Coccidiosis

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

Oocyst excretion (Z)

Schizont I (X(1) ) Gamont Merozoites I (u(1) )

Merozoites II (u(2) )

Schizont II (X(2) )

Eimeria cycle Oocyst uptake (W)

Oocyst excretion (Z) Schizont I (X(1) )

Schizont II (X(2) )

Eimeria cycle Oocyst uptake (W)

Schizont I (X(1) )

Schizont II (X(2) )

Oocyst excretion (Z)

X

( 1)

X

( 2)

t +1 t +1

= a1Wt = λ1 X

Z t + 2 = λ2 X

( 2)

( 1) t

t

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)

Oocyst excretion (Z)

+

Immunity (Y)

– + Schizont II (X(2) )

–

Schizont I (X(1) )

Eimeria cycle with immunity Oocyst uptake (W)

Schizont I (X(1) )

– Schizont II (X(2) )

+ +

– Oocyst excretion (Z)

X

( 1)

X

( 2)

t +1 t +1

= a1Wt = λ1 X

Z t + 2 = λ2 X

Immunity (Y)

( 2)

( 1) t

t

Eimeria cycle with immunity Oocyst uptake (W)

Schizont I (X(1) )

– Schizont II (X(2) )

+ +

– Oocyst excretion (Z)

X

( 1)

X

( 2)

t +1 t +1

= a1Wt = λ1 X

Z t + 2 = λ2 X

( 2)

( 1) t

t

f ( Yt )

f ( Yt )

Immunity (Y)

(

Yt +1 = g Yt , X

( 1)

t

+X

( 2)

t

)

Eimeria cycle with immunity X ( 1) t +1 = a1Wt

X ( 2 ) t +1 = λ1 X ( 1) t f ( Yt )

Z t + 2 = λ2 X ( 2 ) t f ( Yt )

(

Yt +1 = g Yt , X ( 1) t + X ( 2 ) t

)

1 f (Y ) = m 1+ Y ( 1) ( 2) ( 1) ( 2) g Y , X + X = αY + ( β + γY ) X + X

(

)

(

)

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

Log(oocyst excretion)

Single dose and excretion E. tenella

8 7.5 7 6.5 6 5.5 5 0

2

4

Log(oocyst uptake)

6

Model analysis • Model experiments – single dose and excretion • relation between W0 and Z4

– trickle infections – trickle vs single immunisation

Analysis: single dose 7.5

logz 4

l2 l1

6.5

a1λ1λ2W0 Z4 = m ( ) 1 + β a W 1 00 l 1: logz 4=p 1+logw

5.5

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

4.5 0

2

4

6

logw 0

Analysis: single dose E. tenella

8 6 4 2

4

6

8

Analysis: single dose E. acervulina

8 6 4 2

4

6

8

Analysis: single dose E. maxima

8 6 4 2

4

6

8

Model analysis • Model experiments – single dose and excretion • relation between W0 and Z4 • β > 0 (naïve immunity growth) • m ≠ 1 (non-linear immune effectiveness)

– trickle infections & immunisation • conclusions on γ and α

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)

Oocyst excretion (Z)

+

Immunity (Y)

– + Schizont II (X(2) )

–

Schizont I (X(1) )

Eimeria cycle outside the chickens

Environmental oocysts (V) ×1

× a0

Oocyst excretion (Z)

Oocyst uptake (W)

×1

× a1

Immunity (Y)

+

Gamont (G) × λ

– 2

inside the chickens

+

–

Schizont II (X ) (2)

Schizont I (X(1) ) × λ

1

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

outside the chickens

4

5

Environmental oocysts (V) ×1

Oocyst excretion (Z)

2

Immunity (Y)

Gamont (G) × λ

– 2

inside the chickens

0

Oocyst uptake (W)

×1

3

5

× a0

+

3 2

Schizont II (X ) (2)

× a1

+ –

1

Schizont I (X(1) ) × λ

1

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 11 10 9 8 7 6 5 4  7.5

 5

 2.5

logdmax

logv0

2.5

5

7.5

10

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 11 10 9 8 37 6 5 4

4

 7.5

 5

 2.5

logdmax

2

1 schizonts II gamontslogv0

2.5

5

7.5

10

Cleaning after each chicken cohort • Minimizing damage requires optimal cleaning of the shed. • What happens if a proportion ρ of all oocysts are removed after each cohort? • Study relation between logv0 and logvend

Final oocyst level 8

logvend

6 4 2

logv0  7.5

 5

 2.5

2.5  2

5

7.5

10

Removal of proportion 1 − ρ 0

-3

-2

logρ

3

Minimum damage

2

Maximum damage

log ρ 8

1  6

 4

 2

 1  2  3

logv0

 4

Conclusion on cleaning • Removal of a proportion 1 − ρ of oocysts after each chicken cohort cannot minimize damage • Minimizing damage may be done by maximal removal + adding oocysts

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) 1000x20 20000 control model 1000x20 model 100000 model control

1,000,000

100,000

10,000

oocysts x10^3

1,000

100

10

1

0 0

5

10

15

20

25

30

35

40

“damage” related to initial level High oocyst excretion

walk shuffle

mean # excretions/chick

6 5 4 3 2 1 0 0.01

0.1

1

% initial contam ination

10

100

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