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U.S. Department of Health and Human Services

Animal & Veterinary

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Monitoring Antimicrobial Consumption and Occurrence of Resistance in Denmark by Danilo Lo Fo Wong, M.Sc., Ph.D.

DR. WONG: Thanks, Tom. Good afternoon. And as Tom said I will present on behalf of Antonio Vieira, who unfortunately had to leave. But I can assure you I’m as Dutch as he -- as Danish as he is at least.

I have the fortune of working with DANMAP some four or five years ago. So I’m hoping it has not changed it too much. I have only briefly seen these slides, but I think together we can walk through it.

And so DANMAP is, as my former boss, Henry ---, said it is the mother of all antimicrobial programs. So that’s why I also thought you should see how far it has gotten and I didn’t want to keep that from you.

(Slide)

So, it’s monitoring antimicrobial consumption and occurrence of resistance in Denmark. And I think it’s one of the first programs that that actually did both things. I just saw a wonderful example from Korea where they also start monitoring consumption which we can all agree is a great accomplishment because people are usually not happy with that. But I think it’s necessary to make the link between consumption and resistance.

(Slide)

So DANMAP stands for the Danish Integrated Antimicrobial Resistance Monitoring and Research Programme. And you can see that the acronym doesn’t really fit but it’s just a -- it’s a nice way of saying.

The objectives haven’t changed since I last worked on it, to monitor the occurrence of antimicrobial resistance among bacteria from food animals, food of animal origin and humans, so it’s integrated in that sense, which can be done because it’s building on an integrated surveillance system for foodborne pathogens.

It’s to monitor consumption of antimicrobials for food animals and humans, to study associations between consumption and resistance, and to identify routes of transmission and areas for further research. So the monitoring data is actively being used to learn from and they’re doing an excess modeling and research on the data that’s being collected.

(Slide)

Some of the considerations, I guess these are quite generic for surveillance programs, they want to find out what the trends are, have data for research and also risk assessment. And in that sense on the one hand identify the need for a program, but also when interventions are being implemented to see what the effects are of that. So it’s also a monitoring tool for interventions that are in place.

(Slide)

Regarding the methods, they’re using standardized methods throughout the country, which of course is easy because it’s a small country, but still. And their great strength is centralized data management and analysis and they’re using both data from passive and active surveillance.

(Slide)

The sample population that DANMAP is covering is quite impressive, it’s covering 95 percent of all broilers produced in Denmark, 95 percent of pigs and 95 percent of cattle population. It’s a random sample but it represents those populations.

For the diseased populations they cover pretty much everything because the institute that has the database has -- is the function is resistance laboratory and they do get all the samples.

(Slide)

In terms of isolates from food, they’re collected from pre-determined categories. And I’m not sure but I do seem to remember that they do change from year to year, so they have regular cycles of a number of years, so that after four or five years they would have sampled all food categories.

It’s a nationwide collection of samples at slaughterhouses, via carcass swabs, wholesale and retail outlets. And imported food are sampled at point of entry also as part of another program which is called the Case By Case Monitoring Program where they compare contamination of imported foods to the Danish foods and using that to determine whether or not to accept those batches under the SVS Agreement.

(Slide)

In terms of isolates from humans, they come through routine testing of various pathogens in fourteen major sentinel hospitals through Denmark. Data from testing of Campylobacter and Salmonella are submitted to a central public health laboratory located in Copenhagen, called the States Serving Institute.

Entercococci and E. coli isolates from stools from approximately 200 healthy animals is a study that’s been going on called NORMAT standing for normal people in Danish, where they were kind enough to submit regular stool samples and just to monitor the baseline to see what’s out there in the population. From this it would look like that program has stopped, which is unfortunate, but that’s at least where they get some of their baseline data as well. And in apparently in 2008 they found some soldiers to pester with that.

(Slide)

This shows you the data that is included in DANMAP. In humans we have both indicator bacteria, pathogens and consumption of antimicrobials. It actually goes for all categories but fish. So for fish you only have consumption of antimicrobials.

(Slide)

For the bacteria that are included there is E. coli indicator and pathogen, there is Entercococci indicator, Staphylococci, pathogen, Streptococci, pathogen, and Salmonella and Campylobacter, zoonotic.

(Slide)

This is just a schematic overview showing you how data is collected from all the major areas, all the major sectors that are involved in food safety and zoonotic. So, in both food animals, food, and humans there are various institutions that are involved and these remain the same.

Something happened here in the middle but it’s pretty much still the food, the veterinary and public health site, that together with these institutions integrate the data into DANMAP. So, it’s quite comprehensive in that sense.

I’m not sure what Antonio wanted with these boxes, but -- basically the idea is that it goes from the various sectors into an integrated database where they analysis can be done each year.

(Slide)

So, now some of the numbers. This graph shows you for the years 1999 to 2008 probably for Danish broilers, broiler meat, imported broiler meat, domestically acquired human cases and travel abroad human cases for Erythromycin, Nalidixic acid and Tetracycline.

So you see that there seems to be an up going trend in Danish broilers, a rather vague trend in meat, something is happening in the imported broiler meat which probably comes from the biggest part of both domestically acquired. So you can ask yourself how domestically acquired is it. I guess it’s quite difficult to find the origin of the meat when you get the disease from.

(Slide)

Trends in resistance among S. typhimurium from pigs. For me it seems like Tetracycline and Sulfonamide are still on the rise. Ciprofloxacin and Nalidixic acid seem to play a minor role.

(Slide)

Same for trends in multi-drug resistance among pigs. The most thing that I can see is a down going trend for Salmonella DT-12.

(Slide)

This is transfer resistance among indicator E. coli in broilers, cattle and pigs. And you can see the most antibiotics seem to follow similar trends especially in the pig population.

(Slide)

This is an article that I remember quite well. This was published in 2003 by my colleagues, --- Stege, F. Bager, E. Jacobson, A. Thourgaard.

This was the first time that the consumption database was presented to the outside world, called VETSTAT. So this is when the consumption data was included into the analysis.

(Slide)

So, VETSTAT monitors the use of all prescription medicines in animals in Denmark. For production animals, it is both therapeutic use of medicine, sera and vaccines, and coccidiostats at farm level. The prescription information comes directly from the producers and from pharmacies. It has some information, farm identity, animal species, age groups, et cetera. But also medicines for companion animals are monitored but at a less detailed level.

(Slide)

The objectives here are to provide a basis for research on the association, presumption on the one hand and resistance on the other hand of course. Also to find, if there are trends in prescriptions. If there are some veterinarians, for example, that are prescribing more than the average.

And what I can remember from that database, having seen it a few years back, is that you can follow your own prescription behavior and see that against and average. So you will not see individual prescription behaviors of other veterinarians or other producers, but you can see how you are doing in relation to a country or a regional average which in itself should be sort of a self-regulatory tool.

(Slide)

Antimicrobial use in Denmark, as you all know here it was -- the growth promoters were banned which resulted in an increase in therapeutic antimicrobial prescriptions, but it leveled off to a level that was lower than before when you still had growth promoters. It looks like human antimicrobial consumption has been rather stable.

(Slide)

You basically see the same picture for the swine production.

(Slide)

And this is more detail for a number of antibiotics. You see that there has been an increase and decrease -- I’m not sure where this is going but a -- it’s probably mainly driven by --- penicillin and tetracycline.

(Slide)

So, this is just a picture to show you what happens after you -- I think every person was banned here you see the lag time before resistance is disappearing. So if you stop use of a growth promoter or antimicrobials, it still would be residing in the environment, in the population, and it will take several years before it disappears.

(Slide)

And this one is showing avoparcin consumption and resistance to --- among C. coli from pigs where you on the one hand have consumption and the other hand you have the percentage resistance. You can also see there is difference in the same trends, but there is a lag time between --- consumption and subsequent trends in the resistance.

(Slide)

Virginiamycin consumption showing pretty much the same picture for E. faecium in pigs and E. faecium in broilers. After you start the use of virginiamycin.

(Slide)

So, in conclusion DANMAP provides a resistance baseline, and has been doing so since the late nineties. Overall the levels of resistance reflect consumption of antimicrobials. Be it with a time lag, and it’s a good tool to follow national interventions. And actually have an idea of the effectiveness of those interventions.

So, that and on behalf of Antonio, I would like to thank you for your attention.

(Applause)

DR. CHILLER: Any questions?

(Pause)

DR. CARATTOLI: Thank you so much. I would like to introduce myself. I am Alessandra Carattoli. I work in Italy. I am the responsible for research projects for antimicrobial resistance mechanisms in --- for ISS. Which is the equivalent of CDC, FDA in my country.

Okay. Now we go to programs in Africa. The speaker is Samuel Kariuki. And he is Coordinator of the Medical Microbiology course at the Kenya Microbiological Institute and also honorary lecturer at the University of Liverpool. Thank you.