinburgh (STATS19) as a case study. While both models have comparable level of complexity, they bring different advantages. HMMs provide a better interpretation of the data-generating process, whereas GAMs can be superior in terms of forecasting. In our study, both models successfully capture the declining trend and the seasonal pattern with a peak in the autumn and a dip in the spring months. Our best fitting HMM indicates a change in a fast-declining-trend state after the introduction of the 20 mph speed limit in July 2016. Our preferred GAM explicitly models this intervention and provides evidence for a significant further decline in the RTCs. In a comparison between the two modelling approaches, the GAM outperforms the HMM in out-of-sample forecasting of the RTCs for 2018. The application of HMMs and GAMs to routinely collected data such as the road traffic data may be beneficial to evaluations of interventions and policies, especially natural experiments, that seek to impact traffic collision rates