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Abstract: This study aims to quantify the relationship between climate variations and cases of Salmonella infection in subtropical and tropical areas in Australia. Brisbane in a subtropical area and Townsville in a tropical area of Queensland were selected as the study regions. Local meteorological variables and notified cases of Salmonella infection from January 1990 to July 2005 were provided by local authorities. Spearman correlation and time-series adjusted Poisson regression were applied controlling for autoregression, lag effects, seasonal variation and long-term trend. Natural cubic spline and Hockey Stick model were used to estimate a potential threshold temperature. Spearman correlation indicated that maximum and minimum temperatures, relative humidity at 9am and 3pm, and rainfall were all positively correlated with the number of cases in both Brisbane and Townsville, with the lag values of the effects up to 2weeks in Brisbane and 2months in Townsville. Only temperature and rainfall were significantly included in the regression models in both regions. The models suggested that a potential 1°C rise in maximum or minimum temperature may cause a very similar increase in the number of cases in the two regions. No threshold for the effect of maximum or minimum temperature on Salmonella infection was detected in either region. The association between climate variations and Salmonella infection could be very similar in subtropical and tropical regions in Australia. Temperature and rainfall may be used as key meteorological predictors for the number of cases in both regions. [Copyright &y& Elsevier]

To assess the impact of weather on human mortality, particularly among elderly people and people with diseases, the authors conducted an ecological study in Brisbane, Australia. Correlation and autoregressive integrated moving average (ARIMA) regression analyses assessed the relationship between weather and mortality in the general population and the elderly population (65 years of age and older) over the period 1986-1995. In the summer, both cardiovascular diseases and all-cause mortality in the elderly population had significant positive correlations with monthly temperatures. In the winter, negative correlations were found between monthly mean maximum temperatures and cardiovascular-disease mortality, and between monthly mean minimum temperatures and respiratory-disease mortality. Regression models were developed for various target populations and produced similar results. [ABSTRACT FROM AUTHOR]

Increased risk of occupational injuries and illnesses (OI) is associated with ambient temperature. However, most studies have reported the average impacts within cities, states, or provinces at broader scales. We assessed the intra-urban risk of OI associated with ambient temperature in three Australian cities at statistical area level 3 (SA3). We collected daily workers' compensation claims data and gridded meteorological data from July 1, 2005, to June 30, 2018. Heat index was used as the primary temperature metric. We performed a two-stage time series analysis: we generated location-specific estimates using Distributed Lag Non-Linear Models (DLNM) and estimated the cumulative effects with multivariate meta-analysis. The risk was estimated at moderate heat (90th percentile) and extreme heat (99th percentile). Subgroup analyses were conducted to identify vulnerable groups of workers. Further, the OI risk in the future was estimated for two projected periods: 2016–2045 and 2036–2065. The cumulative risk of OI was 3.4% in Greater Brisbane, 9.5% in Greater Melbourne, and 8.9% in Greater Sydney at extreme heat. The western inland regions in Greater Brisbane (17.4%) and Greater Sydney (32.3%) had higher risk of OI for younger workers, workers in outdoor and indoor industries, and workers reporting injury claims. The urbanized SA3 regions posed a higher risk (19.3%) for workers in Greater Melbourne. The regions were generally at high risk for young workers and illness-related claims. The projected risk of OI increased with time in climate change scenarios. This study provides a comprehensive spatial profile of OI risk associated with hot weather conditions across three cities in Australia. Risk assessment at the intra-urban level revealed strong spatial patterns in OI risk distribution due to heat exposure. These findings provide much-needed scientific evidence for work, health, and safety regulators, industries, unions, and workers to design and implement location-specific preventative measures. • Western inland regions of Sydney and Brisbane are at greater risk of OI for workers. • Workers in regions with low NDVI and socio-economic status are vulnerable to heat. • Projected climate change (2016–3045, 2036–2065) will heighten heat-related OI risk. • Location-specific risk estimation of OI is crucial to mitigate the impacts of heat. [ABSTRACT FROM AUTHOR]