Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

Madhur S Dhingra; Jean Artois; Timothy P Robinson; Catherine Linard; Celia Chaiban; Ioannis Xenarios; Robin Engler; Robin Liechti; Dmitri Kuznetsov; Xiangming Xiao; Sophie Von Dobschuetz; Filip Claes; Scott H Newman; Gwenaëlle Dauphin; Marius Gilbert

doi:10.7554/eLife.19571

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

Madhur S Dhingra, Jean Artois, Timothy P Robinson, Catherine Linard, Celia Chaiban, Ioannis Xenarios, Robin Engler, Robin Liechti, Dmitri Kuznetsov, Xiangming Xiao, Sophie Von Dobschuetz, Filip Claes, Scott H Newman, Gwenaëlle Dauphin, Marius Gilbert

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Abstract

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

Original language	English
Journal	eLife
Volume	5
DOIs	https://doi.org/10.7554/eLife.19571
Publication status	Published - 2016

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Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validationFinal published version, 3.08 MB

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Dhingra, M. S., Artois, J., Robinson, T. P., Linard, C., Chaiban, C., Xenarios, I., Engler, R., Liechti, R., Kuznetsov, D., Xiao, X., Dobschuetz, S. V., Claes, F., Newman, S. H., Dauphin, G., & Gilbert, M. (2016). Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation. eLife, 5. https://doi.org/10.7554/eLife.19571

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title = "Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation",

abstract = "Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.",

author = "Dhingra, {Madhur S} and Jean Artois and Robinson, {Timothy P} and Catherine Linard and Celia Chaiban and Ioannis Xenarios and Robin Engler and Robin Liechti and Dmitri Kuznetsov and Xiangming Xiao and Dobschuetz, {Sophie Von} and Filip Claes and Newman, {Scott H} and Gwena{\"e}lle Dauphin and Marius Gilbert",

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T1 - Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

AU - Dhingra, Madhur S

AU - Artois, Jean

AU - Robinson, Timothy P

AU - Linard, Catherine

AU - Chaiban, Celia

AU - Xenarios, Ioannis

AU - Engler, Robin

AU - Liechti, Robin

AU - Kuznetsov, Dmitri

AU - Xiao, Xiangming

AU - Dobschuetz, Sophie Von

AU - Claes, Filip

AU - Newman, Scott H

AU - Dauphin, Gwenaëlle

AU - Gilbert, Marius

PY - 2016

Y1 - 2016

N2 - Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

AB - Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

U2 - 10.7554/eLife.19571

DO - 10.7554/eLife.19571

M3 - Article

C2 - 27885988

SN - 2050-084X

VL - 5

JO - eLife

JF - eLife

ER -

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

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