What is the COVID-19 global policy simulator?

School closures, mandatory face masks, gathering restrictions, and travel bans are some of the policies widely implemented by governments around the world in an attempt to halt the spread of COVID-19. In these unprecedented times we ask ourselves: Why are these interventions more effective in some countries than others? Which policies have had the greatest influence in reducing contagion in my country? How will these policies affect society and the environment in the future?

This is precisely what the COVID-19 Global Policy Simulator aims to find out. Our simulator analyzes the intersection between COVID-19 related policies, contagion rate, and government responses’ impact on society in order to assess the full range of effects that may arise from implementing various policies in response to the global pandemic.

Ready to learn more? Click below to use our interactive dashboard and design your own policy response to the pandemic.

What does it do?

This simulator enables you to simulate what the effects of implementing various COVID-19 policies would be on: a. Contagion rate (1 month); b. Society and the environment (4 years).

It also lets you visualize the intensity with which  government responses have been implemented around the world and analyzes which policies have been the most influential at reducing contagion. 

Who can use it?

This simulator is meant for:

1. Civil society. ie. Anyone impacted by COVID-19. 

2. Policy and decision makers in charge of crafting government responses to the pandemic. 

3. Researchers, academics, NGOs, and international organizations examining the effects of the pandemic and seeking to reduce its negative impact. 

How does it work?

As a user:

  1. Select the policies you would like to examine. 
  2. Choose the intensity with which they would be implemented. 
  3. Pick the indicators you would like to assess. 
  4. Forecast influence. 


The COVID-19 Global Policy Simulator relies almost entirely on open-source data and is supported by a grant from the NUS Resilience and Growth Innovation Challenge. 

If you are an organization that would like to collaborate with us, share data, raise awareness, or lend your time and expertise, contact us. 

Meet the team.

Every one of our team members is devoted to using data for good.

Eleni Ayala

Founder, Team Lead and Coordinator

Lovely Tolin

Economist and Data Specialist

Keila Garcia

Lawyer and Sustainability Specialist

Linda Tirado

Public Health Specialist

Jason Naniong

Quantitative Risk Modelling Consultant

Qifei Zhou

Machine Learning Consultant

Special Acknowledgements

The COVID-19 Global Policy Simulator would not have been possible without the supporting grant from the National University of Singapore’s Resilience and Growth Innovation Challenge. 

A special thank you to Dr. Nay Lin Tun (former teammate), our mentors and advisors, as well as all of the organizations that continue to work towards collecting and publishing open-source data and whose data went into this model. Some notable organizations include: the Oxford COVID-19 Government Response Tracker, Blavatnik School of Government, University of Oxford, the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Our World in Data, and the World Bank DataBank, amongst others. 

For the full list of organizations from which data was sourced, see the documentation section. 


Disclaimer: The COVID-19 Global Policy Simulator relies on open-source data from a variety of organizations. While the Sustain Models team strives to validate and conduct logic checks on all data included, forecasts should not be taken as fact. The COVID-19 Global Policy Simulator remains subject to new developments such as: new waves of COVID-19, coronavirus variants, political changes, under/overreporting, and official data releases from governments. Forecasts will be adjusted accordingly.


See our FAQs!

What do you want to do today?

Policy Intensity Score and Influence Ranking

How intensely have different countries implemented different policies? Which policies have had the greatest influence on reducing contagion?


What will contagion rates look like in one month based on the policy mix that is implemented? Make your own policy mix and find out!

Effects on society

How will implementing different policies affect society in five years? What are the trade-offs policy makers must take into account during the decision making process?

Not sure what you want? Check out our FAQ