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Page 1: Epidemiological modelling of Phytophthora ramorum

Epidemiological modeling of Phytophthora ramorum: network

properties of susceptible plant genera movements in the UK nursery sector

Marco Pautasso,1 Tom Harwood,2 Mike Shaw,2Xiangming Xu3 & Mike Jeger1

1 Imperial College London, UK 2 University of Reading, UK 3 East Malling Research, UK

SOD Symposium III,8 Mar 2007

Page 2: Epidemiological modelling of Phytophthora ramorum

From: Hufnagel, Brockmann & Geisel (2004) Forecast and control of epidemics in a globalized world. PNAS 101: 15124-15129

number of passengers per day

Disease spread in a globalized world

Page 3: Epidemiological modelling of Phytophthora ramorum

NATURAL

TECHNOLOGICAL SOCIAL

food webs

airport networks

cell metabolism

neural networks

railway networks

ant nests

WWWInternet

electrical power grids

software mapscomputing

gridsE-mail

patterns

innovation flows

telephone calls

co-authorship nets

family networks

committees

sexual partnerships DISEASE

SPREAD

Food web of Little Rock Lake, Wisconsin, US

Internet structure

Network pictures from: Newman (2003) The structure and function of complex networks. SIAM Review 45: 167-256

HIV spread

network

Epidemiology is just one of the many applications of network theory

urban road networks

Modified from: Jeger MJ, Pautasso M, Holdenrieder O & Shaw MW (2007) Modelling disease spread and control in networks: implications for plant sciences. New Phytologist in press

Page 4: Epidemiological modelling of Phytophthora ramorum

Different types of networks

Modified from: Keeling & Eames (2005) Networks and epidemic models. Interface 2: 295-307

random scale-free

local small-world

Page 5: Epidemiological modelling of Phytophthora ramorum

Epidemic development in different types of networks

scale-freerandom2-D lattice rewired2-D lattice1-D lattice rewired1-D lattice

From: Shirley & Rushton (2005) The impacts of network topology on disease spread. Ecological Complexity 2: 287-299

N of nodes of networks = 500;p of infection = 0.1;

latent period = 2 time steps;infectious period = 10 time steps

Page 6: Epidemiological modelling of Phytophthora ramorum

Records positive to P. ramorum

0

25

50

75

100

Jan-03Apr-0

3Ju

l-03

Oct-03

Jan-04Apr-0

4Ju

l-04

Oct-04

Jan-05Apr-0

5Ju

l-05

Oct-05

n of

reco

rds nurseries/

gardencentres

Temporal development; England & Wales, 2003-2005; n = 1104

Data source: Department for Environment, Food and Rural Affairs, UK

Page 7: Epidemiological modelling of Phytophthora ramorum

Records positive to P. ramorum

0

50

100

150

200

250

Jan-03Apr-0

3Ju

l-03

Oct-03

Jan-04Apr-0

4Ju

l-04

Oct-04

Jan-05Apr-0

5Ju

l-05

Oct-05

n of

reco

rds estates/

environment

Temporal development; England & Wales, 2003-2005; n = 1456

Data source: Department for Environment, Food and Rural Affairs, UK

Page 8: Epidemiological modelling of Phytophthora ramorum

Nursery records positive to P. ramorum

0%

25%

50%

75%

100%

Jan-03

Apr-03

Jul-0

3Oct-

03Jan

-04Apr-0

4Ju

l-04

Oct-04

Jan-05

Apr-05

Jul-0

5Oct-

05

n of

reco

rds

UK origin

non-UK origin

Data source: Department for Environment, Food and Rural Affairs, UK

Temporal development; England & Wales, 2003-2005; n = 704

Page 9: Epidemiological modelling of Phytophthora ramorum

England and Wales: records positive to Phytophthora ramorum

n = 2788

Jan 2003-Dec 2005

Data source: DEFRA, UKCourtesy of Richard Baker,CSL, UK

Page 10: Epidemiological modelling of Phytophthora ramorum

Web of susceptible genera connected by Phytophthora ramorum (based on genus co-existence in 2788 positive findings in England & Wales, 2003-2005)

Rhodo-dendron

Magnolia

Fagus

Castanea Taxus

Festuca

Laurus

Umbellularia

Drimys

Leucothoe

Kalmia

Parrotia

Syringa

Hamamelis

CamelliaViburnum

Pieris

Quercus

Data source: DEFRA, UK

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y = -0.33x + 1.27R2 = 0.93

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.0 1.0 2.0 3.0 4.0

log10 n of positive P. ramorum records in database

log 1

0 num

ber o

f aff

ecte

d ge

nera

Frequency distribution of number of plant genera affected by Phytophthora ramorum by n of records in the database of 2788

positive findings in England & Wales, 2003-2005)

Data source: DEFRA, UK

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Connectivity loss in the North American power grid due to the removal of transmission substations

From: Albert, Albert & Nakarado (2004) Structural vulnerability of the North American power grid. Physical Review E 69, 025103

transmission nodes removed (%)

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AcknowledgementsAlan Inman, Department for Environment, Food

and Rural Affairs, UK

Claire Sansford, Judith Turner & Richard Baker,

Central Science Laboratory, York, UK

Sandra Denman & Joan Webber, Forest Research, Alice Holt, UK

Ottmar Holdenrieder, ETH, Zurich, CH

Jennifer Parke, Oregon State University

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ReferencesDehnen-Schmutz K, Holdenrieder O, Jeger MJ & Pautasso M (2010) Structural change in the international horticultural industry: some implications for plant health. Scientia Horticulturae 125: 1-15Harwood TD, Xu XM, Pautasso M, Jeger MJ & Shaw M (2009) Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and P. kernoviae in the UK. Ecological Modelling 220: 3353-3361 Jeger MJ & Pautasso M (2008) Comparative epidemiology of zoosporic plant pathogens. European Journal of Plant Pathology 122: 111-126Jeger MJ, Pautasso M, Holdenrieder O & Shaw MW (2007) Modelling disease spread and control in networks: implications for plant sciences. New Phytologist 174: 179-197 Lonsdale D, Pautasso M & Holdenrieder O (2008) Wood-decaying fungi in the forest: conservation needs and management options. European Journal of Forest Research 127: 1-22 MacLeod A, Pautasso M, Jeger MJ & Haines-Young R (2010) Evolution of the international regulation of plant pests and challenges for future plant health. Food Security 2: 49-70 Moslonka-Lefebvre M, Pautasso M & Jeger MJ (2009) Disease spread in small-size directed networks: epidemic threshold, correlation between links to and from nodes, and clustering. J Theor Biol 260: 402-411Moslonka-Lefebvre M, Finley A, Dorigatti I, Dehnen-Schmutz K, Harwood T, Jeger MJ, Xu XM, Holdenrieder O & Pautasso M (2011) Networks in plant epidemiology: from genes to landscapes, countries and continents. Phytopathology 101: 392-403Pautasso M (2009) Geographical genetics and the conservation of forest trees. Perspectives in Plant Ecology, Systematics & Evolution 11: 157-189Pautasso M (2010) Worsening file-drawer problem in the abstracts of natural, medical and social science databases. Scientometrics 85: 193-202Pautasso M & Jeger MJ (2008) Epidemic threshold and network structure: the interplay of probability of transmission and of persistence in directed networks. Ecological Complexity 5: 1-8Pautasso M et al (2010) Plant health and global change – some implications for landscape management. Biological Reviews 85: 729-755Pautasso M, Moslonka-Lefebvre M & Jeger MJ (2010) The number of links to and from the starting node as a predictor of epidemic size in small-size directed networks. Ecological Complexity 7: 424-432 Pautasso M, Xu XM, Jeger MJ, Harwood T, Moslonka-Lefebvre M & Pellis L (2010) Disease spread in small-size directed trade networks: the role of hierarchical categories. Journal of Applied Ecology 47: 1300-1309Xu XM, Harwood TD, Pautasso M & Jeger MJ (2009) Spatio-temporal analysis of an invasive plant pathogen (Phytophthora ramorum) in England and Wales. Ecography 32: 504-516