Title: Imperfect vaccines, within-host dynamics
1Imperfect vaccines,within-host dynamics
parasite evolution
DIMACS Workshop on Evolutionary Considerations in
Vaccine Use, June 27-29, 2005
Sylvain GANDON Génétique et Évolution des
Maladies Infectieuses, UMR CNRS-IRD 2724 IRD, 911
avenue Agropolis 34394 Montpellier Cedex 5,
France sylvain.gandon_at_mpl.ird.fr
2Myxomatosis evolution
Fenner Fantini (1999)
Average mortality of naïve rabbits
Year
3Myxomatosis evolution
From Best Kerr (2000)
Resistant rabbit
Naive rabbit
Virulent virus
?
Avirulent virus
4Myxomatosis evolution
? Virulence can evolve fast (in both
directions) ? To understand this evolution we
need to (1) link within-host dynamics and
parasite fitness (2) include host
heterogeneity
5Outline
- 1. Imperfect vaccines
- 2. Epidemiological models
- 3. Evolutionary models
- - virulence mutants
- - escape mutants
- 4. Epidemiology and evolution
- 5. Conclusion
Vaccines
Epidemiology
Evolution
Both
6Perfect Vaccines(Jenner, 1796)
Vaccine
Naïve host
Immune host
Vaccines
Epidemiology
Evolution
Both
7Imperfect Vaccines
Vaccine
Naïve host
Semi-Immune host
Vaccines
Epidemiology
Evolution
Both
8Semi-immunity
Host resistance may act at different steps of
parasite life cycle
r
r
r
1
2
3
Anti - growth
Anti - transmission
Anti - infection
Vaccines
Epidemiology
Evolution
Both
9Vaccines against malaria
Life cycle of Plasmodium falciparum
sporozoites
RTS,S/ASO2A (Alonso et al. 2004)
merozoites
gametocytes
Vaccines
Epidemiology
Evolution
Both
10Epidemiological Model
Scherer McLean (2002)
p
Naïve Hosts
Recovered Hosts
p
Vaccinated Hosts
Force of infection
Vaccine quality
Vaccines
Epidemiology
Evolution
Both
11Vaccination and eradication
1
0.8
Eradication
0.6
Vaccination threshold
Perfect vaccine
pc
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Basic reproductive ratio before vaccination,
.
Vaccines
Epidemiology
Evolution
Both
12Vaccination and transient dynamics
R011 pc0.91
Vaccination start
p 0.5
p 0.3
p 0.95
p 0.88
p 0.7
Infected individuals
Time (years)
Vaccines
Epidemiology
Evolution
Both
13Evolutionary consequences
Cost of escape
Treated host (e.g. vaccinated)
Escape mutant
Vaccines
Epidemiology
Evolution
Both
14Evolutionary consequences
- Escape evolution
- Virulence evolution
Virulence a
Exploitation strategy
Transmission b
Vaccines
Epidemiology
Evolution
Both
15Evolution of virulence in a heterogeneous host
population
r2
r3
r1
W
r2
WN
W
ESSN
Virulence, a
Vaccines
Epidemiology
Evolution
Both
16Results vaccine quality
Different imperfect vaccines with p0.5
Anti-growth r2
ESS virulence
Anti- Infection r1
Anti-transmission r3
Vaccine efficacy r1, r2, r3
Vaccines
Epidemiology
Evolution
Both
17Virulence evolution and eradication
Results vaccine quantity
r10.5, r20.4
r10.5, r20.6
0.4
0.4
0.3
0.3
ESS virulence
0.2
0.2
0.1
0.1
pc
pb
pc
0
0
0
1
0.2
0.4
0.6
0.8
0
1
0.2
0.4
0.6
0.8
Vaccination coverage, p.
Vaccination coverage, p.
Vaccines
Epidemiology
Evolution
Both
18Conclusion of simple models
- Parasite evolution may erode
- the benefits of vaccination
- Evolution of higher virulence (on naïve hosts)
- Eradication becomes less feasable
- However, some vaccines components (i.e., r1, r3)
may limit virulence evolution.
Vaccines
Epidemiology
Evolution
Both
19Conclusion of simple models
But things are missing from the model -
within-host dynamics (dynamics of immunity) -
mechanistic description of the vaccine effects -
link between virulence (a) and transmission (b)
- link between virulence (a) and clearance
(g) - heterogeneity among infected hosts through
time
Vaccines
Epidemiology
Evolution
Both
20Within-host dynamics
André et al. (2003)
Parasite
r
Immunity
r
Vaccines
Epidemiology
Evolution
Both
21Within-host dynamicsand parasite fitness
Host imunity
Virulence, a
Transmission, b
Clearance, g
Parasitemia
Parasite growth
Time
Infection
Clearance
Clearance
Clearance
Vaccines
Epidemiology
Evolution
Both
22Within-host dynamics vaccination
4
Mean Transmission
2
b
0
0
5
10
15
20
Naïve host
1
Mean Virulence
0.8
0.6
a
0.4
0.2
0
5
10
15
20
0.6
Mean Clearance
Vaccinated host
0.4
g
0.2
0
5
10
15
20
Within-host growth rate, r
Vaccines
Epidemiology
Evolution
Both
23Within-host dynamics vaccination
Vaccines
Epidemiology
Evolution
Both
24Within-host dynamics vaccination
4
Mean Transmission
2
b
0
0
5
10
15
20
12
1
10
Mean Virulence
0.8
8
Parasite fitness, W
0.6
6
a
0.4
4
0.2
2
0
5
10
15
20
0
rn
rv
0
10
20
0.6
Within-host growth rate
Mean Clearance
0.4
Virulence mutant
Wild-type parasite
g
0.2
0
5
10
15
20
Within-host growth rate, r
Vaccines
Epidemiology
Evolution
Both
25Within-host dynamics vaccination
1
Prevalence ofrn and rv
0.5
0
Vaccination coverage
0
0.2
0.4
0.6
0.8
1
0.4
0.3
Mean mortality rate
0.2
0.1
Vaccination coverage
0
0
0.2
0.4
0.6
0.8
1
Vaccines
Epidemiology
Evolution
Both
26Within-host dynamics vaccination
Main results
? Confirms results of simpler modelsvaccination
can promote the evolution of higher virulence?
Coexistence of different strains is possible?
Evolutionary bistability emerges easily? The
virulence mutant is a generalist strategy
Vaccines
Epidemiology
Evolution
Both
27Virulence versus escape evolution
Virulence evolution
Escape evolution
28Virulence versus escape evolution
What are the differences between these
mutants?Escape mutants pay the cost on
transmission (lower b) R0 Virulence mutants
pay the cost on virulence (higher a) R0
Which evolution is more likely?At
epidemiological equilibrium the mutant with the
higher R0 Away from this equilibrium the
mutant with the higher r
b
a
Vaccines
Epidemiology
Evolution
Both
29Epidemiology and evolution
3 strains will compete before and after
vaccination - Wild type, WT a, b, g -
Escape mutant, E a, b, g - Virulence
mutant, V a, b, g
Vaccines
Epidemiology
Evolution
Both
30Epidemiology and evolution
On naïve hosts
? WT wins
On vaccinated hosts
? E wins
Vaccines
Epidemiology
Evolution
Both
31Epidemiology and evolution
Vaccination start
Vaccines
Epidemiology
Evolution
Both
32Conclusion
The ultimate goal is to merge
Evolution Epidemiology Immunology
population
slow, fast
population
fast
cell, individual
very fast
Different spatial scales
Different speeds
33Acknowledgments
Margaret MACKINNON Sean NEE Andrew
READ Jean-Baptiste ANDRÉ Troy DAY
34(No Transcript)