Giuseppe
Emeritus
[Source: PLoS ONE, full text: (LINK). Abstract, edited.]
Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia
Suchithra Naish<SUP>1</SUP><SUP>*</SUP>, Wenbiao Hu<SUP>2</SUP>, Kerrie Mengersen<SUP>3</SUP>, Shilu Tong<SUP>1</SUP>
1 School of Public Health, Queensland University of Technology, Brisbane, Queensland, Australia, 2 School of Population Health, The University of Queensland, Brisbane, Queensland, Australia, 3 Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Abstract
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 (χ<SUP>2</SUP> = 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.
Citation: Naish S, Hu W, Mengersen K, Tong S (2011) Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia. PLoS ONE 6(10): e25688. doi:10.1371/journal.pone.0025688
Editor: Abdisalan Mohamed Noor, Kenya Medical Research Institute - Wellcome Trust Research Programme, Kenya
Received: June 30, 2011; Accepted: September 8, 2011; Published: October 13, 2011
Copyright: ? 2011 Naish et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: SN is supported by a QUT Scholarship. ST is supported by an NHMRC Research Fellowship (#553043) and WH is funded an NHMRC Postdoctoral Research Training Fellowship (#519788). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: s.naish@qut.edu.au
- ------Suchithra Naish<SUP>1</SUP><SUP>*</SUP>, Wenbiao Hu<SUP>2</SUP>, Kerrie Mengersen<SUP>3</SUP>, Shilu Tong<SUP>1</SUP>
1 School of Public Health, Queensland University of Technology, Brisbane, Queensland, Australia, 2 School of Population Health, The University of Queensland, Brisbane, Queensland, Australia, 3 Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Abstract
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 (χ<SUP>2</SUP> = 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.
Citation: Naish S, Hu W, Mengersen K, Tong S (2011) Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia. PLoS ONE 6(10): e25688. doi:10.1371/journal.pone.0025688
Editor: Abdisalan Mohamed Noor, Kenya Medical Research Institute - Wellcome Trust Research Programme, Kenya
Received: June 30, 2011; Accepted: September 8, 2011; Published: October 13, 2011
Copyright: ? 2011 Naish et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: SN is supported by a QUT Scholarship. ST is supported by an NHMRC Research Fellowship (#553043) and WH is funded an NHMRC Postdoctoral Research Training Fellowship (#519788). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: s.naish@qut.edu.au