Immuno-epidemiology of coccidiosis Don Klinkenberg Maite Severins Hans Heesterbeek.

Immuno-epidemiology of coccidiosis

Don Klinkenberg

Maite Severins

Hans Heesterbeek

Coccidiosis

• Caused by Eimeria spp

• Protozoan

• Intestinal infection– sometimes lesions– main problem: production loss

• Seven species in chickens– location in the intestine– no cross-immunity

Parasite classification

• After lecture notes by Kretschmar (micro/macro):

Microparasite Macroparasite Eimeria

Parasite lifespan Short Long Short

Reproduction within host

Rapid None Rapid (but dose effect)

Transmission Direct Indirect Indirect

Infection events One Multiple Multiple

Immunity Complete Partial, slowly acquired

Accumulative, slowly acquired

Model type SIR type Parasite load ???

Essential characteristics

• Transmission through environment

• Dose-dependent infectivity

• Slowly acquired immune response– stronger upon re-infection– reduces parasite excretion

• Within-host dynamics!

This presentation

• Model of within-host dynamics– relation between uptake and excretion of

infectious material (oocysts)– interaction with immune system

• Model of between-host dynamics (I)– coupling excretion and uptake of oocysts– interaction chickens and environment

• Model of between-host dynamics (II)

Within-host model

• Eimeria characteristics:– transmission through oocysts– Eimeria parasitises gut epithelial cells– limited number of asexual generations

Eimeria cycle

Oocyst uptake (W)

Sporozoites

Schizont I (X(1))

Merozoites I (u(1))

Schizont II (X(2))

Merozoites II (u(2))

Gamont

Oocyst excretion (Z)

Eimeria cycle

Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))


Eimeria cycle

tt

tt

tt

XZ

XX

WaX

222

111

2

111

Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))


Adding immunity

• Primarily T cell immunity

• Immunity evoked by schizonts

• Immunity inhibits schizont development

• Keeping the model simple: one immunity variable Y

Eimeria cycle with immunity

Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))


Immunity (Y)+

+– –


Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))


Immunity (Y)

+

+

–

–

tt

tt

tt

XZ

XX

WaX

222

111

2

111


Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))


Immunity (Y)

+

+

–

–

tttt

ttt

ttt

tt

XXYgY

YfXZ

YfXX

WaX

211

222

111

2

111

,


tttt

ttt

ttt

tt

XXYgY

YfXZ

YfXX

WaX

211

222

111

2

111

,

2121,

1

1

XXYYXXYg

YYf

m

Model summary

• Discrete time

• Two asexual schizont generations

• T cell immunity against schizont development

Model analysis

• Compare model experiments to data– relation single dose and excretion

• saturation followed by decrease

– excretion during trickle infections• excretion terminates after some time

– immunising effect of trickle and single immunisation

• trickle immunisation gives better protection

Single dose and excretion

5

5.5

6

6.5

7

7.5

8

0 2 4 6

Log(oocyst uptake)

Lo

g(o

oc

ys

t e

xc

reti

on

) E. tenella

Model analysis

• Model experiments– single dose and excretion

• relation between W0 and Z4

– trickle infections– trickle vs single immunisation

Analysis: single dose

4.5

5.5

6.5

7.5

0 2 4 6 logw 0

logz 4

l 1: logz 4=p 1+logw 0

l 2: logz 4=p 1+(1-m )logw 0-mp 2

l 1

l 2

mWa

WaZ

01

02114

1


2 4 6 8

4

6

8E. tenella


2 4 6 8

4

6

8E. acervulina


2 4 6 8

4

6

8E. maxima

Model analysis

• Model experiments– single dose and excretion

• relation between W0 and Z4

• > 0 (naïve immunity growth)• m ≠ 1 (non-linear immune effectiveness)

– trickle infections & immunisation• conclusions on and

Conclusions within-host model

• Simple model of parasite input-output behaviour

• Single immunity variable can explain experimental data

• Solid basis for studying re-infection and between-host transmission

Between-host model

• Relate excretion to uptake with oocyst level in environment V

• Simplifying assumption: average chicken

Eimeria cycle

Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))


Immunity (Y)+

+– –

Eimeria cycle

× a0

Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))

Gamont (G)


Immunity (Y)+

+– –

Environmental oocysts (V)

× a1

× 1× 2

× 1

× 1

inside the chickens

outside the chickens

Two new parameters

• Per time step of ca. 2 days

• Uptake rate a0

– estimate from a single experiment: 0.01

• Oocyst degradation rate– estimate from couple of articles: 0.5

Interesting variables

• Oocyst level in environment– decrease due to degradation (+ uptake)– increase due to excretion

• Immunity level in average chicken– increase due to presence of schizonts– decrease by fixed rate

• Number of infected cells as measure of damage– numbers of schizonts and gamonts

Basic dynamics

× a0

Oocyst uptake (W)

Schizont I (X(1))

Schizont II (X(2))

Gamont (G)


Immunity (Y)+

+– –

Environmental oocysts (V)

× a1

× 1× 2

× 1

× 1

inside the chickens

outside the chickens

0

1

2

3

4

5

5

3

2

Dynamics in single chicken cohort

• First dose of each infection generation most important– major change compared to previous dose– fast decay of oocysts in environment

• Dynamics can be described in terms of infection generations

Damage in single chicken cohort

• Cumulative damage ≈ maximum damage

7.5 5 2.5 2.5 5 7.5 10

456789

1011

logv0

logdmax

Conclusion on damage

• Production damage is reflected by the maximum number of infected cells

• Damage may take local minimum with intermediate oocyst level V0

• Mechanism – maximum damage if a single infection

generation dominates– minimum when generation dominance

switches

Damage in single chicken cohort

• Cumulative damage ≈ maximum damage

7.5 5 2.5 2.5 5 7.5 10

456789

1011

logv0

logdmax

1234

gamonts

schizonts II

Discussion of the model

• Single ‘average’ chicken

• Deterministic model

• No spatial effects

Different approach

• Individual chickens

• Stochastic model

• Spatial model

• Cost:– No continuous infection/immune level

Individual based model

• Patches interact with walking chickens

• Patches– oocyst level empty, low, medium, high (0; 103;

105; 107)– level rises if chicken excretes higher level– level falls after 14 days without excretion

Individual based model

• Chickens– walk or ‘shuffle’ each hour– pick up maximum daily exposure (0, 101; 3; 5)– excrete once per day depending on

• uptake -4 days• level of immunity (no, partial, full)• regulated by excretion templates

– immunity level may increase depending on• time since first dose• number and level of doses

Example: fit to data (Galmes)

0

1

10

100

1,000

10,000

100,000

1,000,000

0 5 10 15 20 25 30 35 40

oo

cy

sts

x1

0^

31000x2020000controlmodel 1000x20model 100000model control

“damage” related to initial level

High oocyst excretion

0

1

2

3

4

5

6

0.01 0.1 1 10 100

% initial contamination

mea

n #

exc

reti

on

s/ch

ick

walk

shuffle

Local minimum

• Mechanism?– High excretion due to serial medium doses

• medium doses require serial low doses

– If initial level is• high: early excretion of many medium, so serial

medium doses before immunity• intermediate: early exposure for start-up immunity,

but less serial medium exposure• low: many chicks are not immune while others

already shed medium doses

More generalized mechanism for local minimum damage

• Low initial level: exposure of naive chickens to large oocyst quantities excreted by first infection generation

• Intermediate initial level: immunity builds up before large oocyst quantities are available

• High initial level: large oocyst quantities available before immunity is reached

• However: relation to level of mixing yet unclear

Our coccidiosis modellers

• Deterministic continuous model– Don Klinkenberg, Hans Heesterbeek

• Stochastic discrete model– Maite Severins, DK, HH

• Stochastic continuous model (not shown)– Andriy Rychahivskyy, DK, HH

Immuno-epidemiology of coccidiosis Don Klinkenberg Maite Severins Hans Heesterbeek.

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