We strive to create an environment conducive to many different types of research across many different time scales and levels of risk.
We introduce a population dynamics foundation model and dataset able to easily be adapted to solve a wide array of geospatial problems across health, socioeconomic, and environmental tasks.
The relationships between a population of people, their health outcomes, and their local contexts can be very complex. Nevertheless, developing an understanding of these population dynamics can be crucial for addressing complex social problems, such as disease, economic security, disaster response, and much more. Despite the importance, however, accurate predictions for these population dynamics have been elusive for decades and remain a challenge for researchers, policymakers, and businesses.
Traditional approaches to understanding population dynamics tend to rely on data from censuses, surveys, or satellite imagery. While valuable, these types of data each have their own unique shortcomings. Censuses, though comprehensive, are infrequent and expensive; surveys can offer localized insights, but often lack scale and generalizability; and satellite imagery provides a broad overview, but lacks granular detail on human activity. In an effort to mitigate some of these shortcomings, over the years Google has designed, built, and shared a wealth of datasets that offer unique insights into population behavior, including Google Search Trends, COVID-19 Community Mobility Reports, and Access to Emergency Obstetrics Care.