Brunner

• The within-pond epidemiology of an

amphibian ranavirusA synthetic modeling approach

Jesse Brunner

Washington State University

Questions• What which feature(s) of host or pathogen biology are

required to reproduce the broad features of ranaviral

outbreaks in pond-breeding amphibians (i.e., Wood frogs,

Rana sylvatica)?

• Initially low prevalence

• Sudden onset of mortality event in mid-to-late summer (even though Rv

introduced at the beginning of or early in the larval period)

• Some metamorphs leave the pond infected

• How important is water-borne transmission vs direct

transmission?

• How important is the heterogeneity in susceptibility we have

seen in laboratory experiments?

Model assumptions / conditions

• Large population (40–400

tadpoles / m2)

• Medium-sized pond (600 m2

x 1m deep)

• Only one species: Rana • Only one species: Rana

sylvatica

• Epidemic starts from a

single infected tadpole

• Transmission is (quickly)

saturating function of

density

(Brunner et al. in prep)

Initial model

• SIS model with recovery to susceptible state (no immunity)

• No exposed class (immediately infectious)

• Epidemic is far too early

Initial model

• SIS model with recovery to susceptible state (no immunity)

• No exposed class (immediately infectious)

• Epidemic is far too early

Initial model• Does a lower rate of transmission help?

• Only if we lower transmission rate by an order of magnitude!

• Then the epidemic is too slow

water-borne transmission

• Add term for concentration-specific transmission from water

• Probability of infection from LD50 study in Warne et al. 2011

• Add terms for accumulation and loss of virus in water

• Viral shedding: rough estimates range from 102 to 104 pfu/day in lab

experiments with Ambystoma nebulosum (Storfer et al. in prep, Brunner

unpublished data)

Half-life of ranaviruses ranges from • Half-life of ranaviruses ranges from

• 9.65 days in “unsterile” pond water at 20°C (Nazir et al. 2011)

• 0.57 days in pond water at 20–24°C (Johnson & Brunner in prep; see

poster)

water-borne transmission

• Very few tadpoles infected from the water (even with lower

transmission)

water-borne transmission

• Does a longer half-life of Rv in water help?

• Even with very long persistence times, water-borne

transmission contributes very few infections

water-borne transmission

• What about a greater shedding rate?

Even with a

• low rate of direct transmission,

• long persistence time, &

• high shedding rate

water-borne transmission is still minor source of infection compared to direct contacts

Metamorphs & Developmental stages

• Add terms for

metamorphosing tadpoles

(susceptible & infected)

• Rate of metamorphosis is

1/duration of larval period (60-

80d)

• Explicitly model

development from Gosner

(1960) stages 20 – 40

• Rate of development is #

stages / duration of larval period

Metamorphs & Developmental stages

• Does not change the timing or shape of epidemics

• Probability of ranavirus infection and

death changes dramatically with stage

• Modified the transmission terms by

multiplying by the stage-specific odds-

ratio as predicted logistic-regression

Warne et al. 2011

STAGE-SPECIFIC SUSCEPTIBILITY

ratio as predicted logistic-regression

STAGE-SPECIFIC SUSCEPTIBILITY

• Timing of the epidemic is right with estimated transmission rate

• See the sharp increase in cases

Conclusions

• Water-borne transmission is minor relative to direct

transmission (and negligible under more realistic

assumptions)

• Environmental heterogeneity may slow transmission• Environmental heterogeneity may slow transmission

• Epidemics appear later

• More gradual onset of mortality

• Smaller epidemic

• Stage-specific susceptibility may be key in timing,

dynamics, and outcome of ranaviral outbreaks in Wood frogs

Open questions

• How important is transmission from carcasses?

• An important role for scavengers and decomposers?

• Does the stage-specific susceptibility hypothesis hold for

other species?

• Are multihost communities radically different?

• Can these models match real epidemics?