About

This repository contains documentation related to the project "Quantifying the Impact of Data Sharing on Outbreak Dynamics" (QIDSOD) that is

• jointly led by
  • Jundong Li (School of Engineering and Applied Science, Electrical and Computer Engineering, Computer Science & School of Data Science at the University of Virginia) and
  • Daniel Mietchen (School of Data Science at the University of Virginia)
• jointly funded through a COVID-19 Rapid Response grant by
  • the Global Infectious Diseases Institute (GIDI) at the University of Virginia, in partnership with
  • the Office of the Vice-President for Research of the University of Virginia.

Project summary

In this project, we will explore the range of data-related decisions made during public health emergencies like the ongoing COVID-19 pandemic and analyze the flow of information, data, and metadata within networks of such decisions.

Data sharing is now considered a key component of addressing present, future, and even past public health emergencies, from local to global levels. Researchers, research institutions, journals and others have taken steps towards increasing the sharing of data around the ongoing COVID-19 pandemic and in preparation for future pandemics.

We will quantify the effects of data flow modifications to identify parameter sets under which specific modes of sharing or withholding information have the largest effects on outbreak dynamics. For these high-impact parameter sets, we will then assess the current and past availability of corresponding data, metadata, and misinformation, and estimate the effects on outbreak mitigation and preparedness efforts.

Further information

We are just getting started, but here are some resources to help you get into the mood of thinking along.

Research proposal

More details on our plans are available through the research proposal:

• Mietchen D, Li J (2020) Quantifying the Impact of Data Sharing on Outbreak Dynamics (QIDSOD). Research Ideas and Outcomes 6: e54770. https://doi.org/10.3897/rio.6.e54770

Background reading

Some publications that provide an introductory overview to some aspects of our planned research:

• Morgan, Oliver (2019). "How decision makers can use quantitative approaches to guide outbreak responses". Philosophical Transactions of the Royal Society B: Biological Sciences. 374 (1776): 20180365. doi:10.1098/rstb.2018.0365
• Chretien, Jean-Paul; Rivers, Caitlin M.; Johansson, Michael A. (2016). "Make Data Sharing Routine to Prepare for Public Health Emergencies". PLOS Medicine. 13 (8): e1002109. doi:10.1371/journal.pmed.1002109
• Keeling, Matt (2005). "The implications of network structure for epidemic dynamics". Theoretical Population Biology. 67 (1): 1–8. doi:10.1016/j.tpb.2004.08.002
• Castro, K. G. (2007). "Tuberculosis Surveillance: Data for Decision-Making". Clinical Infectious Diseases. 44 (10): 1268–1270. doi:10.1086/514351