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Epidemic simulations require the ability to sample contact networks fromvarious random graph models. Existing methods can simulate city-scale or evencountry-scale contact networks, but they are unable to feasibly simulateglobal-scale contact networks due to high memory consumption. NiemaGraphGen(NGG) is a memory-efficient graph generation tool that enables the simulationof global-scale contact networks. NGG avoids storing the entire graph in memoryand is instead intended to be used in a data streaming pipeline, resulting inmemory consumption that is orders of magnitude smaller than existing tools. NGGprovides a massively-scalable solution for simulating social contact networks,enabling global-scale epidemic simulation studies.

NiemaGraphGen: A memory-efficient global-scale contact network simulation toolkit