Settings

See About tab for scenario details

Parameters

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Forecasts

Cases over time, fitted and forecast

Sensitivity Settings

This controls the proportional change in parameters for sensitivity analysis.

Parameter inclusion

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Parameter Sensitivity

Parameters in bold were fitted to surveillance data. Others parameters are based on literature or manual calibration

About the mpox SMCAM Model v0.1.6

Model Objectives

The mpox Stochastic Moment Closure Approximation Model (SMCAM) aims to quantify and compare the contribution of different behavioral and immunological factors to the maintenance of mpox transmission in Europe. This analysis focuses on population-level risk dynamics, individual-level risk dynamics, waning immunity, and population turnover as plausible factors which either individually or collectively increase the force of infection and lead to sustained transmission in European MSM populations.

Model Approach

We developed a stochastic SEIR model incorporating heterogeneous transmission risk and moment closure approximations. The key feature is that infectiousness is correlated with susceptibility via extreme heterogeneity in risk behavior (e.g. number of sexual partners). The model uses a data-driven approach for estimating risk heterogeneity and focuses on longitudinal changes in risk behavior both at the individual and population level, as well as changes in population immunity.

Applications

This tool allows users to explore forecasting scenarios and parameter sensitivity for mpox transmission in the Netherlands, Spain, and Ireland. Users can modify epidemiological parameters to understand their impact on transmission dynamics and generate probabilistic forecasts under different assumptions about risk behavior, immunity waning, and importation patterns.

Scenarios

The following predefined scenarios are available for forecasting:

  • Default: Uses fitted parameter values without modification
  • Higher transmissibility: Increases transmission rate (r) by 10% to explore scenarios with enhanced viral transmission
  • More importation: Increases importation rate (ι₀) by 3-fold to model higher case importation from other regions
  • Increase in subclinical infections: Models a scenario with more subclinical disease by increasing the infectious period (γᵢ) by 20%, decreasing the detection rate (ρ) by 20%, and decreasing the transmission rate (r) by 15%

Contact Information

Erik Volz

MRC Centre for Global Infectious Disease Analysis

Imperial College London

e.volz@imperial.ac.uk

This application implements the model described in: "Model-based investigation of factors sustaining mpox transmission in Europe in 2025" by Erik Volz, Imperial College London.

App version: 0.1.6