Human population

The understanding of human population characteristics and behaviour lies at the heart of many of the biggest challenges facing society. Important aspects of human populations are not directly measurable at every point in time and space, hence typical sources are a mix of census-type data, administrative records and incomplete observational data. These measurements may often be sufficient to describe some aspects of population (for example the geographical distribution of residential population on census day) but do not provide sufficient insight into other essential dimensions (for example daytime population distributions, travel behaviour, patterns of wealth or wellbeing). Better representation of the population underlies many research and policy challenges such as resource allocation, service delivery, transportation planning and the calculation of prevalance rates. Computational modellign work in this field ranges across data collection, representation and modelling of population, particularly simulation and computation of those characteristics which cannot be directly measured. It includes computational methods for the design of optimal zoning systems and the creation of time-specific probabilistic geographical population distributions, microsimulation of individual-level characteristics and future projections.

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