Microsimulation for demography

Background: Microsimulation consists of a set of techniques for estimating characteristics and modelling change in populations of individuals. Aims: To demonstrate how microsimulation can be used by demographers who want to undertake population estimates and projections. Data and methods: We use data from the 2011 United Kingdom (UK) Census of population to create a synthetic population by age, sex and ethnic group. Static and dynamic microsimulations and the visualisation of results are undertaken using the statistical package R. The code and data used in the static and dynamic microsimulation are available via a GitHub repository. Results: A synthetic population in 2011 by age, sex and ethnicity was produced for the East London Borough of Tower Hamlets, estimated from two Census tables. A population projection was produced for each of these age, sex and ethnicity groups to 2021. We used a projection of the Bangladeshi population to visualise population growth by Middle-layer Super Output Area (MSOA) and to produce a population pyramid of estimates in 2021. Conclusions: We argue that microsimulation is an adaptable technique which is well suited to demography, for both population estimation and projection. Although our example is applied to the East London Borough of Tower Hamlets, the approach could be readily applied in Australia, or any other country

Survey-based naming conventions for use in OBO Foundry ontology development

A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data

The roles of intolerance of uncertainty, anxiety sensitivity and distress tolerance in hoarding disorder compared with OCD and healthy controls

Background: It is suggested that the different psychological vulnerability factors of intolerance of uncertainty (IU), anxiety sensitivity (AS) and distress tolerance (DT) may be in important in hoarding disorder (HD). However, the extent to which these factors are specific to HD compared with other disorders remains unclear. Aims: The current study aimed to investigate differences in IU, AS and DT in three groups: HD (n=66), obsessive compulsive disorder (OCD; n=59) and healthy controls (HCs; n=63). Method: Participants completed an online battery of standardised self-report measures to establish the independent variable of group membership (HD, OCD and HC) and the dependent variables (IU, AS and DT). Results: A MANOVA analysis indicated statistically significant differences in IU, AS and DT between the clinical groups and HCs. Follow-up analyses showed no statistically significant differences between the HD and OCD group for any of the three constructs. The results remained the same when examining the effects of co-morbid HD and OCD. An unexpected finding was the trend for IU, AS and DT to be more severe when HD and OCD were co-morbid. Conclusions: The evidence suggests the absence of a specific relationship between IU, AS or DT in HD and instead is consistent with existing research which suggests that these psychological vulnerability factors are transdiagnostic constructs across anxiety disorders. The implications of the findings are discussed