A collection of websites to assist forecasters
2019 Novel Coronavirus Research Compendium (NCRC)
Johns Hopkins Bloomberg School of Public Health. “We prioritize original, high-quality research for public health action and papers receiving significant attention, regardless of quality.”
OUTBREAK Science Rapid PREreview
A web application for open, rapid reviews of outbreak-related pre-prints.
COVID-19 related publications, updated daily.
MIT’s Rapid Reviews COVID:19 is an open-access overlay journal that accelerates peer review of COVID-19 related research preprints to advance new and important findings, and prevent the dissemination of false or misleading scientific news.
Citation searches.
Maps, charts, and data provided by the Centers for Disease Control and Prevention.
COVID-19 Open Research Dataset – “The Semantic Scholar team at the Allen Institute for AI has partnered with leading research groups to provide CORD-19, a free resource of more than 130,000 scholarly articles about the novel coronavirus for use by the global research community.”
The Delphi group at Carnegie Mellon University involved in epidemiological forecasting.
“Assembled free and open datasets of patent documents, scholarly research works metadata and biological sequences from patents, and deposited them in a machine-readable and explorable form.”
Global dashboard.
Institute for Health Metrics and Evaluation
“This website is a resource to help advance the understanding of the virus, inform the public, and brief policymakers in order to guide a response, improve care, and save lives.”
To understand the replication crisis, you need to know some statistics. This video from Crash Course is a great place to start! (15 minutes long)
Is there a replication crisis in the social sciences? Find out why reproducing results is difficult in this video from UW iSchool (content warning: strong language). (8 minutes long)
This presentation provides a detailed look into the connection between statistics and the replication crisis. (16 minutes)
Explore these pages, written by RM team members, for a deep dive into these topics.
In brief: A good-faith, high-power attempt to reproduce a previously-observed finding.
Slightly longer: A good-faith attempt to reproduce a previously-observed finding, with a sample large enough to find the effect if there.
Much longer: Follow this link!
There is NO COST to participate in Replication Markets.
This research is supported (in part) by the Fetzer Franklin Fund of the John E. Fetzer Memorial Trust. It uses a platform developed for DARPA SCORE, and some staff are supported by SCORE while working on this. We are grateful for their support.
