“It all starts with the University of Chicago vision for data science as an emerging new discipline, which will be reflected in the educational experience,” said Michael J. Franklin, Liew Family Chairman of Computer Science and senior advisor to the Provost for computing and data science. “We are expanding upon the conventional view of data science—a combination of statistics, computer science and domain expertise—to build out the foundations of the field, consider its ethical and societal implications and communicate its discoveries to make the most powerful and positive real-world impact.” Building upon the data science minor and the “Introduction to Data Science” sequence taught by Franklin and Dan Nicolae, professor and chair in the Department of Statistics and the College, the major will include new courses and emphasize research and application. Through the new Data Science Clinic, students will capstone their studies by working with government, non-profit and industry partners on projects using data science approaches in real world situations with immediate, substantial impact. “The courses will take students through the go whole data science lifecycle, with all the concepts that they need to know: data collection, data engineering, programming, statistical inference, machine learning, databases, and issues around ethics, privacy and algorithmic transparency,” Nicolae said. “But for data science, experiential learning is fundamental. Students will partner with organizations on and beyond campus to advance research, industry projects and social impact through what they have learned, transcending the conventional classroom experience.” “The College’s new data science major offers students a remarkable new interdisciplinary learning opportunity,” said John W. Boyer, dean of the College. “The Core introduces students to a world of general knowledge useful for the active, but highly thoughtful practice of modern citizenship, while our brilliant majors enable students to gain active experience in the excitement of fundamental, pathbreaking research. I am delighted that data science will now join the ranks of our majors in the College, introducing students to the rigor and excitement of the higher learning.” Ashley Hitchings never thought she’d be interested in data science. When she arrived at the University of Chicago, she was passionate about investigative journalism and behavioral economics, with a focus on narratives over number-crunching. But the “Introduction to Data Science” sequence changed her view. “I was interested in the more qualitative side, sifting through really large sums of information to try to tease out an untold narrative or a hidden story,” said Hitchings, a rising third-year in the College and the daughter of two engineers. “I had always viewed data science as something very view publisher site much oriented toward people passionate about STEM, but the data science sequence really framed it as a tool that anyone in any discipline could employ, to tell stories using data and uncover insights in a more quantitative and rigorous way.” The courses provided Hitchings with technical skills in programming, data analytics, statistical prediction and visualization, and allowed her to exercise that new toolset on real-world problems. At the end of the sequence, she analyzed the rollout of COVID-19 vaccinations across different socioeconomic groups, and whether the Chicago neighborhoods suffering most from the virus received equitable access. Now she’s using her data science knowledge in a summer internship analyzing health care technology investment opportunities. “Even in roles that aren't data science jobs, per se, I had the skill set and I was able to take on added responsibilities,” Hitchings said.


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To examine the potential epidemiological and evolutionary impacts of ‘vaccine nationalism’, we extend previous models to include simple scenarios of stockpiling between two regions. In general, when vaccines are widely available and the immunity they confer is robust, sharing doses minimizes total cases across regions. A number of subtleties arise when the populations and transmission rates in each region differ, depending on evolutionary assumptions and vaccine availability. When the waning of natural immunity contributes most to evolutionary potential, sustained transmission in low access regions results in an increased potential for antigenic evolution, which may result in the emergence of novel variants that affect epidemiological characteristics globally. Overall, our results stress the importance of rapid equitable vaccine distribution for global control of the pandemic. The SARS-CoV-2 pandemic has led to more than 180 million infections and nearly 4 million fatalities to date ( 1 ). Effective vaccines [e.g., ( 2 – 4 )] have now been approved and are actively being deployed, but numerous important questions remain. Eventually, community immunity may be attained through the deployment of vaccines; however if and when this occurs will be contingent on the characteristics of natural and vaccinal immunity ( 5 – 7 ). As illustrated by the rapid spread and high transmissibility of the ‘delta’ variant ( 8 ), SARS-CoV-2’s evolutionary potential is a major potential obstacle for control ( 9 ). Due to strong public and political pressures and fear of waning immunity, some countries with high vaccine availability are currently resorting to ‘vaccine nationalism’: stockpiling vaccines to prioritize rapid access to their citizenry ( 10 ). Indeed, at the time of writing, 99 and 117 doses per 100 individuals have been administered in the United States and United Kingdom, respectively, while an average of 25 and 3.8 doses per 100 individuals have been administered in India and across Africa, respectively ( 11 ). Recently, the World Health Organization recognized that delayed access to vaccines in countries with low vaccine availability may lead to more evolutionary potential ( 12 ), which could result in immune escape or other phenotypic changes of interest (e.g., increases in transmission). The emergence of future variants capable of evading natural or vaccinal immune responses could threaten containment efforts globally. These concepts underlie the development of a number of policy tools, including the existing COVAX initiative. Furthermore, to ensure that vaccine distribution is ethically-sound and equitable, the “Fair Priority Model” has been proposed ( 13 – 15 ) as a potential replacement to the currently planned proportional allocation (by population size) from COVAX. Prior work has explored optimal prophylactic vaccine allocation for minimizing the final epidemic size of a fully immunizing infection (i.e., one that can be modeled using a susceptible-infected-recovered (SIR) framework) ( 16 ); when interaction between communities (or countries) is considered, equal vaccine distribution is increasingly advantageous in terms of minimizing case numbers ( 16 ). Modeling studies have also shown that coordinated influenza vaccine sharing would reduce the financial and infection burden of influenza outbreaks globally ( 17 ).