ArticlePloS one2011
Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 37 citations in OpenAlex.
- Arbovirus Transmission in Australia from 2002 to 2017.Biology · 2024Article
- Insights into Antibody-Mediated Alphavirus Immunity and Vaccine Development Landscape.Microorganisms · 2021Review
- Spatiotemporal Assessment of COVID-19 Spread over Oman Using GIS Techniques.Earth systems and environment · 2020Article
- Plasmodium co-infection protects against chikungunya virus-induced pathologies.Nature communications · 2018Article
- Mosquitoes as Suitable Vectors for Alphaviruses.Viruses · 2018Review
- The emergence of arthropod-borne viral diseases: A global prospective on dengue, chikungunya and zika fevers.Acta tropica · 2017Review
- Spatiotemporal transmission dynamics of hemorrhagic fever with renal syndrome in China, 2005-2012.PLoS neglected tropical diseases · 2014Article
- Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012.PloS one · 2014Article
- Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.PloS one · 2013Article
- Molecular mechanisms involved in the pathogenesis of alphavirus-induced arthritis.BioMed research international · 2013Review
- Spatial patterns of high Aedes aegypti oviposition activity in northwestern Argentina.PloS one · 2013Article
- Spatiotemporal patterns of Japanese encephalitis in China, 2002-2010.PLoS neglected tropical diseases · 2013Article
- Surveillance should be strengthened to improve epidemiological understandings of mosquito-borne Barmah Forest virus infection.Western Pacific surveillance and response journal : WPSAR · 2012Article
- Arthritogenic alphaviruses--an overview.Nature reviews. Rheumatology · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBarmah 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
findingsWe 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 (χ(2) = 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.
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