Full title: Density dependence and disease dynamics: a cross system synthesis Join Q&A on Slack: bit.ly/EvoEco2

Date: 09/23/24 Abstract: Human mobility is a critical driver of epidemics by substantially altering the probability of encounters, patterns of exposure, and the likelihood of disease propagation. While long-range movements may shape patterns of pathogen importation, short-range mobility and contact structures amplify local epidemics. Characterizing mobility patterns and social mixing across scales is therefore essential for understanding why and how epidemics emerge and spread, as well as for developing effective prevention and control strategies. The COVID-19 crisis, sparked a data-sharing revolution, with network operators such as Orange and Telefonica, along with tech giants like Google, Apple, and Facebook, providing real-time aggregated mobility data from mobile phone traces to track human mobility and help fight the pandemic. Epidemiological research is now focused on developing novel mathematical and computational frameworks to integrate high-resolution mobility data into models, enabling both retrospective analyses and real-time epidemic monitoring. In my talk, I will discuss how we utilized these data during the early stages of COVID-19 in France to capture the dynamic shifts in social mixing caused by mobility interventions and address critical public health questions. Additionally, I will present a retrospective theoretical study that characterizes the mobility factors shaping geographical diffusion across scales in the United States and demonstrates a model designed to optimize reliability for outbreak response while balancing mobility data requirements. Bio: Dr. Giulia Pullano is a postdoctoral fellow at Georgetown University in Washington, DC, USA, working in the Bansal Lab within the Biology Department. Her research focuses on developing mathematical and computational models to understand the geographical dynamics of human-to-human diseases and inform public health policies. She is particularly interested in characterizing seasonal patterns in human behavior and disruptions during epidemics or extreme events to integrate them into epidemic models and optimize public health interventions. From 2020 to 2022, Dr. Pullano has been actively involved in the COVID-19 pandemic response, advising French public health agencies and government authorities. Dr. Pullano earned her PhD in Biomathematics and Public Health from the French National Institute of Health and Medical Research (INSERM), Sorbonne University, and Orange S.A., under the supervision of Dr. Vittoria Colizza. She obtained a Master’s degree in Physics of Complex Systems from Università degli Studi di Torino in 2016 and a Bachelor's degree in Physics from Università degli Studi di Roma La Sapienza in 2014.

This informative conversation is moderated by Kiki Sanford, neurophysiologist and science communicator, and features Provost's Distinguished Associate Professor at Georgetown University's Department of Biology, Shweta Bansal. You may access more information on this recording and others in the Distinguished Lectureship special series on COVID-19 at http://www.sigmaxi.org/lectureships Sigma Xi is an international, multidisciplinary research society whose programs and activities promote the health of the scientific enterprise and honor scientific achievement. Founded in 1886, the Society has elected more than half a million research scientists and engineers to membership, including more than 200 Nobel Laureates. More information at: http://www.sigmaxi.org/

In this talk, we discuss how we can use a multi-scale socio-behavioral disease modeling approach to integrate interacting elements of health, physical and socially-constructed environments, and community and individual behavior to predict social and spatial heterogeneities in respiratory disease burden. In particular, we leverage opportunistic datasets to characterize behavior and disease across geography and time to resolve questions that have eluded explanation without socio-behavioral data; and we develop generative and inferential models for a systematic understanding of the constant, compounding socio-behavioral processes that give rise to disease heterogeneities across individuals, communities, and systems. This recording is a part of a series of talks on the critical impact of modelling during early pandemics and in shaping the future of surveillance systems. Our aim? To broaden the modelling landscape to meet the public health challenges we face today. All talks are available in our YouTube playlist!

Title: The extent of gender and race/ethnicity imbalance in infectious disease dynamics research Speaker: Dr Shweta Bansal (Georgetown University) Date: 7th Aug 2024 - 10:15 to 10:30 Event: (MIPW01) Modelling and inference for pandemic preparedness - a focussed workshop 🔗 Find out more: https://www.newton.ac.uk/seminar/43429 ------------------- FOLLOW US 🌐| Website: https://www.newton.ac.uk 🎥| Main Channel: https://www.youtube.com/@isaacnewtoninstitute 🐦| Twitter: https://twitter.com/NewtonInstitute 💬| Facebook: https://www.facebook.com/newton.institute 📷| Instagram: https://www.instagram.com/isaacnewtoninstitute 🔗| LinkedIn: https://www.linkedin.com/company/isaac-newton-institute-for-mathematical-sciences SEMINAR ROOMS 🥇| INI Seminar Room 1: https://www.youtube.com/@iniseminarroom1 🥈| INI Seminar Room 2: https://www.youtube.com/@iniseminarroom2 🛰️| INI Satellite Events: https://www.youtube.com/@inisatellite ABOUT The Isaac Newton Institute is a national and international visitor research institute. It runs research programmes on selected themes in mathematics and the mathematical sciences with applications over a wide range of science and technology. It attracts leading mathematical scientists from the UK and overseas to interact in research over an extended period. 👉 Learn more about us and our events here: https://www.newton.ac.uk

Network epidemiology to unravel the relationship between behavior and infectious disease Abstract Network science has revolutionized the study of interacting elements, and the field of network epidemiology, which focuses on problems of infectious disease spread, has been one of the best success stories of applied network science. In this talk, I’ll discuss how network science has shaped the modeling of infectious diseases across scales and, in particular, our understanding of the link between host behavior and infectious disease transmission and control. Bio Shweta Bansal is a Provost's Distinguished Associate Professor of Biology at Georgetown University. She is trained as a network scientist and disease ecologist from the University of Texas at Austin and was a fellow of the prestigious RAPIDD Postdoctoral Program (of the US National Institutes of Health and the Department of Homeland Security). At Georgetown University, she leads an interdisciplinary research group that develops data-driven mathematical models to address how social behavior and spatial dynamics shape infectious disease transmission and how knowledge of such processes can improve disease surveillance and control in human and animal disease systems.