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Digital Toolkit
This page summarises the tools described in the ESCAPE report, organised according to the report sections. For each tool, we provide a short running title, contributing institution(s), a brief description, a GitHub link, and reference to publication.
Table of contents
1. Pathogen archetypes
Introductory tools that support the construction and analysis of pathogen archetypes across multiple diseases.
Pathogen Archetypes
Contributors:
London School of Hygiene & Tropical Medicine (LSHTM), University of Hasselt (UH)
A modelling framework that organises infectious diseases into pathogen archetypes based on key characteristics such as transmission route, basic reproduction number, serial interval, and severity. It supports cross-pathogen comparison and helps translate evidence from well-studied infections to novel or emerging threats
Github:
Reference:
2. Key epidemiological variables
Tools in this group estimate core quantities such as the serial interval, latent and infectious periods, reproduction numbers, and overdispersion
Latent & Infectious Period Estimators
Contributors:
National Institute for Public Health and the Environment (RIVM)
A set of estimators that link observed serial intervals and incidence data to the latent and infectious periods in SEIR/SIR models. The tools focus on identifying model-consistent parameterizations, clarifying parameter interpretation and supporting more robust model calibration
Github:
Reference:
Re and k from Cluster Size Distributions
Contributors:
University of Bern (UBern)
This framework estimates the effective reproduction number (Re) and dispersion parameter k using the size distribution of transmission clusters defined by identical viral sequences. It quantifies heterogeneity in transmission and helps identify settings where superspreading plays a substantial role.
Github:
Reference:
mitey & Vink Method – Serial-Interval Inference
Contributors:
National Institute for Public Health and the Environment (RIVM)
The mitey package implements the Vink et al. method to estimate the mean and standard deviation of the serial interval, as well as time-varying case reproduction numbers. It is designed for reproducible analysis and has been applied to scabies and other infectious diseases using routine surveillance and outbreak data.
Github:
Reference:
EpiDelays – Nonparametric Serial-Interval Estimation
Contributors:
University of Hasselt (UH)
EpiDelays implements a nonparametric framework for estimating epidemiological delay distributions including serial-intervals distribution from interval-censored symptom onset data. It provides summary statistics and uncertainty quantification, and is suitable for both retrospective analyses and early outbreak assessment.
Github:
Reference:
3. Reference models
Reference epidemic models that serve as benchmarks for comparison and projecting epidemic outcomes.
Epidemic Graph Diagram Framework
Contributors:
National Institute of Health and Medical Research (INSERM)
The Epidemic Graph Diagram framework couples detailed disease progression with explicit contact network structure using a diagrammatic approach. It can be used to derive epidemic thresholds, study the impact of interventions and interpret complex models via graph operations.
Github:
Reference:
Mass-Action & Configuration-Network Models
Contributors:
National Institute for Public Health and the Environment (RIVM), University of Bern (UBern), University of Hasselt (UH)
A set of implementations comparing classical mass-action models and configuration-network models that incorporate degree heterogeneity. The tools provide analytic expressions and simulation workflows to explore how network structure affects quantities such as initial growth rate, epidemic peak size, and final size.
Github:
Reference:
4. Epidemic trends & effectiveness of measures
Tools for reconstructing epidemic trajectories and quantifying the impact of public health measures.
Socio-Economic Contact Pattern Models
Contributors:
University of Bern (UBern)
These models extend traditional age-structured contact matrices to include socio-economic dimensions such as education or neighbourhood deprivation. They help explore how social structure shapes infection risk and identify groups where tailored measures may be most effective.
Github:
Reference:
Next-Generation Matrix Perturbation Tools
Contributors:
University of Hasselt (UH); University of Antwerp (UA)
A collection of tools for constructing next-generation matrices and performing sensitivity and elasticity analyses over time. They quantify the contribution of different groups (such as age group) to the reproduction number, guiding targeted interventions as epidemics evolve.
Github:
Reference:
NPI Effectiveness Framework
Contributors:
National Institute for Public Health and the Environment (RIVM)
This framework reconstructs a counterfactual reproduction number in the absence of non-pharmaceutical interventions (NPIs), while accounting for immunity, seasonality and variant dynamics. Comparing the observed and counterfactual trajectories yields time-varying estimates of the combined effectiveness of NPIs.
Github:
Reference:
EpiLPS – Nowcasting and Time-Varying Rt
Contributors:
University of Hasselt (UH)
EpiLPS uses Bayesian Laplacian P-splines to jointly model reporting delays and latent incidence, providing nowcasts and estimates of the time-varying reproduction number. It is designed for operational use with unified workflows that can be updated in real time as new data arrive.
Github:
Reference: