Interactive stochastic spatial model

Virus Spillover Simulator

This toy example illustrates a possible application to Nipah virus spillover in Bangladesh. Kr(x) is the spatial reservoir density of Pteropus medius bats, P(x, θ) is the Nipah pathogen density, Ks(x) is human density (the spillover host), and α(x) is a covariate corresponding to date-palm consumption. The example is illustrative rather than calibrated: several parameter values should be adjusted against epidemiological data before the outputs are interpreted as realistic.

This web-app was developed in the framework of the European BCOMING project.
Pathogen densityP(x, θ) = G(θ) [JD * Kr](x)
Spillover intensityλ(x, θ) = (β0 + β1α(x)) Ks(x) P(x, θ)
Branching parameters (control transmission chain length)b(θ) = b0,   d(θ) = d0 + (θ - Os)2
Model time0.0
Spillover seeds0expected -
Active infected people0
People ever infected0
Active transmission chains0
Spatial view

Virus spillover and local transmission

Spillover intensity
--
locally supercritical locally subcritical
t = 0.0
Population trajectory

Infected people over time

actively infectedever infected
Current realization

Diagnostics

Poisson rate-seeds / model-time
Supercritical seed traits-b(θ) > d(θ)
Largest transmission chain-people ever infected