Meet the scientists seeking new insights on COVID-19. Every month, the COVID Information Commons (covidinfocommons.net) brings together a group of researchers studying wide-ranging aspects of the current pandemic, to share their research and answer questions from our community. Learn more about their ongoing efforts in the fight against COVID-19, including opportunities for collaboration.
Community-transmission is responsible for over three-quarters of the COVID-19 cases in the US. Yet, current models do not consider localized behavior to predict virus transmission or the extent of propagation within individualized settings and their surrounding communities. The DETER project will provide such data and demonstrate new three-dimensional means to understand community-level risk.
The objective of this project is the development of a user-friendly, scalable, and modular workflow for conducting a real-time computational phylogenetic analysis of assembled viral genomes, with a primary focus of SARS-CoV-2. The analysis infrastructure that will be built in this project will be broadly applicable to any viral pathogen for which phylogenetic inference is biologically and epidemiologically meaningful.
This project explores how Americans’ views of and behavior towards the coronavirus change - or do not change - over 9 months. This will serve the national interest in progress in science by improving our understanding of how people’s beliefs, attitudes, and behaviors interact both within the same person over time, and between people with individual differences in attitudes at a given time.
The overall purpose of this RAPID project is to urgently advance a safe, sustainable and high-efficiency sterilization technology by conducting collaborative and systematic research on the sterilization mechanism of corona discharge (CD). This project will provide fundamental understanding and technical validation for a portable sterilization technique, the corona discharge, to be safely and effectively used for sterilization and recharge of used face masks, N95 respirators, and PPEs.
This research provides a more adaptive isolation and quarantine process based on actual individuals' mobility patterns. Specifically, it advances the state of knowledge regarding 1) how to define the borders of high-risk patches considering the location and movements of confirmed patients, 2) what is the risk of each patch based on the strength of connectivity between these patches, 3) how this information enables policymakers to make better and faster decisions across the scales, and 4) how models can better simulate the epidemic spread within and among societies.
Different from existing, classic epidemic models, in this project we aim to build novel forecasting models based on cutting-edge AI techniques. The goal is to provide timely, localized information needed by administrators for strategic allocation of resources and planning towards reopening business.