Autonomio's Coronavirus Taskforce

what? • contributions • get involved? • Autonomio • Issues

Trauma Team International is an open collective focused on providing critically important insights to coronavirus decision makers.

:sos: what?

Trauma Team International focus on use of behavioral and statistical methods to help answer critically important questions about prevention of Coronavirus, and its effects on the healthcare system. Questions we focus on include:

1) "what behaviors and mitigation effects yield the most favorable balance between economic, psychological, and health outcomes?"

2) "we have x ventilators / ventilator operators and forecast y patients needing ventilation, but x is smaller than y, what can we do?"

3) "let number of people dying from COVID-19 be x, how can we make x smaller instead of just changing the time distribution?"

:gem: contributions

Trauma Team International's contributions fall under four categories:

• make available meaningful datasets for other reseachers
• make available a tool that dramatically increase access to literature
• make available relevant statistical and machine learning models
• make available relevant end-to-end pipelines

Data, models, and code:

• Pandemik: Behavioral Mitigation Simulator
• ICUSIM: Intensive Care Unit Capacity Simulation
• Intensive Care Unit Burden Dataset
• icucalulator.com
• LiterView: Next-Gen Literature Review
• RK4-based SEIR for Python
• Bayesian COVID-19 Forecasting

Articles:

• "What Can COVID-19 Forecasters Learn from Pascal’s Wager"

:speech_balloon: How to get involved?

📢 Citations

If you use Trauma Team International's research, data, or findings for published work, please cite:

Autonomio. (2020). Retrieved from http://github.com/trauma-team-international/talos.

📃 License

MIT License

:raising_hand: Contributors

• Arun Raguraman
• Dan Todor
• Gregory Kovalchuk
• Henri Peetsman
• Ilkka Sillanpää
• Kevin Sunter
• Mahesh Venkateswaran
• Matti Pärssinen
• Matti Vartainen
• Mikko Kotila
• Prasenjit Dey
• Siim Sainäs

Huge thanks go to everyone else who have contributed, as well as to Cavai and Lily for contributing people with skills beyond belief.

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