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Pathogens and Invasive Species: Insights from Avian Systems Andy Dobson, EEB, Princeton University, Princeton, NJ & Santa Fe Institute, Santa Fe, NM Wes Hochachka, Paul Hurtado, Andre Dhondt – Cornell University Leslie Reperant (Princeton), Thijs Kuiken, Erasmus Labs, The Netherlands Eric Seabloom, NCEAS, Santa Barbara, CA Juliet Pulliam (Princeton), Peter Daszak, Consortium for Conservation Medicine, Steve Luby ICDDR, Dakar, Bangladesh.

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Pathogens and Invasive Species: Insights from Avian Systems

Andy Dobson, EEB, Princeton University, Princeton, NJ&Santa Fe Institute,Santa Fe, NM

Wes Hochachka, Paul Hurtado, Andre Dhondt – Cornell University

Leslie Reperant (Princeton), Thijs Kuiken, Erasmus Labs, The Netherlands

Eric Seabloom, NCEAS, Santa Barbara, CA

Juliet Pulliam (Princeton), Peter Daszak, Consortium for Conservation Medicine, Steve Luby ICDDR, Dakar , Bangladesh.

Menu de jour….

o Pathogens in Invasive Species

o Invasive Species without pathogens

o Phylogenies of Invasive Species

o Hanta virus in Malaysia and Bangladesh

o Avian Influenza in Europe, 2006.

Mycoplasmal conjunctivitis

• caused by the bacterium Mycoplasma gallisepticum

• found in domestic poultry worldwide

• novel strain infects House Finches

• clear external clinical signs

• clinical signs are closely related

to presence of pathogen

Humans aren’t only species at risk – monitoring focuses on humans and livestock….

House finches were introduced into Long Island 1940

the Team: Cornell: Dhondt, Kollias, Cooch ; UW, Madison: HartupNCSU: Ley; Princeton: Dobson ; Emory: Altizer;

+students, collaborators

Tristate Bird Rescue

Jan-Feb 1994

0

10

20

30

40

50

60

70Fe

b-98

Apr

-98

Jun-

98

Aug

-98

Oct

-98

Dec

-98

Feb-

99

Apr

-99

Jun-

99

Aug

-99

Oct

-99

Prev

alen

ce (%

)

ConjunctivitisMG Infection

NS *

MG prevalence linked with clinical signs of conjunctivitis

Mercer County, NJHartup et al. 2001. The Auk. 118(2): 327-333

10 months after first observation(HFDS: Dhondt AA, Tessaglia DL, Slothower RL. 1998.. J. Wildlife Dis. 34: 265-280.

)

Disease Spread Rapidly ThroughEastern North America

After 10 month After 2.5 Years

House Finch abundance decreased dramatically because of the new disease

Bird

s/H

our

1970 1980 1990 2000

01

23

Eastern VA, Eastern MD, DE

Year

Bird

s/H

our

1970 1980 1990 2000

02

46

810

Central PA, Eastern NY

Among-site variation is density dependent

Years Since Threshold Disease Prevalence

Hou

se F

inch

es/P

arty

-Hou

r

0 3

2

3

4

5

6 1994

1995

1996

Hochachka & Dhondt (2000) PNAS 97:5303-5306

1990 1995 2000

4

6

8

10

12

60

70

80

90

100

New York and Pennsylvania%

Fee

ders

with

Hou

se F

inch

es (o

pen

circ

les)

Hou

se F

inch

Gro

up S

izes

(fill

ed d

iam

onds

)

Project FeederWatch – geometric mean per winter

group size declined rapidly

geographic distribution changed little

New York and Pennsylvania – stable numbers

Pathogens disrupt and modify social organization

Parasites and invasive species(with Mark Torchin, Kevin Lafferty, Armand Kuris, NCEAS)

Native and introduced range of green crab

Parasites of the green crab in Europe

Parasites of the green crab in East Coast North America

Parasites of the green crab in Australia

Parasites of the green crab in West Coast North America

Parasites of the green crab in South Africa

Mark Torchin

(a further contribution to US obesity and over-consumption)

ò = molluscs (N = 7)

¢ = crustaceans (N = 3)

p = fishes (N = 6)

Å = amphibians and reptiles (N = 3)

u = birds (N = 3)

£= mammals (N = 4).

(a) Parasite species richness

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1Native

Intr

oduc

ed

Torchin et al. 2003 Nature 421: 628-630

ò = molluscs (N = 7)

¢ = crustaceans (N = 3)

p = fishes (N = 6)

Å = amphibians and reptiles (N = 3)

u = birds (N = 3)

£= mammals (N = 4).

(a) Parasite species richness

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1Native

Intr

oduc

ed

Torchin et al. 2003 Nature 421: 628-630

Release from parasites(mean from 26 ANIMAL species)

02468

1012141618

IntroducedNative

Para

site

spec

ies

Torchin et al. 2003. Nature 421: 628-630

Exotic parasites

Release from parasites(mean from 26 ANIMAL species)

02468

1012141618

IntroducedNative

Para

site

spec

ies

Torchin et al. 2003. Nature 421: 628-630

Colonized from new

regionExotic

parasites

Native and Alien Plants in California

Seabloom, Dobson and Stoms, Ecological Applications

Seabloom, Dobson and Stoms, Ecological Applications

Nipah Virus: a case study

Paramyxoviridae

o Includes measles, distemper , mumps

o Respiratory infections

o Life-long immunity

Hendra virus (Paramyxoviridae): infects bats, horses, humans

A real Nipah victim (on left!)

Pteropid bats are reservoirs for Nipah and Hendra viruses (Photo Raina Plowright)

Nipah virus in Malaysia, 1997-1999Human encephalitic cases

11Jan97 16Aug97 16May98 3Oct98 2Jan99

Perak

01

23

4

27Mar99

Selangor

Num

ber o

f cas

es0

12

34

26Dec98

Negeri Sembilan

Week of onset of illness

010

2030

40

Num

ber o

f cas

es

?

Chapter 4

Nipah virus dynamics in domestic pig populations

Human cases of Nipah virus encephalitis

012345

Jan-97 Apr-97 Jul-97 Oct-97 Jan-98 Apr-98 Jul-98 Oct-98 Jan-99 Apr-99

05

101520253035404550

Jan-97 Apr-97 Jul-97 Oct-97 Jan-98 Apr-98 Jul-98 Oct-98 Jan-99 Apr-99

Num

ber o

f new

cas

es

ß---Why the long delay ?? --------------à ???

Nipah virus dynamics in domestic pig populations

0

5000

0

5000

0

5000

0 100 200 300 400 500 600 700 8000

5000

Time since spillover (days)

Num

ber o

f pig

s in

fect

ed

Sows

Piglets

Weaners

Porkers

Human cases of Nipah virus encephalitis

012345

Jan-97 Apr-97 Jul-97 Oct-97 Jan-98 Apr-98 Jul-98 Oct-98 Jan-99 Apr-99

Epidemics are enhanced in a partially immune population(longer duration and increased total number of infectious individuals)

0.2 0.4 0.6 0.8 1.0

010

020

030

0

Epidemic enhancement in partially immune populations

Dur

atio

n of

epi

dem

ic (i

n da

ys)

Median25/75 %iles

0.2 0.4 0.6 0.8 1.0

010

000

2500

0

Percent of population immune upon introduction of virus

Tot

al n

umbe

r of c

ases

Median25/75 %iles

Nipah virus emergenceRepeated spillover

EphemeralHerd

immunity

Ro is closer to 1 after first outbreak….

Hendra virusin Australia.

Raina Plowright,Peter Daszak,Andy Dobson,Hume Field.

Traveling WavesPlowright et al, in press.

Seasonal dynamics of Avian Influenza: Insights, Models and Wild Speculation

Andy Dobson, Leslie Reperant,EEB, Princeton University, NJ, USA

Neven-Stjepan Fuckar ,PEI, Geology,Princeton University

Thijs Kuiken, Erasmus Medical Center , Rotterdam,The Netherlands

Large diversityof ducks, swans,and geese

Duck and goose phylogeny – comparative approaches

Duck and goose phylogeny – comparative approaches

9.5->12.9%0.8 -> 1.2% 6.5 2.2%

??......??% ?....?

Duck and goose phylogeny – comparative approaches

9.5->12.9%0.8 -> 1.2% 6.5 2.2%

??......??% ?....?Long necks..?herbivorous Short

Necks..?Eat ‘mud’

Piscivorous………….. Marine

Does weather have any influence on duck movements?

Movements of MaximumSurface Air Temperature Isotherms

in Europe from January 1st to March 31st 2006

Locations of cases of HPAI H5N1 virus infection in wild birds

Locations three to one days before infected wilds birds were found

Locations on the day infected wild birds were found

Press enter to start

How could we model this?

o Need data on species distribution and range overlaps between potential hosts

o Need data on how different hosts respond to infection – virulence, shedding, etc

Transmission and Species-Range (& habitat) Overlaps

AB

C

AB

CZero Degree Isocline

SUMMER

Range overlap in summer

Range overlap in winter

AB

C

Zero Degree Isocline

WINTER

Hatched Area is frozen

Seasonal variation in range occupied and inter-specific overlap

SUMMER WINTER

RE

LATI

VE

AR

EA

OC

CU

PIE

D RA

NG

E O

VE

RLA

P

Seasonal variation in transmission

SUMMER WINTER

Ro

- tr a

nsm

iss i

on p

ote n

tial

Between species, Bij

Within species, Bii

Framework to model these transmission dynamics

Relatively standard SIR equations (with N=S+I+R)

( ) ( )dS SIb N N dS f tempdt N

β = − ∆ − −

( ) ( )dI SIf temp d Idt N

β α σ = − + +

dR I dRdt

σ= −

( )1

5

tempf temp

β =

+

Temperaturedependent

transmissionterm

Transmissiondecreases with

increasing temperature

Maximum temperaturefor ‘sustainable’

transmission (Ro>1)

0 10 20 30 40

0.0

0.5

1.0

1.5

2.0

Ro and T emperature

Temperature, Celsius

Ro,

Bas

ic re

prod

uctiv

e nu

mbe

r

Outbreak!

Decline…..

SU

SC

EP

TIB

LES

, RE

CO

VE

RE

D, I

NFE

CTE

D H

OS

TS

0 5 10 15 20

1e-0

21e

+00

1e+0

21e

+04

Single Species Avian Influenza

red = I : blue=S, Green = RTime

Num

bers

Multi-host dynamics

o Expand to three host species

o Different AI-induced mortalities n (5x and 0.1X)

o Within species transmission is higher than between species transmission. But all transmission increases in winter .

Framework to model these transmission dynamics

Relatively standard multi-host species SIR equations (with Ni=Si+Ii+Ri)

1,

1,

(( ) ( )

i ij jj ni

i i i i iin

j n

S s IdS b N N dS f tempdt N

β =

=

= − ∆ − −

∑∑

1,

1,

(( ) ( )

i ij jj ni

ii i in

j n

S s IdI f temp d Idt N

β α σ=

=

= − + +

∑∑

ii i

dR I dRdt

σ= −

( )1

5.

ij

temp

ji

f tempe

s

ββ =

+

Temperaturedependent

transmissionterm

More inter-speciesmixing at colder

tempertures

0 10 20 30 40 50

1e-0

21e

-01

1e+0

01e

+01

1e+0

2

Multi-Host Species Avian Influenza (Blue = T emperature)

Time (Years)

Num

bers

Infe

cted

Long interval between first two outbreaks!!

More stable dynamics

Summary & Policy Implicationso Dynamics of AI is highly sensitive to seasonal

variation in water temperature

o The presence of multiple host species helps stabilize the long term dynamics.

o BUT, there may be long time intervals between initial epidemic outbreaks

o Dynamics dependent upon colder temperatures and annual seasonal variationn So interpretation of data may be very location

dependent

Final cautionary tale….

Conclusions

o Understanding dynamics is central to control of infectious diseases

o Genomics tells us nothing predictive about dynamics –n At best it’s an occasionally useful post-hoc tooln BUT we’ve trained lots of people in this – so they

have to argue it is God’s gift to the health sciences….

o There is essentially no money at NIH for population dynamics

o This is foolish and dangerous