Melbourne School of Psychological Sciences - Research Publications

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    Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic.
    Piraveenan, M ; Sawleshwarkar, S ; Walsh, M ; Zablotska, I ; Bhattacharyya, S ; Farooqui, HH ; Bhatnagar, T ; Karan, A ; Murhekar, M ; Zodpey, S ; Rao, KSM ; Pattison, P ; Zomaya, A ; Perc, M (The Royal Society, 2021-06-09)
    Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.
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    Time is of the essence: an application of a relational event model for animal social networks
    Patison, KP ; Quintane, E ; Swain, DL ; Robins, G ; Pattison, P (SPRINGER, 2015-05-01)
    Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregated to represent a relationship as part of one (or several) pictures of the network of relations among animals, in a way that parallels human social networks. This transformation entails loss of information about interaction timing and sequence, which are particularly important to understand the formation of relationships or their disruption. Here, we describe a new statistical model, termed the relational event model, that enables the analysis of fine-grained animal association data as a continuous time sequence without requiring aggregation of the data. We apply the model to a unique data set of interaction between familiar and unfamiliar steers during a series of 36 experiments to investigate the process of social disruption and relationship formation. We show how the model provides key insights into animal behaviour in terms of relationship building, the integration process of unfamiliar animals and group building dynamics. The relational event model is well suited to data structures that are common to animal behavioural studies and can therefore be applied to a range of social interaction data to understand animal social dynamics.
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    Hepatitis C Transmission and Treatment in Contact Networks of People Who Inject Drugs
    Rolls, DA ; Sacks-Davis, R ; Jenkinson, R ; McBryde, E ; Pattison, P ; Robins, G ; Hellard, M ; Noymer, A (PUBLIC LIBRARY SCIENCE, 2013-11-01)
    Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 estimated deaths attributed yearly to HCV-related liver diseases. It disproportionally affects people who inject drugs (PWID). Currently there is no preventative vaccine and interventions feature long treatment durations with severe side-effects. Upcoming treatments will improve this situation, making possible large-scale treatment interventions. How these strategies should target HCV-infected PWID remains an important unanswered question. Previous models of HCV have lacked empirically grounded contact models of PWID. Here we report results on HCV transmission and treatment using simulated contact networks generated from an empirically grounded network model using recently developed statistical approaches in social network analysis. Our HCV transmission model is a detailed, stochastic, individual-based model including spontaneously clearing nodes. On transmission we investigate the role of number of contacts and injecting frequency on time to primary infection and the role of spontaneously clearing nodes on incidence rates. On treatment we investigate the effect of nine network-based treatment strategies on chronic prevalence and incidence rates of primary infection and re-infection. Both numbers of contacts and injecting frequency play key roles in reducing time to primary infection. The change from "less-" to "more-frequent" injector is roughly similar to having one additional network contact. Nodes that spontaneously clear their HCV infection have a local effect on infection risk and the total number of such nodes (but not their locations) has a network wide effect on the incidence of both primary and re-infection with HCV. Re-infection plays a large role in the effectiveness of treatment interventions. Strategies that choose PWID and treat all their contacts (analogous to ring vaccination) are most effective in reducing the incidence rates of re-infection and combined infection. A strategy targeting infected PWID with the most contacts (analogous to targeted vaccination) is the least effective.
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    Hepatitis C Virus Phylogenetic Clustering Is Associated with the Social-Injecting Network in a Cohort of People Who Inject Drugs
    Sacks-Davis, R ; Daraganova, G ; Aitken, C ; Higgs, P ; Tracy, L ; Bowden, S ; Jenkinson, R ; Rolls, D ; Pattison, P ; Robins, G ; Grebely, J ; Barry, A ; Hellard, M ; Blackard, J (PUBLIC LIBRARY SCIENCE, 2012-10-26)
    It is hypothesized that social networks facilitate transmission of the hepatitis C virus (HCV). We tested for association between HCV phylogeny and reported injecting relationships using longitudinal data from a social network design study. People who inject drugs were recruited from street drug markets in Melbourne, Australia. Interviews and blood tests took place three monthly (during 2005-2008), with participants asked to nominate up to five injecting partners at each interview. The HCV core region of individual isolates was then sequenced and phylogenetic trees were constructed. Genetic clusters were identified using bootstrapping (cut-off: 70%). An adjusted Jaccard similarity coefficient was used to measure the association between the reported injecting relationships and relationships defined by clustering in the phylogenetic analysis (statistical significance assessed using the quadratic assignment procedure). 402 participants consented to participate; 244 HCV infections were observed in 238 individuals. 26 genetic clusters were identified, with 2-7 infections per cluster. Newly acquired infection (AOR = 2.03, 95% CI: 1.04-3.96, p = 0.037, and HCV genotype 3 (vs. genotype 1, AOR = 2.72, 95% CI: 1.48-4.99) were independent predictors of being in a cluster. 54% of participants whose infections were part of a cluster in the phylogenetic analysis reported injecting with at least one other participant in that cluster during the study. Overall, 16% of participants who were infected at study entry and 40% of participants with newly acquired infections had molecular evidence of related infections with at least one injecting partner. Likely transmission clusters identified in phylogenetic analysis correlated with reported injecting relationships (adjusted Jaccard coefficient: 0.300; p<0.001). This is the first study to show that HCV phylogeny is associated with the injecting network, highlighting the importance of the injecting network in HCV transmission.
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    Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks
    McCaw, JM ; Forbes, K ; Nathan, PM ; Pattison, PE ; Robins, GL ; Nolan, TM ; McVernon, J (BMC, 2010-06-10)
    BACKGROUND: Mathematical models of infection that consider targeted interventions are exquisitely dependent on the assumed mixing patterns of the population. We report on a pilot study designed to assess three different methods (one retrospective, two prospective) for obtaining contact data relevant to the determination of these mixing patterns. METHODS: 65 adults were asked to record their social encounters in each location visited during 6 study days using a novel method whereby a change in physical location of the study participant triggered data entry. Using a cross-over design, all participants recorded encounters on 3 days in a paper diary and 3 days using an electronic recording device (PDA). Participants were randomised to first prospective recording method. RESULTS: Both methods captured more contacts than a pre-study questionnaire, but ascertainment using the paper diary was superior to the PDA (mean difference: 4.52 (95% CI 0.28, 8.77). Paper diaries were found more acceptable to the participants compared with the PDA. Statistical analysis confirms that our results are broadly consistent with those reported from large-scale European based surveys. An association between household size (trend 0.14, 95% CI (0.06, 0.22), P < 0.001) and composition (presence of child 0.37, 95% CI (0.17, 0.56), P < 0.001) and the total number of reported contacts was observed, highlighting the importance of sampling study populations based on household characteristics as well as age. New contacts were still being recorded on the third study day, but compliance had declined, indicating that the optimal number of sample days represents a trade-off between completeness and quality of data for an individual. CONCLUSIONS: The study's location-based reporting design allows greater scope compared to other methods for examining differences in the characteristics of encounters over a range of environments. Improved parameterisation of dynamic transmission models gained from work of this type will aid in the development of more robust decision support tools to assist health policy makers and planners.
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    Beyond Bushfires: Community, Resilience and Recovery - a longitudinal mixed method study of the medium to long term impacts of bushfires on mental health and social connectedness
    Gibbs, L ; Waters, E ; Bryant, RA ; Pattison, P ; Lusher, D ; Harms, L ; Richardson, J ; MacDougall, C ; Block, K ; Snowdon, E ; Gallagher, HC ; Sinnott, V ; Ireton, G ; Forbes, D (BMC, 2013-11-04)
    BACKGROUND: Natural disasters represent an increasing threat both in terms of incidence and severity as a result of climate change. Although much is known about individual responses to disasters, much less is known about the social and contextual response and how this interacts with individual trajectories in terms of mental health, wellbeing and social connectedness. The 2009 bushfires in Victoria, Australia caused much loss of life, property destruction, and community disturbance. In order to progress future preparedness, response and recovery, it is crucial to measure and understand the impact of disasters at both individual and community levels. METHODS/DESIGN: This study aims to profile the range of mental health, wellbeing and social impacts of the Victorian 2009 bushfires over time using multiple methodologies and involving multiple community partners. A diversity of communities including bushfire affected and unaffected will be involved in the study and will include current and former residents (at the time of the Feb 2009 fires). Participants will be surveyed in 2012, 2014 and, funding permitting, in 2016 to map the predictors and outcomes of mental health, wellbeing and social functioning. Ongoing community visits, as well as interviews and focus group discussions in 2013 and 2014, will provide both contextual information and evidence of changing individual and community experiences in the medium to long term post disaster. The study will include adults, adolescents and children over the age of 5. DISCUSSION: Conducting the study over five years and focussing on the role of social networks will provide new insights into the interplay between individual and community factors and their influence on recovery from natural disaster over time. The study findings will thereby expand understanding of long term disaster recovery needs for individuals and communities.
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    A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models
    Rolls, DA ; Wang, P ; McBryde, E ; Pattison, P ; Robins, G ; Moreno, Y (PUBLIC LIBRARY SCIENCE, 2015-11-10)
    We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a "hidden population". In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure.
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    The effect of group involvement on post-disaster mental health: A longitudinal multilevel analysis
    Gallagher, HC ; Block, K ; Gibbs, L ; Forbes, D ; Lusher, D ; Molyneaux, R ; Richardson, J ; Pattison, P ; MacDougall, C ; Bryant, RA (PERGAMON-ELSEVIER SCIENCE LTD, 2019-01-01)
    Involvement in voluntary associations is a key form of social capital and plays an especially important role following disaster as a venue for coordination and decision-making for the wider community. Yet, relatively little attention has been paid to how group involvement affects mental health, at either the individual or community level. The aim of this study was to assess the impact of involvement in voluntary associations on mental health among residents of bushfire-affected communities. A longitudinal sample of 642 individuals affected by the 2009 Victorian bushfires in south-eastern Australia were surveyed in 2012 and 2014 (3- and 5-years post-disaster). A further subsample (n = 552) of residents residing continuously within 22 bushfire-affected communities were examined for community-level effects using multilevel regression methods. After adjusting for demographics, disaster exposure, and network variables, group involvement at time 1 bore a curvilinear relationship with PTSD at both time points: moderate involvement was most beneficial, with no participation, or high amounts, yielding poorer outcomes. High amounts of group involvement was likewise linked to a greater risk of major depression. Furthermore, communities with higher median levels of group involvement reported lower levels of PTSD symptoms and major depression two years later. With respect to group involvement, more is not always better. For individuals, moderation - if possible - is key. Meanwhile, community-level health benefits come when most people participate to some extent, suggesting that the distribution of involvement across the community is important.
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    Ethical Use and Impact of Participatory Approaches to Research in Post-Disaster Environments: An Australian Bushfire Case Study
    Gibbs, L ; Block, K ; MacDougall, C ; Harms, L ; Baker, E ; Richardson, J ; Ireton, G ; Gallagher, HC ; Bryant, R ; Lusher, D ; Pattison, P ; Watson, J ; Gillett, J ; Pirrone, A ; Molyneaux, R ; Sexton-Bruce, S ; Forbes, D (HINDAWI LTD, 2018-01-01)
    This paper presents a case study of Beyond Bushfires, a large, multisite, mixed method study of the psychosocial impacts of major bushfires in Victoria, Australia. A participatory approach was employed throughout the study which was led by a team of academic investigators in partnership with service providers and government representatives and used on-site visits and multiple methods of communication with communities across the state to inform decision-making throughout the study. The ethics and impacts of conducting and adapting the approach within a post-disaster context will be discussed in reference to theories and models of participatory health research. The challenges of balancing local interests with state-wide implications will also be explored in the description of the methods of engagement and the study processes and outcomes. Beyond Bushfires demonstrates the feasibility of incorporating participatory methods in large, post-disaster research studies and achieving rigorous findings and multilevel impacts, while recognising the potential for some of the empowering aspects of the participatory experience to be reduced by the scaled-up approach.
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    Influence of Contact Definitions in Assessment of the Relative Importance of Social Settings in Disease Transmission Risk
    Bolton, KJ ; McCaw, JM ; Forbes, K ; Nathan, P ; Robins, G ; Pattison, P ; Nolan, T ; McVernon, J ; Jefferson, T (PUBLIC LIBRARY SCIENCE, 2012-02-16)
    BACKGROUND: Realistic models of disease transmission incorporating complex population heterogeneities require input from quantitative population mixing studies. We use contact diaries to assess the relative importance of social settings in respiratory pathogen spread using three measures of person contact hours (PCH) as proxies for transmission risk with an aim to inform bipartite network models of respiratory pathogen transmission. METHODS AND FINDINGS: Our survey examines the contact behaviour for a convenience sample of 65 adults, with each encounter classified as occurring in a work, retail, home, social, travel or "other" setting. The diary design allows for extraction of PCH-interaction (cumulative time in face-face conversational or touch interaction with contacts)--analogous to the contact measure used in several existing surveys--as well as PCH-setting (product of time spent in setting and number of people present) and PCH-reach (product of time spent in setting and number of people in close proximity). Heterogeneities in day-dependent distribution of risk across settings are analysed using partitioning and cluster analyses and compared between days and contact measures. Although home is typically the highest-risk setting when PCH measures isolate two-way interactions, its relative importance compared to social and work settings may reduce when adopting a more inclusive contact measure that considers the number and duration of potential exposure events. CONCLUSIONS: Heterogeneities in location-dependent contact behaviour as measured by contact diary studies depend on the adopted contact definition. We find that contact measures isolating face-face conversational or touch interactions suggest that contact in the home dominates, whereas more inclusive contact measures indicate that home and work settings may be of higher importance. In the absence of definitive knowledge of the contact required to facilitate transmission of various respiratory pathogens, it is important for surveys to consider alternative contact measures.