I am quite disappointed in the way the Singapore government has handled the covid-19 situation recently. I have mentioned in previous blogs that, apart from the issue of Covid in the foreign workers dormitories, the government had done a good job. However, the recent developments leave me disappointed. Data and analytics, to me, lie at the heart of dealing with Covid19, but unfortunately, the Singapore government as high as it could be on the analytics maturity scale. In this blog post, I will explain why.
But first some background. We have basically had 2 tools for
contact tracing, using 2 different technological approaches and focusing on 2
different things.
Initially, Singapore was officially going via checking-in and checking-out from venues; and that includes parks, not just shops and buildings, and shops/offices within buildings. Almost everywhere you would find QR codes for you to scan. For people without mobile phones, they could use their identity card to register.
What this data allows the government to do is keep track who is in an area and when. The idea is that if someone who is infectious spent time in the same location as you with overlapping time, then you can be sent an appropriate message.
To me, the advantage of this is that it is a low battery utilisation solution, but is quite blunt in the sense that if the shop/building you went to is large, it is possible that you never crossed paths with the infectious person. Basically, you may get a lot of false positives (people who may be tagged as at risk of infection, but whose risk is actually very low).
Then, GovTech, the government’s technology arm, came up with a blue-tooth based tracking system. This one basically captures the signal of all devices in your proximity and records them. Hence you would be informed only if you were in the same space and the same time (close and long enough to establish the Bluetooth connection) as an infectious person.
The advantage of this is that it minimises false positives, but if the virus lingers, increases false negatives (cases when it is thought people are not infected but actually are). That is, if the virus lingers after the infectious person has gone out of range of your device and you walk into that space, and you are at risk, the blue tooth device does not capture this.
Also, this solution is more energy consuming than the previous one. In mitigation, the government provided physical trackers that do not rely on phone battery.
Now, to minimise the cases of false negatives, the government also has people checking in into buildings like previously, but not in specific shops necessarily (this is no longer stringently checked – earlier people were at the doors to enforce). Still, this decreases false negatives since people can be warned even if it was not ‘same time, same place’.
While I was writing this blog, it was just announced that checking-in and out of markets and food courts will be mandatory. And, already some shops have dedicated staff, again, to ensure checking in.
Hence, in terms of technology, Singapore is among the leaders. So why do I say that the analytical maturity of the government is not that high?
Analytics is not about the latest tech, collecting the most information, it’s about collecting and analysing the data you need to answer an issue and making sure the implementation of the analytics is done properly. And to me the government has failed.
1 The data
collected has to be fit for purpose
The earlier QR code driven system captured who was where and
when. This means that, it is possible to say, among the people in Singapore who
was in a particular mall, or shop, or park at the same time. Furthermore, it is also easy to see who was
in a certain location a while after you left. The blue-tooth method captures
who is in close proximity, same time same place.
My question is, which one do you think captures the data required to assess risk of covid better? Not just in terms of minimising false positives or false negatives (this is important), but also in term of capturing the behaviour of the virus.
If covid can only be transmitted by people right next to you, then the blue-tooth method is better. It covers anyone near me who may be at risk if I was infectious. However, if covid can linger in the air or on surfaces after I have left, then the blue-tooth data is utterly inadequate. It does not show who came after me once I was out of blue tooth range.
I understand that what we know of the virus has changed over time, but the idea that close proximity long exposure contact is necessary for infection has been very heavily challenged. You do not want to risk having false negatives going about daily life normally and potentially spreading the virus.
Now this has partially been addressed by enforcing QR check-ins on top of blue-tooth. Stopping checking-in enforcement at shops (say NTUC supermarket) was always strange to me.
2 People
need to be producing the data
Let’s say you have a nice method to collect relevant data, if the data being created and collected? In my view, doing the ‘techy’ things is the easy bit, just like running data through an algorithm is the easiest part of ‘data science’. Getting the data that suits, and interpreting it are critical. This is where, in my view, the Singapore government falls short.
2.1 Inadequate
Data
Minister Ong Ye Kun spelt it out, “But we strongly suspect, and the police also strongly suspect, that the data we have using TraceTogether and SafeEntry are not comprehensive,” he said, emphasising that there is a limit to which they can use the data gathered through the contact tracing platforms. “(1)
“There is a limit to which they can use the data gathered
through the contact tracing” may be interpreted in many ways:
A- Rules restrict how the data is used.
In this case this would not make sense. The data is being
used for the purpose it was contributed by every one who carries and uses the
app or token.
B- The data is not fit for purpose
As discussed, the data that the government has on hand is a
result of the process of collection. The decision was made to go blue-tooth and
risk false negatives and ignore the potential effects of transmission via
air/surfaces. This is ok if that was the conventional wisdom at the time.
However, deciding not to still enforce the checking-in at shops, in my view,
was a short-sighted move.
To this I would add the idea that there was some over-confidence “The SNDGO said that even without check-out data, the Ministry of Health (MOH) can estimate how long a person had been in various venues based on SafeEntry check-ins at other locations, for example.” Where SNDGO means Smart Nation and Digital Government Office (2) As someone who has spent some time in the field, I would hesitate to implement some models when stakes are so high. You can use models to estimate missing data, but it’s not a good idea to deliberately not capture data when accuracy is important. Over-confidence is, in my view, a sign of an organisation that is not mature.
It’s not that it is not possible to make such estimates, but when stakes are high as in the case of covid, the costs of mistakes are large, and when the costs are not large, it makes sense to gather actual data. For example, if it was to calculate people’s steps, it may have been acceptable to estimate, but really not when you are using the data to manage covid 19. And this ties into the final aspect of what the minister said.
2.2 Insufficient Data
“We suspect and the police also strongly suspect, that the data we have using TraceTogether and SafeEntry are not comprehensive”
This is very interesting because as early as March 2021, the
government used data to make trace together compulsory; stating that 90% of
residents had downloaded trace together voluntarily, the government made it
compulsory (3)(4).
As anyone who measures app acceptance and usage would tell you, downloads and users are 2 very different measures. Unless the people who did not download the app are precisely the people who are at risk of infection, it would mean that people do not use the app, and the 90% number used was misleading.
Now, add to this the fact that checking-in and out was not enforced, and you have easily identifiable potential cracks in the system.
The question is why would people bother to download the app but not use it properly. I think there are 2 main reasons. And again, these indicate an organisation that was still in fields of dream mode ‘If I built the app, they will use’ (5) focused on the tech.
A- Trust
It takes trust to allow someone to track your movements; and
the people in Singapore willingly gave up their data to help contact tracing to
contain Covid19. However, the government eroded the trust. While when TraceTogether
was launched, people were assured the data would be used purely for contact
tracing. The government back-tracked 6 months later (6)(7).
Add to this the fact that the government recently publicised the confidentiality of testing for people from the recent clusters. (8) This may lead people to think that their tests are generally not confidential.
B- Privacy
Trust is not helped by the lack of privacy in cases of
Covid. Everyone in Singapore knows that the first person to go to a doctor in
the recent case is a person from Vietnam who entered Singapore via the familial
lane. Similarly, everyone also knows that one of the infected people was a
stall assistant in a particular stall at a particular hawker centre.
On one hand you have people sued under Official Secrets Act (OSA) for leaking the number of covid cases (9) (interestingly it was the head of the data unit who leaked the info), or when restrictions would hit (10), on the other privacy of individuals is easily breached and publicised without anyone taking umbrage– for example, a man on the street would not know how to verify whether someone came into Singapore via familial lanes(11), or fellow stall holders wouldn’t know who the infected fellow stall holder is (12). Hasn’t the SingHealth issues with privacy of data of people in Singapore taught us anything? Are we going to keep on making the same mistakes?
C- Education
I was having a discussion with a friend about the
TraceTogether app. We disagreed on how it should be used. My view is that it
should be on all the time, at least in public. On the other hand, she said it
was sufficient to turn it on, check-in to the buildings, and you turn it off
again. Basically, to me, using TraceTogether as you would safe-entry.
I tried to find evidence that I was right ( 😊 ), but the website of TraceTogether, the FAQs, simply do not answer “how do I use this app”. Educating users is critical if we want to capture the data needed. Assuming that people will know, or there is no need to explain, again, is the hallmark of a technology driven push, ignoring implementation, basically not that high analytical maturity.
I know this friend for many years, and she is no mug. The fact that we can disagree over something as fundamental as to how the app is to be used likely means that there are many people who are unsure about how to use the app. (I am sure that people who use the physical token were given proper instructions upon collection, but when you download the app, there is no one explaining the usage next to you)
In Sum
I believe that how the Singapore Government has dealt with the case outlined above shows that the government’s tech arm is great at building and making technological solutions available, however it lacks in all the thinking surrounding technology from
- the right data is captured to address the situation
- the users are fully aware of what data they are sharing and how it will be used
- the users trust the system to protect their privacy
I would add a fourth point, as I pointed out earlier, technology/data is not magic, it is important to
o
know what can (should) be done and what cannot
(should not) (I am not talking about ethics here, but cold calculations and
decisions about false negatives, false positives, and weighing the impact)
o address any issues, not only using technology, but all the strategy around A Trust, B Privacy, and C Education that can complement technology and enhance the quality and quantity of data.
Parting words
I believe all of us want to get out of restrictions and are willing to sacrifice some privacy and go through some inconveniences to achieve this. Like everywhere there will be some people who may not agree but the trick is to ensure these people are a minority so the analytics can deliver results we all want. I believe that the Singapore Government should spend more effort on the whole solution, rather than focus on technology and treat the other important pieces to the holistic solution as after thoughts. Only then would the government become more mature in its use of data and become data driven, for the sake of people, not technology.
2 https://www.straitstimes.com/tech/tech-news/why-its-not-compulsory-to-do-a-safeentry-check-out
5 https://www.imdb.com/title/tt0097351/
7 https://www.technologyreview.com/2021/01/11/1016004/singapore-tracetogether-contact-tracing-police/
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