Intra-urban risk assessment of occupational injuries and illnesses associated with current and projected climate: Evidence from three largest Australian cities.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Rat-bites of an epidemic proportion in Peshawar vale; a GIS based approach in risk assessment.

Contemporary studies demonstrate that rodent bites do not occur frequently. However, a huge number of cases were reported from Peshawar vale, Pakistan during 2016. Two species, the local black rat Rattus rattus (Linnaeus, 1758) and the invasive brown rat Rattus norvegicus (Berkenhout, 1769) might be the suspected cause. Several studies indicated the invasion of brown rats into Pakistan presumably via port city of Karachi. In this study, we modeled geospatial distribution of rodent bites for risk assessment in the region. Bite cases reported to tertiary care lady reading hospital were monitored from January 1 to August 31, 2016. Among 1747 cases, statistically informative data (n = 1295) was used for analyses. MaxEnt algorithm was employed for geospatial modeling, taking into account various environmental variables (temperature, precipitation, humidity, and elevation) and anthropogenic factors (human population density, distance from roads, distance from water channels, and land use/land cover). MaxEnt results revealed that urban slums (84.5%) are at highest risk followed by croplands (10.9%) and shrublands (2.7%). Anthropogenic factors affecting incidence of rodent bites included host density (contribution: 34.7), distance from water channels (3.2), land use/land cover (2.8), and distance from roads (2). Most of the cases occurred within a radius of 0.3 km from roads and 5 km from water channels. Rodent bite incidence is currently at its peak in Peshawar vale. Factors significantly affecting rodents' bite activity and their distribution and dispersal include urbanization, distance from roads, and water channels. Further studies are needed to determine the impact of invasion by brown rat on bite incidence.