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The value of biosecurity Andrew Robinson
Thank you. It's a real pleasure to be here. I'm delighted.
I know many of you will feel shortchanged, because I was really supposed to be Mark Burgman,
who's the director of CEBRA. He's much more personable than I am. And he's also quite a bit
taller. So I did ask if there could be some little box that I could stand on to give you the sense
that Mark was here, but that was impossible. So I apologise for the lack of box.
As [? Rona ?] said, I am an applied statistician, but I want to emphasise that I come here in
peace. I want to make peace among our tribes. I'm going to talk about some projects that CEBRA
has been working on for the past, well, nearly a year now and before that ACERA-- the
Australian Centre of Excellence of Risk Analysis. And I would point out where these projects
have direct ramifications for the activities of the regulator.
I promise that I'll keep the formulae and the statistics jug into an absolute minimum. Although, I
am contractually obliged to include at least one little piece of Greek somewhere in the
presentation. You get a prize if you find it. Forwards.
So who is CEBRA? CEBRA is a small group, a ragtag group all of academics comprising Mark
Burgman, myself, Tom Kompas, and Susie Hester. But in another sense, CEBRA is everywhere.
CEBRA has links with an exceptionally wide range of organisations, both in Australia and
outside Australia.
As a little side note, we were asked to make our presentations fit these fancy screens, which are
9/16. And that required a rescaling of the images. And I noted with surprise that when the time
came to rescale this particular image, CSIRO was already the right size. So they seem to have
anticipated our needs to change the relationship among all the images.
Anyway, so we have relationships with ANU, with the University of New South Wales, with the
University of New England, and so on. And we draw expertise from all those places because our
skills are very limited.
The kinds of things that ACERA has been working on for the past six years, we have a
smorgasbord of activity and contribution in that broad area of biosecurity and the broad area of
the regulation of biosecurity. There's a shopping list on the left-hand side of the slide that I won't
read out.
But we have a collaboration from West Australia with the Bayes nets. We have a collaboration
with Tom Kompas in the value of biosecurity. We look at the prediction of likely places and
impacts of invasion using tools, such as MaxEnt. And we think about the value of surveillance
and the value of activity to try to wipe out a pest.
And we've been doing the sort of cost effectiveness analyses with two teams at the School of
Botany at the University of Melbourne. So we have a wide palette of activities that covers
analysis and model fitting, and statistics, and even doing things.
As we move forward, CEBRA will encompass five overarching themes of activities that will
contribute towards biosecurity regulation. And the five themes data mining, which is in my
purview, we'll be looking at spatial analysis-- analysis of spatial data sets. We'll have biosecurity
intelligence, which is a topic that I'll touch on briefly in a little while, and benefit-cost analysis,
and, finally, pathway analysis and risk-based management.
So I want to take a moment to pause to think about the regulator. The regulator in this case is the
Department of Agriculture. And I want to talk about the regulator's conundrum.
The regulators conundrum is that the regulator is tasked to protect us, to protect our economy, to
protect our ecosystems, to protect our agriculture, broadly to protect our industry from all kinds
of pests. So the regulator is intended to be a vast umbrella that protects us from the reign of
pests, to which we are continually subject.
However, the regulator operates under constraints. The regulator should not cost too much. The
regulator should not take too long. And the regulator should not impede trade. And we can see
the regulator almost as being a rope in a tug of war with all kinds of different interests pulling
that rope in different directions.
We have the World Trade organisation, we have our trading partners, we have agricultural
industry, we have our populations-- everyone wants it regulated to do something. Everyone
wants it regulated to do something slightly different. And this creates a conundrum for the
regulator-- how do you be the very best regulator you can be, when everybody wants you to be
different?
Well, the simple answer is just do what CEBRA tells you. Sadly, this is not an answer that has
resonated with our colleagues to date. So we have to have a conversation. So the regulator has to
protect us from pests, but not too much. It leaves the regulator in a place of needing to let the
right one in.
And I confess to a shameless attempt to hook into the Zeitgeist, because that's also the title of a
rather popular vampire movie. But I want to emphasise that there's no necessary connection
between vampirism and biosecurity regulation. Just in case I need to make that perfectly clear.
So what does value mean in this context? And I think value, we all agree, means value for effort.
Value means that when the regulator steps in and does something, when the regulator acts, we
want the actions of the regulator to have value to us.
Really, we're asking the regulator be an oracle. We're saying to the regulator, you should get in
there and look where you should look. And don't waste time looking where you shouldn't look,
because that's not profitable. But do make sure that you catch everything.
Well, it's impossible. There's 20 million cargo items every year, for example. That's an absolute
requirement that we say to the regulator, only look where you should look.
And to double down on this, we really look at the regulator retrospectively. We don't say, look
where you should look. We really want to say, you should have looked where you should have
looked.
When we're thinking about the regulator's impact, we are looking back and saying, did you look
where you should have looked? Because if you didn't, then there's a significant problem. But of
course, they didn't know where they had to look until they looked. This doubles down on the
conundrum.
So one of the innovations that we've impressed upon the regulator in CEBRA is to try to vastly
simplify the way the regulator thinks about its environment. We've encouraged the regulator to
think not about the degree of risk. I mean, of course, in terms of broad management, you want to
think about how much risk you're absorbing.
But in terms of planning, in terms of action, we've encouraged the regulator to think about
whether or not they should have been there. That actually turns out to be a very profitable way to
think about the problem of regulation-- should we have been there? Should we have opened that
package?
Even though it leads into an impossible question-- that is, predict where you should have been
before you were there. It still turns out to be a neat way to think about how well you did as a job
as a regulator. And so that's what this string of zeros and ones is intended to imply. It's an
inspection history of when the regulator should and should not have been there.
Of course, things are not always that simple. Often the regulator is cursed with an inactive device
that doesn't change slides when it should. Often, the regulator is cursed with a plethora of
pathways to think about managing-- not often, all the time, all the time. The regulator has to
think about a plethora of pathways, a plethora of potential interventions-- how do you find where
you should be?
So CEBRA has been working for the past couple of years on developing tools to help the
regulator formalise and construct solutions for this problem of how do you go where you ought
to be before you know you really ought to be there? So letting the right one in splits at this point.
It trafficates into three different approaches that I want to talk about that CEBRA has had some
involvement in.
The first one is when you have history, when you know what you think the environment looks
like, because you've been in the environment for long enough. You've measuring if, you've been
capturing things, and you've been taking notes. Then you should do data mining. And that's one
of the activities that we've undertaken.
When you don't have a history of this kind, when you're not sure about the environment, you
need to learn about it. I'm going to talk about a project that has helped us develop tools to gather
data in a responsive, flexible way, allowing for regulation where it is best placed, and trying, as
flexibly as possible, to reduce interventions on pathways that show in the shorter term clean
product. And finally, building an international community of practise to help us impede the
activities of pests off shore, as well as on shore. These are the three projects I'm going to touch
on briefly in my remaining few moments.
So there's a picture of a Russian oil tanker there to remind me to tell you about Russian oil
tankers. They're long, they're large, and sometimes they carry Asian gypsy moths. And you need
to get every square centimetre of the outside of those vessels inspected by a human being to
make sure that they don't have Asian gypsy moths egg sacs on them.
These things can be no larger than a $0.50 coin. And happily we know they cluster under lights.
But still, these little things on that big boat-- it's a very difficult problem.
The lessons we've learned in helping the regulator develop a data mining project simply
encapsulated as follows. You can't find things when you don't look for them. So a data mining
exercise has value in as much as it provides you with a framework for defining what you're
looking for and increasing the probability that you'll actually find it.
Secondly, and this is a really important one, you have to start with the data you have. It's very
tempting. It's very tempting as a regulator to look back at the history of data collection and say,
you know what, these are not the perfect data.
These data are flawed because they don't record every possible deception or every possible effort
that was undertaken. Of course, the data are flawed. This is the real world we're in.
You must start with the data you have. By all means take steps to improve the quality of your
data. But don't impede your analytical efforts. Instead, condition your outcomes on the known
qualities of the data. You can say, well, here's what the data recommend that I do, but I know
they're flawed in the following way. I'm going to tweak this outcome a little bit based on my
understanding and knowledge of the pathway.
You can do that, but don't forget to analyse along that pathway. The reason is that when people
see the data being used, suddenly, their interest in collecting quality data heightens. You'll get
better data when you use the data you have well.
Thirdly, we have to start small. Don't try to come in-- this is a classic academic sin. You want to
walk in with the magic sword of understanding and the shield of regulation, and you want to
protect everybody with these shining weapons. And it just doesn't work.
We have to start with the smallest possible problems and let those be solved unequivocally, and
then grow them. We had to keep our own operations-- thank you-- meaning that we had to make
sure that we went forward with a view to actually operationalising the solutions. And finally, we
need to build bridges within the organisation. It's all very well to bring innovation, but we have
to be sure that the innovation can be implemented and sustained. And this is where the
relationship between CEBRA and ABARES has become so profitable and so important.
If you don't have history, you have to make history. The strategy for making history that we
introduced with the biosecurity regulator was a tool that came from the 1940s called the
continuous sampling protocol. I'll describe it very briefly.
Every partway starts off in an inspect all regime. That is inspect every consignment as it comes
across the boarder. After a certain number of inspecting consignments, if they're all clean, then
shift that pathway to a new mode, in which you only inspect every one in 10, for example,
because you conclude the pathway has demonstrated a level of compliance. So you reduce the
intervention on the pathway.
You maintain some intervention, you maintain a sample, but you reduce it, so that you're just
monitoring the pathway. And of course, if you find something in that monitoring process, you
return the pathway to the full inspection regime. This approach allows you to flexibly and
interactively allocate inspection resources to where the immediate history suggests they will do
the most good, whilst maintaining information collection on the pathways we don't think there's a
problem.
Finally, I want to touch on building bridges. We have developed a community of practise, an
international community of practise, using the international biosecurity intelligence system,
which we used to connect experts on old different kinds of biota across the world. And I
mentioned briefly, a case study is a success where a breeder of oysters in France closed down
because of infestation of oyster herpes virus. And they sold their equipment on the open market.
People bought and imported the equipment to other countries, and started noticing oyster herpes
virus springing up in these other locations.
We were able to detect it using this tool and change regulations so that when used aquaculture
equipment was brought into the country, it had to be disinfected. Previously, that had not been
mandatory. So by means of this tool, we were able to avoid an invasion that was observed in
other locations.
So as an overview, I want to reflect upon the fact that the regulator is caught in an uncomfortable
place. The regulator's life is not a happy one. CEBRA and through its relationship with
ABARES-- ABARES also provide innovation and support to make the regulator's life easier by
making it more measurable and more pleasant.
All of our information is available freely on our website. You can see that on the presentation.
And there's many, many earlier reports by ACERA, which was our predecessor, available on the
ACERA website. And I urge you warmly to mine that resource. Thank you.