Model name: Japanese Encephalitis (JE) model (model under development)
Modellers: Hannah Clapham, Duy Nguyen Institution: National University of Singapore, (previously Oxford University Clinical Research (OUCRU), Vietnam)
This Japanese Encephalitis (JE) model uses a simple transmission model to estimate the impact of vaccination on JE cases. First, the relationship between currently available case data (and subsequently serological data), and environmental, climatic, animal covariates is modelled. The model is then used to estimate transmission intensity across Southeast Asia. A simple transmission model then models the relationship between transmission intensity, vaccine usage and cases. All models are fitted in a Bayesian framework and uncertainty included in the output estimates by sampling from the posterior estimates.
Model name: Japanese Encephalitis (JE) model
Modeller: Sean Moore and Tran Minh Quan
Institution: University of Notre Dame
The number of cases, deaths, and DALYs are calculated by first estimating a national or sub-national level force of infection (FOI) rate per susceptible individual from age-specific case and seroprevalence data prior to the introduction of vaccine. The FOI is then multiplied by the estimated number of susceptible individuals per age class to arrive at an expected number of infections. The number of susceptible individuals is estimated via a spatial analysis of the number of people living in JE-endemic areas. The model incorporates uncertainty in the estimation of the FOI and susceptible population sizes.