What will the world look like when we finally unlock our doors and emerge
into the sunshine, after COVID-19 has passed? Regardless how long it will
take, and how many fellow travelers we will have lost, eventually the
pandemic will end and the survivors need to get back to their lives.
Back to their previous lives? I kinda doubt it. The longer
the pandemic and shelter-in-place last, the more we will change our habits.
And the more we’ll question our previous habits. As many have pointed out,
this is actually a great opportunity, in particular because all the other
catastrophes won’t have gone away, starting with the climate.
I have no crystal ball. But it is time to start thinking about this, and so
I’m starting this new section on my blog to collect opinions on possible
post-COVID-19 futures that I am coming across, starting with this one from
None of them are particularly surprising. But worthwhile reading anyway.
This post provides more details on the “Dynamic Quarantine” exit path from the COVID-19
pandemic that I listed in a previous post.
We need to reduce transmission of the virus to a level where the number of infected
people at any time shrinks, rather than grows.
Absent vaccines or other medications, this requires reduction of in-person contact
between people (“social distancing”).
However, this makes normal functioning of the economy largely impossible. For example, the
state of California just ordered all “non-essential businesses” to be closed. While this
may work in the short term, the longer the lock-down continues, the more things “break”:
from mass unemployment and resulting poverty/defaults/bankruptcies, to the availability of
replacement parts and eventually essentials such as food.
Such “social distancing” may need to continue until a vaccine is available, which may take
many months (12-18 months is a common estimate). It is unclear how to keep the economy
functioning enough for such an extended period of time.
We need better ideas.
The basic idea
Instead of a blanket shutdown of all “non-essential” businesses, confining “everybody”
to their residence, we could shut down only those businesses in which infection is likely,
and confine only those people to isolation whose likelihood of infecting somebody is
higher than a certain threshold. In this approach, those likelihoods are dynamically
determined by means of data collection mostly through mobile phones, and an algorithm that
produces a corresponding score for each person from the collected data.
The likelihood of a subject infecting somebody is determined as a function of what is known about
the health of the subject so far, plus a history of the subject’s interactions with other people
and those people’s likelihood of infecting somebody.
By tracking this information in real time, the blanket closure of businesses and blanket
shelter-in-place of the population can be avoided, and instead be replaced with a sharp,
pinpointed focus on isolating those that are most likely contributing to the spread of the
disease. The remainder of the economy and population can continue to function.
Certain parameters in the algorithm can be tuned to provide different tradeoffs between
reducing spread and inhibiting (or not) the economy.
The infectiousness score in this approach is an estimate for the likelihood that one
person infects another when exposed for a certain time period (e.g. 5 min).
For our purposes here, the infectiousness score is a number between 0 and 1, where
0 means: not infectious (e.g. because a highly reliable test has just cleared the subject)
and 1 means: known to be maximally infectious (e.g. because viral loads have been found to
be high, and the subject behaves promiscuously).
A few definitions first:
P: a person (aka subject)
S(P,t): the infectiousness score of person
P at time
t. Ranges between
0 (not infectious) and 1 (maximally infectious).
The core algorithm is as follows. It deals with direct infection between two people only,
but an extension is discussed below.
- At each time unit (e.g. every hour),
S(P,t) is calculated as a function of:
S(P,t-1): the infectiousness score of the person at the time prior;
S(Pi,τ): the infectiousness score of all people
the subject interacted with in the time period
τ = (t-tw) ... (t-1) (where
is a parameter that determines the length of the time window that’s being considered;
selection of this parameter depends on characteristics of the disease, such as
incubation times, as well as the characteristics of enacted community interventions such
as availability, frequency and accuracy of testing);
- a rating of the subject’s current health derived from the subject’s self-assessment;
- a rating of the subject’s current health based on information from the future (see
- Test results come in with a delay (e.g. one day between
tTest and current time
Once available, the estimate for the infectiousness of the subject between
t will be “overwritten” with an updated, more accurate estimate for that already-passed
time period that takes the results of the test into account.
- Similarly, subjects may be infectious prior to experiencing any symptoms. Once symptoms
are apparent, all prior estimates of infectiousness of the subject will be
recalculated over some time window whose length is determined by some assumptions
about the disease (incubation time, time of infectiousness prior to symptoms etc).
- When subject
P's history is rewritten, the histories (and current score) need to be
recalculated and rewritten of all subjects that have previously taken the history of
P into account for their own scores. They need to now use the rewritten history.
This may happen recursively. History may be overwritten repeatedly for a given
subject, which again triggers rewrites for other subjects. (More efficient algorithms
producing the same result can be found.)
Additional potential inputs to the algorithm:
- A rating of a subject’s interventions that may modify their infectiousness, such as:
- wearing a mask;
- intentionally exhaling at others;
Extension to other forms of transmission
So far, we have assumed that transmission can only occur between two people in the same
location. However, there are other forms of transmissions, such as:
- transmission via a contaminated surface within a certain time interval that the
virus remains active on that surface;
- transmission via air droplets in an enclosed space with a certain time interval.
To account for these forms of transmission, the algorithm is extended to also include
estimates of the infectiousness of objects in certain locations. Similar to people,
these objects have an infectiousness score that is a function of which people (and
their scores) have interacted with it in times prior, its previous infectiousness
score and the passage of time.
The score of objects in the vicinity is considered as part of the algorithm to update
S(P,t) in a corresponding manner to that of people.
Users run an app on their mobile phones.
From time to time, the app asks the user about how they feel. Specifically it asks
about symptoms related to COVID-19, such as fever, fatigue, cough etc.
The app’s main screen shows an easy-to-understand visual representation of the
likely infectiousness score, such as a color code (e.g. green: unlikely to infect).
When the app reports a score above a certain threshold, the subject goes into
shelter-in-place or quarantine. (Legal questions about whether this is voluntary
or legally required are out of scope for this discussion; certainly regulations such
as “must be sheltered-in-place unless score is green” would be possible.)
Before two (or more) people meet in person, they can agree on a maximum score that
participants are allowed to have to be allowed to participate in the meeting. (Such a
maximum score may also be legally mandated.) The participants in the meeting check each
others’ scores before the meeting.
Before a business admits a customer (or employee) onto the premises, they require the
customer or employee to share their score. They will be denied access if the score
is above a certain threshold. They may also deny access to those visitors who do not
have, or are unwilling to display their score.
When the user gets tested, they enable the testing provider to add the test results
to their record so it can be used to calculate the score going forward.
Depending on the implementation choices made, the mobile phone may need to be
connected to the internet, to a local WiFi network and/or have Bluetooth on as sender
or receiver or both.
Assumptions / challenges
Test results can be brought into the system in a way that defeats tampering: we cannot
allow a subject to fake negative test results, for example, or eliminate from consideration
positive test results.
Individuals may be tempted to fake their scores in order to enter a certain venue,
for example, such as by displaying a static screen shot on their phone instead of their
live score. Technical means (e.g. timestamping the display, or simultaneously broadcasting
the score via wireless networking) can be employed to make this more difficult. This
approach would also use technical means (e.g. public keys, app stores) to prevent “rogue apps”
with false scores to participate.
In a naive implementation, the entire record of each subject (e.g. the entire world
population) would be centrally collected. This would create a privacy nightmare and
enable substantial future harm from dangers that are not biological in nature. So we
assume that the implementation would need to be performed in a fashion that does not have
a central point of data collection.
Location accuracy for this app is paramount. The absolute coordinates are less important;
but relative coordinates between two subjects need to be determined as well as possible,
as a distance of 2ft vs 8ft has substantially different impact on likelihood of
transmission. This could be addressed with technical means (e.g. Bluetooth, NFC), user
input (e.g. verify / enter into the app the people currently in close proximity) or a
The space in which an encounter occurs is highly relevant. For example, a 10 min
contact at 6ft inside a small, enclosed space without ventilation has dramatically
different transmission characteristics than contact of the the same duration and distance
in open nature with a slight wind. This also could be addressed with technical means
(e.g. mapping information), use input (e.g. enter into the app whether the surroundings
are enclosed space, ventilated, open window, city street, open nature etc) or a
Approach to Privacy
It appears possible to keep most information needed for the functioning of the system
on individual users’ mobile phones without requiring a centralized data repository:
- The algorithm can run locally on local data.
- Detection of other people in the neighborhood can be performed via local wireless networking
(e.g. WiFi, zeroconf, Bluetooth).
- The communication between mobile phones of people in an encounter to exchange scores can be
performed using secure end-to-end encryption between the phones using any networking technology
including through a centralized backend. This would not compromise privacy significantly.
- To trigger history rewrites in other phones, those connections to other phones can be
remembered and re-activated (including identity / encryption keys). This may use
some existing centralized communication network (e.g. instant messenger) or a decentralized
alternative with a distributed hash table for lookup, for example.
- None of the functionality, or communications require more than pseudonymous identity.
No centralized account, or identity verification is required, with the potential exception
of entering verified testing results. However, in this case, the identity correlation
remains local on the user’s device and is never shared beyond.
Public health reporting and management
- The app can report scores to the public health authorities, who have the ability to
track actual – and best-guess estimates – of the spread of the disease in real time.
- For privacy reasons, scores do not need to be associated with other identifying
attributes, although it may be advantageous to share demographic info such as age,
and approximate (maybe rasterized) geographic location of the subject.
- Key parameters of the algorithm – e.g. thresholds for “acceptable” scores for
certain activities – could be centrally updated by the public health authorities,
in order to “shape” the progression of the disease in real time.
- The intentional distribution of data and computation, instead of centrally collecting
it all, for privacy reasons, needs to be weighed against the need to continually
debug, and improve the algorithm.
- To be able to understand the functioning of the algorithm in the field, and to make
improvements, it appears sufficient to report the time histories of scores centrally,
including rewritten histories. It does not appear necessary to identify the specific other
people whose scores were used as input to the algorithm, nor the locations where
encounters took place.
- Should more detailed information be required, collecting such more detailed information
from a relatively small sample of volunteers should be sufficient.
How we got ourselves into this pandemic was quite straightforward: too little, too
late, too much incompetence, and a shocking lack of preparation.
How we will get ourselves out of it is not so obvious. Here are the avenues I see:
- We do nothing.
If so, the pandemic grows exponentially, infects most humans on the planet in short
order, the healthcare system is so overloaded it might as well not exist, but
the pandemic burns itself out quickly as well.
- Duration: short (say 6 months)
- Healthcare system: overwhelmed by some factors
- Deaths: millions upon millions
- Economy: recovers
- A medication is found relatively quickly.
I think of it like Robutussin extra-extra strength. This (hypothetical) medication gets
symptoms of the infection down to non-lethal levels, say like the common cold. Of course,
I have heard nothing to indicate that such a medication could exist, but if one were
- Duration: medium
- Healthcare system: functioning
- Deaths: few
- Economy: largely not impacted
- Lockdowns, until an effective vaccine is found/developed.
If so, everybody says it’s at least 12 months out, if it can be found. Then it needs to
be mass-produced and delivered. So:
- Duration: 12-18 months
- Healthcare system: stressed
- Deaths: a few percent of population
- Economy: in shambles by the time the vaccine exists
- Lockdowns, but no effective vaccine is found/developed.
That’s of course possible. In which case, we will either stay on indefinite lockdown
or, because we do need to eat and need a functioning economy, the lockdowns will stop
and the situation reverts to “We do nothing” after some time.
- Duration: 18-24 months
- Healthcare system: stressed, then overwhelmed by some factors
- Deaths: millions upon millions, but not immediately
- Economy: in shambles
And finally, perhaps there is a way to throw information technology at the problem:
- Dynamic quarantine. See separate post with details.
The idea is to track the likely infection status, and infectiousness, of everybody
on the planet, plus their movements with respect to other people and things that help
transmission, and continuously update their likely status based on the infectiousness
of the people and things they encountered.
If this were done with enough information, and enough spatial and temporal resolution,
we could with high confidence quarantine only those people who are likely infectious,
and let the rest live their lives – in particular their work and consumption behavior
– relatively unchanged.
- Duration: long term
- Healthcare system: functioning
- Deaths: a function of a parameter in the algorithm
- Economy: impacted, but to a degree determined by a parameter in the algorithm.
To make this kind of thing work, there would literally be thousands of problems to solve,
and there is no guarantee whatsoever those problems could be solved,
but it is an intriguing thought.
Summary: I wish we had the option of “and then a miracle occurs”.
When the Berlin Wall fell, I
didn’t quite make the connection. In hindsight, it was the first major event happening in my lifetime
that would get a big chapter in the history books, but I didn’t quite realize it at the time.
History was the stuffy thing they quizzed you in school about, not something that happened
in the world where you and I barbecued in the sunshine.
There have been several history-book-level events since: the disintegration of the Soviet Union;
the emergence of the internet; the 9/11 attacks; the financial crisis in 2008; but not all that many.
Now, the global Coronavirus pandemic is another one. And I fear the chapter on it in future
history books will be longer, containing more death and human misery, but also more disruptive
impact than any of the others that happened in my lifetime.
The governor of California
that schools in the state – closed since yesterday – would probably not reopen for this
school year. That sounds likely to me. More so, I don’t think they will open on time for the
next school year either, and we’ll be hunkered down and “sheltering in place” for many months
to come. I can see only two ways to get out of this mode:
- We have a vaccine – which everybody tells us is at least a year away; or:
- We have herd immunity – which would take years if the limiting factor is critical
care beds, and it is.
- (Of course there is also “damn the torpedoes and who cares if millions die” but I
hope that won’t be what happens in most places.)
So: what will the world look like if most stores, and restaurants, and hotels, and
movie theaters, and conferences, and what have you, have been closed for a year or more?
If you haven’t been able to visit your friends across town, or your family across the
country for a year or more? If kids grow up without play dates, or without ever hanging out at the
mall or the soccer game? If you haven’t been able to meet new people, or fall in love,
for a year or more? Or: what if all of this gets somehow replicated on-line and life
mostly moves into cyberspace as countless sci-fi novels have it? Whichever it is:
as small as the virus is, its impact is as big.
And then there is economics. If China has record-low pollution right now
(because there has been far less demand for coal-based electrical power), so low that it
supposedly has saved the lives of 77,000 people
already, and the canals in Venice
for the first time in living memory so you can see the fish in them, this tells you more
about what the GDP numbers will look like than any bespectacled talkshow guest ever will.
As my friend Sari says, that’s great for the planet. Not so great if you have a 401k retirement
plan or want to keep a job. The economic impact, and the ripple effect from there, will likely
take up far more pages in the history books than even the pandemic itself. It’s such a big
We are in unchartered territory. Something like this has never happened in human history.
The historians are going to have rows of unfilled PhD positions, so much is there to write about.
For the rest of us: hang on tight, and throw out all preconceived notions of what your life should
be like, because whatever you thought it was going to be 3 months ago is not going to happen.
There is a chance it will be much better – the 77,000 certainly will think so! – but that’s
not guaranteed even for those who don’t die of the virus. I shudder thinking about when real
shortages start to happen, and they will.
We are looking at hard work and much hardship. But perhaps a better chance to save the planet
than even 3 months ago was conceivable. The future is more uncertain than it has ever been
in my lifetime. Fear permeates everything, and much pain is certain. But maybe, maybe, much
good will come out of it, too. I tell myself: let’s try to focus on that.
As of midnight tonight, the residents of all counties in the 8-million people
San Francisco Bay Area, including all of Silicon Valley, have been
to stay at home. What a little virus can do.
No meetups. No restaurants. No venture capital pitches. No trade shows. No business meetings.
No shopping at the mall. No going to work.
Who can, will work on-line. So far, the interwebs are still up – although I experienced
the first choppiness in the video feed during this very announcement today.
This shelter-in-place order is for 3 weeks. Which is laughably impossibly short, because just
the incubation period for the virus might be that long! We’ll be holed up with cabin fever for much,
And when we finally re-emerge, the world will be drastically different, I think. How – I don’t
know; visibility is very bad. But very different for sure.
Hang in there. See you in cyberspace, which is a corona-free zone :-)
I had to venture out today for a new dental crown, and on the way back, I decided
to stop at Trader Joe’s to pick up some eggs. Traffic
on highway 101 was extremely light, although it was Friday afternoon – many people
must be working from home. So I was quite surprised when Trader Joe’s parking lot
Walking into the store, a scene that I had never seen: checkout lines that disappeared
into the back of the store; all registers open; most staffed by two employees for
extra speed. And then: bare shelves, with lots of empty shipping boxes in the aisles –
customers must have been picking up things from shelves faster than employees could
restock and remove their boxes.
I had done my bulk “prepper” shopping the weekend before, when everything was normal
and I only got an occasional glance from people. And today apparently everbody decided
it was time to do the same thing. Must have been Trump’s emergency declaration today.
While waiting in the long time, I had time to observe, and ponder. First, what did
people pile up in their carts? Almost all of the carts I could see had typical
weekend grocery stuff in it. A bag of chips. A can of corn. Some veggies. One guy
had filled his cart mostly with already cut-up fresh fruit. Hardly anybody had enough
stuff in their cart to last for longer than a week, unless they subsist on a chocolate
snack diet. And you are panic-shopping for what, today? So you have to venture out
shopping again in just a few days?
What about high-energy, long-shelf-life bulk food instead? Like 25 or 50 pound bags
of rice, or a few dozen cans of everything from veggies to processed meat? Admittedly
Trader Joe’s is not the store where to get those things … so why even go panic
shop there? Few of the people I saw seemed to have thought through why they are
panic shopping today and what problem they are trying to solve.
But it gets worse. Here I’m standing in line, and for the lack of anything better
to do, I count/estimate the number of people in the store. A few hundred, I thought
(let’s call it 250 for my argument here). Standing all here, in relatively close
proximity, all breathing the same air. And there are exactly three people (me, and an
Asian couple, unsurprisingly) who wear a mask.
To compare, Santa Clara County (about 1.8 million people)
today reports on its website
79 Coronavirus cases, of which 36 are hospitalized. Accounting for the disaster that is
testing in the US, other countries have about 10% of known cases hospitalized, so that
would lead to about 360 known cases if testing had been done properly. However, given the
rapid growth of the disease (currently about 30% a day in the county), many more people
will be contagious prior to the onset of symptoms, and of course there are those
who have few or no symptoms at all. So I will pull a number out of my hat, and claim that
there might be 5x as many cases as there are proven (well, would be proven)
positive test at this time. That leads to 1800 infected, and likely contagious, people
in the county today.
So, back of an envelope, 1 out of 1000 people in Santa Clara County today has the virus
and can infect me. The grocery store, when I was in it, had about 250 people in it,
with new people pouring in as soon as others left. I’d think that certainly more than
a thousand people moved through that store today. Which means at least one infected
person moved through the store, stood in line like everybody else, breathed and exhaled,
and left their infectious droplets in the air around them.
And nobody, nobody – other than the three of us who were wearing face masks – seemed
the least concerned about it. On the same day that the county banned all meetings
above 100 people! (for good reason, given the above calculation!)
The employees, at least, had hand sanitizer at their checkouts and used it frequently.
But each one of those thousand-plus customers walked by a checker within a few feet,
and paused to pay and get their purchases packed, and looked at the checker and spoke
to them in a direct line of sight – and exhaled droplets. There were some Corona
infections in that store today.
And this, ladies and gentlemen, is why epidemics spread. Needlessly. Because people