tetano
Editor, Senior Moderator
Environ Int. 2012 May 7;45C:39-43. [Epub ahead of print]
Did socio-ecological factors drive the spatiotemporal patterns of pandemic influenza A (H1N1)?
Hu W, Williams G, Phung H, Birrell F, Tong S, Mengersen K, Huang X, Clements A.
Source
School of Population Health, The University of Queensland, Australia.
Abstract
BACKGROUND:
Pandemic influenza A (H1N1) has a significant public health impact. This study aimed to examine the effect of socio-ecological factors on the transmission of H1N1 in Brisbane, Australia.
METHODOLOGY:
We obtained data from Queensland Health on numbers of laboratory-confirmed daily H1N1 in Brisbane by statistical local areas (SLA) in 2009. Data on weather and socio-economic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive (CAR) model was used to quantify the relationship between variation of H1N1 and independent factors and to determine its spatiotemporal patterns.
RESULTS:
Our results show that average increase in weekly H1N1 cases were 45.04% (95% credible interval (CrI): 42.63-47.43%) and 23.20% (95% CrI: 16.10-32.67%), for a 1?C decrease in average weekly maximum temperature at a lag of one week and a 10mm decrease in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on H1N1 incidence was found (changes: 0.71%; 95% CrI: 0.48-0.98%). The auto-regression term was significantly associated with H1N1 transmission (changes: 2.5%; 95% CrI: 1.39-3.72). No significant association between socio-economic indexes for areas (SEIFA) and H1N1 was observed at SLA level.
CONCLUSIONS:
Our results demonstrate that average weekly temperature at lag of one week and rainfall at lag of one week were substantially associated with H1N1 incidence at a SLA level. The ecological factors seemed to have played an important role in H1N1 transmission cycles in Brisbane, Australia.
Copyright ? 2012 Elsevier Ltd. All rights reserved.
PMID:
22572115
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/22572115
Did socio-ecological factors drive the spatiotemporal patterns of pandemic influenza A (H1N1)?
Hu W, Williams G, Phung H, Birrell F, Tong S, Mengersen K, Huang X, Clements A.
Source
School of Population Health, The University of Queensland, Australia.
Abstract
BACKGROUND:
Pandemic influenza A (H1N1) has a significant public health impact. This study aimed to examine the effect of socio-ecological factors on the transmission of H1N1 in Brisbane, Australia.
METHODOLOGY:
We obtained data from Queensland Health on numbers of laboratory-confirmed daily H1N1 in Brisbane by statistical local areas (SLA) in 2009. Data on weather and socio-economic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive (CAR) model was used to quantify the relationship between variation of H1N1 and independent factors and to determine its spatiotemporal patterns.
RESULTS:
Our results show that average increase in weekly H1N1 cases were 45.04% (95% credible interval (CrI): 42.63-47.43%) and 23.20% (95% CrI: 16.10-32.67%), for a 1?C decrease in average weekly maximum temperature at a lag of one week and a 10mm decrease in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on H1N1 incidence was found (changes: 0.71%; 95% CrI: 0.48-0.98%). The auto-regression term was significantly associated with H1N1 transmission (changes: 2.5%; 95% CrI: 1.39-3.72). No significant association between socio-economic indexes for areas (SEIFA) and H1N1 was observed at SLA level.
CONCLUSIONS:
Our results demonstrate that average weekly temperature at lag of one week and rainfall at lag of one week were substantially associated with H1N1 incidence at a SLA level. The ecological factors seemed to have played an important role in H1N1 transmission cycles in Brisbane, Australia.
Copyright ? 2012 Elsevier Ltd. All rights reserved.
PMID:
22572115
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/22572115