Thank you very much, Sara. Good evening everyone. Thank you for joining me this evening.
So I'm gonna talk for a little while tonight about mastitis controlling dairy herds and particularly a new initiative we've got planned for the new year. But also some resources that are now available to practitioners and advisors in the UK, around data analysis, both for milk recording data and mastitis data, as well as, antibiotic use benchmarking. So hopefully plenty of interest.
Just to say, yep, part of the University of Nottingham, so, we, do a number of things related to, dairy herd health, particularly in the areas of lameness and mastitis, our commercial herds. He robotically milked, a new building, that we've just moved into, and plenty of scope here for several studies we've got on the go, around housing, and, the stocking rates and the, the ability to move cows into different areas. Also work for QMMS Limited, set up by Andrew Bradley, we're a laboratory consultancy, providing milk recording, bacteriology, and advisory work around the analysis of milk recording and mastitis data in particular, and we're based in Somerset.
Before I go any further, I do want to acknowledge the team, so, this is not my, work, this is very much, the group, led by, Professor Andrew Bradley, Professor Martin Green, Pete Down, Chris Hudson, Bobby Hyde, Katherine Leitch, and Barbara Payne. So many thanks to them. Together the group and others, we have a track record in mastitis research, publishing nationally and internationally on various topics, particularly around the areas of, mastitis control in the dry period and with several studies on the go currently, and we look forward to presenting the findings of those in the new year.
We're also the group behind the development, and ongoing development of the AHDB dairy mastitis control plan, now in its 10th year, and so what I'm gonna talk about today very much, sort of relates to this. And really tonight I'd like to share with you a few things. I've divided really the this evening into two parts.
So I want to talk first of all about the importance of mastitis, particularly relevant when we think about antimicrobial use and reiterate, where mastitis is important regarding the recent taskforce targets for the dairy sector around antimicrobial use benchmarking and where mastitis has roles to play. In benchmarking antimicrobial use within the herds, so the impact, if you like, of mastitis treatments on various metrics that we can measure and monitor in herds around use of antibiotics. And therefore, as, as our clients.
And the industry as a whole is under increasing pressure to reduce antibiotic use. If mastitis is extremely important in driving antibiotic use on farm, well, how can we think about reducing the rate of new infection, reducing the rate of new cases, and improving mastitis control? So here's some things that now we've got available for practitioners and I'd like to introduce some resources that are free to use and download, particularly what we call the mastitis pattern analysis tool, which I'll demonstrate later.
Some of the resources available and to bring it all together at the end, a new initiative, things around the pattern of mastitis, reacting with resources on an ongoing basis, and we really see this as an overarching initiative and we're gonna call it quarter pro and tell you a little bit about that later on. And then at the end, as Sara said, quite happy and please do, you know, send in some questions and we'll have a little bit of discussion at the end. So, starting then with the importance of mastitis and, and obviously plenty talks about why mastitis is important, and we think about financial losses in dairy herds.
Interesting when you work with groups of dairy farms and and milk buyers, it's often er forgotten that that the cost of mastitis, for example, will eclipse. Losses from infectious disease, BVD and yonis by quite some distance, and in fact when you benchmark herds, mastitis is often costing more than the vet bill. And, and here just a little graphic benchmarking the cost in terms of pence per litre, and you can see many herds well over 1 penny a litre or 2, even 3p a litre, depending on the impact of mass pipes and salcon in their herds.
So well known as a cost. Obviously also very important in terms of dairy cow welfare. So we know that the, the welfare of dairy herds, in terms of endemic disease, lameness and mastitis, really big impact in the welfare of dairy herds.
And of course mastitis is such an important, driver of cow welfare because it's so prevalent. Because we do see still a lot of infections and a lot of clinical cases on farm, well then it has the ability to impact cow welfare, in, in a negative way. We also think about mass fights in terms of public health.
In terms of, the milk, product itself, and plenty talked about, things like, bacter scan, total bacterial counts, and other things, Yoni's, antibody, obviously another one. We think about mastitis in terms of its effects on milk quality, and we also think about mastitis in its effects on sustainability. So plenty of data out there about wastage from herds, cows being lost from the herd because of issues with chronic mastitis and high cell count, and actually if we could claw back a lot of these wastage, well, that translates into a lot of cows that we lose from the system.
But I've highlighted there obviously antimicrobials and prudent use of antimicrobials and mastitis is extremely important and very relevant in this one and and certainly a very hot topic. I've also put on there at the end, of course, a real opportunity for us as vets and advisors to get involved in herd health. We're often blessed in terms of the data available with mastitis when compared to other areas of herd health, particularly lameness, where we have the chance to look at cell count data, look at mastitis data, look at antibiotic use, it's captured on farm or by a third party, and we can get involved and do something about it.
So if we think about the antibiotic use then and why mastites is important, this obviously is off the back of the O'Neill report, published now a couple of years ago. And the O'Neill reporter talks about various things, but this statement about an increasingly robust consensus that unnecessary use of antibiotics in animals is a significant concern. I think it's that word unnecessary that we need to focus on.
And because of this concern over unnecessary use, antibiotics in agriculture I've highlighted there in the environment was actually #3 on the, the, the list if you like, the key list of things that came out of the O'Neill report and this aimed to reduce the unnecessary use of antimicrobials. And, and this is difficult now because no one's saying we can't treat a sick animal, but if you look globally, of course, the vast majority of antibiotics are not used in treating sick animals, they're often used in a preventative capacity, or even there as it says, to promote growth and production. So we have to look carefully at this, but particularly then apply that to the dairy sector.
The government have now responded and come out with various statements around the importance of having a focus on preventing infection and reducing inappropriate use of antibiotics. But it's important for us as as vets to understand that at government now there's greater understanding on this focus on prevention of infection, and this is going to be important as we work towards reducing antibiotic use, this idea of a multi-species average of 50 milligrammes per kilo. That is of course already been achieved.
So across all livestock species we're now below 50 milligramme per kilo. But again, we need to think about within the different livestock sectors, how that might look for dairy compared to pigs, poultry, beef and sheep. But also government have came out and said quite clearly that they're going to set sector specific reduction targets, but they're going to underpin this by improvements in husbandry, biosecurity, disease prevention.
So a real opportunity for us as vets to get involved with this. And of course the food manufacturers and retailers are very much keyed into this and are beginning to drive, and in fact already have done. And in some ways, that's left us behind as a profession, they're developing standards for responsible use and starting to set targets as well.
So important we think about this, and this is now just over 12 months old, so if, if you haven't come across this yet, this is the rumour targets taskforce report, and this comes out with targets for the different livestock sectors. Of course we're interested in the dairy sector, so what's the plan for dairy? Now we need to think about discussing with our clients these six key areas that talk about targets for antibiotic use in the dairy sector, and you see there, by the year 2020.
So by the year 2020, our clients have to be thinking about using less tubes, reducing overall usage. But I highlight the middle four here because it, it shouldn't be lost on us and probably already seen it. 4 of the 6 items on that list directly relate to mastitis control in that they talk about number 2 there, intramammary use of products that contain high priority, critically important antibiotic.
Number 3, intramammary use at drying off, so antibiotic dry care therapy. Number 4, lactating cow antibiotic therapy, and number 5, actually the the one that we need to increase, a focus on the use of internal teatse, so non-antibiotic approaches at drying off. That last one's interesting because as a country we we've got pretty good take up of sealand if you compare the UK with other EU countries, but we still have a long way to go, and there's still many herds and clients out there.
I'm sure you can think of your own, that will not entertain the idea of non-antibiotic approaches or won't even use sealants in combination with antibiotic to start with. So these targets, if you like, are based on percentage changes from some sales data looked at in 2015. So as I say, the central four relate to mastitis control, but also actually the first one there, well, that's injectable antibiotic use, with products containing high priority, critically important antibiotic.
And of course the treatment of sick cows of mastitis has often been where we've tended to reach for high priority critically important antibiotics. And at the bottom there, actually a total usage figure, and we'll move on to talk about this shortly, but irrespective of what format we're putting the antibiotic into the animal, an overall usage figure in milligrammes, and a target there you can see by 2020, we need to be aiming towards 21 milligramme per kilogramme of cow, if you like, per population corrected unit PCU. And we need to aim for 21 milligramme by the year 2020, and this is the sort of things that we need to work with our clients in order for the industry to achieve this.
So let's think about this, that's the, a bit of background, if you like, and a focus on the antimicrobial use. Well, what does antimicrobial use look like in dairy herds? If you took a group of dairy herds and you benchmark their antimicrobial use, what would it look like?
Of course, first of all, there's great discussion and an ongoing discussion on the best way of doing this, and essentially if you're going to measure use of antibiotic in herds, it boils down to are we going to do it using a mass-based approach? So we're going to work out milligramme per kilogramme of cow, or are we going to do it on a dose-based approach, which, which is, is quite interesting to do and quite important to do. And are we going to use those doses on a daily basis, so a defined daily dose DDD, or are we going to do A defined course dose, the CD and look at a course rather than days.
And actually there may be variations on a theme depending on countries, so the Dutch have come out with an animal defined dose, etc. So there there's quite a lot of metrics in use, and they all have their uses. And as part of, the AHDB Research partnership, University of Nottingham, work led by Bobby Hyde, we've got a that record, reference there at the bottom, but this is now a resource freely available, so one of the first things I wanted to sort of highlight this evening, you can jump on the internet there, search for AHDB dairy, anti-micro use calculator, and you can download this, spreadsheet.
So I'm just gonna open this up now for you. So, you can download this spreadsheet, open it up and have a play with this and start to benchmark using your own herds. There's instructions there on the front page that you can see.
And the first thing you need to do is enter the number of animals in the hood, unless your dairy client, does a significant amount of animals sort of slaughtered for beef, I would just stick to the number of adult dairy cows in the hood. So we'll put in 200 dairy cows, for example. And then use the basic calculator.
It's worth, when we talk about why just the adult dairy cows, the, the weight, the average weight of a dairy cow set in the background of this is based on the average weight at the time of treatment. So, we don't need to put in numbers for calves. I, you know, I freely admit this is often a contentious issue and people rather, like to put cows and calves.
In, but you can do it on the number of adult dairy cows, and then in the background there's an average weight at time of treatment. So if the animal's treated as a 100 kg calf, as a 400 kg heifer, or as a 750 kg adult, as long as we're all using the same average weight at time of treatment, this allows benchmarking, particularly between countries. Perhaps it's less useful between herds, but it's still of use and can still be done.
So we use the calculator here and you can see what you can do with this spreadsheet now. You can pick a route here, so I'll just add one at the bottom from the drop down menu. I'll add an injectable product.
We populated the tool with all the current injectables that we can think of, so I might have some BetaO LA. We haven't got that one on there. And in this 200 cow herd they might have used 20 bottles of betaox LA.
And you can see the tool immediately converts those 20 bottles of beta ox in that year to that population to a milligramme use of around 3.5, and that's increased this herd's milligramme use per population corrected unit from 17 to just about 21. Hi James, sorry, we could do that in here, can you hear me?
Yeah. We can't see the spreadsheet at the moment. I think what you need to do, if you hover over the screen and click share, you need to change which screen you're sharing with us.
Hover over the screen and stick and share. Yeah, there should be apologies. That's OK, there should be a green button that says share because at the moment we're still seeing the presentation.
Apologies, yeah, OK, so University of Nottingham, yeah, and share screen. Is that better? We still have the presentation, so you should have, if you click, ah, that's the one that's the that's the spreadsheet.
Excellent. So when you're backtrack for a second when you're done and then you can share the presentation again so I'll I'll drop off a gig in now. Yeah.
Sorry about that. It's OK. OK guys, sorry about that.
I realised you couldn't see the spreadsheet, so just to backtrack a bit, when you open up the sheet, you'll have the instructions page, and this gives a bit of background about the different metrics and the average weight at time of treatment, so to reflect, the average weight, so a cow may be treated when it's a calf, when it's a heifer, when it's an adult cow. You can put in then the number of adult dairy cows. And then we can move straight on to the calculator and enter in from a, from dropdown menu, so I was selecting an injectable product, for example, and I was selecting BetaMox LA and I was putting in 20 bottles of Betamo.
And explaining that that was worth around 3.5 milligramme, and that would lift this herd's overall milligramme usage from around 17 to just under 21. And you can see then the tool is calculating for you the milligramme metric, the defined daily dose.
So for this herd, use of these products, tubes, dry cow therapy, and the beta ox we've just added. In a whole year, on average, each cow in the herd would be exposed to just under 4 daily doses of antibiotic in the year. And each cow in the herd, would be exposed to 1.7 courses of antibiotic in the year.
So we're presenting the metrics here, dropping out and separating that component which is critically important, high priority antibiotic. But you can also see the relative contribution of various products. So if we want to see what's driving the milligramme use, well you can very quickly see the impacts of 20 bottles of Penstrep.
As well as the beta ox, you can also see the impact of the dry cow tubes, so there's 400 dry cow tubes. Well, actually in terms of milligramme contribution, that's not very much at all. So we can see the relative contributions of these products.
OK, so I'm just gonna pop out of that for a second, and go back to the presentation. So you can then see with different herds, the impact of er herds which have er poor mastitis control. So this is farm K, just to er show an example, antimicrobial use in a year.
And we've got here a herd with a very high mastitis rate, so the impact of, both the injectables that are being used in this herd, so there's quite a lot of noradine being used for cows that are sick with mastitis. And a lot of tubes used, this is a this is a 400 cow herd, a lot of tubes being used, but you can see the milligramme use is very high, so more, you know, way over twice the target, and also the, the defined daily dose now is 15, so each cow in the herd exposed to 15 days of treatment and 5 courses. So very important, in terms of mastitis control, that we actually sometimes look at antibiotic use and that can often be a a very useful lead in, if you like to discussing mastitis control on farm.
Just to present some recent research, so that's, you know, one or two herds, if you like. What about if we look at a large number of herds, so this is research published in the vet records, this time last year, just before Christmas last year, and this was work led again by Bobby Hide. On 358 dairy herds, where we went and looked and and got the usage data, for antibiotic use in these herds and benchmarked them all.
So in the end, across the 358 farms we had over 80,000 cows. Nearly 300 of the farms we went to the vet practises and asked for the sales data from the vets. On 66 of the farms, we actually took the use data from on-farm software, so these were herds that milk recorded with QMMS and therefore had data on farm, and they used their medicine books in their software on farm, so Uniform Agri, Summit Total Dairy, In herd, their reporting usage on farm using their software.
So we can have a look at perhaps the potential difference between what's reported on farm, or if we look at sales data, because there's pitfalls with both, for example, with sales data, we might have sold products to that client in that year, but they might not have used it. Obviously with on-farm reporting they may underreport what they use. So we could over and underreport it.
But actually in the study there was no difference in the pattern at all, so whether we use sales data or on farm use, we can actually derive the sort of outcomes that we need. Just to then highlight if we line up 358 farms across the X axis there, in terms of increasing milligramme usage, this is milligrammes on the Y axis. We line up these farms from very low use on the left there to high use herds on the right.
And we can see, first of all, what's quite interesting is quite a lot of herds are below the 21 milligramme target for for the year 2020, so many dairy herds are doing very well already. But you see there, out towards the right hand side, a real tail of herds that are very high use and using 30, 40, 50, even 60, 70, 80 milligramme per population corrected unit. So it's quite interesting if we're gonna apply a target across the board.
Perhaps the dairy sector is interesting in that we do quite well for antibiotic use already. In fact, the, the average in this group was 16 milligrammes and 4 daily doses. But clearly we need to be looking and trying to identify these herds out here that are, are, are doing, if you like it much worse.
And in fact the, the worst 25% of farms in this data set accounted for half the antimicrobial use in the study. So we just quickly look at to sort of what drives the milligramme use here. So along the bottom now we've got dry out therapy, CCT we've got foot bath, antimicrobial foot bath usage in orange.
We've got intramammary tubes, this is lactating cow intramammary tubes in green, a little bit of intrauterine use, was washouts, oral use in calves, and then parental therapy in, in purple. And each dot is a farm. And you can see quite clearly that if we're benchmarking milligramme usage, and this, this is going to be used by government, we know that milligramme use is going to be one of the key metrics.
Well, if we're benchmarking milligramme use, dry cow therapy over on the left here has a very negligible impact on milligramme use. So if our herds suddenly stopped using antibiotic dry cow therapy in all their cows tomorrow, you might save 2 or 3 milligrammes off your bottom line, but it's a very, very small amount. Likewise with mastitis tubes, there's a few herds here that are using so many that they are getting to sort of 1015 milligrammes, but the majority of herds mastitis tube use doesn't drive the milligrammes either.
Of course what does drive the milligrammes, as you can see, is parental use, so systemic use of antibiotic, with a lot of herbs up here already at 40, 50, 60 milligrammes without even looking at any other use. Also interesting from the study, and Bobby goes on to talk about this in the paper if you're interested, but actually using antibiotic foot baths and oral products in calves was significantly associated with the risk of a herd being in that worst 25% of, of, of high usage herds. So we know systemic therapy has a big role to play in driving milligramme.
But let's think about the role of mastitis in dairy herds antimicrobial use, just to finish this first section. We bring it all together, why is mastitis er important in terms of antibiotic use? Well, as we've sort of talked about, we know lactating and dry cow tubes don't take up many milligrammes, but what they do do is really drive the daily doses and the courses, so they really drive the doses and the courses.
What drives the milligrammes is injectables, and we know these are often still used, unfortunately inappropriately in mastitis control, and they'll take up a significant amount of the milligrammes. And we do know that critically important antibiotics certainly historically tended to be used in mastitis. So how can we think about improving, if you like, or reducing antibiotic use in mastitis control?
We could say, well, we're just gonna minimise use, we're gonna stop treating some cases. And there's been interest in this, particularly out of North America, in saying, well, if we've got a mild case, particularly when it's caused by E. Coli, that we don't need to treat this with antibiotic tubes.
We could talk about modifying approaches to treatment, and there we think about selective use of antibiotic dry fed therapy in low cell count cows. We think about not using injectable antibiotic when we're treating mild and moderate cases, so if the cow's not sick. But as, as you, you would sort of imagine, and those of you that know myself and the group very well, we know that actually ultimately this is all about avoiding the need to treat in the first place and therefore reducing the occurrence of new cases into the herd.
So, let's just think about a couple of these, before we move on to the second half of the talk. Well, what about mastitis treatment? What about this minimising use idea?
What about this sort of phrase that you often hear, you don't need to treat mild clinical cases with antibiotic when you know these cases are caused by E. Coli. Where does this come from?
Well, first of all, if we're going to take this approach to reducing antibiotic use, in mastitis control, the BVA, responsible use guidelines, well, actually we've bypassed 123 and 4 straight away and we've gone straight to number 5, minimising use. So we need to be clear here that the sort of potential impact around this, but there is good rationale. There is some evidence around identifying causal pathogen, if the causal pathogen is a gramme negative, particularly when it's E.
Coli, there's reasonable evidence again for E. Coli that we don't need to treat with antimicrobials. Just to share with you the original work because this is talked about a lot, but it's important sometimes to say, well, where has this come from, what did the original research show?
These were the Largo papers out of the US in 2011, and this is using a, a, a, a, a byplate if you like, the the Minnesota plates. And the headlines from these studies, certainly the, the short term outcomes, for example, I've highlighted here, if you used an on-farm culture system, to guide treatment of clinical mastitis on farm, you did tend to reduce intramammary antibiotic use and milk withholding time, but then that phrase without significant differences in days to clinical cure, cure rates, etc. And that's fine, but when we dig around in the background of the paper and actually get the numbers up, no statistically significant difference doesn't mean no difference.
And if we look at days to clinical cure, for example, compared to cases which were treated with antibiotic tubes, taking a culture-based approach, waiting for a culture result and then deciding to treat or not to treat meant you had half a day extra to achieve a clinical cure. And if you looked at bacteriological cure risk within 21 days of enrollment, if we treated these mild and moderate cases straight away with antibiotic, we achieved a 71% cure rate. If we delayed treatment based on culture results or didn't treat at all because we'd cultured gramme negatives, we actually had a 60% cure rate.
And this is often what you see in low powered studies, this idea that actually when you look at the power analysis that was presented, this study was underpowered. So the number of cases that were looked at and the power of the study meant that this study was able to detect a difference in clinical cure of a day or more. So if they didn't detect a difference in a day, in terms of clinical cure, well then we can say it's not statistically significantly different.
And if we couldn't detect 17% points difference in cure rates. And this, of course, detected a difference of 11, so between 71 and 60. If we didn't detect a cure rate difference of 17% points, well, again, the paper can say it's not statistically significant.
So an underpowered study, so we've got to be careful with this, we also need to think to ourselves, well, on balance, if we are going to experience a clinical cure delay of up to a day and a decreasing cure rate of up to 17%, is this the right playoff for reducing use of antibiotic? What about cow welfare? What about cost effectiveness of this, what about variation between herds, other gram-negative pathogens, and also the, the, the difficulties if you like, and the challenges of applying research in other countries to the UK system.
And just to when this little bit peeped down with Andrew Martin, particularly up at Nottingham myself, looked at, well, factors affecting the cost effectiveness of on-farm culture approaches to guide treatment. This chart at the bottom here, simply says when, when those herds that are actually seeing a great proportion of their clinical cases caused by gramme negative, so right over on the left hand side here. If, for example, these herds, only 10 to 20% of the clinical cases they see are driven by gramme positives, so therefore most of them are driven by gramme negatives, well then actually the difference in cost, if you like, you've got to set up the incubator, the training, and you've got to put up with a certain amount of recurrence and a reduced cure rate, but actually that's offset with reducing antibiotic use, it becomes perhaps cost effective.
But for a great many herds, and particularly when we think about the UK situation, where we have herds in loose yard systems, in paddocks, at pasture where we see much more gramme positive, strep ubris in particular for herds with increasing amounts of gramme positive cases, well then actually it it's not a cost effective approach. And we could argue could even lead to more mastitis on the farm. So whilst this is interesting and perhaps for some herds on farm culture er and culture-based treatment approaches might be one way we could look at reducing antibiotic use, for a lot of herds in the UK it's unlikely to be an important thing to think about, certainly in the first instance.
So what about avoiding inappropriate use? What can we do here? And we need to think now about do we need to use injectable antibiotics unless the cow is sick.
So for mild and moderate cases, is there evidence to suggest the addition of an injectable antibiotic to our lactating cow therapy when we're treating clinical mastitis, is that actually appropriate use? And actually again, if we look at our 7 point guide for the BVA. Once we're talking about inappropriate use, well this is #2 now, so we're, we're in the sort of right area, we're, we're at the sort of right end if you like of the spectrum, thinking about inappropriate use.
And when you look at the literature. And what evidence there is, for example, supplementation of antibiotic dry cow therapy with injectable antibiotics, supplementation of lactating cow antibiotic therapy with systemic antibiotics. The literature is lacking, and of course these approaches will have a big impact on the milligramme usage in our herds, so we need to think seriously about this.
And actually, not only is there very little evidence to support the addition of injectable antibiotics when we're treating clinical cases, in fact, there's some research that suggests it might actually be detrimental and end up making quarters and cows more susceptible to reinfection. So avoiding inappropriate use, we also need to think about the use of antibiotic dry care therapy in low cell count cows. And there's a greater deal talked about this, and I won't spend too much time on this now, but selective use of antibiotic dry care therapy is not a new idea.
It's been going on for a long time, and there's a great amount of evidence. In fact, we've got, here a meta-analysis. So the highest level of research evidence, reworking of lots of randomised clinical trials, not only from the UK but around the world, that highlights what an impact the use of internal teat sealants have on mass control because you significantly reduce the risk of new infection.
And work done by Andrew Bradley, we been on for 10 years ago now. That that actually looked at the use of sealant in low cell count cows, and actually the use of sealant in low cell count cows not only apparently appeared to increase the susceptibility of these cows to gram-negative infection. Coliforms in the next lation, but also appeared to interfere with the function of the sealant itself.
So putting antibiotic dry cat therapy into low cell count cows in combination with sealant appeared to affect the function of the sealant itself. So great evidence for the use of teat sealants alone in low cell count cows, and as vets now, a great opportunity to use data and software to look at actively prescribing sealant alone, antibiotic in infected cows, but looking at plenty of cows where really we should be prescribing sealants alone. But we know that the dry cow environment that we put these cows into has a huge impact then on the risk of reinfection, and we can't just think, well, we put the sealant in, that'll be fine for the next 8 weeks.
We've got to advise our clients and think seriously about where these cows are going to go and how we can minimise environmental reinfection. So that's got us to the sort of second half of the talk, if you like. Apologies had some technical issues and that's me messing about it earlier on.
But now we need to think about avoiding the need to treat, actually reducing the rate of new infections and how we can avoid the use of antibiotic through improved mastitis control. We're not going to talk about minimising use. We've talked a little bit about modifying use, but let's avoid the need to treat.
It's important because if we just minimise use, well that will reduce our daily doses. If we think about modifying approaches to treatment with selective trica therapy, well that'll reduce some courses. If we think about our injectable use and inappropriate injectable use, that'll reduce the milligramme use.
But importantly, if we avoid the need to treat, that reduces all the antimicrobial use metrics, not just one. So improving and reducing antibiotic use through improved mastitis control is about avoiding the need to treat, reducing the occurrence of new cases. And this is where I want to sort of talk a little bit about now, and a new initiative, that we're going to bring along in the new year called Quarter Pro.
Avoiding the need for effective and sustainable control of mastitis and dairy herds brought about by reducing the rate of new infection, it's rarely driven by treatment decisions alone. Now we're in the right area, working with clients to avoid the need for antimicrobials in our responsible use. And this is important because if we look at mastitis control in the last 20 years, a great amount of research, er coming through the dry period, strain typing for hubris.
But the biggest change in mastitis control, now is this realisation that we will cure infections during the dry period. True cure rates across the dry period are very high, and therefore it's all around prevention of new intramammary infection. And particularly thinking about rather than a one size fits all approach where we still tended to give blanket control measures to our clients, all our clients do the same thing, and this is challenging because farms and their pathogens are very different.
This one size fits all doesn't work, we need to move away from that and towards a herd specific approach where we design control measures specifically for particular herds at a particular time. And how do we achieve this? Well, we know new infections may come from infected cows, and that's still a big focus for a lot of us out there in practise.
We still assume transmission of infection between cows. Well, in fact, actually for the majority of our farms and our clients, 90% of the time at least new infections. Coming from the environment.
But this is a great deal more challenging rather than focusing on the parlour and parlour routines and transmission. We're now out there amongst the buildings, bedding, water, loafing space, paddocks, ventilation, water quality at certain times of the year, it can be a big challenge to get this right and get it consistently right. And then what we tended to do is try and look at the data, we've tried to say, well, if we're going to design bespoke control measures for our herds, we need to think about dry period epidemiology or lactating period epidemiology.
We need to think about environmental or contagious spread of infection, we need to think about are there influences with different parity groups, heifers in particular? Does time of year have a role to play? What about other groups, the highs, the lows, what pathogens are present?
And this can take a long time and involve us looking at a lot of data and we realise that this is often quite a challenge in itself, and can be difficult to do, and importantly can be time consuming to do. And this got us thinking about could we make assessment of data to drive bespoke mastitis control for our clients? Could we make this data assessment process a lot easier and a lot quicker?
Wouldn't it be nice if we could get our her data from the milk recording organisation or on farm software? We could drop. A load of metrics about cell count and mastitis, we could put those metrics into an analysis tool, and then within seconds we could have an output for us to take away and say, right, my pattern is environmental infections in the lactating period.
Of I go and let's think about that. So if you're going to go back to your herds tomorrow and next week, what can you do? So first of all, we've got a mastitis pattern analysis tool for you.
Again, this is going to be freely available and actually is already uploaded for you to use. And so just to point in the direction you can go on to the the website, search for AHDB Dairy Mask's patent tool, and you can download this now, stay free of charge to use. So let's run through how you would use this.
The pattern analysis tool, first of all, we need your client's milk recording data or you need your client's milk recording data. You need to be able to download that. We're then going to convert this milk recording data using some software that again we're going to give you, so we're gonna drop out all the cell counts and mastitis data.
We're then gonna open the mastitis patent tool. We're going to import this converted data on cell counts and mastitis, check the data quality, we've got cell counts, we've got clinical cases, we've got enough cows calving, and we're gonna categorise the herd. So first of all, we're gonna encourage you with your clients, if you don't do this already, download the milk recording common data layer.
So these CDL files are all available, so whether your client milk records with CIS, milk records with NMR or milk records with QMMS, all three milk recording organisations, in the UK provide a CDL file. So we're gonna get the CDL file. We've then made available, so this is this is now going to be freely available in the new year.
We're just putting, putting the finishing touches to this, but we've got a CDL mastitis data converter for you to have. So you're going to load your CDL into this. This is going to take the CDL apart and then generate the cell counter mastitis data that we need.
If you need more functionality, it's worth saying that the total vet software will handle data from on-farm software. So, if you say, well, all the data for this herd is held on farm in uniform agri summit total into her, Westphalia, whatever it is, well then the total that software will also handle this and drop out the mastitis data that you need for this patent tool. We're then gonna open the pattern analysis tool.
And the pattern analysis tool is ready to receive data as you would expect on cell counts, so things about chronic cows, new infections across the dry period, cure rates, mastitis cases in the 1st 30 days, so a classic dry period outcome measure, what happens in heifers, for example, heifers carving in with high cell counts. And we thought, well, yeah, we could ask you to type all this in, go and find it, then type it in. But of course we need this over a long period of time, we need to be able to see, well, what's happening in the last 3 months, what's happening in the 3 months before that, the 3 months before that, etc.
Etc. We need 18 months' worth of data. So not only can we look at the indices themselves, but we can look at how they change over time and start to look at seasonal effects if they're present.
So we thought, well, actually it's much easier if from using this converter tool that you've already dropped out all the cell count and mastitis data electronically. So in fact you could hit a button here, import this data immediately into the tool. And we might start to think about, well, I've got a block calving herd that calves in the autumn, so I want August, September and October to be one of my three months, so I get all the calving cows and I get the dry period measurements right, or my herd turns out in April, or my herd houses in November.
So there may be some things we just need to think about to get the dates right. But then having populated the tool, we can then check the data quality. Think right, our herd here has got 3 recordings in the last 3 months, 3 recordings in the 3 months before that, and so on.
They've got enough cows carving in each 3 month period. There's a few months where they don't carve so many heifers, so we might just have to be a bit careful with that. And they're recording their clinical cases to the milk recording organisation, so these are coming out as well.
So we can check the data. And then we can hit the button and the mastitis pattern analysis tool will say in the last 3 months, the current situation, if you like, based on a traffic light system, the predominant current issue in this herd is an environmental pattern of dry period origin. And we can straight away go off to our clients and say, right, this is not a contagious issue.
This is not an issue with environmental infections in the milking groups, I need to focus, we need to focus on the environment management. In the dry period. The tool is also picking up on some seasonality in the data.
And interesting when you look back in the last 12 months, this trend for the dry period, environmental infection pattern continues. In fact, it becomes very strong when you look in the last year. So we really hope that this is gonna be of use.
And actually then you can click on a button just off to the left in the software, I'll demo it in a minute, where you can say, well there's a bit more information here, so having told you it's environmental dry period, or what sort of things might we think about, what might be important. And of course then it's up to you to go off to see your clients and have a think about what you might look at. How good is the patent tool at selecting the right pattern?
So that's another question in itself. Work is ongoing. We started with 50 herds where we had a known diagnosis in inverted commas, if you like, from herds that were submitted to the mastitis control plan that myself, Andrew Martin and Chris have looked at.
We then tested it with a further 50 herds, and we're getting agreement in about 90% of the herds. So whatever Andrew or Martin or Chris or myself had said in these 100 herds 10 years ago, if we give that same data to the tool, about 90% of the time, the tool agrees with us, or maybe we should say we're agreeing with the tool. And then there's more work done at Nottingham at the moment, so Bobby Hyde's looking at machine learning, so can we improve the predictions that the tool is making?
For example, now the tool is 95% accurate in telling the difference between an environmental pattern and a contagious one. So great interest in refining this tool further. And then we've got some resources for you, so as we go forward now into the new year, we've got some resources, we've always had resources available through the massti control plan and these of course are ongoing.
And the plan, and things around decision support tools that we made available to plan deliverers and they're still available, cost calculators, these are still available, but we're now starting to add to these. So resources, the pattern analysis tool. Say we have a diagnosis, if you like, a pattern of an environmental dry period pattern in the herd, well, now we're thinking about putting some more resources out there, YouTube videos if you like, PDFs to help you out there in practise.
We're trying to make aspects of the original mastitis control plan more bite size. So for example, you can jump online now, these now exist. Search for a HPB dairy dry cow and have a few fact sheets that you could then say, well, given that I've got a dry period pattern, what aspects of my client's dry cow management might I need to focus on.
We've also developed some YouTube videos, so if you can stand the sound of my voice even more, you can jump online and look at some videos around selective dry cow therapy and selecting cows, and also aseptic administration of dry cow therapy. And still a big barrier on farm, and one reason our clients really don't want to go down the route of putting sealant alone in their cows. So something to help us either do with our clients, watch with our clients, tighten up infusion technique on farm.
And there's more resources to follow in the new year. So finally then, how does this all link with Quarter Pro? Last few slides.
Now if we try and put all this together, we've come up with a new initiative. To say, well, if we're going to assess the data quarterly, this is what we'd like to do. We've got, we're blessed in our herds with milk recording data often appreciate these herds that don't, but those herds that milk record and capture mastitis events on farm will really at least every 3 months, we ought to be looking at this, so a quarterly assessment of the data where we use the pattern analysis tool, the pea, to predict fastitis patterns on farm.
And then we're going to react using resources, so we've got these resources available, and we're going to continue to develop a few more, maybe bite-sized chunks of the mastitis control plan, to put some important things out there, so as practitioners and advisors if, If we can get in the right area for mass control and use some of these resources, we can then optimise ongoing mastitis control on farm. So quarterly, using the patent tool with resources to optimise ongoing mastitis control. This was presented at BCVA back in October by Andrew Martin and that the paper's available on the BCVA platform.
But essentially what we're proposing for the new year under the Quarter pro initiative. It's an overarching scheme, maybe an entry level, get us in the right area and get us thinking about mastitis control in a more bespoke way for our clients. If we review the data quarterly, and that means getting the CDL from CIS NMR or QMMS, we're going to put that data in the patent analysis tool, so we're gonna convert it using some software we're going to make available.
You can then populate the mastotis pattern analysis tool and think, well actually is it contagious environmental, is it lactation, dry period, the impact of heifers, with current cases, seasonality, and highlights for this herd now, the current pattern. Well, let's say it's key management areas identified in the dry period from environmental infections, heifers might be important and it might be the winter. And we're trying to refine the pattern.
We may need to drop out into software to look at this data in more detail. You might say, well, let's open up TotalX or Inter Plus and have a look in a bit more detail. Exactly when is this happening?
Is it the winter, is it the summer, you know, what, what the relative contributions here? But that should put us in the right area where we can say let's use the information and resources that we've now got available. So for example, the resources that are coming through and available now in the area of dry care management, the videos on dry care therapy, that should help us come up with some solutions and interventions for our clients.
And actually we may then say, well, this is an entry level thing, we may need some more detail, we might need to drop out here and go and do the plan. I can think of some interventions for my client, but I need to make sure that I've come up with all the things that I could do, or actually for some herds it might be a bit complex, and we need to drop out into the plan. But then we're gonna sit down with our clients and think about optimising ongoing control.
And we may say, well, we're gonna use some cost calculators to try and influence their decision making, try and get some compliance. And in 3 months' time, we're gonna go through the whole process again, download the CDL again, convert it using our free software, give it to the patent tool, and away we go again. Is the pattern changing?
Are we in the right area? And on top of that, we may occasionally then say, well, let's benchmark antibiotic use. So that's quarter pro.
I've got a couple of examples. I'm, I'm well aware it's 9 o'clock and apologies, you know, I messed about a little bit earlier on, but I've got a few examples, if you would like to see, the, the, the tool in action, is that OK, everyone? Sara, Paul, is that alright?
Have I got a minute or two? Yes, go ahead, James. Yeah.
So, just going to, come out here now and share with you, the, the desktop for a minute, hopefully that's OK, still see that. So, what I've been talking about is getting the CDL, so for example, you might have downloaded, your CDL for Steven. Downloaded that earlier on.
This data converter for CDLs, like I say, we're just putting the finishing touches to it now version one, but you can load your CDL, get it cracking, and that will take it apart, drop out all the cell counter mastitis data from the CDL. And once it's finished, you'll have a file available, but then you can go to your patent analysis tool and you can say my CDL converter has sorted this out for me, so I'm ready to import the data into my patent analysis tool. So let's find Steven's file, one I prepared earlier.
And we can immediately populate the patent analysis tool with all the data out of the milk recording CDL file in the format we need, calculating the sort of metrics we need to know about, dry period cure rate, new infections and lactation, proportion of chronic cows, mastitis cases in the 1st 30 days, and crucially for the 3 months ending 31st of October, the 3 months prior to that, the 3 months prior to that, and so on. I can just hit the next button, check the quality of the data. Is Stephen telling his milk recorder clinical cases?
Yes, he is, thankfully. We've got a few heifers, we go through periods where the heifer's numbers aren't great, but we've got good numbers of calving cows and recordings and just hit the next button, and in seconds we've got the fact that in the last 3 months, the predominant, predominant current issue is environmental dry period. So if you have, if you have to get off the fence.
And say let's concentrate in one area, we're going to concentrate about dry cos. So that's the example I gave you, but I just wanted to demonstrate how quick that is. If we go back to data entry and say, well what about another farm, so let's drop out data for er Chris, for example, .
Let's get his milk recording CDL file. Let's drop out all the metrics we need around cell count and mastitis. Check the data quality of Chris's CDL.
Yeah, he's reporting mastitis cases. Again, some issues with low numbers of heifers carving in some months, and this is a smaller herd, but. Should be adequate data available, we hit next, completely different herd in that for the last 3 months, and certainly for the last year, the predominant current issue is environmental infections in lactation.
And actually they do quite well for the dry period, particularly recently, and particularly well in the control of contagious mastitis, and the tool highlighting important seasonal patterns, so we might want to go out into Chris's data in a bit more detail and look at patterns in the rate of new cases. And in fact, if you do that, this is much more of a winter housing issue for this herd. Just to highlight, that's how long it took to convert the data for Steven, so the data is ready to put in our patent tool.
So we hope that this, provides yourselves as practitioners and advisors with readily available tools to, get on with mastitis control on farm. So apologies, that's a couple of minutes over. I do hope that was of use, more than happy to take some questions and answers, and thank you very much for listening.
Thank you. Thank you very much, James. That was a really, really interesting, presentation, and he certainly gave us a great overview of the, the Quarter pro initiative and what we can achieve with it, as well as highlighting, a lot of the resources that are actually freely available to us.
So just apologies again for the technical difficulties that we've had, and, also for running over a little bit. But just before we, before we take any questions, I just want to ask everybody if they could just spare 30 seconds to complete the feedback survey that should have popped up, in a new tab in your browser as we went through the webinar. Depending on which device you are using to watch the webinar, the survey doesn't always present itself.
So if that's the case, just please feel free to email any feedback that you've got, to office atheebinarett.com. If you're listening to this as a recording, Then you can add comments on the website underneath the recording or emailing them in to Office at Webinar vets again.
So that's great. We have got time for a couple of questions, so keep them coming in, while we've got James live tonight. I'll just amalgamate a couple of questions on a similar theme here.
And it's probably one that you get asked an awful lot, James. But, it's absolutely great when we have data, for farms. But in the instance where we're dealing with farms that maybe don't record or don't fully record.
Is there any way of, of using any somatic cell count data that we've got or how, and, and the second part of that would be, what's the absolute number of minimum recordings that you'd need to be able to make a diagnosis? Yeah, OK, so thanks, sorry, yeah, so, and I see the question there about farmers not recording. Yeah, agree, big frustration, and the reality is, ultimately, actually the absence of milk recording data is a massive barrier, and there are, sort of problems with that.
Herds that don't record, well, for a start, we can still use their clinical mastitis data. And through the mastitis control plan, there's some simple, tip charts available. So for example, if I've got my herds recording clinical cases, for a moment, the first thing I'd want to know is, do more than 1 in 12 of my cows that are in the 1st 30 days of lactation get clinical mastitis.
So you can just get your clients to write down the next 12 cows that are due to calve. And say, right down the calving date when they do it, and put a tick next to them if you have to treat them for mastitis within 30 days after that calving date. If more than 1 in 12 cows are having ticks next to them, well then that's very likely to relate to a dry period diagnosis.
For for cell count outcomes if they're not milk recording, again, you can say to your clients, right, write down the next lump of cows that are due to calve, and as well as monitoring whether or not they get mastitis in the first month. Look at getting a California mastitis test done on day 4 after calving, so a CMT on day 4, actually has very good sensitivity and specificity for identifying likely infected cows, so obviously they may not be clinical, but we're trying to get a subclinical outcome if more than 10%. Of cows are California test positive at day 4 after calving, that's also a very good marker for dry period infections, so herds which don't have any milk recording or mastitis data in electronic formats.
We can still get to a basic diagnosis of is this or is this not likely to be driven by the dry period, because if less than 1 in 12 cows calve in with mastitis in the first month, and less than 10% of cows are California test positive on day 4, well then look elsewhere, don't focus on the dry period, we need to think about lactation. In terms of minimum number of milk recordings, yeah, a bit more difficult now, anything more than every other month gets very, very difficult. So, I, it doesn't have to be monthly all the time, but every 6 weeks is better, every 8 weeks is just about usable, but what you start to lose is you start to lose the ability to have a first milk recording test day cell count after carving.
So if we're milk recording less often than monthly, say we're doing every 8 weeks, we've just milk recorded and then a cow calf tomorrow, well then she has to wait the better part of 8 weeks before she gets her first cell count. And then if it's a high cell count, it's very difficult to know, did she carve in with the infection causing that high cell count or is this something that happened in lactation. So milk recording frequency, anything more than every 8 weeks is very difficult to use.
6 to 8 weeks is OK, but we have to accept the fact that we'll miss some fresh carvers and an ability to think about infection status of calving. That's brilliant, thank you very much. Some good practical advice there as well for herds that don't record.
If a farmer did start recording, and was going to go monthly, what's the mini minimum number of monthly recordings that you would require to be able to make a diagnosis? Yeah, I, I mean, clearly, actually, if you're gonna do this, you actually need, at least 18 months' worth of data, because until cows go through a dry period and out the other side again, it's actually quite difficult to look at cure rates and new infection rates across the dry period. So when you start milk recording, you're still probably more focused on clinical mass bitter cases cos you.
You can do a lot with clinical cases, because you could say, well, let's go back and capture 18 months' worth of clinical data, and perhaps let's use that in the first instance, particularly in low cell count herds, where the clinical data is likely to be more important than the cell count data, you know, in the first instance. I'd actually flip it the other way, Sara, and say, I, I'm willing to bet you now one of the barriers to this. Is those herds that do the milk recording but don't capture the mastitis data, electronically for their milk recorder or the milk recorder doesn't capture the mastitis data, that will be more of a barrier, I, I would suggest going forward in that you'll get the CDL, you'll convert it using the converter software, you'll plonk it into the massti patent tool, and there'll be no clinical cases reported at all.
We've had a little think about that, because again, it it's, it's not insurmountable, and actually, in fact, when, when look at the CDL data converter, there is an option to merge clinical cases into it. So if you can get 18 months' worth of clinical mastitis data into a spreadsheet, then you can actually merge that data in and then have it available for the patent tool. So yeah, issues both ways, you know, they might not milk cord for very long, in which case probably do it off the clinicals in the first instance while you accrue.
More, more cell count data, because really you need 18 months' worth of clinical cases and cell counts to have a robust diagnosis. You can do some short term things, so we do look in the last 3 months and you can start to get an idea, but until you've got 18 months' worth of data, it the, the, the pattern, if you like, is less robust. Brilliant, thank you for taking us through that.
Just one very final, very quick question relating to the pattern analysis tool. The question here as to what the numbers next to the output relate to. I don't know whether you can take a slide showing that.
Yeah, of course, yeah, so, can everyone see that OK? Yeah. Yes, it's coming up.
So, the numbers are arbitrary, so it's a traffic light system, so in the background of the tour when we have discussions about this, effectively we're waiting, the contagious dry environmental, lactating period environmental. And the others depending on the metrics. So for example, a good example would be if the dry period cure rate, for example, is very poor in the last 3 months, that will give more points to a contagious diagnosis.
So if you've got a sort of classic contagious herd, dry period cure rate, you know, below 50%, 30% of the cow's chronic, no seasonal patterns, very high bulk cell count, you start to rack up points. Against a contagious diagnosis, so the numbers next to the green, amber, and red are, are an arbitrary points score derived from, what the different metrics, give, if you like, to that area of the pattern. So to have, to have a very low score for contagious here, will have a combination of low cell count herds, very good cure rates, seasonal patterns, you know, for example, those will mean that actually the points that are being accrued against a contagious diagnosis will going to be hardly any points, particularly in the last 3 months in this herd.
So it's an arbitrary point scoring system derived from a weighting applied from the different metrics. Brilliant. And just to clarify, does that run between 0 and 100?
Is 100 the maximum? Yes, it does. Yeah, absolutely it does, it, it, it does, it does run between 0 and 100, yes.
There's there's a bit more data, so it's worth saying, I presented, this at BCVA in 2017, so the paper about the pattern analysis tool specifically is available on the BCVA platform, for, for the October 2017, er conference. Thank you. Thank you for directing us to that.
Brilliant. Well, I think we'll, we'll wrap it up there, but just to say thank you again, James, that was a really, really great presentation, really interesting, incredibly useful.
