Coronavirus Crisis

Are we underestimating the crisis posed by the Wuhan Coronavirus (2019-nCoV)? Are we prepared?

The Coronavirus (2019-nCoV) outbreak is serious and the impact underestimated. While china has taken the necessary measures, Europe and the US are complacent.

Initially observed in Wuhan, Hubei Province there are currently >7000 confirmed infections with a fatality rate of 2-3% indicating the worst case scenario of as many as 210 million deaths worldwide. As a comparison, SARS reached a maximum <10K cases with ~10% fatality rate. Spanish Flu infected (possibly) 500 million and killed an estimated 50 million but this is difficult to confirm since it coincided with the first war (Spain was a neutral country where reports were publicised).

The lesson of Spanish flu is that, if left unchecked, a virus can lead to a catastrophe. Mass movements of people during the first world war in close quarters and with regular rotations from the rear, to the front and regular leave, meant the virus spread incredibly quickly. The SARS epidemic shows what can be achieved when intense quarantine procedures are put in place. Unfortunately, in the case of the current outbreak, the mass movement of people near the outbreak location (as occurs during Lunar New Year) and the ease of travel to other countries via plane, coupled with the long incubation period means the virus has spread far and fast.

The extreme quarantine measures used in China are appropriate and sensible. By effectively shutting the country down for two weeks the spread can be halted and the worst impact (which can take >100 days to occur) can be avoided.

In contrast, in London people use public transport twice daily for up to 3 hours, no one wears protective masks when ill and most refuse to take sick leave. There is a single entry point for the UK health service (famous for cramped waiting rooms), the general practitioner (GP), ensuring that the sickest people are brought together with the most vulnerable.

Understanding the situation is important and combatting misinformation even more so. Social media is (actually) useful here. This thread combines some valuable scientific insights. Below are are some resources that can help to dig a little deeper:

Resources for understanding the spread:

  • A great, simple and down to earth review of the math behind epidemic modelling covered by Elsevier. Great start.  
  • Virus simulator: This is developed by Simon Andrews and his GitHub is packed with useful repos (including Fast QC for high throughput sequencing analysis). Unfortunately the virus simulator doesn’t do a great job of explaining the background calculations.
  • Plague inc is a bit more of an actual game. But remains terrifyingly realistic..
  • GLEAMviz has a pretty sweet (and advanced) modelling tool for global epidemics. It is quite a serious tool.

Understand the genetics:

  • The DNA sequence is free to download on the genbank database.
  • The protein crystal structure has already been studied (press release in Mandarin) and is apparently available directly from the researcher. The protein data bank (PDB) number is 6LU7 but is listed as unavailable. Seems strange they would not share this data..
  • A recent paper comparing SARs and 2019 nCoV is available on BioRxiv.
  • Singer et al,  (from the Gifford Lab) have developed GLUE a tool for studying the evolution of viruses and that is worth exploring. Their GitHub page is a bit all over the place but definitely worth exploring if you are knowledgable in the area.
  • NGL Viewer: a web application for molecular visualization
  • Cant say this is totally applicable but the Chodera Lab is incredible. They have some work on ligand design and mostly focus on computational design of small molecules.

Developing vaccines/detection or other intervention:

  • The Baker lab  in U Washington is a world leader here. They developed the well-known and popular Rosetta protein modelling software.
  • Huge potential for on demand vaccines, virus detection and riboswitches are coming out of the Collin’s Lab (MIT) and the lead author (Keith Pardee) on those now has a group at UoT.
  • Computation design of vaccines is a HOT topic and should be a great application of our societies computing power. Work from Khan et al. looks impressive.
  • Lots of companies are “changing the world” (quotes imply great cynicism and eye rolling) and a few (e.g., exotec biologics) are applying (you guessed it!) machine learning to vaccine development. It is unclear if this is for real.

If you have come upon a recommended resource or we have made an error here please reach out on social media: @opencelllondon and tell us!

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