Clinic on Meaningful Modeling of Epidemiological Data

The 15th MMED clinic ~ June 15-26, 2026 ~ Muizenberg, Cape Town, South Africa

  1. Projects
  2. Potential project

Measles Transmission Dynamics: Model Fitting with Real Surveillance Data

Project pitch

Measles is one of the most contagious infectious diseases known, with a basic reproduction number (R0) of 12-18 , far higher than COVID-19 or influenza. Despite a safe, effective vaccine, large outbreaks have continued globally due to gaps in vaccination coverage. The 2019 DRC outbreak (>300,000 suspected cases, >6,000 deaths) represents a low-income, high-burden country with chronically low vaccination coverage. This project uses these real, recent, messy datasets to practice the core MMED skills of model building, likelihood-based fitting, and critical interpretation.

Research area(s)

  • Epidemiological modelling
  • Disease surveillance & outbreak analysis
  • Vaccine-preventable diseases

Data

Type of data

WHO provisional Measles & Rubella Monthly Surveillance Data

Description and status of data

  • Monthly incidence data with the caveat that suspected cases include unconfirmed diagnoses (reporting delays and under-ascertainment are real and discussable)
  • Vaccination coverage (MCV1 & MCV2)
  • Population denominators (UN World Population Prospects)

Software

Must have some experience using R.

Potential research question(s)

  • What are the estimated transmission rate (β) and recovery rate (γ), and hence (R0), for measles in the chosen setting, and how well does a simple SIR model fit the observed data?

  • Potential (additional) questions depending on the structure they choose:

    • Does adding an exposed/latent class improve the model fit? What does this tell us about model structure and identifiability?
    • What if MCV1 coverage had been 85% instead of 77%?
    • What if a supplementary immunisation campaign had reduced susceptibility by an additional 10%?

Resources

  • Sodjinou et al. (2022): Epidemiological characteristics of a protracted and widespread measles outbreak in the Democratic Republic of Congo, 2018–2020
  • Memon et al. (2020): Mathematical analysis for a new nonlinear measles epidemiological system using real incidence data from Pakistan
  • Kuddus et al. (2021): Mathematical analysis of a measles transmission dynamics model in Bangladesh with double dose vaccination