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Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model.

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Title: Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model.
Authors: Huang, Xiaodong1, Clements, Archie C.A.2, Williams, Gail3, Mengersen, Kerrie4, Tong, Shilu1, Hu, Wenbiao1 w2.hu@qut.edu.au
Source: Environmental Research. Apr2016, Vol. 146, p308-314. 7p.
Subjects: H1N1 influenza, Bayesian analysis, Spatiotemporal processes, Estimation theory, Infectious disease transmission
Geographic Terms: Queensland
Abstract: Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with t he transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Research is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model.
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  Data: <searchLink fieldCode="AR" term="%22Huang%2C+Xiaodong%22">Huang, Xiaodong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Clements%2C+Archie+C%2EA%2E%22">Clements, Archie C.A.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Williams%2C+Gail%22">Williams, Gail</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Mengersen%2C+Kerrie%22">Mengersen, Kerrie</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Tong%2C+Shilu%22">Tong, Shilu</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Hu%2C+Wenbiao%22">Hu, Wenbiao</searchLink><relatesTo>1</relatesTo><i> w2.hu@qut.edu.au</i>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Research%22">Environmental Research</searchLink>. Apr2016, Vol. 146, p308-314. 7p.
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  Data: Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with t he transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Research is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.envres.2016.01.013
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        Text: English
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        StartPage: 308
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      – SubjectFull: H1N1 influenza
        Type: general
      – SubjectFull: Bayesian analysis
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      – SubjectFull: Spatiotemporal processes
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      – SubjectFull: Estimation theory
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      – SubjectFull: Infectious disease transmission
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      – SubjectFull: Queensland
        Type: general
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      – TitleFull: Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model.
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              Text: Apr2016
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