<aside> 💡 Project Summary: This is a work-in-progress repository of the current research on Coronavirus and the disease it causes (Covid-19), displayed in a digestible format.
Problem: Even though more than 24,000 research papers have been published on Coronavirus, not everyone reads them because either research is too complicated and dense, or it's too hard to derive conclusions.
Solution: Thus, this project. The idea is to help capture, summarize, and display accurate information on Coronavirus in a manner that facilitates reading.
Contact: My name is Abhinav Kejriwal (LinkedIn, Twitter, YouTube) and I'm a Computer Science student at UC Berkeley. Please reach out to me at ak1 [at] berkeley [dot] edu for any clarifications, concerns, comments and/or please feel free to comment on this document. Please also feel free to let me know which questions you'd like to be answered next.
Survey: If you want any particular questions to be researched, enter them here.
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Table of Contents:
Click to navigate to a question.
(Q = Question; C = Claim; N = Note)
Pick of the coronavirus papers: Absent antibodies suggest mystery immune response
This research paper from Stanford dated Apr 11, 2020 has the main conclusion that:
The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases. Population prevalence estimates can now be used to calibrate epidemic and mortality projections.
A few videos are best to get a grip of the entire situation. I'll link them below.