Measles
LSHTM measles model
Lead modeller: Mark Jit
Link to all modelling group members
Institution(s): London School of Hygiene & Tropical Medicine (LSHTM)
Brief description of model:
DynaMICE (Dynamic Measles Immunisation Calculation Engine) is a compartmental dynamic model of measles transmission and disease. It is based on a model initially developed by investigators at the London School of Hygiene & Tropical Medicine, Harvard University and the University of Montreal with WHO funding to inform the impact of measles supplementary immunisation activities (SIAs). It has now been expanded to consider the impact of routine first and second doses as well as SIA doses in 117 low- and middle-income countries under country-specific schedules. It has been used to answer strategic questions for a range of global stakeholders including Gavi, BMGF, WHO and UNICEF.
DynaMICE has a finely age-stratified SIRV (Susceptible-Infectious-Recovered-Vaccinated) structure and uses synthetic contact matrices to inform transmission between age groups to estimate measles cases. The deaths resulting from these cases are then calculated from case-fatality risks from a global meta-regression. The model assumes vaccine efficacy for a first routine dose to increase with age and vaccine protection to be lifelong. It also incorporates survey data on vaccine timeliness by modelling deployment at weekly time steps for children aged between 0 and 2 years old, as well as on the association between receiving a first routine dose of measles and receiving an SIA dose.
Figure 3. Susceptible population younger than 5 years by vaccination delivery strategy (2000–20)
Model code (where available):
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PSU measles model
Lead modeller: Matt Ferrari
Link to all modelling group members
Institution(s): Pennsylvania State University (PSU)
Brief description of model:
This is a stochastic, age-specific, phenomenological transmission model that is fit independently to each country based on annual cases reported to WHO. Herd effects are represented in an annualized attack rate function that assumes reduced transmission as population immunity increases. Model parameters (attack rate function and observation rates) are updated annually based on new reported cases in collaboration with WHO. Model projections reflect stochastic variation in transmission and confidence intervals on estimated parameters.
Model code (where available):