The GLEAMviz simulator is a client-server application implementing the GLEAM model, meant to be used by epidemiologists and policy makers to analyse pandemic threats, forecast their evolution and help addressing the challenges faced in developing intervention strategies that minimise their impact.
GLEAM is a stochastic meta-population model that uses three fundamental layers, the population layer, the mobility layer and the disease layer. The world population is divided into more that 3200 sub-populations centred around the major airline transportation hubs: the population layer uses data from the Gridded Population of the World project by SEDAC (https://sedac.ciesin.columbia.edu/data/collection/gpw-v4). Those census areas are interconnected through two different mobility networks, long range mobility uses data about airline passengers collected from OAG, while short range mobility between neighbouring regions is simulated using commuting data. In each sub-population the disease dynamics uses a compartmental modelling approach: the evolution of the epidemic is determined by equations describing the transition of individuals between different compartments.
The GLEAM model has been extended in different ways, for example by integrating it with detailed Agent Based Models at the country level, and has been used and validated in many real life scenarios, starting from the 2009 H1N1 flu pandemic. By using the GLEAMviz simulator is possible to perform scenario analysis and estimate the efficacy of various containment strategies.
The GLEAMviz client allows users to design simulations of infectious disease outbreaks with high level of flexibility. It is possible to define complex compartmentalisations and input the transition parameters in a structured way, then, specifying the initial conditions, is possible to simulate the evolution of a pandemic estimating relevant quantities such as incidence, invasion time, etc.. The tool allows to simulate various mitigation strategies, i.e. the usage of drugs or vaccines, and compare the predicted evolution with the baseline scenario.