Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    ‘What drives commuter behaviour?': a Bayesian clustering approach for understanding opposing behaviours in social surveys
    (Oxford University Press, 2019-08-23) Dawkins L; Williamson DB; Barr S; Lampkin SR
    The city of Exeter, UK, is experiencing unprecedented growth, putting pressure on traffic infrastructure. As well as traffic network management, understanding and influencing commuter behaviour is important for reducing congestion. Information about current commuter behaviour has been gathered through a large on‐line survey, and similar individuals have been grouped to explore distinct behaviour profiles to inform intervention design to reduce commuter congestion. Statistical analysis within societal applications benefit from incorporating available social scientist expert knowledge. Current clustering approaches for the analysis of social surveys assume that the number of groups and the within‐group narratives are unknown a priori. Here, however, informed by valuable expert knowledge, we develop a novel Bayesian approach for creating a clear opposing transport mode group narrative within survey respondents, simplifying communication with project partners and the general public. Our methodology establishes groups characterizing opposing behaviours based on a key multinomial survey question by constraining parts of our prior judgement within a Bayesian finite mixture model. Drivers of group membership and within‐group behavioural differences are modelled hierarchically by using further information from the survey. In applying the methodology we demonstrate how it can be used to understand the key drivers of opposing behaviours in any wider application.
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    Prevalence and genetic diversity of Theileria equi from horses in Xinjiang Uygur Autonomous region, China.
    (Elsevier B.V., 2023-07-01) Zhang Y; Shi Q; Laven R; Li C; He W; Zheng H; Liu S; Lu M; Yang DA; Guo Q; Chahan B
    Theileria equi is a tick-borne intracellular apicomplexan protozoan parasite that causes equine theileriosis (ET). ET is an economically important disease with a worldwide distribution that significantly impacts international horse movement. Horses are an essential part of the economy in Xinjiang which is home to ∼10% of all the horses in China. However, there is very limited information on the prevalence and genetic complexity of T. equi in this region. Blood samples from 302 horses were collected from May to September 2021 in Ili, Xinjiang, and subjected to PCR examination for the presence of T. equi. In addition, a Bayesian latent class model was employed to estimate the true prevalence of T. equi, and a phylogenetic analysis was carried out based on the 18S rRNA gene of T. equi isolates. Seventy-two horses (23.8%) were PCR positive. After accounting for the imperfect PCR test using a Bayesian latent class model, the estimated true prevalence differed considerably between age groups, being 10.8% (95%CrI: 5.8% - 17.9%) in ≤ 3-year-old horses and 35.7% (95%CrI: 28.1% - 44.5%) in horses that were > 3 year-old. All T. equi isolates had their 18S rRNA gene (430bp) sequenced and analyzed in order to identify whether there were multiple genotypes of T. equi in the Xinjiang horse population. All of the 18S rRNA genes clustered into one phylogenetic group, clade E, which is thus probably the dominant genotype of T. equi in Xinjiang, China. To summarize, we monitored the prevalence of T. equi in horses of Xinjiang, China, with a focus on the association between age and the occurrence of T. equi by Bayesian modelling, accompanied by the genotyping of T. equi isolates. Obtaining the information on genotypes and age structure is significant in monitoring the spread of T. equi and studying the factors responsible for the distribution.