Po-Shen Loh
Dear PM Lee, I'm the mathematician you communicated with on Facebook about 2 years ago, when you posted the simpler way of solving quadratic equations that I found. I'm a Carnegie Mellon math professor and the National Coach of the USA Math Olympiad team, and a Combinatorialist by training. Over the last year, I have invented a new approach to controlling pandemics, powered by Game Theory and Graph Theory. I think it would be particularly powerful in the Singaporean context (based upon my understanding of culture from my parents, who grew up in Singapore). I would love to work with you and Singapore on this new category of tool.
It is fundamentally different from contact tracing, and is based upon aligning incentives so that even selfish behavior contributes to pandemic control. I would love to speak with you about this if you are interested, because I am sure that with your mathematical background, you would grasp it immediately, and see how it brings more power than other approaches used thus far.
The key concept starts off quite simple. It is a smartphone app that helps the app user directly reduce their own chance of getting infected, by telling them the graph-theoretic distance between each new positive case and them. (In contrast, standard apps are designed to make the app user not infect other people.) This is radar, but for pandemics, against the metric space of graph-theoretic distance. Its messages can be communicated in plain language: "someone just tested positive, and they frequently spend time with someone who frequently spends time with someone who frequently spends time with you." (Distance 3.) However, the breakthrough is that by showing people how this graph-theoretic distance changes over time (just like radar), each individual person (who seeks to avoid infection) naturally raises their guard as the infection strikes nearer and nearer.
This is a completely different mechanism than contact tracing. Standard contact tracing is top-down, and by the time it involves an individual, they are asked to take actions to protect everyone else from them. Our approach works bottom-up (analogously to a free market economy instead of a command economy): the individual is empowered to protect themself from everyone else.
This system could help maintain economic and border activity, by making each individual resident more resistant to getting infected, so that even if cases enter the country, they are less able to spread.
I've been discussing this concept with many scientists over the past year. The technical paper describing the theoretical foundation of the concept is at https://arxiv.org/pdf/2010.03806.pdf, and it has even been implemented into an app (www.novid.org), although it would be a pleasure and an honor to work with your government's app as well. The scientific community has been receptive as well. Surprisingly, this is an entirely new mechanism for pandemic control, even though it is so simple in retrospect.
Lee Hsien Lanjiao Loong
Thanks for sharing your interesting idea! I've passed this to the team at GovTech to take a closer look. Hope you are keeping well. – LJL
Dear PM Lee, I'm the mathematician you communicated with on Facebook about 2 years ago, when you posted the simpler way of solving quadratic equations that I found. I'm a Carnegie Mellon math professor and the National Coach of the USA Math Olympiad team, and a Combinatorialist by training. Over the last year, I have invented a new approach to controlling pandemics, powered by Game Theory and Graph Theory. I think it would be particularly powerful in the Singaporean context (based upon my understanding of culture from my parents, who grew up in Singapore). I would love to work with you and Singapore on this new category of tool.
It is fundamentally different from contact tracing, and is based upon aligning incentives so that even selfish behavior contributes to pandemic control. I would love to speak with you about this if you are interested, because I am sure that with your mathematical background, you would grasp it immediately, and see how it brings more power than other approaches used thus far.
The key concept starts off quite simple. It is a smartphone app that helps the app user directly reduce their own chance of getting infected, by telling them the graph-theoretic distance between each new positive case and them. (In contrast, standard apps are designed to make the app user not infect other people.) This is radar, but for pandemics, against the metric space of graph-theoretic distance. Its messages can be communicated in plain language: "someone just tested positive, and they frequently spend time with someone who frequently spends time with someone who frequently spends time with you." (Distance 3.) However, the breakthrough is that by showing people how this graph-theoretic distance changes over time (just like radar), each individual person (who seeks to avoid infection) naturally raises their guard as the infection strikes nearer and nearer.
This is a completely different mechanism than contact tracing. Standard contact tracing is top-down, and by the time it involves an individual, they are asked to take actions to protect everyone else from them. Our approach works bottom-up (analogously to a free market economy instead of a command economy): the individual is empowered to protect themself from everyone else.
This system could help maintain economic and border activity, by making each individual resident more resistant to getting infected, so that even if cases enter the country, they are less able to spread.
I've been discussing this concept with many scientists over the past year. The technical paper describing the theoretical foundation of the concept is at https://arxiv.org/pdf/2010.03806.pdf, and it has even been implemented into an app (www.novid.org), although it would be a pleasure and an honor to work with your government's app as well. The scientific community has been receptive as well. Surprisingly, this is an entirely new mechanism for pandemic control, even though it is so simple in retrospect.
Lee Hsien Lanjiao Loong
Thanks for sharing your interesting idea! I've passed this to the team at GovTech to take a closer look. Hope you are keeping well. – LJL
