Multimodeling approach to evaluating the efficacy of layering pharmaceutical and nonpharmaceutical interventions for influenza pandemics.

When an influenza pandemic emerges, temporary school closures and antiviral treatment may slow virus spread, reduce the overall disease burden, and provide time for vaccine development, distribution, and administration while keeping a larger portion of the general population infection free. The impact of such measures will depend on the transmissibility and severity of the virus and the timing and extent of their implementation. To provide robust assessments of layered pandemic intervention strategies, the Centers for Disease Control and Prevention (CDC) funded a network of academic groups to build a framework for the development and comparison of multiple pandemic influenza models. Research teams from Columbia University, Imperial College London/Princeton University, Northeastern University, the University of Texas at Austin/Yale University, and the University of Virginia independently modeled three prescribed sets of pandemic influenza scenarios developed collaboratively by the CDC and network members. Results provided by the groups were aggregated into a mean-based ensemble. The ensemble and most component models agreed on the ranking of the most and least effective intervention strategies by impact but not on the magnitude of those impacts. In the scenarios evaluated, vaccination alone, due to the time needed for development, approval, and deployment, would not be expected to substantially reduce the numbers of illnesses, hospitalizations, and deaths that would occur. Only strategies that included early implementation of school closure were found to substantially mitigate early spread and allow time for vaccines to be developed and administered, especially under a highly transmissible pandemic scenario.

Sexually transmissible infections (STI) and HIV testing and diagnosis among Aboriginal and non-Aboriginal adolescents in contact with the Australian justice system: a cross-sectional study.

BACKGROUND: It is unclear what factors are associated with sexually transmissible infections (STI) and HIV testing and diagnosis among justice-involved adolescents, and if these differ for Aboriginal or Torres Strait Islander peoples. METHODS: A cross-sectional survey of 465 justice-involved adolescents (aged 14-17years) from Australia was conducted between 2016 and 2018. Participants were asked about sexual behaviours, STI/HIV knowledge, and prior STI diagnoses and testing. RESULTS: Approximately 38% (n =130) of those sexually active had ever been screened for STI/HIV and 17.8% (n =23) had been diagnosed with an STI. No participant reported living with HIV. For Aboriginal participants, being male (aOR 3.6, 95% CI 1.3-10.1) and having under three sexual partners in the past 12months (aOR 3.1, 95% CI 1.2-8.0) was associated with never having had an STI/HIV test. For non-Aboriginal participants, being male (aOR 2.7, 95%CI 1.2-5.7), single (aOR 2.4, 95% CI 1.2-4.9), attending school (aOR 2.4, 95% CI 1.1-5.1), not having sought sexual health information (aOR 2.8, 95% CI 1.4-5.8), and having a lower STI/HIV knowledge score (aOR 2.3, 95% CI 1.1-5.0) were associated with never having had an STI/HIV test. Factors associated with STI diagnosis were non-heterosexual sexual orientation (aOR 5.6, 95% CI 1.1-28.2), transactional sex (aOR 11.2, 95% CI 3.0-41.3), and having sought sexual health information (aOR 3.5, 95% CI 1.0-12.5). CONCLUSIONS: Males, particularly Aboriginal male adolescents, should be engaged with sexual health promotion and testing services as soon as they come into contact with the justice system. Approaches should consider different cultural, gender and sexual orientations.

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support.

This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of (i) an automatic semantic-aware scheduling method that coordinates jobs across two separate high performance computing systems; (ii) a data pipeline to collect, integrate and organize national and county-level disaggregated data for initialization and post-simulation analysis; (iii) a digital twin of national social contact networks made up of 288 Million individuals and 12.6 Billion time-varying interactions covering the US states and DC; (iv) an extension of a parallel agent-based simulation model to study epidemic dynamics and associated interventions. This pipeline can run 400 replicates of national runs in less than 33 h, and reduces the need for human intervention, resulting in faster turnaround times and higher reliability and accuracy of the results. Scientifically, the work has led to significant advances in real-time epidemic sciences.

What patient assessment skills do pharmacist independent prescribers require to prescribe immunomodulators in myeloma?

AIM: To gain consensus on the patient assessment skills required by pharmacist independent prescribers prescribing immunomodulators in myeloma across National Health Service Scotland. METHODS: This was a two-phase study which used nominal group technique to gain local consensus followed by a two-round eDelphi questionnaire to gain national consensus across all cancer networks. SETTING: This project was conducted across the three cancer networks within NHS Scotland: South East Scotland Cancer Network; West of Scotland Cancer Network and North Cancer Alliance. SUBJECTS: Participants were invited from each cancer network (South East Scotland Cancer Network, West of Scotland Cancer Network and North Cancer Alliance) and included haematology consultants, haematology specialist registrars, haematology advanced nurse practitioners and haematology pharmacists. RESULTS: There were five participants in the nominal group technique. Twenty-two out of 31 patient assessment skills gained local consensus, seven patient assessment skills did not gain consensus and two patient assessment skills were deemed irrelevant. There were 12 and 14 participants in round one and two of the eDelphi questionnaire, respectively. Twenty-nine patient assessment skills were included in the first-round questionnaire and 21 gained consensus. The remaining eight patient assessment skills were included in round two where seven did not achieve consensus and one achieved disagreement consensus. CONCLUSION: This research outlines 21 patient assessment skills required for pharmacist independent prescribers to prescribe immunomodulators for myeloma patients according to haematology specialists in Scotland. Discussion on patient assessment skills without consensus showed that the pharmacist independent prescribers would have a shared responsibility with the consultant. This work should inform the development of a competency framework to allow training of pharmacist independent prescribers in Scotland. Some patient assessment skills could be transferrable for pharmacist independent prescribers prescribing systemic anti-cancer therapy for other haematological malignancies.

"That's the Lowest Place on Earth!" Experiences of the Carceral Spaces of Australian Police Custody for Marginalized Young Men.

Young men are overrepresented among people detained in police custody in Victoria, Australia, a closed institution that has mostly escaped public scrutiny. Our study sheds light on this underexamined place from the perspective of 28 marginalized young men (aged 19-24) detained there prior to adult prison. Drawing on Bacchi's "What's the problem represented to be?" approach and the subdiscipline of carceral geography, we disrupt the assumed purpose of police custody as a place to simply detain people while awaiting court and/or transfer to prison. We illustrate how police custody, although ostensibly for ensuring the safety and protection of the community, privileges that of some over others, with detrimental effects for marginalized groups. We highlight how harsh, degrading, hostile environments intersected with lived experiences and exacerbated psychological, social, and physical health harms; made possible young men's constitution as dirty, violent, and subhuman; and worked to legitimize breaches of human rights.

EpiViewer: an epidemiological application for exploring time series data.

BACKGROUND: Visualization plays an important role in epidemic time series analysis and forecasting. Viewing time series data plotted on a graph can help researchers identify anomalies and unexpected trends that could be overlooked if the data were reviewed in tabular form; these details can influence a researcher's recommended course of action or choice of simulation models. However, there are challenges in reviewing data sets from multiple data sources - data can be aggregated in different ways (e.g., incidence vs. cumulative), measure different criteria (e.g., infection counts, hospitalizations, and deaths), or represent different geographical scales (e.g., nation, HHS Regions, or states), which can make a direct comparison between time series difficult. In the face of an emerging epidemic, the ability to visualize time series from various sources and organizations and to reconcile these datasets based on different criteria could be key in developing accurate forecasts and identifying effective interventions. Many tools have been developed for visualizing temporal data; however, none yet supports all the functionality needed for easy collaborative visualization and analysis of epidemic data. RESULTS: In this paper, we present EpiViewer, a time series exploration dashboard where users can upload epidemiological time series data from a variety of sources and compare, organize, and track how data evolves as an epidemic progresses. EpiViewer provides an easy-to-use web interface for visualizing temporal datasets either as line charts or bar charts. The application provides enhanced features for visual analysis, such as hierarchical categorization, zooming, and filtering, to enable detailed inspection and comparison of multiple time series on a single canvas. Finally, EpiViewer provides several built-in statistical Epi-features to help users interpret the epidemiological curves. CONCLUSION: EpiViewer is a single page web application that provides a framework for exploring, comparing, and organizing temporal datasets. It offers a variety of features for convenient filtering and analysis of epicurves based on meta-attribute tagging. EpiViewer also provides a platform for sharing data between groups for better comparison and analysis. Our user study demonstrated that EpiViewer is easy to use and fills a particular niche in the toolspace for visualization and exploration of epidemiological data.

GenoLIB: a database of biological parts derived from a library of common plasmid features.

Synthetic biologists rely on databases of biological parts to design genetic devices and systems. The sequences and descriptions of genetic parts are often derived from features of previously described plasmids using ad hoc, error-prone and time-consuming curation processes because existing databases of plasmids and features are loosely organized. These databases often lack consistency in the way they identify and describe sequences. Furthermore, legacy bioinformatics file formats like GenBank do not provide enough information about the purpose of features. We have analyzed the annotations of a library of ∼2000 widely used plasmids to build a non-redundant database of plasmid features. We looked at the variability of plasmid features, their usage statistics and their distributions by feature type. We segmented the plasmid features by expression hosts. We derived a library of biological parts from the database of plasmid features. The library was formatted using the Synthetic Biology Open Language, an emerging standard developed to better organize libraries of genetic parts to facilitate synthetic biology workflows. As proof, the library was converted into GenoCAD grammar files to allow users to import and customize the library based on the needs of their research projects.

Development of a domain-specific genetic language to design Chlamydomonas reinhardtii expression vectors.

MOTIVATION: Expression vectors used in different biotechnology applications are designed with domain-specific rules. For instance, promoters, origins of replication or homologous recombination sites are host-specific. Similarly, chromosomal integration or viral delivery of an expression cassette imposes specific structural constraints. As de novo gene synthesis and synthetic biology methods permeate many biotechnology specialties, the design of application-specific expression vectors becomes the new norm. In this context, it is desirable to formalize vector design strategies applicable in different domains. RESULTS: Using the design of constructs to express genes in the chloroplast of Chlamydomonas reinhardtii as an example, we show that a vector design strategy can be formalized as a domain-specific language. We have developed a graphical editor of context-free grammars usable by biologists without prior exposure to language theory. This environment makes it possible for biologists to iteratively improve their design strategies throughout the course of a project. It is also possible to ensure that vectors designed with early iterations of the language are consistent with the latest iteration of the language. AVAILABILITY AND IMPLEMENTATION: The context-free grammar editor is part of the GenoCAD application. A public instance of GenoCAD is available at http://www.genocad.org. GenoCAD source code is available from SourceForge and licensed under the Apache v2.0 open source license.

Sequence verification of synthetic DNA by assembly of sequencing reads.

Gene synthesis attempts to assemble user-defined DNA sequences with base-level precision. Verifying the sequences of construction intermediates and the final product of a gene synthesis project is a critical part of the workflow, yet one that has received the least attention. Sequence validation is equally important for other kinds of curated clone collections. Ensuring that the physical sequence of a clone matches its published sequence is a common quality control step performed at least once over the course of a research project. GenoREAD is a web-based application that breaks the sequence verification process into two steps: the assembly of sequencing reads and the alignment of the resulting contig with a reference sequence. GenoREAD can determine if a clone matches its reference sequence. Its sophisticated reporting features help identify and troubleshoot problems that arise during the sequence verification process. GenoREAD has been experimentally validated on thousands of gene-sized constructs from an ORFeome project, and on longer sequences including whole plasmids and synthetic chromosomes. Comparing GenoREAD results with those from manual analysis of the sequencing data demonstrates that GenoREAD tends to be conservative in its diagnostic. GenoREAD is available at www.genoread.org.

Factors associated with unintended pregnancy and contraceptive practices in justice-involved adolescent girls in Australia.

INTRODUCTION: Despite a decline in unintended teenage pregnancy in Australia, rates remain higher amongst justice-involved adolescent girls, who are more likely to be from disadvantaged socio-economic backgrounds, have histories of abuse, substance use and/or mental health issues. Furthermore, exposure to the criminal justice system may alter access to education and employment and opportunities, potentially resulting in distinct risk-factor profiles. We examine factors associated with unintended pregnancy, non-contraceptive use and Long-Acting Reversible Contraception (LARC) in a sample of sexually active, justice-involved adolescent girls from Western Australia and Queensland. METHODS: Data from the Mental Health, Sexual Health and Reproductive Health of Young People in Contact with the Criminal Justice System (MeH-JOSH) Study was analysed on 118 sexually active adolescent girls. Participants were aged between 14 and 17 years, purposefully sampled based on justice-system involvement and completed an anonymous telephone survey. We constructed two multivariate models taking reproductive outcomes as the dependent variables. RESULTS: Over one quarter (26%, 30/118) reported a past unintended pregnancy, 54 did not use any contraception at their last sexual encounter, and 17 reported LARC use. Following adjustments in the multivariate analysis, lifetime ecstasy use was associated with both unintended pregnancy (aOR 3.795, p = 0.022) and non-contraception use (aOR 4.562, p = 0.004). A history of physical abuse was also associated with both any contraception (aOR 3.024, p = 0.041) and LARC use (aOR 4.892, p = 0.050). Identifying as Aboriginal & Torres Strait Islander, education/employment status and geographic location appeared to have no association. CONCLUSION: Our findings suggest that justice-involved adolescent girls have distinct risk factors associated with unplanned pregnancy and contraception use compared to the general population, but more research is required to understand the mechanisms and contexts underlying these risk factors. How exposure to physical violence may encourage contraception and LARC use, in particular, warrants further attention as does the association with ecstasy use.

Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections.

Scenario-based modeling frameworks have been widely used to support policy-making at state and federal levels in the United States during the COVID-19 response. While custom-built models can be used to support one-off studies, sustained updates to projections under changing pandemic conditions requires a robust, integrated, and adaptive framework. In this paper, we describe one such framework, UVA-adaptive, that was built to support the CDC-aligned Scenario Modeling Hub (SMH) across multiple rounds, as well as weekly/biweekly projections to Virginia Department of Health (VDH) and US Department of Defense during the COVID-19 response. Building upon an existing metapopulation framework, PatchSim, UVA-adaptive uses a calibration mechanism relying on adjustable effective transmissibility as a basis for scenario definition while also incorporating real-time datasets on case incidence, seroprevalence, variant characteristics, and vaccine uptake. Through the pandemic, our framework evolved by incorporating available data sources and was extended to capture complexities of multiple strains and heterogeneous immunity of the population. Here we present the version of the model that was used for the recent projections for SMH and VDH, describe the calibration and projection framework, and demonstrate that the calibrated transmissibility correlates with the evolution of the pathogen as well as associated societal dynamics.

Novel multi-cluster workflow system to support real-time HPC-enabled epidemic science: Investigating the impact of vaccine acceptance on COVID-19 spread.

We present MacKenzie, a HPC-driven multi-cluster workflow system that was used repeatedly to configure and execute fine-grained US national-scale epidemic simulation models during the COVID-19 pandemic. Mackenzie supported federal and Virginia policymakers, in real-time, for a large number of "what-if" scenarios during the COVID-19 pandemic, and continues to be used to answer related questions as COVID-19 transitions to the endemic stage of the disease. MacKenzie is a novel HPC meta-scheduler that can execute US-scale simulation models and associated workflows that typically present significant big data challenges. The meta-scheduler optimizes the total execution time of simulations in the workflow, and helps improve overall human productivity. As an exemplar of the kind of studies that can be conducted using Mackenzie, we present a modeling study to understand the impact of vaccine-acceptance in controlling the spread of COVID-19 in the US. We use a 288 million node synthetic social contact network (digital twin) spanning all 50 US states plus Washington DC, comprised of 3300 counties, with 12 billion daily interactions. The highly-resolved agent-based model used for the epidemic simulations uses realistic information about disease progression, vaccine uptake, production schedules, acceptance trends, prevalence, and social distancing guidelines. Computational experiments show that, for the simulation workload discussed above, MacKenzie is able to scale up well to 10K CPU cores. Our modeling results show that, when compared to faster and accelerating vaccinations, slower vaccination rates due to vaccine hesitancy cause averted infections to drop from 6.7M to 4.5M, and averted total deaths to drop from 39.4K to 28.2K across the US. This occurs despite the fact that the final vaccine coverage is the same in both scenarios. We also find that if vaccine acceptance could be increased by 10% in all states, averted infections could be increased from 4.5M to 4.7M (a 4.4% improvement) and total averted deaths could be increased from 28.2K to 29.9K (a 6% improvement) nationwide.

GenoCAD for iGEM: a grammatical approach to the design of standard-compliant constructs.

One of the foundations of synthetic biology is the project to develop libraries of standardized genetic parts that could be assembled quickly and cheaply into large systems. The limitations of the initial BioBrick standard have prompted the development of multiple new standards proposing different avenues to overcome these shortcomings. The lack of compatibility between standards, the compliance of parts with only some of the standards or even the type of constructs that each standard supports have significantly increased the complexity of assembling constructs from standardized parts. Here, we describe computer tools to facilitate the rigorous description of part compositions in the context of a rapidly changing landscape of physical construction methods and standards. A context-free grammar has been developed to model the structure of constructs compliant with six popular assembly standards. Its implementation in GenoCAD makes it possible for users to quickly assemble from a rich library of genetic parts, constructs compliant with any of six existing standards.

Nonfatal Strangulation During Domestic Violence Events in New South Wales: Prevalence and Characteristics Using Text Mining Study of Police Narratives.

Nonfatal strangulation (NFS) is a common form of domestic violence (DV) that frequently leaves no visible signs of injury and can be a portent for future fatality. A validated text mining approach was used to analyze a police dataset of 182,949 DV events for the presence of NFS. Results confirmed NFS within intimate partner relationships is a gendered form of violence. The presence of injury and/or other (non-NFS) forms of physical abuse, emotional/verbal/social abuse, and the perpetrator threatening to kill the victim, were associated with significantly higher odds of NFS perpetration. Police data contain rich information that can be accessed using automated methodologies such as text mining to add to our understanding of this pressing public health issue.

Scalable Epidemiological Workflows to Support COVID-19 Planning and Response.

The COVID-19 global outbreak represents the most significant epidemic event since the 1918 influenza pandemic. Simulations have played a crucial role in supporting COVID-19 planning and response efforts. Developing scalable workflows to provide policymakers quick responses to important questions pertaining to logistics, resource allocation, epidemic forecasts and intervention analysis remains a challenging computational problem. In this work, we present scalable high performance computing-enabled workflows for COVID-19 pandemic planning and response. The scalability of our methodology allows us to run fine-grained simulations daily, and to generate county-level forecasts and other counter-factual analysis for each of the 50 states (and DC), 3140 counties across the USA. Our workflows use a hybrid cloud/cluster system utilizing a combination of local and remote cluster computing facilities, and using over 20,000 CPU cores running for 6-9 hours every day to meet this objective. Our state (Virginia), state hospital network, our university, the DOD and the CDC use our models to guide their COVID-19 planning and response efforts. We began executing these pipelines March 25, 2020, and have delivered and briefed weekly updates to these stakeholders for over 30 weeks without interruption.

Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness.

We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 to 24 months to vaccinate their citizens. These time estimates and the emergence of new viral strains urge us to find quick and effective ways to allocate the vaccines and contain the pandemic. While current approaches use combinations of age-based and occupation-based prioritizations, our strategy marks a departure from such largely aggregate vaccine allocation strategies. We propose a novel approach motivated by recent advances in (i) science of real-world networks that point to efficacy of certain vaccination strategies and (ii) digital technologies that improve our ability to estimate some of these structural properties. Using a realistic representation of a social contact network for the Commonwealth of Virginia, combined with accurate surveillance data on spatiotemporal cases and currently accepted models of within- and between-host disease dynamics, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals' degree (number of social contacts) and total social proximity time is significantly more effective than the currently used age-based allocation strategy in terms of number of infections, hospitalizations and deaths. Our results suggest that in just two months, by March 31, 2021, compared to age-based allocation, the proposed degree-based strategy can result in reducing an additional 56-110k infections, 3.2- 5.4k hospitalizations, and 700-900 deaths just in the Commonwealth of Virginia. Extrapolating these results for the entire US, this strategy can lead to 3-6 million fewer infections, 181-306k fewer hospitalizations, and 51-62k fewer deaths compared to age-based allocation. The overall strategy is robust even: (i) if the social contacts are not estimated correctly; (ii) if the vaccine efficacy is lower than expected or only a single dose is given; (iii) if there is a delay in vaccine production and deployment; and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are significant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed.

"A spray bottle and a lollipop stick": An examination of policy prohibiting sterile injecting equipment in prison and effects on young men with injecting drug use histories.

BACKGROUND: Australian young male prisoners with histories of injecting drug use are more likely to report injecting in prison, to do so more frequently, and to be involved in more un-safe injecting-related practices than their older counterparts. Despite international evidence that prison needle and syringe programs are both feasible and effective in reducing the harms associated with injecting drug use in prison, these young men do not have access to such equipment. METHODS: We critically analyse the interview transcripts of 28 young men with histories of injecting drug use who were recently released from adult prisons in Victoria, Australia, and prison drug policy text. We use Bacchi's 'What's the problem represented to be?' approach to examine how the 'problem' of injecting drug use in prison is represented in prison drug policy, including the assumptions that underpin these problematisations, and the subjectification and lived effects that are produced for the young men in our study. RESULTS: Our analysis reveals how prison drug policy enables the creation and re-use of homemade injecting equipment crafted from unsterile items found in prison, and that in doing so the policy produces a range of stigmatising subjectification effects and other harmful material effects (such as hepatitis C virus transmission and injecting related injury and harms). Findings highlight, how injecting drug use is represented in policy silences other ways of understanding the 'problem' that may have less harmful effects for incarcerated young men who inject drugs. CONCLUSION: We argue that somewhat paradoxically, the approach of prohibiting access to sterile injecting equipment in prison-which is constituted as a solution for addressing such harms-in fact helps to produce them.

From 5Vs to 6Cs: Operationalizing Epidemic Data Management with COVID-19 Surveillance.

The COVID-19 pandemic brought to the forefront an unprecedented need for experts, as well as citizens, to visualize spatio-temporal disease surveillance data. Web application dashboards were quickly developed to fill this gap, including those built by JHU, WHO, and CDC, but all of these dashboards supported a particular niche view of the pandemic (ie, current status or specific regions). In this paper, we describe our work developing our own COVID-19 Surveillance Dashboard, available at https://nssac.bii.virginia.edu/covid-19/dashboard/, which offers a universal view of the pandemic while also allowing users to focus on the details that interest them. From the beginning, our goal was to provide a simple visual way to compare, organize, and track near-real-time surveillance data as the pandemic progresses. Our dashboard includes a number of advanced features for zooming, filtering, categorizing and visualizing multiple time series on a single canvas. In developing this dashboard, we have also identified 6 key metrics we call the 6Cs standard which we propose as a standard for the design and evaluation of real-time epidemic science dashboards. Our dashboard was one of the first released to the public, and remains one of the most visited and highly used. Our group uses it to support federal, state and local public health authorities, and it is used by people worldwide to track the pandemic evolution, build their own dashboards, and support their organizations as they plan their responses to the pandemic. We illustrate the utility of our dashboard by describing how it can be used to support data story-telling - an important emerging area in data science.

Evaluating the impact of international airline suspensions on the early global spread of COVID-19.

Global airline networks play a key role in the global importation of emerging infectious diseases. Detailed information on air traffic between international airports has been demonstrated to be useful in retrospectively validating and prospectively predicting case emergence in other countries. In this paper, we use a well-established metric known as effective distance on the global air traffic data from IATA to quantify risk of emergence for different countries as a consequence of direct importation from China, and compare it against arrival times for the first 24 countries. Using this model trained on official first reports from WHO, we estimate time of arrival (ToA) for all other countries. We then incorporate data on airline suspensions to recompute the effective distance and assess the effect of such cancellations in delaying the estimated arrival time for all other countries. Finally we use the infectious disease vulnerability indices to explain some of the estimated reporting delays.

Aboriginal mothers in prison in Australia: a study of social, emotional and physical wellbeing.

OBJECTIVE: To describe the social, emotional and physical wellbeing of Aboriginal mothers in prison. METHODS: Cross-sectional survey, including a Short Form Health Survey (SF-12) and Kessler Psychological Distress Scale (5-item version) administered to Aboriginal women who self-identified as mothers. RESULTS: Seventy-seven Aboriginal mothers in New South Wales (NSW) and 84 in Western Australia (WA) participated in the study. Eighty-three per cent (n=59) of mothers in NSW were in prison for drug-related offences, 64.8% (n=46) of mothers in WA were in prison for offences committed under the influence of alcohol. Sixty-eight per cent (n=52) of mothers in NSW and 35% (n=28) of mothers in WA reported mental health problems. Physical (PCS) and Mental (MCS) component scores of SF-12 varied for mothers in NSW and WA. Mothers in NSW experienced poorer health and functioning than mothers in WA (NSW: PCS 49.5, MCS 40.6; WA: PCS 54.4, MCS 48.3) and high levels of psychological distress (NSW: 13.1; WA 10.1). CONCLUSIONS: Aboriginal mothers in prison have significant health needs associated with physical and mental health, and psychological distress. Implications for public health: Adoption of social and emotional wellbeing as an explanatory framework for culturally secure healthcare in prison is essential to improving health outcomes of Aboriginal mothers in prison in Australia.