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OBJECTIVE: We undertook an integrated analysis of genomic and epidemiological data to investigate a large health-care-associated outbreak of coronavirus disease 2019 (COVID-19) and to better understand the epidemiology of COVID-19 cases in Tasmania, Australia. METHODS: Epidemiological data collected on COVID-19 cases notified in Tasmania between 2 March and 15 May 2020, and positive samples of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or RNA extracted from the samples were included. Sequencing was conducted by tiled amplicon polymerase chain reaction with ARTIC v1 or v3 primers and Illumina sequencing. Consensus sequences were generated, sequences were aligned to a reference sequence and phylogenetic analysis was performed. Genomic clusters were determined and integrated with epidemiological data to provide additional information. RESULTS: All 231 COVID-19 cases notified in Tasmania during the study period and 266 SARS-CoV-2-positive samples, representing 217/231 (94%) notified cases, were included; 184/217 (84%) were clustered, 21/217 (10%) were unique and 12/217 (6%) could not be sequenced. Genomics confirmed the presence of seven clusters already identified through epidemiological links, clarified transmission networks in which the epidemiology had been unclear and identified one cluster that had not previously been recognized. DISCUSSION: Genomic analysis provided useful additional information on COVID-19 in Tasmania, including evidence of a large health-care-associated outbreak linked to an overseas cruise, the probable source of infection in cases with no previously identified epidemiological link and confirmation that there was no identified community transmission from other imported cases. Genomic insights are an important component of the response to COVID-19, and continuing genomic surveillance is warranted.

Globally, and nationally in Australia, bushfires are expected to increase in frequency and intensity due to climate change. To date, protection of human health from fire smoke has largely relied on individual-level actions. Recent bushfires experienced during the Australian summer of 2019-2020 occurred over a prolonged period and encompassed far larger geographical areas than previously experienced, resulting in extreme levels of smoke for extended periods of time. This particular bushfire season resulted in highly challenging conditions, where many people were unable to protect themselves from smoke exposures. The Centre for Air pollution, energy and health Research (CAR), an Australian research centre, hosted a two-day symposium, Landscape Fire Smoke: Protecting health in an era of escalating fire risk, on 8 and 9 October 2020. One component of the symposium was a dedicated panel discussion where invited experts were asked to examine alternative policy settings for protecting health from fire smoke hazards with specific reference to interventions to minimise exposure, protection of outdoor workers, and current systems for communicating health risk. This paper documents the proceedings of the expert panel and participant discussion held during the workshop.

ISSUE ADDRESSED: Physical activity is lower and rates of preventable common diseases are higher in regional/rural than urban Australia. Active commuting (walking/bicycling to get from one place to another) may benefit health through increased physical activity, but most evidence of its correlates come from urban studies. This study aimed to investigate associations between active commuting, socio-demographic characteristics, behaviours, total physical activity and health in a regional/rural Australian state. METHODS: This study used data from the 2016 Tasmanian Population Health Survey, a representative cross-sectional self-report survey of 6,300 adults in Tasmania, Australia. Logistic regression modelling investigated associations between socio-demographic, behavioural and health characteristics and past week active commuting frequency. RESULTS: In multivariable models, being younger, having tertiary qualifications, living in a socio-economically advantaged area, being physically active, having a healthy body mass index and good/excellent self-rated health were associated with engaging in more active commuting. Inner regional dwellers were no more likely than outer regional dwellers to actively commute after covariate adjustment. CONCLUSION: Strategies to promote active commuting in regional/rural areas might consider targeting older adults, those less educated, those living in socio-economically disadvantaged areas, those less physically active, those with poorer health and those with higher body mass index. Research could further investigate why these groups appear to be less active for commuting purposes. SO WHAT?: Increasing physical activity and active commuting may help to reduce rates of preventable common diseases in regional/remote areas.