An economic case for providing free access to antiretroviral therapy for HIV-positive people in South Australia

Background As financial constraints can be a barrier to accessing HIV antiretroviral therapy (ART), we argue for the removal of copayment requirements from HIV medications in South Australia. Methods Using a simple mathematical model informed by available behavioural and biological data and reflecting the HIV epidemiology in South Australia, we calculated the expected number of new HIV transmissions caused by persons who are not currently on ART compared with transmissions for people on ART. The extra financial investment required to cover the copayments to prevent an HIV infection was compared with the treatment costs saved due to averting HIV infections. Results It was estimated that one HIV infection is prevented per year for every 31.4 persons (median, 24.0–42.7 interquartile range (IQR)) who receive treatment. By considering the incremental change in costs and outcomes of a change in program from the current status quo, it would cost the health sector $17 860 per infection averted (median, $13 651–24 287 IQR) if ART is provided as a three-dose, three-drug combination without requirements for user-pay copayments. Conclusions The costs of removing copayment fees for ART are less than the costs of treating extra HIV infections that would result under current conditions. Removing the copayment requirement for HIV medication would be cost-effective from a governmental perspective.

The healthy immigrant effect: Patterns and evidence from four countries

The existence of a healthy immigrant effect—where immigrants are on average healthier than the native born—is a widely cited phenomenon across a multitude of literatures including epidemiology and the social sciences. There are many competing explanations. The goals of this paper are twofold: first, to provide further evidence on the presence of the healthy immigrant effect across source and destination country using a set of consistently defined measures of health; and second, to evaluate the role of selectivity as a potential explanation for the existence of the phenomenon. Utilizing data from four major immigrant recipient countries, USA, Canada, UK, and Australia allows us to compare the health of migrants from each with the respective native born who choose not to migrate. This represents a much more appropriate counterfactual than the native born of the immigrant recipient country and yields new insights into the importance of observable selection effects. The analysis finds strong support for the healthy immigrant effect across all four destination countries and that selectivity plays an important role in the observed better health of migrants vis a vis those who stay behind in their country of origin.

Understanding causal relationships between the built and social environment, health and associated behaviours and risk factors

Introduction: Built environment interventions designed to reduce non-communicable diseases and health inequity, complement urban planning agendas focused on creating more ‘liveable’, compact, pedestrian-friendly, less automobile dependent and more socially inclusive cities.However, what constitutes a ‘liveable’ community is not well defined. Moreover, there appears to be a gap between the concept and delivery of ‘liveable’ communities. The recently funded NHMRC Centre of Research Excellence (CRE) in Healthy Liveable Communities established in early 2014, has defined ‘liveability’ from a social determinants of health perspective. Using purpose-designed multilevel longitudinal data sets, it addresses five themes that address key evidence-base gaps for building healthy and liveable communities. The CRE in Healthy Liveable Communities seeks to generate and exchange new knowledge about: 1) measurement of policy-relevant built environment features associated with leading non-communicable disease risk factors (physical activity, obesity) and health outcomes (cardiovascular disease, diabetes) and mental health; 2) causal relationships and thresholds for built environment interventions using data from longitudinal studies and natural experiments; 3) thresholds for built environment interventions; 4) economic benefits of built environment interventions designed to influence health and wellbeing outcomes; and 5) factors, tools, and interventions that facilitate the translation of research into policy and practice. This evidence is critical to inform future policy and practice in health, land use, and transport planning. Moreover, to ensure policy-relevance and facilitate research translation, the CRE in Healthy Liveable Communities builds upon ongoing, and has established new, multi-sector collaborations with national and state policy-makers and practitioners. The symposium will commence with a brief introduction to embed the research within an Australian health and urban planning context, as well as providing an overall outline of the CRE in Healthy Liveable Communities, its structure and team. Next, an overview of the five research themes will be presented. Following these presentations, the Discussant will consider the implications of the research and opportunities for translation and knowledge exchange. Theme 2 will establish whether and to what extent the neighbourhood environment (built and social) is causally related to physical and mental health and associated behaviours and risk factors. In particular, research conducted as part of this theme will use data from large-scale, longitudinal-multilevel studies (HABITAT, RESIDE, AusDiab) to examine relationships that meet causality criteria via statistical methods such as longitudinal mixed-effect and fixed-effect models, multilevel and structural equation models; analyse data on residential preferences to investigate confounding due to neighbourhood self-selection and to use measurement and analysis tools such as propensity score matching and ‘within-person’ change modelling to address confounding; analyse data about individual-level factors that might confound, mediate or modify relationships between the neighbourhood environment and health and well-being (e.g., psychosocial factors, knowledge, perceptions, attitudes, functional status), and; analyse data on both objective neighbourhood characteristics and residents’ perceptions of these objective features to more accurately assess the relative contribution of objective and perceptual factors to outcomes such as health and well-being, physical activity, active transport, obesity, and sedentary behaviour. At the completion of the Theme 2, we will have demonstrated and applied statistical methods appropriate for determining causality and generated evidence about causal relationships between the neighbourhood environment, health, and related outcomes. This will provide planners and policy makers with a more robust (valid and reliable) basis on which to design healthy communities.