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Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia
In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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National Institute of Environmental Health Sciences
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1459919/ https://www.ncbi.nlm.nih.gov/pubmed/16675420 http://dx.doi.org/10.1289/ehp.8568 |
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author | Naish, Suchithra Hu, Wenbiao Nicholls, Neville Mackenzie, John S. McMichael, Anthony J. Dale, Pat Tong, Shilu |
author_facet | Naish, Suchithra Hu, Wenbiao Nicholls, Neville Mackenzie, John S. McMichael, Anthony J. Dale, Pat Tong, Shilu |
author_sort | Naish, Suchithra |
collection | PubMed |
description | In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. |
format | Text |
id | pubmed-1459919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | National Institute of Environmental Health Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-14599192006-05-23 Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia Naish, Suchithra Hu, Wenbiao Nicholls, Neville Mackenzie, John S. McMichael, Anthony J. Dale, Pat Tong, Shilu Environ Health Perspect Research In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. National Institute of Environmental Health Sciences 2006-05 2005-12-15 /pmc/articles/PMC1459919/ /pubmed/16675420 http://dx.doi.org/10.1289/ehp.8568 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. |
spellingShingle | Research Naish, Suchithra Hu, Wenbiao Nicholls, Neville Mackenzie, John S. McMichael, Anthony J. Dale, Pat Tong, Shilu Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia |
title | Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia |
title_full | Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia |
title_fullStr | Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia |
title_full_unstemmed | Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia |
title_short | Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia |
title_sort | weather variability, tides, and barmah forest virus disease in the gladstone region, australia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1459919/ https://www.ncbi.nlm.nih.gov/pubmed/16675420 http://dx.doi.org/10.1289/ehp.8568 |
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