“Finding Online Extremists in Social Networks”
Speaker: Tauhid Zaman
KDD Career Development Professor in Communications and Technology
MIT Sloan School of Management
YINS Affiliate Alison Galvani combines technology and mathematics to predict patterns of deadly infectious disease
Alison P. Galvani, the youngest person ever appointed to an endowed professorship at the medical school, has combined technology with the power of mathematics to predict patterns of deadly infectious disease. Galvani’s work has changed the trajectory of disease treatment and prevention. (Photo by Harold Shapiro)
The ecology of disease
From the flu to Ebola, predicting and then stifling pathogens’ spread
Alison P. Galvani, Ph.D., the Burnett and Stender Families Professor of Epidemiology, has devoted her research career to tracking diseases, and to transforming data into predictive maps and practical policy recommendations. So distinguished is her body of work that in 2015, at age 38, Galvani became the youngest-ever appointee to an endowed professorship at the School of Medicine.
When Galvani was just 5 years old, growing up in San Francisco, her mother—a clinical psychologist—died. According to Galvani, her grief instilled in her an abiding passion for helping the downtrodden and orphaned.
When she was in high school, a copy of Richard Dawkins’ book The Blind Watchmaker sparked her interest in evolutionary biology. Galvani took it upon herself to write a letter to Dawkins challenging some of his premises and outlining some of her own ideas about evolutionary processes. Dawkins praised Galvani in his reply and encouraged her to apply to the University of Oxford for an undergraduate degree in biology.
Galvani not only took his advice, but remained at Oxford to pursue a doctorate under theoretical biologist Robert May. Following a postdoctoral fellowship at the University of California, Berkeley, she came to Yale as a junior faculty member. By that time her pioneering work in behavioral epidemiology—how human behavior leads to and affects disease transmission—was well underway. “I’m fascinated by the power of mathematics to contribute in very practical ways to the benefit of society,” she says.
Galvani’s team at Yale has conducted international investigations into the transmission of HIV, influenza, Ebola, and Zika, among other pathogens. “We are most interested in projects that have the potential to improve policy and save lives,” she says. Her work on influenza and rotavirus has led to concrete policy changes and made vaccination programs in Israel and the United Kingdom more cost effective.
Galvani established the Center for Infectious Disease Modeling and Analysis (CIDMA) within the School of Public Health in 2014, shortly before the Ebola epidemic hit western Africa. When it did, she offered her team’s help in understanding the disease’s dynamics to Liberia’s health ministry, which welcomed the aid. Galvani and her colleagues worked tirelessly to generate models to capture the level of virus in patients, the patients’ survival outcomes, and the social behavior of affected families, all of which formed the basis for effective ways to stem the epidemic. Their predictions of the impact of combined interventions—published in the journal Science—forecast trajectories of the epidemic in Liberia with remarkable accuracy.
Galvani’s team also developed a smartphone app to track the location of symptomatic patients. Previously, with only pencil and paper to do that job, the arrival of ambulances had been delayed by as much as several days. With resources in Liberia severely limited, CIDMA contributed more than 30 computers and phones to the Ebola response team so that the mobile application could function. Patients received hospital care far more rapidly, improving recovery rates and curtailing further transmission.
Galvani has received numerous honors including the Blavatnik Award for Young Scientists from the New York Academy of Sciences, the Bellman Prize, and a Guggenheim Fellowship.
Throughout her career, as she has managed students and postdocs, and raised three children in a home that also includes a dog and a full chicken coop, Galvani has continued to apply the lessons of evolutionary biology that she first learned from Dawkins. “The same principles of ecology and species conservation apply, but in reverse,” she says. “In disease systems, we want to drive the parasite species extinct.”
Targeting the social networks of group violence
A strong network of friends may be just as big a factor in acts of group violence as having a charismatic leader or a savvy battle plan, according to a new study.
Researchers studied the social dynamics of the Nyangatom, a nomadic tribal group in East Africa that is regularly involved in violent raids with other groups. The researchers mapped the interpersonal connections among Nyangatom men over a three-year period, focusing on how those friendship networks affected the initiation of raids and participation in those raids.
The findings, which appear the week of Oct. 10 in the Proceedings of the National Academy of Sciences, may also apply to potentially violent activities associated with terrorism, revolutions, and gangs.
“Social interactions in networks are crucial for the emergence of positive phenomena, like cooperation and innovation, but they also play a role in other sorts of collective behavior, like the seemingly spontaneous emergence of violence,” said Nicholas Christakis, co-director of the Yale Institute for Network Science (YINS) and senior author of the study. Christakis is a professor of sociology, ecology & evolutionary biology, biomedical engineering, and medicine at Yale.
“People go to war with their friends, and the social network properties of such violent activities have rarely been explored,” Christakis added.
The study found that the initiation of Nyangatom raids depended on the presence of leaders who had participated in many raids, had more friends, and held central positions in the social network. However, membership in raiding parties depended on a population much larger than the leaders’ network of friends. Non-leaders, in fact, had a bigger impact on raid participation than leaders, by virtue of their own friendships.
“Collective action doesn’t get off the ground with just a charismatic leader attracting random followers,” said Alexander Isakov, co-first author of the study and a postdoc at the Human Nature Lab at YINS. “People are driven to participate in the group predominantly due to friendship ties.”
A surprising aspect of the findings, according to the researchers, was the interplay between leadership and friendship in an environment without any formal hierarchy. The Nyangatom raiding groups are informal groups of peers, yet individuals played distinct roles that mirrored a formal leadership structure.
“They have no formal political leaders or chiefs,” said co-first author Luke Glowacki, a research fellow at the Institute for Advanced Study in Toulouse, France. “The lack of political centralization creates an opportunity to study the social dynamics of collective action in a way that is difficult in a state society such as our own. We wanted to know how, outside of formal leadership or institutions, real-world collective behavior, including violence, is initiated.”
The researchers said their work suggests that diminishing a leader’s impact may prevent an original spark of violence. Yet the study also suggests that once violence begins, participants are likely to join in from throughout the entire group’s population. Once initiated within a network, violent tendencies and groups propagate.
In addition, the study offers a mathematical system to observe multiple groups over a period of time and determine who the leaders are in the overall population.
Additional co-authors of the study are Richard Wrangham of Harvard University, Rose McDermott of Brown University, and James Fowler of the University of California-San Diego.
Forrest Crawford, YINS Faculty Affiliate and YSPH Researcher, Receives National Award for Innovative, Creative Science
A Yale School of Public Health researcher is one of the 2016 recipients of the NIH Director’s New Innovator Award. The prestigious award funds the work of investigators who are conducting highly creative, innovative research in the early stages of their careers.
Forrest W. Crawford, Ph.D., assistant professor of biostatistics and of ecology and evolutionary biology, was granted the award for his project, titled “Network-based epidemiology for hidden and hard-to-reach populations.” Through development of novel statistical and computational methods, Crawford aims to dramatically improve epidemiological surveillance for hidden and hard-to-reach populations.
The groups at highest risk for adverse epidemiological health outcomes, like HIV infection, can also be the most difficult for public health researchers to study. For example, groups that experience social stigma or discrimination, like injection drug users, sex workers and men who have sex with men, may fear exposure or persecution if they participate in a research study. This difficulty limits the capacity of public health researchers to collect accurate information about disease burden and risk factors in these groups. Lack of information about risk groups makes it difficult for policymakers to target public health interventions to the populations that most need them.
“This award will allow us to devote time and resources to solving one of the most difficult problems in public health and epidemiology,” said Crawford, who joined the school’s faculty in 2012 and is also a member of the Center for Interdisciplinary Research on AIDS (CIRA) at Yale.
Traditional methods for learning about the characteristics of a large population rely on random sampling from a list of all individuals who meet certain inclusion criteria. However, in epidemiological studies of hidden and hard-to-reach groups, no such list exists, and researchers must resort to methods that leverage the social structure of the target population to recruit subjects. In many studies, participants are asked to refer or recruit others who meet inclusion criteria to researchers. The most popular such social link-tracing method is called “respondent-driven sampling”, or RDS.
In his proposal, Crawford outlines a new method of analyzing data gathered through RDS, and also plans to create easy-to-use, open-source, web-based software that implements these methods. With these new tools, researchers will better able to collect accurate information about hidden, at-risk populations, and infer properties of social networks and estimate population characteristics in order to design better clinical studies, which could ultimately lead to better interventions in these challenging populations. His work also represents a unique opportunity to bridge the divide between the emerging field of network science and epidemiological surveillance for key populations.
This award will allow us to devote time and resources to solving one of the most difficult problems in public health and epidemiology”
FORREST W. CRAWFORD
The NIH Director’s New Innovator Award was created in 2007 to support young investigators conducting potentially paradigm-shifting work in their fields. Recipients are awarded $1.5M over five years. The New Innovator Award is part of the high-risk, high-reward program, whose aim is to “support scientists of exceptional creativity who propose highly innovative approaches to major contemporary challenges in biomedical research.”
“This is a fantastic honor and it reflects on the remarkable research that Forrest has done during a relatively short time at YSPH,” said Dean Paul Cleary. “This project is vitally important and it aligns closely with the mission of the school.”
At Yale, Crawford’s research group focuses on creating statistical, computational, and mathematical tools to solve the most pressing challenges in the field of public health, with a particular emphasis on statistical problems in epidemiology that are not solvable by standard methods. His experience in biology, epidemiology, medicine, public health, mathematics, and statistics has resulted in important contributions to innovative cross-disciplinary research in biology, medicine, and public health.
The challenges of RDS in reaching at-risk, hard-to-reach populations led him to examine the problems of the method. He has previously published on the nature of data collected by RDS, and has participated in a UNAIDS panel on population size estimation for key risk groups.
In addition to his work on disease rate estimation in hidden populations, Crawford focuses on statistical methods for learning from stochastic processes in genetics, evolution, epidemiology, neuroscience, and public health. His ongoing projects include studies of infectious disease dynamics, vaccine effects, network diffusion processes and molecular evolution. He received his Ph.D. from UCLA in 2012.
“Forrest is a rising star in statistics. His work is bringing modern statistical and computational approaches to addressing some of the most significant and challenging public health problems. We are very proud of his accomplishments and honored to have him as our colleague,” said Hongyu Zhao, chair of the Department of Biostatistics.
See the full list of recipients at commonfund.nih.gov/newinnovator/Recipients16.