469 resultados para Thomsen disease


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Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

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Barmah Forest Virus (BFV) disease is the most rapidly emerging mosquito-borne disease in Australia. BFV transmission depends on factors such as climate, virus, vector and the human population. However, the impact of climatic and social factors on BFV remains to be determined. This paper provided an overview of current research and discusses the future research directions on the BFV transmission. These research findings could be regarded as an impetus towards BFV prevention and control strategies.

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Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.