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superspreading

ANALYTICS
Velocity0.0

Estimation of individual-level variation in transmission

epiverse-trace.github.io/superspreading ↗

superspreading now asks whether a pathogen will emerge at all, not just how unevenly it spreads.

epiverse-tracesuperspreadingbranching-processpathogen-emergencetransmission-heterogeneity
◆Current state
superspreading quantifies individual-level variation in transmission — the offspring distributions and summary metrics behind the 20/80 rule — and calculates probabilities of epidemic, extinction and containment. With 0.4.0 it added probability_emergence(), estimating whether an introduced pathogen can evolve into sustained human-to-human transmission. The package moved from experimental to stable in the same release.
◆Where it's heading
Scope has widened one published framework at a time. 0.2.0 added network-based reproduction numbers, 0.3.0 added the Lloyd-Smith formulation of proportion_transmission() and vendored a branching-process simulator to drop the {bpmodels} dependency, and 0.4.0 implemented and extended the Antia et al. emergence model. Each addition brings a vignette reproducing the source paper's figures, which is how this package treats a method as delivered.
◆Prediction
The established pattern — implement a published framework, extend it, document it against the original figures — makes another literature-derived addition likelier than internal refactoring.

◆Recent moves

  1. 1y ago

    probability_emergence() extends the package into pathogen emergence risk

    ⚡ SPARK

    A new function implements the Antia et al. (2003) framework for the probability that a pathogen introduced to humans evolves into a sustained outbreak, and extends it to multiple introductions. The package also declares itself stable rather than experimental.

    View source ↗
  2. 1y ago

    Lloyd-Smith transmission proportions; bpmodels dependency removed

    proportion_transmission() gains a method argument switching to the Lloyd-Smith et al. (2005) calculation of transmission from the most infectious X% of cases, and the branching-process simulation is vendored into the package so {bpmodels} can be dropped as a dependency.

    View source ↗
  3. 2y ago

    Network reproduction numbers and joint individual/population control

    calc_network_R() estimates the reproduction number for heterogeneous contact networks, and probability_epidemic() and probability_extinct() bring individual- and population-level control into a single framework.

    View source ↗
  4. 2y ago

    First release: offspring distributions and epidemic risk metrics

    The initial release provides offspring distributions absent from base R, probabilities of epidemic, extinction and containment, and summary metrics for clustering and transmission concentration.

    View source ↗