Episode 86: COVID Models, Spring Term, Human Rights Workshops - Transcript

Release date: Friday, April 30, 2021

Hosted by Brandon Sweet and Pamela Smyth

Brandon

This is Episode 86 of Beyond the Bulletin.

Hello and welcome to Episode 86 of Beyond the Bulletin. From the University of Waterloo, I'm Brandon Sweet, editor of the Daily Bulletin.

Pamela

And from Media Relations, I'm Pamela Smyth.

Brandon

On this podcast, we go beyond the pages and pixels of the Daily Bulletin to inform you about important news and views from our community.

Pamela

This time, I speak with Professor Chris Bauch about computer modelling of COVID-19.

Brandon

Thank you for joining us as we go Beyond the Bulletin.

Pamela

How are you doing this week?

Brandon

I am doing pretty okay, how about yourself?

Pamela

Good. Counting down to my vacation days, because I have so many unused vacation days.

Brandon

You and me both.

Pamela

We’re gonna be off at the same time actually.

Brandon

Okay, well, I don't remember when I'm taking time off.

Pamela

I'm taking a number of Mondays off in May, which is very nice. And because I just find that two-day weekends are just not long enough for me to get everything done that I need doing.

Brandon

Not at all.

Pamela

And also taking some Mondays off in June.

Brandon

Nice. I had to do that one summer several years ago. I think I took Friday's off for the entire summer period, which was nice. It's a nice way to burn up vacation days. I guess.

Pamela

That would be nice. I can't take Fridays, though. because that is the day that I post the podcast.

Brandon

Exactly. Yeah, yeah. So I understand you take your Mondays but then you get a case of the Mondays on Tuesdays.

Pamela

I have a case of the Mondays all the time. For those listening who don't know, our podcast comes out on Fridays. We have a lot of people who listen on days other than the day it comes out.

Brandon

That's right. That's the thing about podcasts, they persist. They're available anytime. So looking back, let's see what's been happening. The province of Ontario has extended the current provincial shutdown and stay-at-home orders until May 20, 2021. This affects in-person teaching, research and other operations on campus including the beginning of spring term, which is set to begin on May 10. That said, there is no change in the restrictions in the extended shutdown including current research activity restrictions.

Pamela

In person course activity can only begin if subject matter or instruction requires that it be taught in person, such as clinical or hands-on training with a limit of 10 students per section with some exemptions in health-care disciplines. Faculty associate deans have been contingency planning for spring term and have identified courses that will begin in person or remotely during the stay-at-home order. Instructors will consult with their Associate Dean or chair for clarity and direction and should inform students about class format, whether in person or remote for the beginning of the spring term as soon as possible.

Brandon

A list of spring undergraduate and graduate courses that are offered in person is available online. We'll put that link in our show notes. In terms of travel restrictions, crossing the border into Ontario from another province is permitted for the purpose of moving to the region or into residence on campus. Students are not required to quarantine before crossing an inter-provincial border. However, the Ontario government is strongly recommending that anyone travelling between provinces self-isolate for 14 days upon arrival.

Pamela

If you are coming to Waterloo from another province, please make a plan to self-isolate for two weeks before mixing with housemates or other community members.

Brandon

If you will be travelling by land across the provincial border to come to Waterloo, you can apply for a letter to confirm your need to reside in Waterloo region during the spring term. There are two forms to request a letter: one for undergraduate and one for graduate students. We will put that link in our show notes as well.

Pamela

At this time, the shutdown does not impact the arrival of international students. Federal and provincial 14 day quarantine requirements and the provincial COVID-19 testing requirement are still mandatory upon arrival into Canada. International students should continue to follow Waterloo’s travel processes and remember that students are not permitted to quarantine in residence.

Brandon

For more information check the university's Coronavirus website.

Pamela

Some sad news from the Faculty of Mathematics. Professor Tom Coleman, dean of math from 2005 to 2010, and professor of combinatorics and optimization from 2005, passed away after a battle with cancer.

Brandon

Born in Montreal in 1950, he earned his undergraduate degree, master's and PhD from the University of Waterloo, graduating in 1979. Tom was a professor of computer science at Cornell University before becoming dean of the Faculty of Mathematics. More recently, Professor Coleman held the Ophelia Lazarus University Research Chair in the Department of Combinatorics and Optimization, and he was the director of the Waterloo Research Institute in Insurance Securities and Quantitative Rinance or WATRISQ, which I will say is one of my favorite University acronyms.

Pamela

You love acronyms more than this university, I think. Professor Coleman had a very prolific research career spanning the fields of development of computational models and tools for compute intensive and challenging problems with emphasis on applications and computing methodologies…whoa… such as automatic differentiation and cluster computing technologies.

Brandon

I will take your word for it.

Pamela

Wow, there will be a test.

Brandon

His most well-known work was based on fundamental design and analysis of algorithms for trust-region methods and optimization. He was the author of three books on computational mathematics and published over 80 journal articles in the area of optimization, automatic differentiation, parallel computing, computational finance and optimization applications.

Pamela

Tom will be greatly missed by his students former and present, colleagues and friends. A funeral has taken place. He is survived by his spouse, Professor Yuying Lee and his children. our condolences to them.

Brandon

John Dick has been named Concept by Velocity’s new interim director. John has been with Concept and Velocity as a business adviser since November 2020. He was a co-founder of Nicoya Life Sciences along with University of Waterloo and Conestoga College students working out of what was then called the Velocity Foundry, before graduating to their own space back in 2016. During his time at Nicoya, John was the chief science officer and saw the team grow from two co-founders to more than 40 employees.

Pamela

Concept has an interview with John on their website that outlines his vision for the future of student innovation at Waterloo. We'll put the link in our show notes.

Brandon

Now, here's what's coming up. Human Rights Equity and Inclusion has released its spring schedule of workshops, which are available to all current students, faculty and staff. This spring, new renewed or refreshed workshops include: listening, acting and taking responsibility in the anti-racist movement; responding to disclosures how to support a friend who experiences trauma; how masculine-identifying folks can engage in bystander intervention; 2SLGBTQ+  fundamentals; and radical solidarity for a collective future.

Pamela

Equity-related workshops now include information to help guide participants to the workshop that is right for them by including whether the workshop is considered introductory, intermediate or advanced. We'll put the link to the full spring calendar in our show notes.

Brandon

Like in any Canadian spring, the temperature bounces from cold to warm back to cold again, but whatever the temperature, it's always the right time for a cold on, am I right, Pamela?

Pamela

Well, you're right there, but I'm going to still going to give you a chilly reception for that one, Brandon.

 Brandon

And that is richly deserved. And the reason I bring that up is because the Alumni Happy Hour Box is back with a refreshing summer twist. So you can crack open a cold one, bring it to your balcony, yard, patio or wherever you can enjoy the weather. Because the Happy Hour Box has everything you need to keep your beverages cold, your thirst quenched and your warrior spirit alive.

Pamela

The Alumni Happy Hour Box is a partnership between Alumni Relations and the Craft Brand company, a Toronto agency that partners with brewers to offer renowned beverages to Ontario beer lovers. One of the cofounders of Craft Brand is Waterloo alumnus Chris Goddard, who credits his theatre and performance degree with helping him become not only an actor, but a good listener and an adaptive risk-taker--skills that have proven useful on and off the stage.

Brandon

Craft brands online store, the aptly named Bodega, offers limited-release brews, exclusive offerings and all the classics—and it delivers across Ontario. So the beer box will cost you $25, and there is also a non-alcoholic beer box available for 20. Both boxes include two 20-ounce Waterloo Alumni travel tumblers, which are double-wall insulated with sliding closure lids, and a Waterloo Alumni 18-can soft-shell event cooler that features a zippered main compartment with adjustable shoulder straps along with four cans of alcoholic or non-alcoholic beverages for your enjoyment.

Pamela

What about snacks? I need snacks or it's not happy hour for me.

Brandon

That's right! Well, I'm sure you can fit some snacks in there too.

Pamela

I love snacks. I even love the word snacks. Alumni can order their box today and you'll get it in time to celebrate Alumni Weekend on June 4 and 5. This offer is available while supplies last, of course. We'll put the link in our episode show notes on SoundCloud.

Brandon

I feel like we need to discuss this snack thing, explore this a little further. Pamela what is what is your favourite snack?

Pamela

Oh, I love salty and sweet things, so I'm gonna say beer nuts.

Brandon

Oh, I do enjoy a good beer nut that's for sure.

Pamela

What about you?

Brandon

Oh I would have to my go-to is chocolate-covered raisins.

Pamela

But that doesn't go with beer.

Brandon

Doesn't have to. I'm just talking about snacks. Waterloo faculty and staff are invited to a virtual Return to Campus Town Hall on Tuesday, May 11 from 1:30 to 2:30pm on Microsoft Teams. You can join the conversation as President Feridun Hamdullahpur and Vice-president Academic and Provost James Rush outline the University's plans to expand in- person experiences for many more of our students this fall and ways the University is preparing to invite more employees back to campus to support Waterloo’s academic mission.

Pamela

Associate Provost Human Resources Marilyn Thompson, who has been a guest on this very podcast, will host and moderate the town hall event. Attendees can take part in a live q & a following the leaders’ presentation using the virtual chat features in Microsoft Teams. We'll put the registration link in our episode show notes on SoundCloud.

Brandon

Speaking of episodes, keep on the lookout for a bonus episode of The Beyond the Bulletin podcast, which will be released on Monday, May 3.

Pamela

This episode will feature a repeat broadcast of our recent interview with Professor Kelly Grindrod from the School of Pharmacy. It was originally broadcast on April 9, but it'll have a new q & a with her. It'll bring you up to date on the current COVID-19 situation and vaccination rollout. A lot can change in three weeks, especially these days.

Brandon

That's right, it seems that three weeks’ worth of change happens every day.

And now the interview. Since the beginning of the pandemic, our next guest has provided important information to government and public-health officials to help them make informed decisions. Professor Chris Bauch and his team in applied mathematics create computer models that outline likely consequences of certain decisions and actions. He's here to tell us what computer modelling is and what it isn't.

Pamela

Hello, Chris, I'm glad you could join me.

Chris

Hi, thanks for having me.

Pamela

What is computer modeling?

Chris

So computer modeling is basically creating representation of the world inside your computer. Sometimes they're called computer models sometimes are called mathematical models. To use an analogy, a toy car, for example, is a great example of a model. It looks like a car, it's got four wheels that rolls like a car. But of course it doesn't have air conditioning. It's not the same size as a car. But it represents the idea of a car. And in the same way, we create these computer models or mathematical models to represent important features of real-world systems that we're interested in and understanding better.

Pamela

Well, it seems like there are so many variables, though, and things that can affect an outcome. How do you, how do you take that into account when you're dealing with a transmissible disease?

Chris

What you have to do is you use your experience based on modelling from previous infectious diseases, previous pandemics, previous seasonal outbreaks of diseases, to learn what elements your model needs, and which ones are less important. So that's the first thing is you have to have the experience from other systems to understand what's important for us to include in COVID models. And then you also have to systematically assess the impact of uncertainties. So for example, if you are less certain about the probability of mortality or the probability of getting infected, then your model projections have to represent that uncertainty using, you know, for example, best- and worst-case scenarios. Scenario A might be everyone follows physical distancing recommendations. Scenario B might be 50 per cent of the people follow physical distancing recommendations. And we present both those scenarios to kind of explain what would happen under those circumstances. Now, we don't necessarily know which circumstance will unfold, especially over a longer time horizon. But knowing that information can at least be useful to decision-makers to recommend or to figure out what to do about school and workplace closure, for example.

Pamela

You don't make recommendations, you just suggest what could happen, right?

Chris

That's right. My job is to say, you know, if you do this or that, then this is our best guess for what's going to happen, according to the models. So we provide information to help the government and to help the population in general, individuals protect their loved ones.

Pamela

How accurate are mathematical models?

Chris

So mathematical models are not crystal balls, which can tell you exactly what's going to happen. They range in accuracy, depending upon what you're modelling, and how you're using it. So for example, if you're talking specifically about mathematical models, they can predict the right trend, they can often be qualitatively correct, even if they aren't quantitatively correct. And what I mean is, for example, they can predict that you'll have a second wave. But they might be off in terms of exactly when that wave is going to peak, and exactly how many cases you'll have. For example, we predicted back last summer that Ontario would have a second wave followed very rapidly by a third wave. And that's essentially the pattern that we've seen here. But because we were predicting so far in advance, it was you know, back in August, when we were just coming out the first wave, our model predicted the peaks would happen earlier than they have actually occurred. And they can be qualitatively accurate over longer timescales. As, as that example illustrates, they can also be quantitatively accurate over shorter timescales. So if you want to project cases ahead maybe a couple of weeks to a month, they can do that fairly accurately if they've got good data, and if the structure is appropriate for the kind of projections that you would make.

Pamela

You've done a number of models since the pandemic started. Why did you decide to model the things that you modelled?

Chris

We chose our models based on questions that were on many people's mind. For example, back last spring and early summer, one of the questions was, you know, when and how should we reopen. And we constructed a model to look at different approaches through opening. For example, you could either reopen the entire province at once, or you could reopen different health units at different times. And our model showed that if you reopen different health units at different times, that's potentially a better approach. And the province ended up doing that in the end, even though at first they wanted to do everything in lockstep. Other questions we looked at include how to prioritize the vaccine. And that's an important question, because, of course, the supplies are limited, and we have to choose who gets the vaccine first. And so last fall, we started to look at this question anticipating that it would be an issue. And we looked at which age groups should we prioritize for the vaccine if we want to minimize the total number of deaths in the population. So all of our questions are motivated by things that are on the minds of the public and decision-makers.

Pamela

On the question of who should get the vaccine, were you specifically looking at age, or just who should get it, what their job is, where they live?

Chris

So we have two separate studies. And when I say we, this is actually I'm not doing all this on my own. My grad students are working on it, my collaborators at the Perimeter Institute and Guelph. In the two different studies, we looked at first of all the age question. So whether it should be 60-plus-year-olds first, 80-plus-year-olds first, or whether we should give it uniformly to everyone regardless of age. And then our second study looked at contact. So what if we can figure out who has the most contacts, for example, because of their work or because for whatever reason, and what happens if we can vaccinate them first. Now, in the case of the age study, we find that we found out that which age should get it first depends upon when the vaccine becomes available. And we found that if the vaccine becomes available early in 2021, then you can prevent the most deaths by vaccinating the elderly first. If it had become available later in 2021, it would have made sense to vaccinate uniformly. And like I said, those results were generated before, you know, the vaccine program actually started running. But as the vaccine program did start in December, January in Ontario, our results supported the approach that the government used of prioritizing the elderly first, and then going to other age groups.

Pamela

It’s got to be difficult, because you also didn't know that there was going to be a big contamination at the Johnson & Johnson factory, for instance. So there are some things that are just beyond your control.

Chris

That's right, yeah. So all of our projections are subject to certain provisos that you can vaccinate a certain number of people per week. If the numbers are actually outside of that range, maybe higher than we allowed for or lower, then we allow for that. And those projections don't apply. But the general insight of that model is dependent on most of the details of how quickly the vaccine becomes available in the sense that the basic insight of the model is that if you can vaccinate enough people before a pandemic wave comes, then you can prevent more deaths by distributing the vaccine uniformly in the population. Because the vaccine not only protects the people you vaccinate, but also it stops them from infecting others. And therefore, if you can get vaccine coverage up high enough, before a pandemic wave hits you, then the vaccine will actually prevent the wave because you're blocking most of the transmission in the community. And so that's a good example of using your understanding of how pandemics work and you're in order to interpret these modeling results, the exact trajectory to get to that herd immunity from the vaccine doesn't matter as much as the percentage of people that you've ended up vaccinating. And if you have vaccinated them, even if there have been some stops and starts along the way, like with the J & J vaccine, then that approach might work. But of course, as it happened, you know, we were facing a pandemic wave by you know, in January. And in those circumstances, the model tells you that you should always vaccinate the elderly first. Even if you have relatively high vaccination rates, because in the middle of a wave, you can prevent more deaths by protecting the vulnerable. And in between waves, you can prevent more deaths by building up your herd protection to actually stop future waves. So we had a second study, which looked at what is the impact of vaccinating, people who have more contacts. Get information on contacts from things like COVID Alert and other contact-tracing apps. Because these apps can tell you if you've been in contact with a large number of other people. And our thinking was that, well, you know, maybe we could modify the functioning of these apps so that they can also tell you, ‘hey, you're the top 10 per cent of contacts, maybe you should get vaccinated as a prompt.’ And, yeah, and we found that, you know, if you can identify and motivate that top 10 per cent of people with most contacts, then you can actually reduce transmission very effectively—much more effectively than trying to target certain age groups, for example. And that's a great way to get the transmission itself under control. But there are other factors that come into it. You know, for example, one reason we vaccinate health-care workers is the principle of reciprocity. The principle that these are people who have risked their life for us, and, and therefore, maybe they should have first crack at the vaccine. And that's strictly an equity-based principle. Right? So, it's not just about minimizing cases and deficit, sometimes it's also about equity and fairness. So that's why there's so many opinions out there is that who to vaccinate first really depends upon what you think is the most important criteria. And our models are about outcomes, like cases and deaths. But you can't measure equity, for example, as an outcome. That’s difficult to do.

Pamela

Last week, Dr. Theresa Tam, Canada's chief public health officer, indicated that the latest modelling that you weren't involved in actually says that the number of new cases could start to go down in May, depending on the public health restrictions. And it also showed that if 75 per cent of adults have received their first doses and 20 per cent have received their second doses of the vaccines, restrictions could lighten up. What do you think of these new models? Do you think that makes sense?

Chris

Yeah, this makes sense to me. And this is consistent with the outputs that our models have been producing. And, in fact, if you look at Ontario, the curve might have already flattened, the seven-day moving averages is declining, as it has been for a week now. And so I think Ontario, we might have flattened the curve, which would be great. Likewise, you know, if we can get those numbers vaccinated, given what we know about how well the vaccines block transmission, this, would indeed allow us to lift up the restrictions.

Pamela

Does that mean 75 per cent of adults in our area have to have had their first dose, and 20 per cent had their second?

Chris

Well, that's on average. So some areas, it would be less, and some it would be more. And you know, the kind of factors that would influence that include, for example, density of housing. If you know, in some areas where there's a high population density, there's more transmission, and so you would need more people vaccinated. I'm thinking of Toronto, for example, or even in Waterloo, some, you know, some areas with high-density housing, multi-generational households, and a lot of households where people have jobs where they can't avoid contacts. They might work in grocery stores, for example. They'll need a higher vaccination rate. Whereas if you think of smaller communities in the countryside where people have, there's a low population density, it's easier for people to distance, maybe they can work from home or they're working on a farm, where they don’t have to contact others indoors a lot, then they'll have a much lower percentage vaccinated that they need. So that's just the average. And it'll be a bit higher or lower, depending upon the local circumstances.

Pamela

I understand. Okay. I'm just not sure how we would know what we're supposed to do. But I guess we just follow orders, we just do it the Region tells us to do.

Chris

Yeah, so this number is like a long-term strategic objective. In terms of deciding when to actually open, they're not going to wait until, you know we've hit 75 per cent and then reopen everything. They're going to monitor things much as they've been doing throughout the pandemic. They'll be looking at ICU cases, ICU admissions, hospitalizations, and those things will all start to decline because of the vaccine program. And so that's how the decision will be made in practice is that there'll be monitoring those hospitalizations and ICU cases. If they continue declining, and if the vaccine rate is high enough in any given health unit, they'll say, “okay, this the health unit can start to reopen again.” I think that 75 per cent number is really looking ahead towards, you know, not only reopening, but preventing a fourth wave potentially in the fall or winter. This is more like in terms of, you know, long-term reopening—when can things get back to a new normal. So that's kind of, you know, how we have to interpret that.

Pamela

Is there anything that you've examined that would sort of shine light on what the fall might be like?

Chris

No, we haven't looked into the fall yet. I think the big factor is going to be how many people accept the vaccine. So like I said, I think vaccine supply will probably not be a big issue for much longer. And even vaccinating children will start to happen, because they're doing clinical trials in children now for several of the vaccines. And so we'll also be able to vaccinate school-aged children eventually. So the big question is how many people will actually accept the vaccine. And if there's too much vaccine hesitancy, then that will leave a large pool of susceptible persons. And it might be large enough to allow for another wave in the fall or the winter. And so that's my big concern. And it's related to that unknown of how many people actually accept the vaccine, and will it be enough.  But if we can get those people vaccinated, if we can overcome that vaccine hesitancy, then we can, you know, prevent a fall/winter wave for sure. And even at the university, I think we could go back to in-person learning. But we do have to deal with that issue.

Pamela

What about these variants of concern? Has that factored into your research?

Chris

Yes. So for the variants of concern, we've updated our model to include, for example, the B117 variant that's now dominant in Ontario. And this B117 variant is perhaps the biggest variant of concern because it's so transmissible— so much more transmissible than other variants. And also, it seems to be more serious in terms of the infection. But that's already with us, right? So that's not, it's now part of the ground fact, it's not something we have to worry about in the fall or winter. So conceivably, other variants could emerge. We don't know yet but we're already kind of dealing with B117, which is the biggest variant of concern, I think. Even for the longer term, waht the models can do, even though they're not perfect crystal balls that can tell you everything, they can give you important insights. For example, what we've learned from models is the instead of flattening the curve. And despite uncertainties, the exact number of cases and exact deaths rate, you know, despite all that uncertainty, if you reduce contacts, if you reduce transmission, you'll delay the epidemic peak and lower it. And that insight, for example, was instrumental in saving tens of thousands of lives in Ontario alone back in March 2020. So the insights are really perhaps as important use of models as are the predictions, the projections. And a great example of why that's important is the power of exponential growth. And I can illustrate that with a story about a king. A king had an advisor that had served for many years, and he wished to reward this advisor for his years of service. The advisor, who was very canny and good at math said, “Okay, just take a chessboard, eight by eight chessboard, and you put one grain of rice on the first square. You put two on the second square, and then you double it each time. So four grains of rice in the third square, then 8,16 32, etc. And then just give me all that rice. And I'll take that as payment.” And so the king said, ‘Well, how hard can that be? I'll do that.’ And so he started putting the rice grains down. And then he quickly realized that he didn't have enough rice in the entire kingdom to satisfy the request. And in fact, if you do that calculation, the amount of rice in the 64th square exceeds the current annual production of rice on the entire planet. Modern-day production. So it's a huge number. And so that illustrates the power of things that multiply themselves. And that's exactly what a pandemic is about. We have a virus that multiplies itself. Each infected person will infect around two and a half other persons on average in the absence of any control effort. You know, if you don't do anything, you know, cases look like they're pretty low, like the first few pieces of the chessboard. But then at some point, they just blow up in your face. So because of that, you need to look ahead and apply restrictions before the cases has reached that point. Because if you wait until the cases have blown up, and you start to apply restrictions, you're going to spend a lot of time in lockdown trying to get them back down again. And this is one mistake that many public health authorities around the world have made again and again—actually, it's not even public health authorities, it's the governments that are making the call. They don't look forward far enough in advance to avert that outcome. And that's how countries like New Zealand and China have been able to do it quite successfully is by acting soon acting decisively. And they've had been able to return to normal more quickly than other countries where it's been allowed to get out of hand.

Pamela

So what's next for you and your team?

Chris

One project is trying to estimate how many lives were saved by the March 2020 lockdown, and also by the one that started on Boxing Day in 2020. We have all the data from the last year that we can use to improve the model and make sure it's realistic. We can adjust the model parameters so that it captures, reproduces what actually happened. And then we can kind of rewind it and say, ‘Okay, well, what happens if we adjust the model so that we didn't lock down? What if we had gone for so-called herd immunity strategy instead? Then we can predict how many cases and deaths we would have had.’ And, for example, in the March 2020, lockdown, our results are showing that if we hadn't locked down and if people hadn't bothered to social distance, we would have had 175,000 deaths in the best-case scenario, instead of the 3,000 that we actually had. So that shows that the lockdown had a huge impact and in saving lots of lives in Ontario.

Pamela

 Oh, wow.

Chris

I think a lot of people want to know, you know, what are we accomplishing with this? And perhaps there's even some skepticism that, “Oh, you don't really need lockdown. Because, you know, COVID is just like the flu. And you know, people should just get it and get it over with and have their natural immunity.” So it kind of justifies those efforts. And, you know, anyone who wore a mask, or distanced, or tried to stay home, you know, they were saving lives in the process. And we wanted to show, you know, this is how many lives collectively we were able to save for these efforts.

Pamela

Right. I have to say that one of the big,  one of the scariest things about this pandemic for me has been like the unknown, it's the things you can't see. And so having these models, and even though they're not, you know, they're not predicting, like the weather or something, they do give us an idea of what could be coming. And I think that as scary as those second and third waves are, it is sort of reassuring to know, at least, that it's coming, as opposed to being surprised. Like a sneak attack or something.

Chris

Yeah, I agree with that. And the alternative is basically guessing and hoping. So, you know, it's better to have predictions with some caveats, limitations then than to not have any idea what's coming your way. And that gives you have much stronger basis to act.

Pamela

I agree. Thank you so much. And thank you to your team, for all the work that you're doing to help us stay more informed.

Chris

Thank you, Pamela. Yeah, it's been a nice interview.

Brandon

Well, that about wraps it up for us this week. You can find all of our past shows and the helpful links on soundcloud.com. To ensure you don't miss an episode, please subscribe to the Beyond the Bulletin Podcast wherever you get your podcasts and recommend us to your colleagues and Waterloo alumni.

Pamela

Also, don't forget to check out our bonus episode with updated vaccine information from Professor Kelly Grindrod. And also remember to do your part to limit the spread of COVID-19 in our community. You can get in touch with us via email at bulletin at uwaterloo dot ca.

Brandon

As always, thanks for listening as we went beyond the bulletin.

Pamela

Did you understand what computer modelling was before Brandon?

Brandon

Well, I assume it's not computers strutting down the runway. Although I'd kind of like to see that.