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Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

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Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers David Pigott; [email protected] Thursday, 17 th March 2016
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Page 1: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Investigating the spatial

epidemiology of zoonotic viral

haemorrhagic fevers

David Pigott; [email protected]

Thursday, 17th March 2016

Page 2: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Hypothetical outbreak progression

2

Page 3: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Suspected life-cycle of Ebolavirus

3

Page 4: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Considering Ebola spatially

• Zoonotic transmission of Ebola

oSpatial consideration of potential for animals to spread

EVD

o Identify risk areas for “spillover” infections

.V.

• Secondary human-to-human transmission of Ebola

oSpatial assessment of how disease propagates

through human populations

4

Page 5: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Species distribution models

• Consider a species

oThree factors influence

where it can be found

─ Biotic

─ Abiotic

─ Movement

• How can we leverage

covariate information to

characterise the niche

of a disease?

5

B A

Picture: Freya Shearer (based upon Peterson et al. 2008)

Page 6: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Species distribution models

• Using models to interpret variation in reported occurrences within

environmental space

o Extract environmental correlates at case/control locations

o Model suitability as a non-linear function of environmental

correlates

o Make predictions for all other cells

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Picture: Nick Golding

Page 7: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

How BRTs work

• Combine regression trees with boosting

Boosting: apply shrinkage and iteratively improve

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Elith et al. (2008). J Anim Ecol, 77: 802-813.

Page 8: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

How BRTs work

• Bootstrapping to estimate prediction uncertainty

Ebola:

200-times shrinkage;

10-fold cross-validation; Area under the curve validation

500 bootstrap submodels

8

Page 9: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Ebola

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Ebola index cases Background samples Covariates

Page 10: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Zoonotic risk of EVD

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Page 11: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Next steps?

• What is the true nature of

risk?

o Dynamics in reservoirs?

o Spillover exposure?

o Human element of risk?

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Plowright et al. (2015) Ecological dynamics of

emerging bat virus spillover Proc Roy Soc B

Dynamics of Hendra virus

infection

Page 12: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Next steps

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Page 13: Investigating the spatial epidemiology of zoonotic viral haemorrhagic fevers

Acknowledgements

• Multiple members of the Spatial Ecology and Epidemiology

Group, Oxford as well as collaborators internationally

• Mapping reference

o Pigott, Golding et al. (2014) Mapping the zoonotic niche of Ebola

virus disease eLife

• Some SDM resources

o Elith et al. (2008) A working guide to boosted regression trees J.

Anim. Ecol.

o Peterson et al. (2011) Ecological Niches and Geographic

Distributions

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