Computational Social Science Forum — Large-scale Spatial Network Models for modeling disease and information passing for people experiencing homelessness in metropolitan areas

CSS Training Program

November 9, 2021
4:00pm to 5:00pm
Virtual Participation


Computational Social Science Forum
Date: Tuesday, November 9, 2021
Time: 4:00-5:00 PM Pacific Time
Location: Virtual Participation – Register to attend via Zoom

Large-scale Spatial Network Models for modeling disease and information passing for people experiencing homelessness in metropolitan areas

Speaker: Zack Almquist, Assistant Professor of Sociology, University of Washington
Abstract: Recent increases in homelessness in the United States have been described as a nationwide emergency. The negative impacts of homelessness on communities and individuals are well-established, including significant impacts to health, safety, and social and economic equality. To address the effects of increasing homeless populations, particularly in cities on the west coast of the US where numbers are growing rapidly, social scientists must understand the size and distribution of their homeless populations, as well as how information and resources are diffused throughout these communities. Currently, there is limited publicly available information on people experiencing homelessness in the United States. The available information comes largely from the count estimates of homeless across the US gathered annually by the US Housing & Urban Development point-in-time (PiT) survey. While it is theorized in the literature that the networks of homeless individuals provide access to important information for social scientists in areas such as health (e.g. needle exchanges) or access (e.g. information diffusion about the location of new shelters), it is almost never measured and if measured only at a very small scale. In this work I introduce methods for simulating realistic social support and information networks in the homeless population. I then follow this up with new data from Anderson et al (2021) to directly estimate the parameters of this model and estimate the infection and mortality rate of COVID-19 in the homeless population in Nashville, TN. Finally, I will conclude with future directions for this work.

The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. This Forum is organized as part of the Computational Social Science Training Program, and weekly meetings are hosted by researchers from BIDS and D-Lab. The group welcomes social scientists and researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. Interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact for more information or if you are interested in presenting current research for an upcoming session.


Zack W. Almquist

Assistant Professor of Sociology, University of Washington

Zack W. Almquist is an Assistant Professor in Sociology at the University of Washington. He also holds positions as an Adjunct Assistant Professor in Statistics, Data Science Fellow in the eScience Institute and the Training Core PI in the Center for Studies in Demography and Ecology. Before coming to UW he held positions as a Research Scientist at Facebook and as an Assistant Professor in Sociology and Statistics at the University of Minnesota. He has served or serves on the Editorial Boards for the journals Social Networks, Sociological Perspectives, Population and Environment, and Sociological Methodology. Prof. Almquist is recipient of the American Sociological Association’s Leo Goodman Award and his research has been funded by the NSF, ARO and NIH.

His research centers on the development and application of mathematical, computational and statistical methodology to problems and theory of social networks, demography, education, homelessness, and environmental action and governance. Currently, his research program is focused on understanding, modeling, and predicting the effects that space (geography) and time have on human interaction (communication or needle sharing) and social processes (information passing or disease transmission). Dr Almquist’s research has been published in highly regarded peer-reviewed journals such as the Proceedings of the National Academy of Sciences, Journal of Computational and Graphical Statistics, Sociological Methods & Research, Sociological Methodology, Population Space and Place, Mathematical Population Studies, American Journal of Human Biology and Political Analysis.