Abstract
To understand the current situation of public health in a region and to analyze the impact of public health interventions, researchers need more refined information on the health of individuals than what is currently available. While research surveys and population cohort studies may contain a large amount of data, they do not provide a comprehensive coverage of a population and may not account for all components of the built environment that the population lives in, which may have an impact on their health. This project focuses on the development of a Synthetic Ecosystem – a digital platform that provides a virtual representation of a given population within a given geographic region. It depicts the characteristics of the individuals in the population in addition to the built environment that surrounds them. The principal step in this process involves the development of a ‘Synthetic Population’, a synthetically generated population built from Canadian census data, that statistically represents the population of interest. Statistical methods such as Iterative Proportional Fitting were used to develop a synthetic population for Montreal. Built environment data (healthcare services, food organizations, etc.) were analyzed and overlayed with the synthetic population in a Business Intelligence platform to provide a user-friendly visualization of the Synthetic Ecosystem. This holistic representation will serve as a platform for decision support for public health researchers and allow for effective decision-making. The next steps include enhancing the synthetic population by incorporating data from population cohort studies and assign cohort-specific characteristics directly to specific population segments.
