2.5. Bridging Data for Better Health Outcomes

1
00:00:06,200 --> 00:00:07,919
Speaker:
Hello and welcome to Going Macro
2
00:00:07,919 --> 00:00:09,640
Speaker:
On Micro, the podcast where we
3
00:00:09,640 --> 00:00:11,240
Speaker:
explore emerging themes in
4
00:00:11,240 --> 00:00:12,519
Speaker:
microbiology.
5
00:00:12,519 --> 00:00:14,599
Speaker:
Brought to you by
Beckman Coulter.
6
00:00:14,599 --> 00:00:16,239
Speaker:
I am your host, Doctor Julie Ann
7
00:00:16,239 --> 00:00:17,719
Speaker:
Lough, a science communicator,
8
00:00:17,719 --> 00:00:19,719
Speaker:
passionate about sharing stories
9
00:00:19,719 --> 00:00:21,280
Speaker:
exploring the future of health
10
00:00:21,280 --> 00:00:22,719
Speaker:
and science.
11
00:00:22,719 --> 00:00:24,539
Speaker:
In this, our second series, we
12
00:00:24,539 --> 00:00:26,280
Speaker:
continue to explore the concept
13
00:00:26,280 --> 00:00:28,000
Speaker:
of one health, an integrated
14
00:00:28,000 --> 00:00:29,960
Speaker:
approach that recognizes that
15
00:00:29,960 --> 00:00:31,839
Speaker:
the health of people, animals,
16
00:00:31,839 --> 00:00:33,759
Speaker:
and ecosystems are all
17
00:00:33,759 --> 00:00:35,479
Speaker:
interconnected.
18
00:00:35,479 --> 00:00:37,880
Speaker:
When we think about the
challenges facing our health,
19
00:00:37,880 --> 00:00:41,880
Speaker:
from pandemics to antibiotic
resistance, it's clear no one
20
00:00:41,880 --> 00:00:43,600
Speaker:
exists in a vacuum.
21
00:00:43,600 --> 00:00:45,759
Speaker:
We are all in this together.
22
00:00:45,759 --> 00:00:48,560
Speaker:
Following on from the last four
episodes where we heard about
23
00:00:48,560 --> 00:00:51,939
Speaker:
the importance of environmental
sampling in identifying emerging
24
00:00:51,939 --> 00:00:55,920
Speaker:
trends in antibiotic resistance
and the role of Beckman Coulter
25
00:00:55,920 --> 00:00:58,850
Speaker:
in contributing to the One
Health initiative we are
26
00:00:58,850 --> 00:01:02,619
Speaker:
bringing both experts together
to continue this dialogue.
27
00:01:02,619 --> 00:01:06,180
Speaker:
Joining me is Doctor Andrew Lee
from Queen's University Belfast
28
00:01:06,180 --> 00:01:10,260
Speaker:
in the UK, who focuses on
environmental sampling as a tool
29
00:01:10,260 --> 00:01:13,859
Speaker:
in epidemiology and monitoring
the emergence of antimicrobial
30
00:01:13,859 --> 00:01:15,939
Speaker:
resistance, or AMR.
31
00:01:15,939 --> 00:01:17,560
Speaker:
And Doctor Stephanie Mitchell,
32
00:01:17,560 --> 00:01:19,340
Speaker:
head of scientific affairs at
33
00:01:19,340 --> 00:01:20,500
Speaker:
Beckman Coulter.
34
00:01:20,500 --> 00:01:22,659
Speaker:
Both of you, welcome back to the
podcast.
35
00:01:22,659 --> 00:01:23,900
Speaker:
Thanks for having me, Julie Ann.
36
00:01:23,900 --> 00:01:25,500
Speaker:
Yeah, excited to be here.
37
00:01:25,500 --> 00:01:26,140
Speaker:
Great.
38
00:01:26,140 --> 00:01:27,780
Speaker:
Well, fantastic to have you
both.
39
00:01:27,780 --> 00:01:30,260
Speaker:
I'm going to start off with you,
Andrew, on this one, I think.
40
00:01:30,260 --> 00:01:33,540
Speaker:
And let's begin a little bit by
discussing surveillance.
41
00:01:33,540 --> 00:01:37,340
Speaker:
You both mentioned this as key
to the understanding of what's
42
00:01:37,340 --> 00:01:38,859
Speaker:
happening in the real world.
43
00:01:38,859 --> 00:01:41,099
Speaker:
So what's going on out there, I
suppose.
44
00:01:41,099 --> 00:01:42,659
Speaker:
And both of you work in this
45
00:01:42,659 --> 00:01:44,840
Speaker:
critical area for you, Andrew,
46
00:01:44,840 --> 00:01:46,379
Speaker:
in your opinion, how does
47
00:01:46,379 --> 00:01:48,260
Speaker:
surveillance play a vital role
48
00:01:48,260 --> 00:01:49,719
Speaker:
in the one health approach and
49
00:01:49,719 --> 00:01:51,099
Speaker:
what does it mean for public
50
00:01:51,099 --> 00:01:52,180
Speaker:
health outcomes?
51
00:01:52,180 --> 00:01:54,760
Speaker:
For me, surveillance is the is
52
00:01:54,760 --> 00:01:57,049
Speaker:
the the foundation stone, the
53
00:01:57,049 --> 00:01:58,040
Speaker:
plinth, whatever you want to
54
00:01:58,040 --> 00:01:58,719
Speaker:
call it.
55
00:01:58,719 --> 00:02:01,159
Speaker:
Upon the whole what,
56
00:02:01,159 --> 00:02:02,680
Speaker:
the whole one health approach
57
00:02:02,680 --> 00:02:04,359
Speaker:
Uh rests upon.
58
00:02:04,359 --> 00:02:06,599
Speaker:
Um. Without it, you're not going
anywhere.
59
00:02:06,599 --> 00:02:09,800
Speaker:
And I feel it's an incredibly
important part of it,
60
00:02:09,800 --> 00:02:11,379
Speaker:
Uh, just personally, from the
61
00:02:11,379 --> 00:02:13,199
Speaker:
work that I do, a lot of it
62
00:02:13,199 --> 00:02:14,840
Speaker:
would be around surveillance,
63
00:02:14,840 --> 00:02:16,219
Speaker:
because surveillance is key for
64
00:02:16,219 --> 00:02:17,979
Speaker:
that, that early detection,
65
00:02:17,979 --> 00:02:20,159
Speaker:
which then ramps up that rapid
66
00:02:20,159 --> 00:02:21,199
Speaker:
response.
67
00:02:21,199 --> 00:02:22,479
Speaker:
And so you're flying blind if
68
00:02:22,479 --> 00:02:23,819
Speaker:
you don't have any surveillance
69
00:02:23,819 --> 00:02:27,520
Speaker:
on what, uh, might be impacting
70
00:02:27,520 --> 00:02:29,319
Speaker:
the whole one health sphere,
71
00:02:29,319 --> 00:02:31,039
Speaker:
whether that's climate change,
72
00:02:31,039 --> 00:02:32,080
Speaker:
whether we're talking about
73
00:02:32,080 --> 00:02:34,219
Speaker:
emerging zoonotic pathogens from
74
00:02:34,219 --> 00:02:35,360
Speaker:
the animal side of things, or
75
00:02:35,360 --> 00:02:36,620
Speaker:
whether we're talking about
76
00:02:36,620 --> 00:02:38,680
Speaker:
another potential, uh, human
77
00:02:38,680 --> 00:02:39,759
Speaker:
relevant pandemic.
78
00:02:39,759 --> 00:02:41,919
Speaker:
And I guess for you, Stephanie,
as well, you kind of touched on
79
00:02:41,919 --> 00:02:43,639
Speaker:
this before, really, isn't it?
80
00:02:43,639 --> 00:02:44,560
Speaker:
If we don't know what's going
81
00:02:44,560 --> 00:02:46,240
Speaker:
on, we don't know how to tackle
82
00:02:46,240 --> 00:02:46,599
Speaker:
it.
83
00:02:46,599 --> 00:02:47,000
Speaker:
Yeah.
84
00:02:47,000 --> 00:02:50,039
Speaker:
And I could not agree more with
Doctor Lee on this.
85
00:02:50,039 --> 00:02:51,840
Speaker:
Um, in my opinion, the first
86
00:02:51,840 --> 00:02:53,560
Speaker:
step to solving any problem is
87
00:02:53,560 --> 00:02:55,145
Speaker:
you have to see the problem
88
00:02:55,145 --> 00:02:55,729
Speaker:
fully.
89
00:02:55,729 --> 00:02:59,330
Speaker:
And surveillance provides you
the ability to see.
90
00:02:59,330 --> 00:03:01,289
Speaker:
And I think, you know, we all
91
00:03:01,289 --> 00:03:02,409
Speaker:
are working in our own little
92
00:03:02,409 --> 00:03:02,770
Speaker:
sector.
93
00:03:02,770 --> 00:03:04,490
Speaker:
So we may see a piece of the
puzzle.
94
00:03:04,490 --> 00:03:08,729
Speaker:
So I think to really solve the
problem holistically, we need to
95
00:03:08,729 --> 00:03:13,090
Speaker:
see everybody's pieces of the
puzzle and how that inner web of
96
00:03:13,090 --> 00:03:17,229
Speaker:
AMR, you know, across that one
health continuum connects,
97
00:03:17,229 --> 00:03:21,110
Speaker:
because that can then allow you
to look for correlations,
98
00:03:21,110 --> 00:03:24,650
Speaker:
initiate rapid responses like
Doctor Lee suggested.
99
00:03:24,650 --> 00:03:27,250
Speaker:
But also, see, I'm seeing
something maybe over in my
100
00:03:27,250 --> 00:03:30,889
Speaker:
domestic animal agricultural
space that's concerning.
101
00:03:30,889 --> 00:03:32,169
Speaker:
What do I need to do now?
102
00:03:32,169 --> 00:03:33,650
Speaker:
What proactive steps can I do
103
00:03:33,650 --> 00:03:36,289
Speaker:
now to safeguard human in
104
00:03:36,289 --> 00:03:38,370
Speaker:
addition to, you know, working
105
00:03:38,370 --> 00:03:40,009
Speaker:
to solve the acute problem in
106
00:03:40,009 --> 00:03:41,330
Speaker:
the agricultural space, for
107
00:03:41,330 --> 00:03:42,009
Speaker:
example.
108
00:03:42,009 --> 00:03:45,289
Speaker:
So again, like data is power,
right?
109
00:03:45,289 --> 00:03:47,490
Speaker:
So data allows you to see it
110
00:03:47,490 --> 00:03:49,250
Speaker:
allows you to make connections,
111
00:03:49,250 --> 00:03:51,729
Speaker:
trends, correlations, maybe even
112
00:03:51,729 --> 00:03:53,259
Speaker:
causations, but probably mostly
113
00:03:53,259 --> 00:03:55,370
Speaker:
correlations that allows you to
114
00:03:55,370 --> 00:03:56,949
Speaker:
drive actionability.
115
00:03:56,949 --> 00:04:00,110
Speaker:
And then hopefully eventually
policy changes.
116
00:04:00,110 --> 00:04:01,430
Speaker:
And then, you know, coming from
117
00:04:01,430 --> 00:04:04,550
Speaker:
my perspective, drive innovation
118
00:04:04,550 --> 00:04:06,870
Speaker:
around new devices and data
119
00:04:06,870 --> 00:04:09,370
Speaker:
science softwares and tools to
120
00:04:09,370 --> 00:04:10,930
Speaker:
help, you know, continue to
121
00:04:10,930 --> 00:04:12,349
Speaker:
bring the surveillance data
122
00:04:12,349 --> 00:04:13,710
Speaker:
together so that, again, we can
123
00:04:13,710 --> 00:04:16,110
Speaker:
continue to see the problem and
124
00:04:16,110 --> 00:04:17,310
Speaker:
how the problem is evolving,
125
00:04:17,310 --> 00:04:18,350
Speaker:
because we know it's not going
126
00:04:18,350 --> 00:04:20,589
Speaker:
to be a single one stop shop
127
00:04:20,589 --> 00:04:20,990
Speaker:
problem.
128
00:04:20,990 --> 00:04:24,189
Speaker:
It's going to be a continuing
evolution problem.
129
00:04:24,189 --> 00:04:26,389
Speaker:
I guess I think that brings me
on to a really good point.
130
00:04:26,389 --> 00:04:27,269
Speaker:
You've mentioned, you know, the
131
00:04:27,269 --> 00:04:28,470
Speaker:
agriculture and the human health
132
00:04:28,470 --> 00:04:28,870
Speaker:
people.
133
00:04:28,870 --> 00:04:30,709
Speaker:
They can't work in individual
silos.
134
00:04:30,709 --> 00:04:33,189
Speaker:
And that's what the One Health
Framework really is all about.
135
00:04:33,189 --> 00:04:34,750
Speaker:
It's that idea that people,
136
00:04:34,750 --> 00:04:36,230
Speaker:
animals and ecosystems are all
137
00:04:36,230 --> 00:04:37,470
Speaker:
interconnected.
138
00:04:37,470 --> 00:04:39,430
Speaker:
So how does the surveillance
139
00:04:39,430 --> 00:04:41,910
Speaker:
then integrate all those aspects
140
00:04:41,910 --> 00:04:44,230
Speaker:
of health data to inform human
141
00:04:44,230 --> 00:04:45,350
Speaker:
health strategies?
142
00:04:45,350 --> 00:04:48,069
Speaker:
So I was actually thinking about
this the other day.
143
00:04:48,069 --> 00:04:54,329
Speaker:
I feel that there are a lot of
really awesome grassroot efforts
144
00:04:54,329 --> 00:04:57,709
Speaker:
of people, you know, in their
institution, in their community,
145
00:04:57,709 --> 00:05:02,329
Speaker:
in their country, doing awesome
work to make progress in their
146
00:05:02,329 --> 00:05:03,569
Speaker:
area for AMR.
147
00:05:03,569 --> 00:05:05,250
Speaker:
I think we need to work more
148
00:05:05,250 --> 00:05:07,250
Speaker:
towards and improve is the
149
00:05:07,250 --> 00:05:08,810
Speaker:
coordination of all of these
150
00:05:08,810 --> 00:05:10,689
Speaker:
individual efforts that everyone
151
00:05:10,689 --> 00:05:12,649
Speaker:
is undertaking, because they
152
00:05:12,649 --> 00:05:14,449
Speaker:
understand the severity of the
153
00:05:14,449 --> 00:05:15,250
Speaker:
issue.
154
00:05:15,250 --> 00:05:18,829
Speaker:
And I think that coordination is
key to starting to bring
155
00:05:18,829 --> 00:05:23,649
Speaker:
together not just people to talk
about stuff, but actual data.
156
00:05:23,649 --> 00:05:24,089
Speaker:
Right?
157
00:05:24,089 --> 00:05:28,209
Speaker:
Get the data together, analyze
the data in certain ways.
158
00:05:28,209 --> 00:05:29,310
Speaker:
And so it's that layer of
159
00:05:29,310 --> 00:05:30,810
Speaker:
coordination of each of these
160
00:05:30,810 --> 00:05:32,490
Speaker:
individual efforts that I think
161
00:05:32,490 --> 00:05:35,370
Speaker:
is our next step in progressing
162
00:05:35,370 --> 00:05:37,410
Speaker:
in how we see the problem, and
163
00:05:37,410 --> 00:05:39,009
Speaker:
then also how we come up with
164
00:05:39,009 --> 00:05:40,209
Speaker:
innovative solutions to the
165
00:05:40,209 --> 00:05:41,009
Speaker:
problem.
166
00:05:41,009 --> 00:05:41,569
Speaker:
Yeah.
167
00:05:41,569 --> 00:05:44,329
Speaker:
Um, Doctor Mitchell has hit the
nail on the head there.
168
00:05:44,329 --> 00:05:47,910
Speaker:
So she has, um, I you might have
heard me snigger there a little
169
00:05:47,910 --> 00:05:49,050
Speaker:
bit just at the start.
170
00:05:49,050 --> 00:05:50,870
Speaker:
Uh, Not simply because I suppose
171
00:05:50,870 --> 00:05:52,509
Speaker:
I would answer it with great
172
00:05:52,509 --> 00:05:54,430
Speaker:
difficulty, is how you make
173
00:05:54,430 --> 00:05:56,649
Speaker:
everyone start talking because
174
00:05:56,649 --> 00:05:58,089
Speaker:
you know everyone is doing
175
00:05:58,089 --> 00:06:00,069
Speaker:
really good work all in their
176
00:06:00,069 --> 00:06:00,790
Speaker:
own sectors.
177
00:06:00,790 --> 00:06:02,910
Speaker:
But when you start to get trying
178
00:06:02,910 --> 00:06:04,829
Speaker:
to drive people together,
179
00:06:04,829 --> 00:06:06,170
Speaker:
sometimes it's like, you know,
180
00:06:06,170 --> 00:06:08,069
Speaker:
trying to stick to polar
181
00:06:08,069 --> 00:06:09,490
Speaker:
opposites together or, you know,
182
00:06:09,490 --> 00:06:11,430
Speaker:
try to force to the same side of
183
00:06:11,430 --> 00:06:13,110
Speaker:
two magnets together or whatever.
184
00:06:13,110 --> 00:06:15,189
Speaker:
It's having and fostering
185
00:06:15,189 --> 00:06:17,350
Speaker:
networks that are collaborative
186
00:06:17,350 --> 00:06:19,350
Speaker:
in this way, but also that
187
00:06:19,350 --> 00:06:20,970
Speaker:
people understand, you know,
188
00:06:20,970 --> 00:06:22,949
Speaker:
nobody's trying to railroad
189
00:06:22,949 --> 00:06:24,949
Speaker:
somebody or try to encroach in
190
00:06:24,949 --> 00:06:25,430
Speaker:
their areas.
191
00:06:25,430 --> 00:06:28,470
Speaker:
It's about identifying and
having an honest conversation
192
00:06:28,470 --> 00:06:32,250
Speaker:
about why all these areas should
be overlapping and working
193
00:06:32,250 --> 00:06:34,670
Speaker:
together for the benefit of all.
194
00:06:34,670 --> 00:06:36,449
Speaker:
That is a quite a bit of a
195
00:06:36,449 --> 00:06:38,509
Speaker:
struggle still, and quite a bit
196
00:06:38,509 --> 00:06:39,589
Speaker:
of that struggle actually comes
197
00:06:39,589 --> 00:06:42,069
Speaker:
down to even just organizations
198
00:06:42,069 --> 00:06:43,550
Speaker:
or institutes just putting up
199
00:06:43,550 --> 00:06:45,449
Speaker:
some money for a, you know, a
200
00:06:45,449 --> 00:06:47,254
Speaker:
couple of days together, a
201
00:06:47,254 --> 00:06:47,639
Speaker:
coffee
202
00:06:47,639 --> 00:06:47,959
Speaker:
Morning.
203
00:06:47,959 --> 00:06:50,079
Speaker:
Whatever you whatever way you
want to describe it.
204
00:06:50,079 --> 00:06:53,319
Speaker:
Because let's face it, as much
as, um, virtual meetings have
205
00:06:53,319 --> 00:06:54,920
Speaker:
been great, so they have.
206
00:06:54,920 --> 00:06:57,720
Speaker:
And driving that forward,
sometimes you can't beat just
207
00:06:57,720 --> 00:06:59,980
Speaker:
getting into a room, same room
together and having a good
208
00:06:59,980 --> 00:07:02,879
Speaker:
natter, because then you can
properly read people's body
209
00:07:02,879 --> 00:07:04,000
Speaker:
language face to face.
210
00:07:04,000 --> 00:07:07,920
Speaker:
You know, you can put your
emotional argument to the person
211
00:07:07,920 --> 00:07:08,800
Speaker:
and backwards and forwards.
212
00:07:08,800 --> 00:07:10,360
Speaker:
So I think a lot of what Doctor
213
00:07:10,360 --> 00:07:11,920
Speaker:
Mitchell has said is absolutely
214
00:07:11,920 --> 00:07:12,600
Speaker:
right.
215
00:07:12,600 --> 00:07:15,360
Speaker:
Um, but there will be challenges
in this.
216
00:07:15,360 --> 00:07:17,600
Speaker:
Um, I'm sure she has seen
challenges.
217
00:07:17,600 --> 00:07:18,360
Speaker:
I definitely have seen
218
00:07:18,360 --> 00:07:19,319
Speaker:
challenges with her still
219
00:07:19,319 --> 00:07:21,319
Speaker:
ongoing challenges with with
220
00:07:21,319 --> 00:07:22,959
Speaker:
trying to get sectors to talk
221
00:07:22,959 --> 00:07:23,839
Speaker:
together.
222
00:07:23,839 --> 00:07:27,399
Speaker:
Um, and uh, and, and it'll be
something that will always have
223
00:07:27,399 --> 00:07:28,240
Speaker:
to be worked at.
224
00:07:28,240 --> 00:07:30,240
Speaker:
You were saying that you've
experienced so many challenges.
225
00:07:30,240 --> 00:07:31,000
Speaker:
Are there any particular
226
00:07:31,000 --> 00:07:32,319
Speaker:
examples you're you're able to
227
00:07:32,319 --> 00:07:33,399
Speaker:
talk about, or is it a lot of it
228
00:07:33,399 --> 00:07:35,519
Speaker:
just down to maybe institutions
229
00:07:35,519 --> 00:07:37,139
Speaker:
being slightly slower to to
230
00:07:37,139 --> 00:07:38,959
Speaker:
change how they operate or
231
00:07:38,959 --> 00:07:40,480
Speaker:
people learning to communicate
232
00:07:40,480 --> 00:07:41,319
Speaker:
better?
233
00:07:41,319 --> 00:07:45,660
Speaker:
How how do you think, other than
having coffee mornings and
234
00:07:45,660 --> 00:07:46,579
Speaker:
eyeballing each other.
235
00:07:46,579 --> 00:07:48,079
Speaker:
Like, do you think that there's,
236
00:07:48,079 --> 00:07:49,540
Speaker:
I don't know, is it a case of
237
00:07:49,540 --> 00:07:50,860
Speaker:
policy change to get people
238
00:07:50,860 --> 00:07:51,939
Speaker:
communicating better or
239
00:07:51,939 --> 00:07:53,540
Speaker:
institutional change?
240
00:07:53,540 --> 00:07:54,660
Speaker:
It definitely is.
241
00:07:54,660 --> 00:07:58,579
Speaker:
And I'm sure Doctor Mitchell has
her own views on this as well.
242
00:07:58,579 --> 00:08:03,139
Speaker:
And certainly jump in and add
add to it, Stephanie.
243
00:08:03,139 --> 00:08:09,540
Speaker:
Uh, but a lot of it comes down
to, um, for example, if you're
244
00:08:09,540 --> 00:08:13,860
Speaker:
sharing data, sometimes the
databases that organizations use
245
00:08:13,860 --> 00:08:16,740
Speaker:
are are completely different.
246
00:08:16,740 --> 00:08:18,240
Speaker:
And so if you're just trying to
247
00:08:18,240 --> 00:08:19,379
Speaker:
have that straightforward
248
00:08:19,379 --> 00:08:22,620
Speaker:
sharing of data, um, that takes
249
00:08:22,620 --> 00:08:24,319
Speaker:
some work to get it into a
250
00:08:24,319 --> 00:08:25,180
Speaker:
common form.
251
00:08:25,180 --> 00:08:27,060
Speaker:
So it does that everyone can
share.
252
00:08:27,060 --> 00:08:28,740
Speaker:
Likewise, you mentioned there
253
00:08:28,740 --> 00:08:30,420
Speaker:
policy, and I do think they will
254
00:08:30,420 --> 00:08:31,980
Speaker:
have to be that leadership,
255
00:08:31,980 --> 00:08:33,100
Speaker:
whether that's at the political
256
00:08:33,100 --> 00:08:34,379
Speaker:
level or whatever, whether it's
257
00:08:34,379 --> 00:08:35,879
Speaker:
just, this is what's going to
258
00:08:35,879 --> 00:08:36,620
Speaker:
happen.
259
00:08:36,620 --> 00:08:38,019
Speaker:
Accept it.
260
00:08:38,019 --> 00:08:40,940
Speaker:
We're going to make this policy,
we're going to make it law.
261
00:08:40,940 --> 00:08:42,340
Speaker:
Let's move forward.
262
00:08:42,340 --> 00:08:44,240
Speaker:
Um, because last month I was
263
00:08:44,240 --> 00:08:46,220
Speaker:
there at, um, the big EU Wish
264
00:08:46,220 --> 00:08:48,200
Speaker:
consortium meeting in Dublin,
265
00:08:48,200 --> 00:08:49,320
Speaker:
and it brought together all the
266
00:08:49,320 --> 00:08:50,720
Speaker:
wastewater groups throughout
267
00:08:50,720 --> 00:08:52,700
Speaker:
Europe, uh, except the UK,
268
00:08:52,700 --> 00:08:54,080
Speaker:
because unfortunately, we're no
269
00:08:54,080 --> 00:08:56,039
Speaker:
longer a part of that, uh, at
270
00:08:56,039 --> 00:08:56,720
Speaker:
the moment.
271
00:08:56,720 --> 00:08:59,120
Speaker:
Um, but we were there, um, we
272
00:08:59,120 --> 00:09:00,559
Speaker:
were listening and it was, it
273
00:09:00,559 --> 00:09:02,840
Speaker:
was just a big get a load of
274
00:09:02,840 --> 00:09:03,960
Speaker:
people in the room from across
275
00:09:03,960 --> 00:09:06,000
Speaker:
all EU countries where it's
276
00:09:06,000 --> 00:09:07,259
Speaker:
going to be made law to do
277
00:09:07,259 --> 00:09:08,320
Speaker:
wastewater surveillance, this
278
00:09:08,320 --> 00:09:10,200
Speaker:
primary surveillance that that
279
00:09:10,200 --> 00:09:11,980
Speaker:
broaches the whole one health
280
00:09:11,980 --> 00:09:12,919
Speaker:
approach.
281
00:09:12,919 --> 00:09:14,360
Speaker:
And it was just about that it
282
00:09:14,360 --> 00:09:15,639
Speaker:
wasn't a conference to get
283
00:09:15,639 --> 00:09:15,960
Speaker:
together
284
00:09:15,960 --> 00:09:17,320
Speaker:
and here's my interesting
findings.
285
00:09:17,320 --> 00:09:17,919
Speaker:
It was right.
286
00:09:17,919 --> 00:09:19,399
Speaker:
What do we need to do?
287
00:09:19,399 --> 00:09:23,720
Speaker:
How do we make this policy, what
is a priority list of pathogens,
288
00:09:23,720 --> 00:09:27,080
Speaker:
etc., etc., etc.. Where does AMR
fit into it all that it was just
289
00:09:27,080 --> 00:09:29,399
Speaker:
a bare bones straight, straight
to the point.
290
00:09:29,399 --> 00:09:33,639
Speaker:
And so it's going to need to be
policies need to be acted.
291
00:09:33,639 --> 00:09:34,840
Speaker:
Um, it's going to need to have
292
00:09:34,840 --> 00:09:36,399
Speaker:
some hard conversations with
293
00:09:36,399 --> 00:09:37,960
Speaker:
certain organisations to say,
294
00:09:37,960 --> 00:09:39,860
Speaker:
get over yourself, stop being so
295
00:09:39,860 --> 00:09:40,799
Speaker:
egotistical.
296
00:09:40,799 --> 00:09:41,860
Speaker:
You know what I mean?
297
00:09:41,860 --> 00:09:45,220
Speaker:
At the end of the day, what is
the common goal here?
298
00:09:45,220 --> 00:09:47,860
Speaker:
Improving health outcomes for
everyone.
299
00:09:47,860 --> 00:09:49,940
Speaker:
That equity of health outcomes.
300
00:09:49,940 --> 00:09:51,059
Speaker:
Improving it for everyone.
301
00:09:51,059 --> 00:09:52,340
Speaker:
This is what needs to be done.
302
00:09:52,340 --> 00:09:54,179
Speaker:
Are you going to stand in the
way or not?
303
00:09:54,179 --> 00:09:55,340
Speaker:
Yeah, absolutely.
304
00:09:55,340 --> 00:09:58,779
Speaker:
Um, I agree, infrastructure is
important.
305
00:09:58,779 --> 00:10:00,340
Speaker:
How people are doing their
surveillance.
306
00:10:00,340 --> 00:10:02,419
Speaker:
Surveillance definitions may
vary.
307
00:10:02,419 --> 00:10:07,320
Speaker:
Um, and so when you start to
merge data together, you have to
308
00:10:07,320 --> 00:10:10,379
Speaker:
kind of accept that there's
going to be slight differences
309
00:10:10,379 --> 00:10:13,539
Speaker:
in how, you know, certain
surveillance studies were done.
310
00:10:13,539 --> 00:10:14,620
Speaker:
Obviously, it would be great if
311
00:10:14,620 --> 00:10:16,340
Speaker:
we could get together beforehand
312
00:10:16,340 --> 00:10:18,580
Speaker:
and come to a common definition
313
00:10:18,580 --> 00:10:20,379
Speaker:
and a common protocol so
314
00:10:20,379 --> 00:10:21,620
Speaker:
that the data is clean on the
315
00:10:21,620 --> 00:10:22,220
Speaker:
other side.
316
00:10:22,220 --> 00:10:23,899
Speaker:
But that's not where we are
today.
317
00:10:23,899 --> 00:10:24,220
Speaker:
Right.
318
00:10:24,220 --> 00:10:25,919
Speaker:
So except where we are today
319
00:10:25,919 --> 00:10:27,299
Speaker:
and, you know, just make sure
320
00:10:27,299 --> 00:10:28,100
Speaker:
that you understand the
321
00:10:28,100 --> 00:10:29,240
Speaker:
limitations when you start to
322
00:10:29,240 --> 00:10:29,460
Speaker:
merge.
323
00:10:29,460 --> 00:10:32,059
Speaker:
But having that infrastructure I
324
00:10:32,059 --> 00:10:33,299
Speaker:
would say, is the next pillar
325
00:10:33,299 --> 00:10:34,860
Speaker:
that you build on top of
326
00:10:34,860 --> 00:10:36,580
Speaker:
actually doing the surveillance
327
00:10:36,580 --> 00:10:38,340
Speaker:
itself, getting the data, having
328
00:10:38,340 --> 00:10:39,950
Speaker:
the infrastructure to merge
329
00:10:39,950 --> 00:10:41,710
Speaker:
data, analyze data is critically
330
00:10:41,710 --> 00:10:42,669
Speaker:
important.
331
00:10:42,669 --> 00:10:44,149
Speaker:
And I'm so glad, Andrew, you
332
00:10:44,149 --> 00:10:46,149
Speaker:
brought up ego because I think
333
00:10:46,149 --> 00:10:48,669
Speaker:
that is such a driver in a lot
334
00:10:48,669 --> 00:10:51,429
Speaker:
of individual but also
335
00:10:51,429 --> 00:10:53,850
Speaker:
organizational and political
336
00:10:53,850 --> 00:10:55,870
Speaker:
issues or challenges that we see
337
00:10:55,870 --> 00:10:57,110
Speaker:
when we try to bring two people
338
00:10:57,110 --> 00:10:57,669
Speaker:
together.
339
00:10:57,669 --> 00:10:58,070
Speaker:
Right?
340
00:10:58,070 --> 00:11:00,190
Speaker:
It's like you're in you're in
human health.
341
00:11:00,190 --> 00:11:01,870
Speaker:
What do you know about animal?
342
00:11:01,870 --> 00:11:02,149
Speaker:
Right.
343
00:11:02,149 --> 00:11:03,629
Speaker:
What do you know about that?
344
00:11:03,629 --> 00:11:07,350
Speaker:
And making sure that we see that
common ground and that we align
345
00:11:07,350 --> 00:11:10,990
Speaker:
on that common ground and say,
okay, yes. Put the egos aside,
346
00:11:10,990 --> 00:11:13,429
Speaker:
check them at the door, check
the titles at the door.
347
00:11:13,429 --> 00:11:13,870
Speaker:
Right.
348
00:11:13,870 --> 00:11:18,629
Speaker:
We're all here to solve a common
problem that we all have.
349
00:11:18,629 --> 00:11:19,990
Speaker:
And so I'm so glad you brought
350
00:11:19,990 --> 00:11:21,129
Speaker:
that up because I think that is
351
00:11:21,129 --> 00:11:23,289
Speaker:
like truly kind of fundamental
352
00:11:23,289 --> 00:11:24,570
Speaker:
because ego drives
353
00:11:24,570 --> 00:11:25,710
Speaker:
territorialism.
354
00:11:25,710 --> 00:11:25,990
Speaker:
Right.
355
00:11:25,990 --> 00:11:27,110
Speaker:
Like this is my data.
356
00:11:27,110 --> 00:11:29,070
Speaker:
Like I don't want to share my
data.
357
00:11:29,070 --> 00:11:32,070
Speaker:
And that's going to that's going
to undermine every everything
358
00:11:32,070 --> 00:11:32,830
Speaker:
that we're doing.
359
00:11:32,830 --> 00:11:35,190
Speaker:
If we're not able to share data
360
00:11:35,190 --> 00:11:38,210
Speaker:
and understand data privacy and
361
00:11:38,210 --> 00:11:38,690
Speaker:
understanding.
362
00:11:38,690 --> 00:11:40,929
Speaker:
We have the boundaries of how we
use that data.
363
00:11:40,929 --> 00:11:42,049
Speaker:
When we share the data, how the
364
00:11:42,049 --> 00:11:43,330
Speaker:
data is going to be used or not
365
00:11:43,330 --> 00:11:44,090
Speaker:
used.
366
00:11:44,090 --> 00:11:47,009
Speaker:
When you inform, you know, the
owner, quote unquote, I have air
367
00:11:47,009 --> 00:11:50,009
Speaker:
quotes of that data of how
you're going to use it.
368
00:11:50,009 --> 00:11:51,289
Speaker:
I think all of that also needs
369
00:11:51,289 --> 00:11:52,649
Speaker:
to kind of be wrapped in into
370
00:11:52,649 --> 00:11:52,970
Speaker:
the how.
371
00:11:52,970 --> 00:11:55,929
Speaker:
I think sometimes we focus so
much on, like the more science
372
00:11:55,929 --> 00:11:59,210
Speaker:
of like, what's the protocol,
what's the data analysis, how do
373
00:11:59,210 --> 00:12:00,529
Speaker:
we move forward.
374
00:12:00,529 --> 00:12:02,090
Speaker:
But I think also addressing some
375
00:12:02,090 --> 00:12:04,289
Speaker:
of the social aspects of of
376
00:12:04,289 --> 00:12:05,730
Speaker:
bringing a multidisciplinary
377
00:12:05,730 --> 00:12:07,169
Speaker:
team together and making sure we
378
00:12:07,169 --> 00:12:08,850
Speaker:
work and row in the same
379
00:12:08,850 --> 00:12:10,529
Speaker:
direction, and that there we're
380
00:12:10,529 --> 00:12:12,970
Speaker:
all aligned to what we're doing,
381
00:12:12,970 --> 00:12:14,129
Speaker:
I think is also critically
382
00:12:14,129 --> 00:12:16,250
Speaker:
important in making this boat go
383
00:12:16,250 --> 00:12:17,250
Speaker:
forward.
384
00:12:17,250 --> 00:12:19,009
Speaker:
It's such an important point
there, isn't it?
385
00:12:19,009 --> 00:12:21,450
Speaker:
It's that idea of like, yeah,
checking the egos at the door.
386
00:12:21,450 --> 00:12:23,570
Speaker:
Everybody's going in the same
direction.
387
00:12:23,570 --> 00:12:26,129
Speaker:
But but we all need to help each
other get in that direction.
388
00:12:26,129 --> 00:12:28,529
Speaker:
And working together is is
synergistic.
389
00:12:28,529 --> 00:12:30,210
Speaker:
It's not taking away from
anybody.
390
00:12:30,210 --> 00:12:33,250
Speaker:
It's not trying to replace
anybody's individual efforts.
391
00:12:33,250 --> 00:12:36,389
Speaker:
Um, Andrew, within your own
field, what key surveillance
392
00:12:36,389 --> 00:12:39,690
Speaker:
strategies have you found to be
the most effective, I suppose,
393
00:12:39,690 --> 00:12:42,950
Speaker:
for tracking infections to give
you that bigger picture.
394
00:12:42,950 --> 00:12:47,190
Speaker:
Well, I suppose our lab being a
primary surveillance lab working
395
00:12:47,190 --> 00:12:51,230
Speaker:
in the field of environmental
epidemiology to cover
396
00:12:51,230 --> 00:12:54,750
Speaker:
everything, as we discussed, you
know, all types of water,
397
00:12:54,750 --> 00:12:57,429
Speaker:
sediments, wastewaters, all that
sort of stuff.
398
00:12:57,429 --> 00:13:03,429
Speaker:
For us, it's that primary lab
based techniques to generate
399
00:13:03,429 --> 00:13:08,590
Speaker:
that immediate data, all those
molecular biology methods that
400
00:13:08,590 --> 00:13:15,070
Speaker:
we use day in, day out PCR,
qPCR, digital PCR, followed by
401
00:13:15,070 --> 00:13:18,389
Speaker:
sequencing or next generation
sequencing, which I joke with a
402
00:13:18,389 --> 00:13:20,950
Speaker:
Illumina rep the other day when
they were sticking their head in
403
00:13:20,950 --> 00:13:22,029
Speaker:
to have a coffee.
404
00:13:22,029 --> 00:13:24,629
Speaker:
Um, when are we going to stop
calling it next gen sequencing?
405
00:13:24,629 --> 00:13:28,110
Speaker:
We've been calling it that now
for longer than I've been doing
406
00:13:28,110 --> 00:13:29,309
Speaker:
it, which you know.
407
00:13:29,309 --> 00:13:34,110
Speaker:
So the sequencing is moving
apace and it's a very strong
408
00:13:34,110 --> 00:13:36,129
Speaker:
tool and we use that regularly.
409
00:13:36,129 --> 00:13:37,889
Speaker:
And so it's all those those
410
00:13:37,889 --> 00:13:39,889
Speaker:
molecular based techniques that
411
00:13:39,889 --> 00:13:41,809
Speaker:
we use here in the lab are what
412
00:13:41,809 --> 00:13:44,090
Speaker:
um, that would be key
413
00:13:44,090 --> 00:13:45,789
Speaker:
surveillance strategies for us
414
00:13:45,789 --> 00:13:47,210
Speaker:
to immediately give that real
415
00:13:47,210 --> 00:13:48,649
Speaker:
time information and then follow
416
00:13:48,649 --> 00:13:50,450
Speaker:
it up by that slightly slower
417
00:13:50,450 --> 00:13:51,129
Speaker:
information.
418
00:13:51,129 --> 00:13:53,809
Speaker:
As we discussed before, if we're
looking at bacteria, we're
419
00:13:53,809 --> 00:13:56,690
Speaker:
looking at fungi or whatever,
culturing those and learning
420
00:13:56,690 --> 00:13:57,610
Speaker:
more information about.
421
00:13:57,610 --> 00:14:02,129
Speaker:
Because remember, just genomic
data alone won't necessarily
422
00:14:02,129 --> 00:14:03,769
Speaker:
fill in the whole picture.
423
00:14:03,769 --> 00:14:05,610
Speaker:
You need the other half of the
house.
424
00:14:05,610 --> 00:14:06,850
Speaker:
And that gets right back to the
425
00:14:06,850 --> 00:14:08,009
Speaker:
conversation that we were just
426
00:14:08,009 --> 00:14:09,129
Speaker:
having about.
427
00:14:09,129 --> 00:14:12,929
Speaker:
And as I liked Stephanie's point
about data being key, you need
428
00:14:12,929 --> 00:14:16,570
Speaker:
to try to get as much of that
data as you can.
429
00:14:16,570 --> 00:14:18,009
Speaker:
But for us, getting back to the
430
00:14:18,009 --> 00:14:19,090
Speaker:
question that you actually
431
00:14:19,090 --> 00:14:20,669
Speaker:
asked, key surveillance
432
00:14:20,669 --> 00:14:22,889
Speaker:
strategies that we would employ
433
00:14:22,889 --> 00:14:24,730
Speaker:
in the lab day in, day out are
434
00:14:24,730 --> 00:14:27,269
Speaker:
all those PCR based approaches,
435
00:14:27,269 --> 00:14:29,250
Speaker:
those those sequencing based
436
00:14:29,250 --> 00:14:30,090
Speaker:
approaches.
437
00:14:30,090 --> 00:14:30,649
Speaker:
Yeah.
438
00:14:30,649 --> 00:14:32,299
Speaker:
Um, I think whole genome
439
00:14:32,299 --> 00:14:34,779
Speaker:
sequencing has become kind of a
440
00:14:34,779 --> 00:14:35,820
Speaker:
I would say at this point a
441
00:14:35,820 --> 00:14:37,080
Speaker:
table stakes when it comes to
442
00:14:37,080 --> 00:14:37,860
Speaker:
surveillance.
443
00:14:37,860 --> 00:14:41,059
Speaker:
Not so much maybe in the US
clinical labs, but the public
444
00:14:41,059 --> 00:14:44,179
Speaker:
health labs have fully embraced
next generation sequencing.
445
00:14:44,179 --> 00:14:47,740
Speaker:
But I will say Andrew, Sanger
sequencing still still exists
446
00:14:47,740 --> 00:14:48,340
Speaker:
and is used.
447
00:14:48,340 --> 00:14:48,580
Speaker:
Right.
448
00:14:48,580 --> 00:14:51,860
Speaker:
So we still need to say NGS for
a while.
449
00:14:51,860 --> 00:14:54,179
Speaker:
But yeah, so that is a big
component.
450
00:14:54,179 --> 00:14:57,740
Speaker:
And I totally agree that
there's, there's other pieces of
451
00:14:57,740 --> 00:15:01,019
Speaker:
information that are just as
important as the genomic data.
452
00:15:01,019 --> 00:15:03,100
Speaker:
So also the diversity of the
453
00:15:03,100 --> 00:15:05,799
Speaker:
data to actually show the full
454
00:15:05,799 --> 00:15:07,620
Speaker:
spectrum of color of the problem
455
00:15:07,620 --> 00:15:08,860
Speaker:
as well, I think is also
456
00:15:08,860 --> 00:15:10,500
Speaker:
important, you know, from from
457
00:15:10,500 --> 00:15:12,620
Speaker:
our side at Beckman Coulter, you
458
00:15:12,620 --> 00:15:15,120
Speaker:
know, we we use phenotypic
459
00:15:15,120 --> 00:15:17,779
Speaker:
testing to kind of also inform,
460
00:15:17,779 --> 00:15:19,299
Speaker:
inform surveillance.
461
00:15:19,299 --> 00:15:21,899
Speaker:
So as you know, many
laboratories will generate
462
00:15:21,899 --> 00:15:26,100
Speaker:
antibiograms based off
diagnostic cultures, um, using
463
00:15:26,100 --> 00:15:27,100
Speaker:
the phenotypic data.
464
00:15:27,100 --> 00:15:28,779
Speaker:
So you would um, at a yearly
465
00:15:28,779 --> 00:15:30,679
Speaker:
cadence or even sooner than a
466
00:15:30,679 --> 00:15:31,240
Speaker:
year,
467
00:15:31,240 --> 00:15:32,980
Speaker:
laboratories will put out an
468
00:15:32,980 --> 00:15:34,159
Speaker:
antibiogram of percent
469
00:15:34,159 --> 00:15:35,639
Speaker:
susceptible to the routinely
470
00:15:35,639 --> 00:15:37,679
Speaker:
reported drugs for the common
471
00:15:37,679 --> 00:15:39,120
Speaker:
organisms that they see in their
472
00:15:39,120 --> 00:15:39,720
Speaker:
institution.
473
00:15:39,720 --> 00:15:43,080
Speaker:
And so that that, to me has
twofold purposes.
474
00:15:43,080 --> 00:15:45,159
Speaker:
One is helping to inform empiric
475
00:15:45,159 --> 00:15:46,759
Speaker:
therapy decisions at the
476
00:15:46,759 --> 00:15:48,639
Speaker:
individual patient level, which
477
00:15:48,639 --> 00:15:50,600
Speaker:
we know obviously ripples out
478
00:15:50,600 --> 00:15:52,039
Speaker:
into the community and into the
479
00:15:52,039 --> 00:15:54,159
Speaker:
one health sector, but also can
480
00:15:54,159 --> 00:15:55,799
Speaker:
inform infection prevention
481
00:15:55,799 --> 00:15:57,519
Speaker:
strategies and other things, and
482
00:15:57,519 --> 00:15:59,039
Speaker:
also uses to track general
483
00:15:59,039 --> 00:16:01,320
Speaker:
trends in resistance, regardless
484
00:16:01,320 --> 00:16:02,759
Speaker:
of the mechanism, but general
485
00:16:02,759 --> 00:16:03,159
Speaker:
trends.
486
00:16:03,159 --> 00:16:04,220
Speaker:
And that also allows you
487
00:16:04,220 --> 00:16:06,019
Speaker:
potentially to pick up novel
488
00:16:06,019 --> 00:16:08,120
Speaker:
resistant mechanisms that we
489
00:16:08,120 --> 00:16:09,519
Speaker:
don't know about yet that maybe
490
00:16:09,519 --> 00:16:10,879
Speaker:
you wouldn't recognize with a
491
00:16:10,879 --> 00:16:12,480
Speaker:
genomic approach.
492
00:16:12,480 --> 00:16:15,039
Speaker:
So I think both are really
important to make sure that
493
00:16:15,039 --> 00:16:17,519
Speaker:
we're understanding the
mechanisms and what's going on,
494
00:16:17,519 --> 00:16:20,480
Speaker:
how those mechanisms
specifically are spreading like
495
00:16:20,480 --> 00:16:24,240
Speaker:
plasmids, but then also making
sure that we're doing that
496
00:16:24,240 --> 00:16:27,970
Speaker:
phenotypic testing to stay
appraised of new things that
497
00:16:27,970 --> 00:16:29,340
Speaker:
might be happening.
498
00:16:29,340 --> 00:16:30,679
Speaker:
Yeah and that phenotypic
499
00:16:30,679 --> 00:16:32,720
Speaker:
testing is very important to to
500
00:16:32,720 --> 00:16:34,379
Speaker:
bridge that gap between what we
501
00:16:34,379 --> 00:16:36,179
Speaker:
see as potential highways of
502
00:16:36,179 --> 00:16:37,100
Speaker:
AMR.
503
00:16:37,100 --> 00:16:41,840
Speaker:
So it is you know, you have your
classic ideal bug that is
504
00:16:41,840 --> 00:16:45,299
Speaker:
phenotypically and genotypically
resistant to something.
505
00:16:45,299 --> 00:16:46,500
Speaker:
But then what?
506
00:16:46,500 --> 00:16:47,580
Speaker:
You know, if you discover
507
00:16:47,580 --> 00:16:49,620
Speaker:
something that genotypically
508
00:16:49,620 --> 00:16:52,139
Speaker:
appears to carry those resistance
509
00:16:52,139 --> 00:16:53,620
Speaker:
mechanisms, but then it
510
00:16:53,620 --> 00:16:54,899
Speaker:
immediately dies when it's faced
511
00:16:54,899 --> 00:16:56,659
Speaker:
with even the lowest dose of
512
00:16:56,659 --> 00:16:57,019
Speaker:
something.
513
00:16:57,019 --> 00:16:59,799
Speaker:
So, you know, is that is that
one of those classic, you know,
514
00:16:59,799 --> 00:17:04,119
Speaker:
secondary reservoirs that under
the right conditions that could
515
00:17:04,119 --> 00:17:07,920
Speaker:
either flip a switch and become
resistant or it could, you know,
516
00:17:07,920 --> 00:17:11,660
Speaker:
just keep those resistance genes
circulating until something else
517
00:17:11,660 --> 00:17:13,500
Speaker:
comes along and hoovers them up.
518
00:17:13,500 --> 00:17:14,579
Speaker:
So it's that's why it's
519
00:17:14,579 --> 00:17:16,480
Speaker:
incredibly important to, to to
520
00:17:16,480 --> 00:17:18,400
Speaker:
mix up that phenotypic and
521
00:17:18,400 --> 00:17:20,420
Speaker:
genotypic screening.
522
00:17:20,420 --> 00:17:21,640
Speaker:
And Stephanie mentioned there
523
00:17:21,640 --> 00:17:23,019
Speaker:
like real world implications of
524
00:17:23,019 --> 00:17:24,700
Speaker:
some of the surveillance at her
525
00:17:24,700 --> 00:17:25,099
Speaker:
end.
526
00:17:25,099 --> 00:17:28,359
Speaker:
Have you had real world outcomes
that have been influenced by
527
00:17:28,359 --> 00:17:29,720
Speaker:
your surveillance strategies?
528
00:17:29,720 --> 00:17:30,319
Speaker:
Andrew.
529
00:17:30,319 --> 00:17:30,759
Speaker:
Oh, yeah.
530
00:17:30,759 --> 00:17:35,299
Speaker:
I mean, um, the wastewater
surveillance effort, when we
531
00:17:35,299 --> 00:17:38,119
Speaker:
when the program was running
here in Northern Ireland, um,
532
00:17:38,119 --> 00:17:43,240
Speaker:
whenever the UK started to wind
down individual testing, we
533
00:17:43,240 --> 00:17:47,039
Speaker:
became the, the program that
picked up that slack.
534
00:17:47,039 --> 00:17:48,279
Speaker:
And so while there was still
535
00:17:48,279 --> 00:17:50,660
Speaker:
surveillance of strains ongoing,
536
00:17:50,660 --> 00:17:52,059
Speaker:
if somebody was in the hospital,
537
00:17:52,059 --> 00:17:53,700
Speaker:
you know, when they got tested
538
00:17:53,700 --> 00:17:55,460
Speaker:
and that was then sent through,
539
00:17:55,460 --> 00:17:56,640
Speaker:
you know, we were there giving
540
00:17:56,640 --> 00:17:58,200
Speaker:
that that weekly, that daily
541
00:17:58,200 --> 00:17:59,720
Speaker:
feedback as to what we're seeing
542
00:17:59,720 --> 00:18:01,200
Speaker:
circulating at that point in the
543
00:18:01,200 --> 00:18:01,599
Speaker:
community.
544
00:18:01,599 --> 00:18:05,599
Speaker:
And so from then, there was
quite a few specific examples
545
00:18:05,599 --> 00:18:08,640
Speaker:
where we were able to, to
quickly help out.
546
00:18:08,640 --> 00:18:10,819
Speaker:
So there were and able to
547
00:18:10,819 --> 00:18:12,640
Speaker:
quickly give, you know, viral
548
00:18:12,640 --> 00:18:14,400
Speaker:
load by qPCR straight in with
549
00:18:14,400 --> 00:18:16,480
Speaker:
digital PCR to check for, for
550
00:18:16,480 --> 00:18:18,480
Speaker:
variants in a near real time way
551
00:18:18,480 --> 00:18:20,279
Speaker:
before the the sequencing data
552
00:18:20,279 --> 00:18:20,960
Speaker:
followed up.
553
00:18:20,960 --> 00:18:22,039
Speaker:
And yeah, okay.
554
00:18:22,039 --> 00:18:25,009
Speaker:
We are seeing that variant now
new variant or whatever.
555
00:18:25,009 --> 00:18:26,549
Speaker:
But even even, you know,
556
00:18:26,549 --> 00:18:28,369
Speaker:
rewinding right back to whenever
557
00:18:28,369 --> 00:18:30,750
Speaker:
we had those various phases, um,
558
00:18:30,750 --> 00:18:32,369
Speaker:
in the early dying days of the
559
00:18:32,369 --> 00:18:33,769
Speaker:
Alpha variant, whenever Delta
560
00:18:33,769 --> 00:18:34,930
Speaker:
was coming on the horizon, we
561
00:18:34,930 --> 00:18:36,650
Speaker:
were asked to just quickly jump
562
00:18:36,650 --> 00:18:38,910
Speaker:
on to a few hotspots within
563
00:18:38,910 --> 00:18:40,289
Speaker:
within Northern Ireland that
564
00:18:40,289 --> 00:18:42,170
Speaker:
were thought that there might be
565
00:18:42,170 --> 00:18:43,609
Speaker:
the rise of Delta there, do some
566
00:18:43,609 --> 00:18:44,930
Speaker:
near source testing, and we were
567
00:18:44,930 --> 00:18:46,849
Speaker:
able to immediately provide real
568
00:18:46,849 --> 00:18:47,890
Speaker:
time information.
569
00:18:47,890 --> 00:18:50,849
Speaker:
You know, um, those locations
were said, oh, nobody's positive
570
00:18:50,849 --> 00:18:51,329
Speaker:
in our place.
571
00:18:51,329 --> 00:18:55,009
Speaker:
And we want what, you know, look
at all this.
572
00:18:55,009 --> 00:18:58,349
Speaker:
Look at the glaring red across
the board that's coming out of
573
00:18:58,349 --> 00:18:59,529
Speaker:
the wastewater and that.
574
00:18:59,529 --> 00:19:02,369
Speaker:
And so we were, you know, we
were able to help out there.
575
00:19:02,369 --> 00:19:07,309
Speaker:
And then the most recent study
that we've done, uh, doing near
576
00:19:07,309 --> 00:19:11,269
Speaker:
source wastewater, air and air
monitoring within a care home,
577
00:19:11,269 --> 00:19:13,809
Speaker:
you know, we were able to
provide rapid, real time
578
00:19:13,809 --> 00:19:18,170
Speaker:
information on the rise of, uh,
you know, some SARS infections
579
00:19:18,170 --> 00:19:19,890
Speaker:
or norovirus infections.
580
00:19:19,890 --> 00:19:21,980
Speaker:
Um, and then they were able to
581
00:19:21,980 --> 00:19:24,910
Speaker:
quickly sort of clamp down and
582
00:19:24,910 --> 00:19:27,049
Speaker:
reduce extra cleaning within the
583
00:19:27,049 --> 00:19:27,910
Speaker:
care home
584
00:19:27,910 --> 00:19:32,430
Speaker:
Um, and then that that helped
stop the spread of that.
585
00:19:32,430 --> 00:19:35,430
Speaker:
And certainly the spread could
have been worse than it was.
586
00:19:35,430 --> 00:19:38,529
Speaker:
So both large and small at the
587
00:19:38,529 --> 00:19:40,509
Speaker:
wastewater municipal plant sort
588
00:19:40,509 --> 00:19:42,190
Speaker:
of scale at the towns and cities
589
00:19:42,190 --> 00:19:43,990
Speaker:
scale, and then right down to
590
00:19:43,990 --> 00:19:45,990
Speaker:
that near source wastewater
591
00:19:45,990 --> 00:19:46,630
Speaker:
surveillance.
592
00:19:46,630 --> 00:19:49,210
Speaker:
We have proven examples of where
593
00:19:49,210 --> 00:19:50,470
Speaker:
the information that we have
594
00:19:50,470 --> 00:19:52,390
Speaker:
generated has, has been
595
00:19:52,390 --> 00:19:54,589
Speaker:
immediately put into play to
596
00:19:54,589 --> 00:19:56,109
Speaker:
stop spread.
597
00:19:56,109 --> 00:19:56,950
Speaker:
And that's what it is.
598
00:19:56,950 --> 00:19:59,390
Speaker:
It's that I love that applied
science side of thing.
599
00:19:59,390 --> 00:20:01,990
Speaker:
You're doing something straight
away that can have a real world
600
00:20:01,990 --> 00:20:05,950
Speaker:
impact pretty quickly if the
right procedure is followed.
601
00:20:05,950 --> 00:20:07,049
Speaker:
That's the thing I really like
602
00:20:07,049 --> 00:20:08,349
Speaker:
about like environmental and
603
00:20:08,349 --> 00:20:09,910
Speaker:
wastewater sampling is that
604
00:20:09,910 --> 00:20:11,349
Speaker:
population level information
605
00:20:11,349 --> 00:20:13,349
Speaker:
that you're getting that you
606
00:20:13,349 --> 00:20:15,450
Speaker:
know, from one or two, you know,
607
00:20:15,450 --> 00:20:16,710
Speaker:
multiple samples, but certainly
608
00:20:16,710 --> 00:20:17,990
Speaker:
not the same as having to swab
609
00:20:17,990 --> 00:20:19,910
Speaker:
every individual's nose or, or
610
00:20:19,910 --> 00:20:21,009
Speaker:
throat to figure out what's
611
00:20:21,009 --> 00:20:21,569
Speaker:
going on.
612
00:20:21,569 --> 00:20:21,849
Speaker:
Yeah.
613
00:20:21,849 --> 00:20:25,509
Speaker:
So, Julie Ann, if I could add in,
um, you know, I think wastewater
614
00:20:25,509 --> 00:20:28,809
Speaker:
is really important because it's
it's shedding light, right?
615
00:20:28,809 --> 00:20:32,410
Speaker:
Because I think previously when
we thought surveillance, it was.
616
00:20:32,410 --> 00:20:33,730
Speaker:
And even to this day, it's
617
00:20:33,730 --> 00:20:35,009
Speaker:
people coming into the hospital,
618
00:20:35,009 --> 00:20:36,849
Speaker:
they're being admitted where we
619
00:20:36,849 --> 00:20:38,529
Speaker:
want to, you know, have robust
620
00:20:38,529 --> 00:20:40,069
Speaker:
infection control practices to
621
00:20:40,069 --> 00:20:41,970
Speaker:
prevent the spread within the
622
00:20:41,970 --> 00:20:44,410
Speaker:
hospital with at risk patients
623
00:20:44,410 --> 00:20:45,329
Speaker:
in there.
624
00:20:45,329 --> 00:20:50,849
Speaker:
But how can we effectively
design policies and strategies
625
00:20:50,849 --> 00:20:56,490
Speaker:
and solutions when we're missing
the entire rest of the community
626
00:20:56,490 --> 00:21:00,170
Speaker:
that lives and interacts and
engages with each other outside
627
00:21:00,170 --> 00:21:01,569
Speaker:
of the hospital?
628
00:21:01,569 --> 00:21:05,289
Speaker:
And so I think that's been a
blind spot for a very long time.
629
00:21:05,289 --> 00:21:06,490
Speaker:
And I think to some extent it
630
00:21:06,490 --> 00:21:07,750
Speaker:
still is a little bit of a blind
631
00:21:07,750 --> 00:21:09,650
Speaker:
spot, but we're working towards
632
00:21:09,650 --> 00:21:10,289
Speaker:
improving that.
633
00:21:10,289 --> 00:21:12,190
Speaker:
Wastewater is a great example,
634
00:21:12,190 --> 00:21:14,369
Speaker:
um, surveying ticks and
635
00:21:14,369 --> 00:21:16,670
Speaker:
mosquitoes for zoonotic
636
00:21:16,670 --> 00:21:17,529
Speaker:
diseases.
637
00:21:17,529 --> 00:21:19,769
Speaker:
And then also, you know,
638
00:21:19,769 --> 00:21:21,730
Speaker:
some effort to try to move
639
00:21:21,730 --> 00:21:23,029
Speaker:
surveillance out of just the
640
00:21:23,029 --> 00:21:25,069
Speaker:
hospital doors into the
641
00:21:25,069 --> 00:21:26,529
Speaker:
community so that we can really
642
00:21:26,529 --> 00:21:28,670
Speaker:
see what's going on in the
643
00:21:28,670 --> 00:21:29,349
Speaker:
community.
644
00:21:29,349 --> 00:21:32,930
Speaker:
How are how are people who are
colonized spreading these things
645
00:21:32,930 --> 00:21:33,750
Speaker:
amongst each other?
646
00:21:33,750 --> 00:21:35,470
Speaker:
And then it's only that one
647
00:21:35,470 --> 00:21:36,869
Speaker:
individual person that happens
648
00:21:36,869 --> 00:21:38,410
Speaker:
to get sick is the one that we
649
00:21:38,410 --> 00:21:39,349
Speaker:
currently survey at the
650
00:21:39,349 --> 00:21:39,990
Speaker:
hospital.
651
00:21:39,990 --> 00:21:42,029
Speaker:
So in thinking about really
652
00:21:42,029 --> 00:21:43,190
Speaker:
making sure we understand the
653
00:21:43,190 --> 00:21:44,809
Speaker:
problem and we don't have blind
654
00:21:44,809 --> 00:21:47,150
Speaker:
spots moving surveillance
655
00:21:47,150 --> 00:21:48,869
Speaker:
outside of the hospital doors
656
00:21:48,869 --> 00:21:50,509
Speaker:
into the environment, the
657
00:21:50,509 --> 00:21:52,430
Speaker:
community, et cetera, I think is
658
00:21:52,430 --> 00:21:55,670
Speaker:
going to be really key for us to
659
00:21:55,670 --> 00:21:57,430
Speaker:
figuring out where we can
660
00:21:57,430 --> 00:21:58,990
Speaker:
actually place strategic
661
00:21:58,990 --> 00:22:01,109
Speaker:
solutions to stop some of this
662
00:22:01,109 --> 00:22:02,269
Speaker:
spread of antimicrobial
663
00:22:02,269 --> 00:22:03,549
Speaker:
resistance.
664
00:22:03,549 --> 00:22:04,630
Speaker:
Yes, it is, isn't it?
665
00:22:04,630 --> 00:22:06,269
Speaker:
Because that's where the rest of
the world is living.
666
00:22:06,269 --> 00:22:07,349
Speaker:
It's, you know, we need to find
667
00:22:07,349 --> 00:22:08,509
Speaker:
out what's happening at a, at a
668
00:22:08,509 --> 00:22:09,970
Speaker:
population level sort of
669
00:22:09,970 --> 00:22:10,789
Speaker:
globally.
670
00:22:10,789 --> 00:22:12,470
Speaker:
And I guess that brings me on to
671
00:22:12,470 --> 00:22:14,089
Speaker:
my next point where, you know,
672
00:22:14,089 --> 00:22:15,029
Speaker:
we've just talked about the
673
00:22:15,029 --> 00:22:18,279
Speaker:
importance of surveillance in
674
00:22:18,279 --> 00:22:20,079
Speaker:
general, but also in tracking
675
00:22:20,079 --> 00:22:21,359
Speaker:
and spotting antimicrobial
676
00:22:21,359 --> 00:22:21,960
Speaker:
resistance
677
00:22:21,960 --> 00:22:22,400
Speaker:
AMR.
678
00:22:22,400 --> 00:22:24,279
Speaker:
So how does the work of Beckman
679
00:22:24,279 --> 00:22:26,680
Speaker:
Coulter contribute to tracking
680
00:22:26,680 --> 00:22:27,519
Speaker:
of AMR?
681
00:22:27,519 --> 00:22:28,480
Speaker:
Yeah, absolutely.
682
00:22:28,480 --> 00:22:31,160
Speaker:
So, you know, as mentioned
earlier, we we mostly live in
683
00:22:31,160 --> 00:22:34,480
Speaker:
the clinical space where we do
phenotypic susceptibility
684
00:22:34,480 --> 00:22:37,720
Speaker:
testing for diagnosis, you know,
for patient treatment.
685
00:22:37,720 --> 00:22:39,619
Speaker:
But you can aggregate that data,
686
00:22:39,619 --> 00:22:40,440
Speaker:
you know, within your
687
00:22:40,440 --> 00:22:43,160
Speaker:
institution, um, at the floor
688
00:22:43,160 --> 00:22:44,279
Speaker:
level, at the patient level,
689
00:22:44,279 --> 00:22:45,400
Speaker:
depending on how you want to do
690
00:22:45,400 --> 00:22:46,839
Speaker:
your antibiogram.
691
00:22:46,839 --> 00:22:48,359
Speaker:
Um, and you can track trends.
692
00:22:48,359 --> 00:22:49,920
Speaker:
But if you're an institution
693
00:22:49,920 --> 00:22:51,480
Speaker:
within a system, you could
694
00:22:51,480 --> 00:22:53,160
Speaker:
imagine if you could aggregate
695
00:22:53,160 --> 00:22:54,619
Speaker:
that even higher, you could like
696
00:22:54,619 --> 00:22:56,240
Speaker:
meta it up, right, to be at the
697
00:22:56,240 --> 00:22:56,960
Speaker:
system level.
698
00:22:56,960 --> 00:22:58,240
Speaker:
And then if we get to the point
699
00:22:58,240 --> 00:23:01,319
Speaker:
where we feel safe with sharing
700
00:23:01,319 --> 00:23:02,759
Speaker:
our data, we don't feel that
701
00:23:02,759 --> 00:23:03,859
Speaker:
we're going to get scooped,
702
00:23:03,859 --> 00:23:04,119
Speaker:
right.
703
00:23:04,119 --> 00:23:06,400
Speaker:
We put the ego at the door that
704
00:23:06,400 --> 00:23:07,579
Speaker:
that data can then be
705
00:23:07,579 --> 00:23:08,720
Speaker:
aggregated, aggregated,
706
00:23:08,720 --> 00:23:09,480
Speaker:
aggregated.
707
00:23:09,480 --> 00:23:13,759
Speaker:
And so that's one, one piece of
that.
708
00:23:13,759 --> 00:23:18,839
Speaker:
And as we mentioned briefly on
the previous podcast, you know,
709
00:23:18,839 --> 00:23:22,359
Speaker:
we are interested in looking at
the veterinary space as well,
710
00:23:22,359 --> 00:23:27,079
Speaker:
particularly companion animals,
again, to try to embody this one
711
00:23:27,079 --> 00:23:30,559
Speaker:
health approach so that
surveillance can be done at the
712
00:23:30,559 --> 00:23:34,619
Speaker:
veterinary side of the
multifaceted AMR web.
713
00:23:34,619 --> 00:23:36,160
Speaker:
And so we can start to pull in
714
00:23:36,160 --> 00:23:38,119
Speaker:
that data as well and aggregate
715
00:23:38,119 --> 00:23:40,059
Speaker:
from a different sector, which
716
00:23:40,059 --> 00:23:41,460
Speaker:
we talked about earlier, and how
717
00:23:41,460 --> 00:23:42,700
Speaker:
important that is to not have
718
00:23:42,700 --> 00:23:43,819
Speaker:
blind spots.
719
00:23:43,819 --> 00:23:44,140
Speaker:
Yeah and
720
00:23:44,140 --> 00:23:46,660
Speaker:
Andrew, in terms of your
wastewater surveillance and
721
00:23:46,660 --> 00:23:49,960
Speaker:
environmental sampling in
Northern Ireland, and, you know,
722
00:23:49,960 --> 00:23:52,039
Speaker:
obviously there's other groups
across Europe doing this type of
723
00:23:52,039 --> 00:23:52,779
Speaker:
thing as well.
724
00:23:52,779 --> 00:23:54,200
Speaker:
How is it contributing to
725
00:23:54,200 --> 00:23:56,660
Speaker:
tracking of AMR? In a variety of
726
00:23:56,660 --> 00:23:56,980
Speaker:
ways.
727
00:23:56,980 --> 00:23:58,900
Speaker:
But generally looking at that
728
00:23:58,900 --> 00:24:00,579
Speaker:
very area that Stephanie has
729
00:24:00,579 --> 00:24:02,220
Speaker:
just touched upon outside of the
730
00:24:02,220 --> 00:24:05,420
Speaker:
clinic, gaining an idea of that
731
00:24:05,420 --> 00:24:07,579
Speaker:
data that exists that isn't
732
00:24:07,579 --> 00:24:09,500
Speaker:
captured under the current
733
00:24:09,500 --> 00:24:10,299
Speaker:
methods.
734
00:24:10,299 --> 00:24:12,250
Speaker:
And that's why we feel very
735
00:24:12,250 --> 00:24:14,640
Speaker:
strongly that tracking AMR
736
00:24:14,640 --> 00:24:15,920
Speaker:
through wastewater and
737
00:24:15,920 --> 00:24:17,359
Speaker:
environmental samples is key,
738
00:24:17,359 --> 00:24:19,079
Speaker:
and that's the next phase, you
739
00:24:19,079 --> 00:24:19,960
Speaker:
know, of wastewater
740
00:24:19,960 --> 00:24:20,880
Speaker:
surveillance.
741
00:24:20,880 --> 00:24:24,799
Speaker:
Environmental based epidemiology
is going, as I mentioned last
742
00:24:24,799 --> 00:24:27,480
Speaker:
month when us all together at
that meeting, you know, there
743
00:24:27,480 --> 00:24:29,920
Speaker:
was there was dedicated sessions
on AMR alone.
744
00:24:29,920 --> 00:24:33,119
Speaker:
You know, wastewater is being
looked at beyond checking for
745
00:24:33,119 --> 00:24:35,839
Speaker:
the next pandemic causing
pathogen or checking about the
746
00:24:35,839 --> 00:24:39,440
Speaker:
current state of things with
with seasonal pathogens that we
747
00:24:39,440 --> 00:24:42,160
Speaker:
have to learn to live with in
getting an idea on on what their
748
00:24:42,160 --> 00:24:45,240
Speaker:
levels currently are, and it's
now moving towards dedicated
749
00:24:45,240 --> 00:24:47,440
Speaker:
projects, looking at AMR.
750
00:24:47,440 --> 00:24:48,839
Speaker:
And that is incredibly
important.
751
00:24:48,839 --> 00:24:50,799
Speaker:
And next year, in fact, we even
752
00:24:50,799 --> 00:24:52,599
Speaker:
have got a project coming online
753
00:24:52,599 --> 00:24:53,480
Speaker:
where we're going to be looking
754
00:24:53,480 --> 00:24:54,640
Speaker:
at microplastics in the
755
00:24:54,640 --> 00:24:56,660
Speaker:
environment and how they may
756
00:24:56,660 --> 00:24:58,720
Speaker:
influence, you know, the rise of
757
00:24:58,720 --> 00:25:00,000
Speaker:
antimicrobial resistance within
758
00:25:00,000 --> 00:25:01,500
Speaker:
bacteria or even, you know,
759
00:25:01,500 --> 00:25:03,859
Speaker:
their pathogenicity in, in
760
00:25:03,859 --> 00:25:04,599
Speaker:
Total.
761
00:25:04,599 --> 00:25:06,079
Speaker:
So to say, you know, you think
762
00:25:06,079 --> 00:25:07,319
Speaker:
about microplastics in the
763
00:25:07,319 --> 00:25:07,759
Speaker:
environment.
764
00:25:07,759 --> 00:25:10,119
Speaker:
We're not just talking about
plastics that are just come off
765
00:25:10,119 --> 00:25:11,700
Speaker:
your milk bottle or whatever.
766
00:25:11,700 --> 00:25:12,859
Speaker:
There's going to be plastics in
767
00:25:12,859 --> 00:25:13,900
Speaker:
the environment that are
768
00:25:13,900 --> 00:25:16,259
Speaker:
impregnated with antimicrobials
769
00:25:16,259 --> 00:25:17,019
Speaker:
and chemicals.
770
00:25:17,019 --> 00:25:21,099
Speaker:
And how's that then driving
antimicrobial reservoirs.
771
00:25:21,099 --> 00:25:24,500
Speaker:
So that's the project that we're
excited to have come on board
772
00:25:24,500 --> 00:25:27,539
Speaker:
next year, which takes us again
in a slightly different
773
00:25:27,539 --> 00:25:29,019
Speaker:
direction looking at that.
774
00:25:29,019 --> 00:25:31,779
Speaker:
But, you know, the the data that
775
00:25:31,779 --> 00:25:33,920
Speaker:
we have generated so far around
776
00:25:33,920 --> 00:25:35,640
Speaker:
AMR and the environment as well,
777
00:25:35,640 --> 00:25:37,339
Speaker:
it doesn't make for easy reading
778
00:25:37,339 --> 00:25:39,099
Speaker:
because we talk there a bit
779
00:25:39,099 --> 00:25:40,640
Speaker:
about culturing and I don't
780
00:25:40,640 --> 00:25:41,480
Speaker:
know, Stephanie, if you'll
781
00:25:41,480 --> 00:25:41,700
Speaker:
agree.
782
00:25:41,700 --> 00:25:45,339
Speaker:
Let's face it, the anaerobes
always get the short straw.
783
00:25:45,339 --> 00:25:45,859
Speaker:
So they do.
784
00:25:45,859 --> 00:25:48,339
Speaker:
Nobody ever wants to look at
anaerobes or culture them
785
00:25:48,339 --> 00:25:50,660
Speaker:
because it's difficult to do so
and all that there.
786
00:25:50,660 --> 00:25:52,299
Speaker:
But they are..
787
00:25:52,299 --> 00:25:54,740
Speaker:
They are as important as the
aerobes as they are.
788
00:25:54,740 --> 00:25:57,539
Speaker:
And and the data that we're
generating, you know, just
789
00:25:57,539 --> 00:26:01,700
Speaker:
looking there at some of the
metagenome assembled genomes
790
00:26:01,700 --> 00:26:05,339
Speaker:
that we've been generating out
of the care home data, we're
791
00:26:05,339 --> 00:26:10,529
Speaker:
we're seeing anaerobes carrying
pretty hefty extended spectra
792
00:26:10,529 --> 00:26:13,109
Speaker:
spectrum, beta lactamases and
things like that.
793
00:26:13,109 --> 00:26:14,089
Speaker:
All the stuff that's on the
794
00:26:14,089 --> 00:26:16,769
Speaker:
WHO's list of priority genes to
795
00:26:16,769 --> 00:26:17,950
Speaker:
to monitor.
796
00:26:17,950 --> 00:26:19,289
Speaker:
And so obviously, we need to
797
00:26:19,289 --> 00:26:20,950
Speaker:
continue to just sift about data
798
00:26:20,950 --> 00:26:22,049
Speaker:
a bit more and make sure we're
799
00:26:22,049 --> 00:26:23,109
Speaker:
actually seeing what we're
800
00:26:23,109 --> 00:26:23,549
Speaker:
seeing.
801
00:26:23,549 --> 00:26:25,470
Speaker:
But that's that's quite scary.
802
00:26:25,470 --> 00:26:27,829
Speaker:
We're missing a whole area all
together.
803
00:26:27,829 --> 00:26:28,029
Speaker:
Yeah.
804
00:26:28,029 --> 00:26:30,630
Speaker:
So this is like a couple of
other blind spots.
805
00:26:30,630 --> 00:26:30,990
Speaker:
Right.
806
00:26:30,990 --> 00:26:32,710
Speaker:
So one is anaerobes, one hundred
807
00:26:32,710 --> 00:26:34,569
Speaker:
percent agree rarely is is
808
00:26:34,569 --> 00:26:35,950
Speaker:
anaerobic antimicrobial
809
00:26:35,950 --> 00:26:37,829
Speaker:
susceptibility testing performed
810
00:26:37,829 --> 00:26:39,109
Speaker:
when you send a diagnostic
811
00:26:39,109 --> 00:26:40,150
Speaker:
culture one because it's
812
00:26:40,150 --> 00:26:41,029
Speaker:
challenging right.
813
00:26:41,029 --> 00:26:43,890
Speaker:
But CLSI actually just redid
814
00:26:43,890 --> 00:26:45,609
Speaker:
their antibiogram for the
815
00:26:45,609 --> 00:26:47,509
Speaker:
anaerobes, which I think was
816
00:26:47,509 --> 00:26:48,349
Speaker:
quite old.
817
00:26:48,349 --> 00:26:50,869
Speaker:
Um, but we're seeing shifts,
right?
818
00:26:50,869 --> 00:26:53,069
Speaker:
We're seeing trends, um, in
819
00:26:53,069 --> 00:26:54,849
Speaker:
resistance where it's like, oh,
820
00:26:54,849 --> 00:26:56,269
Speaker:
we should probably pay attention
821
00:26:56,269 --> 00:26:56,950
Speaker:
to that.
822
00:26:56,950 --> 00:26:59,210
Speaker:
Um, because again, we're kind of
823
00:26:59,210 --> 00:27:00,509
Speaker:
blind because no one's doing the
824
00:27:00,509 --> 00:27:01,069
Speaker:
testing.
825
00:27:01,069 --> 00:27:04,569
Speaker:
So this is, I think, a wake up
call that okay, we have a blind
826
00:27:04,569 --> 00:27:08,170
Speaker:
spot here and we might need to
focus some efforts in
827
00:27:08,170 --> 00:27:11,450
Speaker:
understanding our anaerobic
friends a little bit better.
828
00:27:11,450 --> 00:27:13,009
Speaker:
And then to your point earlier
829
00:27:13,009 --> 00:27:15,630
Speaker:
about microplastics, I think
830
00:27:15,630 --> 00:27:19,369
Speaker:
another blind spot we have is
831
00:27:19,369 --> 00:27:20,690
Speaker:
understanding in the
832
00:27:20,690 --> 00:27:24,049
Speaker:
environment, um, what heavy
833
00:27:24,049 --> 00:27:25,910
Speaker:
metals might be present, what
834
00:27:25,910 --> 00:27:27,970
Speaker:
other things are there that are
835
00:27:27,970 --> 00:27:30,890
Speaker:
often carried on plasmids that
836
00:27:30,890 --> 00:27:33,049
Speaker:
carry antimicrobial resistance,
837
00:27:33,049 --> 00:27:36,650
Speaker:
that selects for the bacterium
838
00:27:36,650 --> 00:27:38,049
Speaker:
to want to take that plasmid up,
839
00:27:38,049 --> 00:27:40,089
Speaker:
not because there's potentially
840
00:27:40,089 --> 00:27:41,890
Speaker:
an antibiotic in the soil, but
841
00:27:41,890 --> 00:27:44,089
Speaker:
because that plasmid carries a
842
00:27:44,089 --> 00:27:45,529
Speaker:
resistance mechanism or a
843
00:27:45,529 --> 00:27:47,369
Speaker:
tolerance mechanism to a heavy
844
00:27:47,369 --> 00:27:49,170
Speaker:
metal, or to something else
845
00:27:49,170 --> 00:27:50,329
Speaker:
that's threatening it in the
846
00:27:50,329 --> 00:27:51,289
Speaker:
environment.
847
00:27:51,289 --> 00:27:57,690
Speaker:
And understanding that piece of
selection that's driving the
848
00:27:57,690 --> 00:28:03,410
Speaker:
spread of AMR, kind of like as a
carrier, not the main driver,
849
00:28:03,410 --> 00:28:05,849
Speaker:
but there's something else
that's driving that plasmid to
850
00:28:05,849 --> 00:28:10,089
Speaker:
to be spread in the environment,
which then ultimately comes to
851
00:28:10,089 --> 00:28:12,549
Speaker:
us in the hospital, which makes
it challenging for treatment.
852
00:28:12,549 --> 00:28:16,650
Speaker:
So I think that's another area
that we could really start to
853
00:28:16,650 --> 00:28:22,150
Speaker:
explore those kind of
interconnections between non
854
00:28:22,150 --> 00:28:27,670
Speaker:
antimicrobial resistance,
selective pressure basically.
855
00:28:27,670 --> 00:28:28,029
Speaker:
Yeah.
856
00:28:28,029 --> 00:28:31,549
Speaker:
And we would we would do a lot
of one side of our houses.
857
00:28:31,549 --> 00:28:33,490
Speaker:
We do a lot of nutrient analysis
858
00:28:33,490 --> 00:28:35,789
Speaker:
and and work closely with uh a
859
00:28:35,789 --> 00:28:37,109
Speaker:
lot of the companies here that
860
00:28:37,109 --> 00:28:38,829
Speaker:
are responsible for um,
861
00:28:38,829 --> 00:28:40,089
Speaker:
basically a lot of the
862
00:28:40,089 --> 00:28:42,069
Speaker:
nationwide composting that, you
863
00:28:42,069 --> 00:28:43,630
Speaker:
know, you get your, your brown
864
00:28:43,630 --> 00:28:44,750
Speaker:
bin collected and everything
865
00:28:44,750 --> 00:28:45,069
Speaker:
like that.
866
00:28:45,069 --> 00:28:48,690
Speaker:
And they're very interested, um,
from their point of view, about
867
00:28:48,690 --> 00:28:51,710
Speaker:
having an analysis set up that
they can quickly see what sort
868
00:28:51,710 --> 00:28:54,589
Speaker:
of heavy metals are present
within their compost heaps,
869
00:28:54,589 --> 00:28:56,589
Speaker:
because even with the best will
in the world, you know, you're
870
00:28:56,589 --> 00:28:59,750
Speaker:
going to have leaching of these
into groundwater supplies.
871
00:28:59,750 --> 00:29:02,349
Speaker:
And this gets back to how we're
872
00:29:02,349 --> 00:29:03,569
Speaker:
all responsible for the
873
00:29:03,569 --> 00:29:04,650
Speaker:
environment because if you're
874
00:29:04,650 --> 00:29:06,730
Speaker:
lazy enough with your food waste
875
00:29:06,730 --> 00:29:08,269
Speaker:
bin to chuck a few AAA
876
00:29:08,269 --> 00:29:09,609
Speaker:
batteries in there or something
877
00:29:09,609 --> 00:29:11,230
Speaker:
like that there, then, you know,
878
00:29:11,230 --> 00:29:13,009
Speaker:
come on, there's there's ways
879
00:29:13,009 --> 00:29:14,329
Speaker:
and means of disposing of that
880
00:29:14,329 --> 00:29:16,130
Speaker:
properly, but you don't realize
881
00:29:16,130 --> 00:29:17,690
Speaker:
the ramification of if enough
882
00:29:17,690 --> 00:29:19,650
Speaker:
people do that and enough heavy
883
00:29:19,650 --> 00:29:21,970
Speaker:
metals get into the environment
884
00:29:21,970 --> 00:29:23,269
Speaker:
from people just, you know,
885
00:29:23,269 --> 00:29:25,670
Speaker:
being, let's face it, lazy,
886
00:29:25,670 --> 00:29:26,410
Speaker:
then
887
00:29:26,410 --> 00:29:30,250
Speaker:
Um, well, as I said before, you
can't say you weren't warned.
888
00:29:30,250 --> 00:29:31,730
Speaker:
And we see this in the hospital,
too.
889
00:29:31,730 --> 00:29:34,130
Speaker:
We've seen, you know, tolerance
890
00:29:34,130 --> 00:29:35,630
Speaker:
or resistance mechanisms to
891
00:29:35,630 --> 00:29:37,450
Speaker:
common disinfectants, for
892
00:29:37,450 --> 00:29:38,049
Speaker:
example.
893
00:29:38,049 --> 00:29:39,049
Speaker:
And that's actually what's
894
00:29:39,049 --> 00:29:41,410
Speaker:
driving the, the, the plasmid to
895
00:29:41,410 --> 00:29:43,150
Speaker:
be transferred and sustained in
896
00:29:43,150 --> 00:29:43,930
Speaker:
the population.
897
00:29:43,930 --> 00:29:47,730
Speaker:
Not so much the, the AMR that it
happens to carry as well.
898
00:29:47,730 --> 00:29:50,609
Speaker:
So, um, I think we're seeing it
in both and I think we're
899
00:29:50,609 --> 00:29:53,609
Speaker:
starting to get an idea, but I
think we should definitely start
900
00:29:53,609 --> 00:29:56,529
Speaker:
to really look at some of these
other driving factors.
901
00:29:56,529 --> 00:29:58,769
Speaker:
It's not just the antimicrobial
902
00:29:58,769 --> 00:30:00,210
Speaker:
that might drive the spread of a
903
00:30:00,210 --> 00:30:00,900
Speaker:
plasmid.
904
00:30:00,900 --> 00:30:03,259
Speaker:
It's potentially these other
things as well.
905
00:30:03,259 --> 00:30:03,619
Speaker:
Yeah.
906
00:30:03,619 --> 00:30:05,400
Speaker:
And again, just to hark back to
907
00:30:05,400 --> 00:30:06,579
Speaker:
what I was saying about the data
908
00:30:06,579 --> 00:30:08,180
Speaker:
we've generated from the care
909
00:30:08,180 --> 00:30:10,000
Speaker:
home, obviously, you know,
910
00:30:10,000 --> 00:30:13,319
Speaker:
everybody, when you have a care
911
00:30:13,319 --> 00:30:14,859
Speaker:
home, there's a lot of cleaning
912
00:30:14,859 --> 00:30:16,220
Speaker:
that goes on there by necessity
913
00:30:16,220 --> 00:30:16,619
Speaker:
and everything.
914
00:30:16,619 --> 00:30:18,180
Speaker:
But seeing the amount of
915
00:30:18,180 --> 00:30:20,339
Speaker:
resistance we were that is
916
00:30:20,339 --> 00:30:22,259
Speaker:
driven by disinfection agents
917
00:30:22,259 --> 00:30:23,700
Speaker:
and things like that there it is
918
00:30:23,700 --> 00:30:24,140
Speaker:
scary.
919
00:30:24,140 --> 00:30:27,339
Speaker:
So, you know, then then the care
homes caught between a rock and
920
00:30:27,339 --> 00:30:27,859
Speaker:
a hard place.
921
00:30:27,859 --> 00:30:29,339
Speaker:
Well, no, we need to clean.
922
00:30:29,339 --> 00:30:30,700
Speaker:
That's the right and proper way.
923
00:30:30,700 --> 00:30:32,579
Speaker:
And yes, we don't disagree at
all with that.
924
00:30:32,579 --> 00:30:35,400
Speaker:
But, you know, even though
925
00:30:35,400 --> 00:30:36,940
Speaker:
you're doing it right and proper
926
00:30:36,940 --> 00:30:38,740
Speaker:
and you're not thinking that
927
00:30:38,740 --> 00:30:41,339
Speaker:
it's having an onward impact, it
928
00:30:41,339 --> 00:30:41,579
Speaker:
is.
929
00:30:41,579 --> 00:30:44,299
Speaker:
So how do we how do we get
around that?
930
00:30:44,299 --> 00:30:46,460
Speaker:
How do we get around that?
931
00:30:46,460 --> 00:30:49,220
Speaker:
And think of of maybe better
ways?
932
00:30:49,220 --> 00:30:50,380
Speaker:
Well, the first way of doing
933
00:30:50,380 --> 00:30:52,339
Speaker:
that is by just generating that
934
00:30:52,339 --> 00:30:53,660
Speaker:
data and understanding what
935
00:30:53,660 --> 00:30:54,059
Speaker:
we're seeing.
936
00:30:54,059 --> 00:30:56,420
Speaker:
What a great place to end this
episode.
937
00:30:56,420 --> 00:31:00,160
Speaker:
We've discussed the importance
of surveillance in understanding
938
00:31:00,160 --> 00:31:03,279
Speaker:
what is happening in the wider
world and the real world
939
00:31:03,279 --> 00:31:06,480
Speaker:
implications of monitoring in
terms of stepping up infection
940
00:31:06,480 --> 00:31:10,279
Speaker:
control measures or anticipating
trends in health needs.
941
00:31:10,279 --> 00:31:13,279
Speaker:
In the next episode, we're going
to discuss emerging trends in
942
00:31:13,279 --> 00:31:16,759
Speaker:
antimicrobial resistance and how
to prioritize the challenges
943
00:31:16,759 --> 00:31:18,240
Speaker:
that lie ahead.
944
00:31:18,240 --> 00:31:20,720
Speaker:
Going Macro on Micro is a
podcast supported by
945
00:31:20,720 --> 00:31:24,519
Speaker:
Beckman Coulter exploring
emerging themes in microbiology.
946
00:31:24,519 --> 00:31:26,680
Speaker:
Subscribe to the podcast
wherever you listen to.
947
00:31:26,680 --> 00:31:30,480
Speaker:
Stay up to date with each new
episode as it's released.
948
00:31:30,480 --> 00:31:33,200
Speaker:
You can also join our online
professional community by
949
00:31:33,200 --> 00:31:36,799
Speaker:
searching for Beckman Coulter
microbiology on LinkedIn.
950
00:31:36,799 --> 00:31:38,400
Speaker:
There you'll find discussions on
951
00:31:38,400 --> 00:31:39,759
Speaker:
a variety of interesting
952
00:31:39,759 --> 00:31:41,440
Speaker:
microbiology topics.
953
00:31:41,440 --> 00:31:44,039
Speaker:
Until next time when we go macro
and micro.
954
00:31:44,039 --> 00:31:44,880
Speaker:
Goodbye.