An epidemiological approach for the deployment of disease … · 2011. 8. 22. · An epidemiological approach for the deployment of disease control in successive crops RMT modélisation

An epidemiological approach for the deployment of disease control in successive crops

RMT modélisation - 29 sept. 2009, Paris

UMR BIO3P - équipe Epidémiologie Sol et Systèmes (EPSOS)

INRA – Centre de Rennes

Doug Bailey, Sylvain Poggi, Vincent Faloya

Objectives

– Devise models for disease and inoculum dynamics across successive crops.

– Extend the models to allow for inherent variability.

– Parameterise the models for chemical, biological and cultural control.

– Identify criteria for invasion and persistence.

– Use the models to optimise control.


Approach

Population dynamics

Epidemic processes

Macro

Meso

Micro

Spatio-temporalmodels

Temporalmodels

Pathozonedynamics

Modelling Experimentation

Field/Micro-plot

Micro-plot/Microcosm

MicrocosmEpidemic componentsGrowth rates

Primary infectionSecondary infection

Pathozonecomponents

Disease maps


Start point: Model derivation (single crop)

Susceptible

Exposed

Infected

Removed

( ) ( )d1

d p s

S Nb I N r X r I S

t κ= − − +

( )d

d p s i

Er X r I S rE

t= + −

d

d i r

IrE r I

t= −

d

d r

Rr I

t=


Important features of epidemic behaviour

Stochasticity(What is the risk of disease?)

Dynamically generated variability(Do small differences in control early in an epidemic lead to large difference in final

disease levels?)

Invasion thresholds(Are there critical combinations of parameters that lead to invasion or control?)

Persistence and hidden infestation(Does the quality of an epidemic affect persistence into the next susceptible crop?)(Does cryptic infection pose a risk for persistence of disease in future crops?)





disease levels?)





0.000 0.001 0.002 0.003 0.004 0.005

0.00

0.25

0.50

0.75

1.00

Like

liho

od

of

dis

ease

-fre

e si

tes

rp (rate of primary infection)

Disease riskDisease progress




Dynamically generated variability(Do small differences in control early in an epidemic lead to large difference in

final disease levels?)




Dynamically generated variability(Does a small amount of control early in an epidemic lead to

large difference in final levels of disease?)

5 10 15 205 10 15 2001020304050

5 10 15 205 10 15 20

01020304050

Time (Days)

Nu

mb

er o

f d

ise

ase

d p

lan

ts

(a) Control of primary infection

(b) Control of secondary infection157

75

-Tv+Tv


0 500 1000 1500 2000 2500

0

20

40

60

80

100

Biofumigation of R. solani in sugar beet by B. napus(Can we exploit DGV for control of field epidemics?)

No mustard

Mustard removed

Mustard incorporated

Supervisors:

Philippe LucasFrançoise Montfort

Thierry Doré

Collaborator for epidemiogical analysis:

Joao Filipe

Natacha Motisi (PhD)

1ary

2ary

( )d

d p s

Sr X rI S

t=− +

( )d

d p s

Ir X rI S

t= +

d

d d

Xr X

t=−

2dexp(-0.5(log( / )/ ) )

d

ss s s

rt

tα γ β=

Susceptible

Infected

Inoculum

Secondary infection

% d

isea

se p

lant

s

Thermal time


0 500 1000 1500 2000 25000

1e-6

2e-6

3e-6

4e-6

0 500 1000 1500 2000 25000.00000

0.00002

0.00004

0.00006

0.00008

0.00010

Net rate of primary infection Net rate of secondary infection

No mustard

Mustard removed

Mustard incorporated

Biofumigation of R. solani in sugar beet by B. napus(Are the large differences in final levels of disease caused by

control of primary or secondary infection?)





disease levels?)

Invasion thresholds(Are there critical combinations of parameters that lead to invasion or

control?)



Distance (r ) between donor and recipient sites

0 5 10 15 20

Pro

babi

lity

of c

olon

isat

ion

0.0

0.2

0.4

0.6

0.8

1.0

Pc

rc

a) b) c)

r > rc

r < rc

Donor Recipient

r

How do spatial invasion thresholds arise?

New Phyt. (2000) 146: 535-544

Fungal hyphae Pathozone Population


The effect of resource strength on the probability of colonisation between sites

0 2 4 6 8 10 12 14 16 18 20

Pro

babi

lity

of c

olon

isat

ion

(P )

0.0

0.2

0.4

0.6

0.8

1.0

Pc

Distance between donor and recipient

Low nutrientHigh nutrient


Experimental validation in microcosms(Can a soil-borne plant pathogen exploit an invasion threshold?)

Probability of colonisation (P) between donor and recipient.

0.0 0.2 0.4 0.6 0.8 1.0

Pro

port

ion

of p

atch

es s

how

ing

inva

sive

spr

ead

0.0

0.2

0.4

0.6

0.8

1.0

6 DAYS12 DAYS

NON INVASIVESPREAD

INVASIVE SPREAD

18DAYS


Controlling the invasive spread of disease(Can we use biological agents to block invasion?)

0.0

0.2

0.4

0.6

0.8

1.0

0 5 10 15 20 2545678910

Prob

abili

ty o

f di

seas

eDistance (mm)

0.0

0.2

0.4

0.6

0.8

1.0

0 5 10 15 20 2545678910

Prob

abili

ty o

f di

seas

e

Distance (mm)

Tim

e (d

ays)

-BIOCONTROL +BIOCONTROL


Proportion of sites removed from a population

0.0 0.2 0.4 0.6 0.8 1.0P

ropo

rtio

n of

pop

ulat

ions

sh

owin

g in

vasi

ve s

prea

d

0.0

0.2

0.4

0.6

0.8

1.0

Invasivespread

Non-invasivespread

42%

40%

Otten & Gilligan 2006:Eur J. Soil Sci: 57: 26-37Otten et al., 2004New Phyt: 163: 125-132

Proportion of sites removed from a population

0.0 0.2 0.4 0.6 0.8 1.0P

ropo

rtio

n of

pop

ulat

ions

sh

owin

g in

vasi

ve s

prea

d

0.0

0.2

0.4

0.6

0.8

1.0

Invasivespread

Non-invasivespread

Protection of individual sites(Do we need to protect the entire crop?)





disease levels?)


Persistence and hidden infestation(Does the quality of an epidemic affect persistence into the next susceptible crop?)

(Does cryptic infection pose a risk for persistence of disease in future crops?)


2 4 6 8 10 12 14 16 18 20 22

0

10

20

30

40

50

2 4 6 8 10 12 14 16 18 20 22

0

10

20

30

40

50

Nu

mb

er o

f d

ise

ase

d p

lan

ts

Time (days)Time (days)

1st Season 2nd Season

0 5 10 15 20 25

0.0

0.5

1.0

1.5

2.0

2.5

Time (days)

Cfu

g-1

- Trichoderma

+ Trichoderma

Inter-season inoculum dynamics

Spread and control of disease in successive crops


Documents

An epidemiological approach for the deployment of disease … · 2011. 8. 22. · An epidemiological approach for the deployment of disease control in successive crops RMT modélisation