 Let me start by going to some of the websites I mentioned. I'm a member of the Divitrio Advisory Group for Integrated Surveillance of Antimicrobial Resistance. This is abbreviated as AGI-SAR. So if I do a Google search, so let me just, you know, so if I do a web search for W-H-O AGI-SAR, you'll see a few relevant pages. These first web pages are on the Divitrio website. The Divitrio Advisory Group on Integrated Surveillance of Antimicrobial Resistance. And you see a picture of us, and if I zoom in, oh, I don't know where, oh, here I am. I'm apparently in the same white shirt now. You see me in the white shirt standing at the staircase. This is me over here. There's a meeting we had in Carolina. So Divitrio AGI-SAR was established in December 2008 to support Divitrio efforts to minimize the public health impact of AMR associated with the use of antimicrobials and food animals. Over 30 international renowned experts news. So the picture that you see there is from October 2016 that was held hosted by the veterinary group at North Carolina State and the United States. But they've had, we've had these meetings all over the world. So this is the Divitrio web page on AGI-SAR. You can see on the right AMR from Food Chain Global Action Plan on AMR. If I go down further, you'll see Terms of Reference, you'll see Integrated Surveillance of AMR. You'll see Integrated Surveillance, application of a one health approach to surveillance of resistance. And they give some priorities. If a country has no activities at all and they have an interest in this field, the first recommendation is to look at enteric pathogens like salmonella campylovacter in humans. So even though the focus is animal, you're looking at the impact in public health on humans. So you start doing surveillance of salmonella campylovacter in the human population because of its relationship to food animals. If you've already done that or if you're doing multiple things at once, the next good place to continue is retail meats. Go to the market, just buy some chicken legs, just buy some beef, just buy some other items that are ready for consumption, animal meat. Because even though that's not the animal, the living animal, this is exactly what the people are eating in the source of the infections. So a lot of this one health is about the relationship of resistance to its impact on human health. So starting with humans moving on to the retail meats for human consumption, there's of course in a completely other sector, which is also part of one health, but often not WHO's focus, which is animal health. And I'll come to some of those web pages. Before I do that, let me just click here, Integrated Surveillance of AMR, just see what that's on that page. It's that document that I just mentioned, Guidance on Integrated Surveillance. So that's one thing to do, is just do a web search for WHO-Agisar and you will see these pages. I'm going to go back to my web search, WHO-Agisar. You see this one down here is simply agisar.org, agisar.org is about exactly the same project of actually the same people, the exact same everything. The difference is that, and it's even got that same document, the difference is that this web page is hosted by Denmark. It's hosted by actually by Renee, Renee's group that I just received an email from. So this is more technically oriented. So this is led by the Danish Technical University with a strong veterinary component, led by a number of veterinarians and veterinary microbiologists. And on this page, Critically Important, Integrated Surveillance, Setting up an Integrated Program. It's probably a little summary of this document. So the document goes into representation, sampling, frequency of testing, culture methods, data management. They do recommend the use of the HUNET software. If I click on Experts, it talks about the AMR Monitoring Subcommittee. So this is one of Deborah Jo's main technical leads for Integrated One Health Surveillance. The CDC, the CDC Entire Pathetric Room is another one. Okay, what else do we have here? Okay, those are those two pages. The U.S., no, let's not do that yet, sorry, okay. So there's also, if I go to OIE, OIE is the Organisation Internationale des Episodes or something like that. In English it's translated, and the new name of the organization is the Organization in fact was renamed. This organization is the World Organization for Animal Health. They kept the abbreviation, so it is still OIE. So if I do OIE, Antimicrobial Resistance, and you see it's the first, well the first link is for the media, the second link is OIE for AMR Strategy. Let me go to that one. So the OIE Strategy for Antimicrobial Use and the Prussian Use of Antimicrobials, part of their interest of course is impact of antibiotic use on human health, but also a very big aspect of their interest is the impact of antibiotic resistance on animal health. Things like mastitis or turkeys or swine, respiratory diseases, a very big cause of economic loss in the aquaculture industry. You know, fish, shellfish, when you have, when you have a resistant cow, you treat the cow. When you have resistant chickens, animals, sick chickens, you either kill the chickens or you treat the chickens, and often you do it individually or on the basis of that herd. But you treat the animals individually, well I also take that back, you can also put antibiotics into the food and into the water. But I want to contrast it with the animal situation, the fish situation. The fish situation, you pour tons and tons of antibiotic into open waterways. You put the antibiotics into ponds, fish farms, and they end up with large amounts of antibiotic exposure, large amounts of antibiotic use, and you end up with very high rates of loss. Antibiotic resistance in the cattle population doesn't usually kill the cow, it leads to decreased milk production. You have to have a delay between the antibiotic being given to the cow and the time that their meat or milk can be used again. But in the fish population, you often end up with the complete loss of all of the fish in that pond because of a multi-resistant strain that's just infecting the entire pond. So there are important elements of animal health, animal welfare, and productivity of food production. So let's see, I'm just looking for a table of contents here. I don't see a table of contents, but it's only, I don't know, it's about an eight-page or ten-page document. So that's not a website, that's a PDF file which I did not notice. I'll click on, well just click on this first one here, AMR, the Four Media, hopefully that will have some links in-house. But antimicrobial resistance, and then you see here, strategy on, I think this is the document we just opened, fact sheet, risk associated with the use of antimicrobials in animals worldwide, veterinary medicine, products and vaccines, AMR broadcast. So the OIE has a lot of relevant resources. They have resources on how to do effective treatment of animals in different animal food production areas. So that's OIE. I'm going to go back and do a web search, and this time I will put FAO, antimicrobial resistance. FAO is the food, so OIE, World Headquarters is in Paris. FAO, the World Headquarters is in Rome. Antimicrobial resistance, at some point these sites all link to each other. I just didn't see that, but it is what is called the tripartite. The tripartite is these three organizations, OIE, FAO and WHO, working together with Agisar, working together to have integrated strategies, communication strategies, technical surveillance strategies. So now I'm on the page of FAO. I described as a tripartite, which means three organizations, but more recently there has been an increasing involvement of both UNEP and UNDP. UNEP is the United Nations Environmental Program. So they're interested in antimicrobial use in waterways, on farms, with the drains off to rivers. So the environmental aspect of antibiotic exposure is increasingly recognized, and I'll come back and talk about another project called Tricycle. And also UNDP, UN, is the UN Development Program, which has a key interest in building of clinics, building of infrastructure, water sanitation. So when I talk about the tripartite, it has always been three organizations, WHO, FAO and OIE. But now those two other organizations are increasingly active and have their own activities, UNDP and UNEP. I mentioned this one integrated project. It's called the E. coli. It's called the Tricycle project, or if I type E. coli, Tricycle, ESBL. I'm just finding a way to do a search. Okay, good. And this is on the first link here is on the Debrecha website, home news. So this is a project called Tricycle. This particular article is about the project's implementation in Indonesia, where they are looking for ESBL production among E. coli in human, animal, food, and water samples, river water, sewage water, groundwater, sanitation. So this is an example of a project that WHO and others are implementing. There is a project called Debrecha Glass. If I go to just doing another search right now and if I type Debrecha Glass, well, Debrecha Glass, WHO Glass, I don't know if that's going to come up with it. Oh, good. It's actually the first link. Glass is an abbreviation for the Global Antimicrobial Resistance Surveillance System. We have just had a project for the first five years with a human protocol. I am now working with them to draft, well, me and many other people, to draft the set for the first five years. We're now working on the second five years. In the second five years, this is expanding from antibiotic resistance to include antimicrobial use, but also including some of the augustar elements. So for the next five years, you will see the Debrecha activities broaden to include some of these integrated one health activities. Okay, the tricycle project, they're not doing that yet. Let me go back to tricycle. I'm going to simply type tricycle. I'm going to do something that's got nothing to do with Hoonat. I'm going to spell tricycle, tricycle. I'm going to type the word site, colon, Debrecha.int. This is a nice way to improve your search. I'm looking for the word tricycle on the Debrecha website. If I just look for the word tricycle, of course, I'm going to get a lot of pictures of bicycles, of three-wheeled bicycles. But I want to look for tricycle on the Debrecha website, Debrecha.int with the word site. So then, let's see, this is about the same Indonesia one. Okay, I'll go to this one here, the third link and see what that tells me. Oh, okay, well, this is a PDF document, which I didn't notice. If I look for tricycle here in this document, let's see where is it. Here it is at number two, development of ESBL producing global antibiotic surveillance tricycle, development of a global harmonized protocol for simplified and integrated surveillance system with a single indicator, ESBL production in E. coli, in humans, food chain, and environment. The protocol is being developed in 2017, so this is out of date. But feel free to do Google searches on your own. And if you have any trouble, just let me know and I can direct you to the correct people. One of the correct people is, in fact, Renee, who just, you know, actually if you look at my inbox today, you know, I've gotten a number of emails from Renee. That's him as well. Okay. So let's see. What else can I show you? There are a lot of countries with nice national programs and models for integrated surveillance. I am most familiar, of course, with the U.S. system. The name of that system is called NARMS. So I'm going to go back and do another Google web search and just type NARMS. And let me type NARMS anti-microbial resistance just to avoid confusion with anything else with the word NARMS in it. And you'll see three main web pages. NARMS hosted by the CDC. NARMS hosted by the Food and Drug Administration. And NARMS somewhere hosted by the U.S. Department of Agriculture. So let me go to the CDC website, and of course the site's all linked to each other. So NARMS, National Anti-Microbial Resistance Monitoring System, for enteric pathogens. It originally was supposed to eventually be everything, but the CDC does everything, but they don't call it NARMS. They only call it NARMS for the enteric pathogen. Established 1996, October 2020 virtual public meeting, if anyone wants to join that. All of these data, so NARMS now, the CDC, post, of course, the human data. So all NARMS data are publicly available for download. The MIC values, links to the whole genome sequencing. You can do search options. You've got graphs. So this is a nice example of what's possible. Somewhere we can link to the FAA, I'm sorry, the FDA, but the easiest way, I'm just going to go back to my Google search. And I'm going to go now to the second set of links here, which is FDA. In fact, FDA is the primary funder. So the FDA gets the money from the U.S. government, and the FDA gives money to the CDC and to USDA to run the project, to do the technical aspects of the project. So NARMS, 20 years of NARMS, what we have learned so far, what is next? The lead of that is a friend of mine, Patrick McDermott. He used to be here in Boston. NARMS, NARMS, NARMS, so anyway, and they also have the data source somewhere. Okay, here's integrated reports and summaries. They have an interactive website just like the CDC does. Data interacts with the data in NARMS now. Compare resistance for human retail meats and animals. Genomic data. Let me do one more web search. And this time, specifically, I will put NARMS and USDA. So here you see ARS, the Anemic Over-Resistance Surveillance or System, I don't know. Oh, and that one's for Southeast Asia. I don't want that one, USDA. And I can just put here site USDA.gov. Hopefully that will find it. I'll just go to this one anyway. So NARMS, FDA, CDC, USDA, humans. Oh, that's not Southeast, your world. That's Southeast of the United States. That's where the laboratory is based. It's in Georgia. That's about two hours from the CDC. So you see the links for CDC, FDA, then the food animals. So CDC is responsible for human, FDA for the retail meats, and the USDA does the food animals, the living animals. Living animals or recently dead carcass slaughterhouse animals. Good. Another thing, so right now, I'm not talking about Hoonet, but these are valuable resources for you to know about in this field. There is also the UN doing United Nations and Microbial Resistance. So the US, let's see, this 2019, this one's good enough. So the UN has had a small number of health issues before it. Of course, most health issues are led by WHO, but a few things, what are they? HIV, AIDS, Ebola, non-communicable diseases, and antimicrobial resistance. As far as I know, these are the four topics, four health topics taken up by the UN. They're taken up by the UN in recognition that this is not purely a human health issue. All of the issues that I mentioned, AIDS, non-communicable diseases, Ebola, have important health ramifications. They also have important economic and travel and business trade implications. So because of that, the United Nations has established the UN AdHoc Interagency Coordinating Group on Antimicrobial Resistance. So I'm going to click on that and see if it gives me a nice link. So this is the UN Interagency Coordinating Group on Antimicrobial Resistance, which is how they bring together formally FAAO, WHO, OIE, and UNEP and UNDP. You see here the key roles of those three organizations. So this is a structure allowing for integrated surveillance from not only a health perspective, but a political economic perspective as well. Let's play it alarm clock. OK, I showed you the website for the CDC. Many other countries. Canada has C-PARS. It's the Canadian Integrated Program on Antimicrobial Resistance Surveillance. Almost all the European countries do as well. So if I go to Netherlands, it's one of the more advanced. So it's Denmark, so it's Sweden, Netherlands, Antimicrobial Resistance, Integrated Surveillance. That project, let's see. This looks more like an inventory. So that was not necessarily the best line for me to choose. Oh, actually, no. This is just that same Doviger document I already showed you. But in there, there must have been a list. Here it is Maron. Maron is the animal integrated. This is the report. And that's about the construction of antimicrobial use in the Netherlands, both in the human and animal sectors. So a lot of countries have something. Lower resource countries, Thailand, is one of the more advanced. And Thailand, Integrated Surveillance, Antimicrobial Resistance, New Chapter. I won't go into the website. You can do some of these on your own. Called KoiPars. This is not an ongoing project, but it was a very valuable, I think, a five-year project. KoiPars. And it's been published. This is from Columbia. So they get the part of their name from Canada in English. And they just put change C for Canada, C-O for Columbia. A pilot project for poultry farms, slaughterhouses, and retail meat. Look at the human, animal, and food integration. Okay, those are the main websites and links I can think of. Later on today's call, I'm going to talk about breakpoints, but I may as well dive into that now. If I go to CLSI.org, I'm moving now more into data management. CLSI is United States Clinical and Laboratory Standards Institute. If I click on shops, these are commercial documents. A few of the documents are available for free. But, you know, but well, I'll go into that because the free documents, in fact, are very valuable. It's some of the most important ones. So I just clicked on shop standards. Let's see what I can find here. They recently reorganized the website. So I'm looking for their categories. Of course, they redeveloped it a lot for COVID. Microbiology resources, let me click on that. Let me click on standards again. So I'm clicking on standards and see if I can see the categories. There you see it on the left. I have to move my, go to meat and control so I can see it. So here you see that. So CLSI is a large organization that has many areas. Chemistry, toxicology, hematology, immunology, microbiology, molecular diagnostics, and then also specifically veterinary medicine. So of course, microbiology means human medicine, but veterinary medicine as well. So first I'll show the human, well, this probably has both, but, so microbiology, some of the key documents are the M100. It is the break points for human health, for bacteria. M60, the break points for human health for yeast. M61, the human break points for fungi. There's also the M45, let me go, let me browse standards. M2 is how do you do a distribution test? I'm looking for the M45. That's page one, page two. Also there is a search thing at the top. I've got to use the search. So here you see the M45 are the break points for disk and MIC testing for infrequently isolated fastidious bacteria. So I think it's like campylobacter, aromones, a number of bioterrorism things would be there. So that's the M45. Okay, now I'm gonna go to the veterinary section, veterinary medicine. So these are the featured ones. I'll start with the featured ones. Vet zero, well, that's a strange one to be featuring. So you see vet zero three are the disk and MIC break points for aquatic animals, fish, shellfish, et cetera, for distribution. The vet zero four or vet zero three supplement is for the MIC testing, okay? But that's not comprehensive, of course. Let me go back to veterinary medicine standards. Hopefully that will be more comprehensive. So vet zero one, how do you do a distribution test? The vet zero eight, which is also known as the vet zero one supplement are the breakpoint tables. What are the disk diffusion breakpoints? What are the MIC breakpoints? Vet zero three is how do you make breakpoints? That's the job of the experts. That's not the job of routine laboratories. Vet zero three zero four I mentioned is for aquatic health. Vet zero five is, I'm a co-author on this one is analysis and presentation of data on how do you analyze data from the food and animal sector? That document is the vet zero five. It's about statistics and histograms and MIC value graphs. There's a human equivalent called the M39. I'm also a co-author on the M39. The vet zero six is about the studious bacteria in animals and the most important one actually I already passed the most important one. The most important one is the vet zero eight. The vet zero eight is the one that has the breakpoints. What is this one on nine? Well, I forgot about this document. Understanding susceptibility data as a component of an antimicrobial stewardship in veterinary sectors. That was published in 2019. Okay, I'm just gonna search for the M39. If I search here for the M39, you'll see the M39. So I'm a co-author of this one. And you see it's analysis and presentation of cumulative antibiotic data on the human side. And the vet zero five is the same thing, but on the animal side. Okay, this is the CLSI. The other one is UCAST. And that everything in UCAST is free, which is a big, oh, let me go back to CLSI. If I do a web search for CLSI free, and the first thing you'll see is free resources, CLSI. And you see the M100 human bacteria, the M60 human yeast, human yeast. Skip the M23, not important for routine lab. M23, not important, vet zero eight. So the routine breakpoints are there. So let me just go into the vet zero eight, it's free. You cannot download it, you cannot print it, but you can read it in its entirety online. So I clicked on that link. Welcome to CLSI vet. Click here to use guest access. So I'm clicking here to use guest access. And you see there's one document here. Good, so I click on that one document. Also, this is the first time I'm seeing this. They must have read, I looked at this two weeks ago. It's the same content that I am very familiar with, but they made it prettier. It used to not be blue and white. So they recently reorganized and updated the website. Okay, and I really just looked at this about two weeks ago. Okay, so here on the left, you see the table of contents. Very important, well, the most important, of course, is not visible. It's further down. There it is. The most important is still not visible. Here it is. Table two A, breakpoints for enterobacteriaceae. Table two B, breakpoints for pseudomonas. Table two C, two D, two E, two F, and you see some of the veterinary pathogens. Menheimia, hemolytica, pastorella, actinobacillus, flernomonia, histophilus somnit. So these are a lot of veterinary specific pathogens. So the most important part of this document are, is table two. What else do we have here? We have table three. Table three are the quality control ranges. No, it's not. Table two three is a list of the QC strains. Table four are the QC ranges for the different bacteria for disdiffusion. Table five are the QC ranges for MIC values. Table one, let me go to table one. Table one, antimicrobials that could be considered for testing. And the human document has the same table. So for swine, cattle, bovine, mystitis, these are antibiotics that you consider testing. Amicacin, dogs only, genomycin. Of course, having seen this, I don't completely agree with this because my general recommendation is basically test everything all the time, except for the rare drugs that you wanna only test infrequently. You might wanna report it selectively. So I would basically test and report. Oh, okay, I see what they're doing here. Yeah, group A is test and report. So always test these, but only report it out depending on the animal. So if it's a dog, don't report out the safety of four. So that's always test, always report. Group B is always test, but selectively report. So they're also saying test all of these as well. So test everything at the top, test everything in group A, test everything in group B. Group A, tell the doctor. Group B, don't tell the doctor. It's more for epidemiology or it's more for stewardship reserve agents that we don't want to use. Then there's group C. Group C is selective testing. This is for your multi-resistant strains that usually you don't need, but you might need them at some point. Finally, group D, I don't know about finally. I'm not sure what this one is. Selectively test, selectively report. What's group C? Oh, I see, okay. This is slightly different from the human document. Group C, if you can read sideways, says there are no veterinary breakpoints. So there are breakpoints, but there are human breakpoints. So they're just warning you. There are breakpoints, but these are human breakpoints. And what you will start to see over the years is a lot of these drugs will start to move to group A and group B. So these drugs do not yet have that very specific breakpoints. It's a work in progress. Group D is selective testing for the very resistant strains. On the human side, there's also group U for urine, but urine infections in animals apparently did not merit inclusion in that list. Antibiotic agents, the pharmaceutical sponsor. So this is a free document all of you can look at. So some of the most important tables here I mentioned. Table one, what can you think about testing? The many different table twos are the breakpoints. Table four are the QC ranges for disc. Table five are the QC ranges for MIC. And then they have other things that are useful as well. Finally, in this document, table of contents, you see there's a section here called overview of changes. Overview of changes is great for people who don't want to reread the documents every year. They're telling you that they're renaming things. They changed clostridium difficile, it's not clostridioides. So that way, they're telling you what they added a new section, added a new section. So sometimes what people do is they buy the document once and then every year, every couple of years, they just look at the changes. Group A, they added ampicillin, horses, they added these things. So that's the sealer side veterinary documents, including these three documents that you cannot copy. Well, maybe they changed it. I wonder if I can try to save this. Well, let me see if I can do that. I'm gonna go to the webpage, click on file, more tools, save page as. Well, it comes across an HTML page, so you might even want to try that. I know in the past you could actually just do copy paste. If I do control A, everything's copied. And then if I go to Word or Excel, well, Excel's better because the formatting is not optimal. So if I go to Excel and if I go to new file here and I click on paste, everything will come, you know, one table at a time. But you know, it's not, it's not formatted nicely. So you need to spend some time cleaning up the formatting. But you know, the documents available online, as long as you have a good internet connection, you can just look at it online. So all of that's about sealer side. I'm now gonna go to UCAST. That's the European committee on enemy microbial susceptibility testing. Here on the left, it says clinical breakpoints. And you see they have the clinical breakpoints as a PDF file. They have as an Excel file. So let me go to the Excel file. It's downloading now. Okay, and it's now opening. Everything completely free. You see different sheets, the table of contents, changes from the previous version. I can go to the table for the intervector alleys, table for pseudomonas, table for synatrophomonas, similar to the CLSI in content, but free. Okay, so some of the main differences, I'm gonna close this Excel file. Okay, some of the main differences is that they have ready the human breakpoints. They do not have ready veterinary breakpoints. So here at the bottom on the left, you see AST of veterinary pathogens. So click on AST of veterinary pathogens. And you'll see that this committee was established in 2015. However, they have a vision document. They have guidance on how to collect and handle pharmacokinetic data, pharmacokinetic pharmacodynamic. They do not yet have breakpoints. They are far delayed. So en route towards European breakpoints. So this is from 2017. I guess this is a publication. En route towards veterinary breakpoints. A position paper explaining the vet cast approach. And you'll see some of the main people here. So let's see, what else do we have here? So if it comes to purely, if you are taking care of sick animals, then the CLSI has done the pharmacokinetic, pharmacodynamic. So for sick animals, CLSI is currently the only group that has veterinary specific treatment clinical breakpoints. The Europeans will, it just is gonna take some time. There's one distinction. Another distinction. So in that case, CLSI is better, more complete. It's a much older organization. The Europeans is a mixture. It's a merger of what used to be the French and the British and the Dutch and the German and the Norwegian and the Swedish and the Spanish. So there's so many different European breakpoints, committees, and they eventually settled and integrated onto that, you know, onto you cast. In fact, the French ones still exist. I'm gonna get to the French ones, particularly useful for the people in the call from Cameroon. So in most areas, the CLSI is much further developed on the veterinary side. There's one very important exception. It's this area called ECOFs. ECOFs are the epidemiological cutoff values. In fact, CLSI also has these, but they abbreviated as ECV. So ECV, epidemiological cutoff value. ECOF, epidemiological cutoff value. It means the same thing. And for such a new concept, it's unfortunate that they just went in two different directions on the abbreviation. Oh, there's gonna comment there when I went to Sweden. There are also, most ways CLSI and UCAS are getting closer, which is great. There used to be a lot of differences. Philosophical differences, technical differences. Over the years, the differences have gotten less and less. Unfortunately, sometimes they continue to go in different directions. So UCAS and CLSI both have R, I, and S categories, but they've gone in a different direction. So for CLSI, I means intermediate. But the Europeans have said, no, intermediate, it's actually really susceptible with increased exposure. So they've gone in a philosophical direction. But the saying is that if the bacteria is a little bit resistant, then the patient animal human would still get better as long as you increase the dosage. So a lot of people think that I means intermediate, and that was true. Well, it was not true when I started in 1989. When I started in 1989, I was indeterminate. Maybe they weren't sure. In 1993, 94, they renamed, they had another category called moderately susceptible. So the CLSI grouped together the old moderately susceptible with the old indeterminate and renamed it as intermediate. And CLSI still calls it intermediate. The Europeans have said, well, let's continue to call it I, otherwise everyone's going to be upset. But I is now defined as susceptible, but with increased exposure, higher dosing. So there's some areas where CLSI new casters still continue to go in different ways, which is unfortunate, okay. So regarding what is an epidemiological cut of value, this is very important, especially in the food and animal sector. The CLSI has a few of these, but UCAS is very comprehensive. Let me click on link. What do I mean by that? Let me just break up an example. And I click on the search data. Let me just skip that. Okay, search database. And let me just go into diffusion. And let me choose a drug like ampicillin. Good. Okay. And the black area, that's fine, okay. So now people ask, so now I'm moving away from the websites, moving on to the science of today's call about breakpoints. With breakpoints, people think that R means the bacteria has some resistance. And S, that it doesn't have resistance. That is not exactly correct. The purpose of the CLSI and UCAS breakpoints is not exactly, it's not to find resistance genes. It's not to find resistant bacteria. The purpose of CLSI and UCAS breakpoints is to predict clinical outcome. That's a different concept. The main distinction is there are bacteria that are a little bit resistant. And if they're a little bit resistant, the patient would probably still get better. So this is what we call clinically susceptible. So normally, like a normal E. coli maybe has its own diameter, 25 to 30 millimeters. But there's one E. coli that's maybe 21 millimeters and maybe it's a little bit resistant. What the clinical breakpoint is saying is that, I know it's a little bit resistant, but the patient will probably get better because of the high doses that we used to treat. So the purpose of CLSI and European clinical breakpoints is not to find resistance. The purpose of the breakpoints is to predict whether or not you can safely give this drug to a sick person and hope for a good clinical outcome. And you will have a good clinical outcome if the bacteria is purely susceptible or if the bacteria is a little bit resistant. So that's clinical breakpoint. So everything you've learned about breakpoints is not exactly about finding resistance. It's about predicting clinical outcome. But there are other cases where you do want to find resistance genes. It might be a low-level resistance, the patient would probably get better, but still the bacteria has some resistance. So they came up with this idea of epidemiological cutoff values to distinguish not between susceptible and resistant, but between wild type and not wild type. And what you see here in black is the wild type population. Yeah, here's E. coli. So here's C on the left, E. coli. What else have I just clicked on E. coli? Good, yeah, it even shows me the graph. That's what I was hoping. So these are the routine normal-sensitive bacteria. And they're saying the wild type is the black area. And so that's what we call wild type. Anything far above that is hyper susceptible. Anything below that is not wild type. So here you see for citrofactor-froindii, you do see a lot of bacteria down here, but they are not considered to be wild type. That's right, they're not wild type. Let me click on the graph for that. Well, actually, that's a bad example. So let me go to a nicer example. Well, I'll just go to the E. coli. So what they're saying, and there is a judgment call here, they're saying basically, if it's 14 millimeters or higher, we're going to call it normal wild type. If it is 14 millimeters or below, we're going to call it not wild type. How is that important for analysis purposes? So when you are analyzing data from animals and from food, which breakpoint should you use? Should you use the human breakpoints or the animal breakpoints, the animal clinical breakpoints, or should you use these epidemiological cutoff values? And the answer is you want all three. The answer is it depends on what you're trying to do. So this is one element of why the animal interpretation analysis, you need to be more careful about that. If your goal is to compare your animal and food results to the human surveillance program, I suggest you use the human clinical breakpoints because that's what the human people are doing. So it allows me to compare the animal resistance with the human resistance using the human criteria. So comment one, if your goal is to compare with the human reports, use the human breakpoints, then everything is on the same page. That's goal one, comparing with human results. Goal two is maybe you want to compare, maybe you're taking care of sick animals. You have a sick horse, a sick cow, a sick fish. In that case, you should use the CLSI clinical breakpoints specific for that animal. I did not, I said CLSI, not UCAS, because as I mentioned earlier, UCAS does not yet have any animal specific breakpoints. So if you're going to use the UCAS breakpoints for animals, basically you're still using the human breakpoints. So this, and the UCAS will have clinical breakpoints, but right now, if you're taking care of sick animals, CLSI is really the right way to go for the time being because they're the only ones who have done all the pharmacokinetic, pharmacodynamic data for different species as you saw. So if your goal is comparing with human medicine, use the human breakpoints. If your goal is treating sick animals, use the CLSI animal breakpoints. If your goal is really just finding resistance genes, use the epidemiological cutoff values. Let's take the very common example of you go to the supermarket, the researcher goes to the supermarket and buys some chicken legs. These chickens are dead. This is the chicken meat. So we're not trying to care of a sick chicken. The chicken cannot get any sicker than being dead, served in plastic at the supermarket. So we don't really care about the human breakpoints. We don't really care about the animal breakpoints, except as it allows us to make predictions for the living human and the living animal population. So when you're dealing with food, what you really are kind of mostly interested in is, does this bacteria have resistance or not? I don't care about the sicker animal. The chicken meat is dead already. So for the food surveillance, you're the epidemiological cutoff values are the ones that are gonna tell you, this one probably has a resistance gene. These probably do not have a resistance gene. So all three breakpoints are relevant and interesting and useful, depending on what your interest is. I've been talking a lot. I'm just gonna take a question break. Can people still hear me? I'm always afraid I'm talking and the audio went off. No, we hear you very well, a lot of clear. Okay. Any other questions right now? I'm heading towards UNED. I promise I'm heading towards UNED. So Roger's... There's a question in the chat box. Yeah, sorry, go ahead. What I was saying is that Roger's had a question on the chat box. He was asking about AST standards specific to environmental health samples, if there are any. Well, let's see, for the AST, for the susceptibility portion, no, there won't be because, you know, we're just trying to find, take care of the sick animals, the sick humans. So if you're doing environmental samples, regarding breakpoints, if your goal is to link the environmental samples to human health, use the human breakpoints. If you're trying to correlate it with animal health, use the animal breakpoints. And if you simply want to know if the bacteria in the environmental samples have or do not have resistance genes, then use the epidemiological cut-off values, which are those tables that I was just showing. So I've given you guidance on how to interpret resistance test results from environmental samples, either use human or animal or epidemiological cut-off values, depending on your needs. What I have not chatted about, because I am not an expert in this, is how do you do sampling? You know, what rivers, do you concentrate it? Do you select the media? I can write to people who can answer that kind of question. I'm gonna go to a different webpage here. Jorge Mateo. No, Dabucho. Images. Oh, there he is. I'll see if I can get one only of him. Surgery from Guatemala. So, okay, so he's in that one that I showed you. So this is Jorge right here. So he's the Dabucho lead on food safety on antimicrobial resistance. That looks like auto cars in the back, but auto cars is a bit taller than that. So Jorge is the Dabucho contact for Dabucho, for antimicrobial resistance in the food safety area. Renee Hendrickson. I think it's with an E and a Danish technical university. And if I go to images, so there's Renee. And it's a very good person, Yop Vogner. Yop Vogner, E is Dutch, how do you spell it? Vogner, I think, and I go to images. So yeah, there's Yop. So Yop is both a veterinarian and a veterinary microbiologist. So he has, this one's in English, he has another one's in Dutch, he's from the Netherlands. He is now contracted by FAO for one year to work with them for Asia Pacific, unfortunately because of COVID he's stuck in the Netherlands but he's still working remotely. So these are some of the experts, especially on the food and animal side. For environmental, I don't know individuals but these people have expertise in that area and contacts in that area. So I don't know, environmental, environmental sampling, antimicrobial resistance and laboratory processing. Here's just an article from 2016. It was small-scale poultry farming and it gets very specialized. How do you do it in these different sectors? I don't know any of these people, the University of Minnesota. So you can do some searches. If you have trouble finding things, let me know and I can put you into their correct direction. In fact, why don't I just, UNEP, I mentioned the organization, but UNEP and antimicrobial resistance. So this is a link from 2017. Antimicrobial resistance from environmental pollution according to the UN environmental program, antibiotic use, livestock, and a lot of the animal antibiotics of course simply end up in the water supply and in the environment. So that's UNEP and resistance. If I go to UNDP and antimicrobial resistance, multi-sectoral HIV, okay, this is from November, 2019. So this is the website for the UN Development Program and they have this article about antimicrobial resistance. So as you can see, the UNDP, UNEP activities are much more recent. So you see they have a 2018 strategic plan. I think that might be the global strategic plan, not specifically on resistance. So this is the whole strategic plan, but if I go to the strategic plan, hopefully resistance is in there somewhere. Antimicrobial, I'm gonna have to wait for the document to fully load. I don't see anything obvious. Oh, let me put antibiotic. Well, let me put the word resistance. No, I don't see anything, but you can look around. If you don't find what you want, let me know. And I don't always know, but I do know people who would know. The tricycle project is, so let's see. E-coli tricycle project environmental sample. Because this project is underway, so they are giving people, this project is an article about it. So for this project, I'm sure there's some kind of sampling guidance, I was now retired, but yeah, you can look around and see if you find something. Okay, other questions? Okay, we'll continue. I mentioned UCAST, I mentioned CLSI, I mentioned the French. Anybody who knows France knows that French is always a little special. So almost all the European committees have merged into UCAST and disestablished themselves. The German dean no longer exists. SRGA principle didn't no longer exist. CRG from the Netherlands no longer exist. The French still exists. So it's CISFM, Comité de l'Antibéogram de l'Associété Française de Microbiologie, Antibéogram. Comité de l'Antibéogram de l'Associété Française. Okay, so this is their document, so it's integrated with UCAST. So it's not as if they're completely divorced to a very large degree they have merged with UCAST. There are certain things however, I'll just, there's one particular example, I know there are other examples. So now that you've got, oh that's homophilus. There are certain things, so most of these breakpoints that you see in front of you, the MIC breakpoints are on the left. Oh, I'm sorry, this is quality control, I'm on the wrong table. If I keep on going, keep on going. Also, there's intrinsic resistance. All these tables do have, I skipped over that. There are other useful resources here where it's intrinsic resistance. I went over it too quickly, anyway. So, but here you see the clinical breakpoints. Let me see if I can find intrinsic resistance. So, entrensique, naturel. Yeah, so here you can see it is, they're saying that acinetobacterbomani is usually resistant to this, this and this. This is a useful educational table for what resistance is to expect. CLSI also has the same table, I don't know if the numbers are the same, but they're the same concept. Okay, so those are the intrinsic resistance tables. They're now going a lot further down. Good, so these are the clinical breakpoints. Let me just find an example. So here you see the sensitive and resistant MIC breakpoints, sensitive resistant distifusion breakpoints. So most of these numbers are exactly the same as in UCAST. There are some differences. For example, the French do have distifusion breakpoints from oxycyline, but UCAST doesn't, the UCAST has just used ampicillin. So this is almost the same as UCAST, but there are some small differences. Okay, the reason I mentioned the French is normally I would not have mentioned the French except Cameroon is on the call. So the French materials, because the UCAST documents are only in English. So the document in French could be useful. The other reason I mentioned the French document is they do have a veterinary version from 2019, but you do have to take it a bit with a grain of salt because it's mostly the same as the human breakpoints. So this document is made for the animals, but in most cases they're just copied over the clinical breakpoints. So this is the veterinary document. So it would have like aprymycin. Aprymycin is purely a veterinary drug. So for the human and veterinary drugs, what you see here are the human breakpoints. If it's a purely a veterinary drug, then they do have animal breakpoints. So for the French speaking countries, I mentioned that UCAST does not yet have veterinary documents, breakpoints, but the French do. So this could be a useful resource for the French speaking countries and for non-French if you simply want to use the tables. Good. Now, what was I speaking about? Okay, good. That's the Eccos, the French. Good. Okay. I want to mention this one thing that I came across very recently called CLUB. I'm going to say see, let me just put CLUB. No, not enough. Laboratory. No, not enough. Here it is, number three. FAO. So this is made by a group in Italy and in Italy they see Sisteme di Laboratori. So Sisteme di Laboratori, they abbreviate to CLUB. So CLUB is a lab information system for veterinary labs, not only in microbiology, I believe it does chemistry and blood bank and hematology. It does, you know, I think it does all the laboratory sectors. I only spoke with them about the microbiology component. So CLUB, let me go down further. There's an impressive map somewhere just where the map is. Let me go to, that's a news item. CLUB FAO is System of Laboratories for Africa. CLUB for Africa, that's probably the same article. So here's a PDF document. Let me open the PDF. Well, it's not the PDF yet. Download the full load PDF. So if you're interested and joined for free, well, okay, oh, it is downloading good. So if you're interested in a veterinary laboratory information system, oops, I somehow just accidentally closed the document. Let me try to, where did I go? Let me do it again. Now downloading. Good, okay. So if you're interested in a veterinary laboratory system in Africa, you know, CLUB for Africa, Laboratory Information System for the world, but you know, Erickle Danegro, he's Italian. He's my main contact now on the CLUB system. We're working on an interface so that CLUB and UNED can exchange data. And it tells you about it. So you can do a search for CLUB FAO. Let me go back to do another similar search. CLUB map laboratory and see if I can find the map. That's a different CLUBs. I don't know what that is. I think it's this one here. This is the map I'm looking for. CLUB FAO in Africa and some points of interest. Well, in fact, they put CLUB, I didn't know that. Okay, there's a PowerPoint in the right of the video. I don't want to see the video. I'm trying to find the map. So let me go back and let me just go here and open in a new window. So I wish I could show you that big because it actually tells you the status of implementation. I've done this before. Let me just see if I can go back and just refine my search a little bit. Okay, good, that's better. So Ethiopia, there it is. So in green, green means CLUB. You see there's one icon. So that's CLUB supported by IZSAM. IZSAM is the Italian Instituto Zonotico di Sanita. It's the Italian Zoonotic Health Group in this region. So they're the ones who are primarily involved and that's what Ethiopia has. And then if you have two icons like down here, that's supported by both FAO and ISAM. And then if it's this icon, oh, actually I've got the wrong thing. The one in Ethiopia is FAO supported and then the orange one, I don't see any orange right now, that support will be installed. And then the last one is CLUB is requested. So Mozambique and Tunisia have requested it. Ethiopia, September, 2017. So at some point, maybe on the phone call, maybe knows about these activities. If not, I can find out the right person from Ercole in Italy. Okay, that was the last of the web resources I was thinking to show you. If there are no more questions on web resources, then I'll move on to the Hunnet software. We'll start closing documents. All right, John, can I ask one question? Yes. Go ahead. Yeah, yeah, do we have also this sales guide line break point for parasites like malaria, resistance parasites. Right, so, okay, that's a very specialized field. So I am not familiar with it. Malaria, malaria in vitro susceptibility testing is not a commonly test performed. So I would just have to direct you to do web searches, PubMed searches. So there are no break points. The predominant mechanism for finding resistance is simply clinical. The patient does not get better. And of course, if the patient doesn't get better, it might be because of resistance. It might be because the patient was too sick and they were going to die anyway because they were too sick. It might be because they don't have malaria. You think they have malaria, you treat them for malaria, but they don't have malaria. Or they don't take the drug or they take the drug, but the drug is poor quality or it's the wrong drug. So the routine, because this is such a specialized testing in vitro, and maybe EPHI does it, I do not know, but I am not familiar with the details of in vitro testing. And as far as I know, you basically would just record it as R or S, resistant or susceptible, and not a quantitation. So in HUNA, you would just simply type the letter R or the letter S. I may not be correct and this is not my area of expertise. There is for malaria, there is a mechanism called, what is it, lot quality testing for treatment failures. This is again clinically oriented. I'm not, malaria. Failing to detect, keeping the high quality issues with testing. Well, this particular one is not, this is about the lot quality methodology and malaria, but it's not about resistance testing. So no, I don't have a good answer to that question. There is a WHO network, what is the network called? Malaria, WHO, anemic, malaria, resistance. There is a surveillance network for this. So for HIV, it's called HIV ResNet. I don't remember, let's CDC born. It might be this one. I think this one is the one supported by WHO, the worldwide anti-malarial resistance network, tools and resources. So you might want to look at something like this, external quality assurance, online courses. So you can look into those resources. That's one parasite. There are other parasites, of course, like in Africa, trapanosoma, trapanosoma resistance, is an increasing problem in the veterinary sector. But I personally do not know how they do the testing. Recently, so here you see genomics. Yeah, that's another way to do it. It's just skip the culture-based testing and just go immediately to gene detection. So I would suspect from malaria that there are PCR tests to find resistance. And then the result is you found it or you didn't find it, positive or negative. I've lived in Mali for two years and Mali does not have cows or it does not have large, most of the country has no cows because they would die because of trapanosomiasis. They cannot survive with the African sleeping sickness except in the western part of the country. In the western part of the country, they have these very small cows and the very small cows are resistant to trapanosoma so the cows there can live. Like in Senegal, if you have a cow with trapanosomiasis, they become very resistant and it's hard to treat them. There is one drug that always works but it has its own trouble, trapanosomiasis treatment. It's a drug that many of you have heard of, what is it, methylene blue. Many of you know methylene blue because we use it in the laboratory for staining images. But you can use it for staining but you can also use it for treating sick cows. The problem with methylene blue and sick cows is the meat turns blue and then you can't sell it because nobody wants to eat blue meat. So anyway, so the resistance is certainly a commercial interest in the food sector. So I'm kind of guessing that increasingly it's moving to whole genome sequencing or PCR or multi-local sequence typing. Thank you, John. For most of my career, the food and animal laboratories have had much less resources and staff and activities and samples. That's often how we're in the public health, you know, the resources have been but it's interesting now with whole genome sequencing and many times it's the food and animal people who are taking the lead because of the relevance for outbreak detection. So in a lot of the countries I go to, the veterinary labs, the food labs are the ones that first receive the whole genome sequence machines and training because of the commercial importance of food outbreaks. So I'm kind of guessing it's just moving increasingly to molecular testing. Okay, great. Other questions? If not, I'll go on to Hunett. Okay. Okay, and I understand there are some people from Cameroon on the call. I don't know. I don't speak French. I spent two years in Malia, so I'm good enough to speak French with an accent. If you want, you can choose language, French, and you'll see all of Hunett in French. Long, English. Okay, back to English. Let's see. Of course, Cameroon is bilingual. Everybody met from Cameroon speaks both languages very fluently. In fact, the main contact, my main contact at WHO in, so World WHO, Walter Fuller. No, no, no, not a sexist phonist. Let me put World Health Organization. No, I don't want, who is Walter Fuller? Fuller, well, he's here, but not a picture of him. So he's my main technical contact. You even see technical contact, two technical contacts and antimicrobial resistance. Walter Fuller, he, in fact, is from Cameroon. So if you want a national contact, he'd be a very good source. Obviously fluent in both English and French. And Letitia Gehimbere, I believe she's from Burundi. So for most of the French-speaking countries, she takes the lead. For most of the English-speaking countries, he takes the lead, but both speak both languages fluently, but they have to divide the content up somehow. So let's just out of convenience. Okay, good. So now we're in Hunett. I'm gonna click on new laboratory basically everything I've taught you so far in Hunett for humans is almost exactly the same thing for animals. Well, most of it is exactly the same. I'll show you the small number of differences. I'll click on new laboratory and I'm going to say here, okay, Ethiopia, laboratory name, let's see, One Health Test Laboratory. And I'm gonna call this OHT, One Health Test Lab, OHTL. By the way, we recently made a change. This always had to be a three letter code. We now change it to a 10 letter code so you can go longer than just three. Okay, Antibod, okay, very important. Is this predominantly a human lab, a human public health lab or a human clinical hospital lab or a human outpatient lab? Or is it a lot of human animal food environment? Human animal food, we have a lot of things environmental. We still need more guidance and advice on how to make a better software. I go to my, so far that's the only difference. Antibiotics, just like before, I'll put in things like ampicillin and I choose CLSI, 10 micrograms. I'll put in some veterinary drugs like enrolphloxacin, CLSI. I'll put in aprymycin, that's veterinary CLSI. Her method for himself, I'm not sure. It's definitely human. I don't know if it's also animal. So putting some of both, I'll put vancomycin. That's definitely human. I don't know if it's also animal. I don't know if foxes and, no, abilamycin, not veterinary. Tytilamycin, Tytilacin, okay, good. So I'm just putting my human, so there's no difference. You just choose the drugs that you're testing. Human animal food. If I click on breakpoints, you see there are just diffusion breakpoints. Well, I did not put any MIC. Let me put some MIC. Let me put Tytilacin by MIC. Now you see Tytilacin twice. D for disk and for MIC. Or I can also put by eTasks. Penicillin, I don't know if penicillin's for veterinary. Let me put penicillin eTasks and penicillin disk. I'll now go to breakpoints. So you see my disk breakpoints. I'll just go directly to species specific. So here you can see, and directly you see human, ampicillin, the breakpoints. So ampicillin, you can see here. Let me try, no, I can't highlight it. So ampicillin, you see here, ampicillin. Everything at the top is ampicillin and it's all human. And that must mean that there are no animal breakpoints. And then you see norephloxacin and you see cats, dogs, swine. So you see the different animals side of infection. You'll see respiratory, pastorella, respiratory and cattle, respiratory and swine. And you see the breakpoints are different. Well, surprise it's that. Well, it's different because of the different blood levels, the dosing, the typical sites of infection in human, et cetera. Okay, great. And I'm gonna click on okay. So who knows all of that automatically? Species specific. I see all my human breakpoints for penicillin. I see my cattle breakpoints for penicillin. I see my human meningitis. I see my horses for staff. My horses for strap. Soon it automatically knows all the breakpoints. So okay. And then once a year, you can click on update breakpoints and you'll get the new breakpoints. Panels, we do need to add on, we do need to add on some very specific breakpoints. I'm sorry, not breakpoints but panels. Like I don't have an option here specifically for homophilus, whatever that one was, but you just treat it, you just treat it like a normal homophilus. So homophilus is here. I just don't have those special ones. Some of them don't need their own special ones, but you know, we'll put them on eventually. So right now you just put the closest thing and that works perfectly fine. So as you can see for antibiotics, there really is no difference. You're just having to choose veterinary drugs in addition to the human drugs. One of the comments I mentioned about NARMS, the US system, they have agreed between the human and the animal and food, what antibiotics to test. So they all test exactly the same drugs. I think that all the drugs they test, almost all the drugs they test are human drugs, many of which are also animal drugs. I can't think of any example where they're testing a purely animal drug, but it's possible they are. But my point is that they decided among themselves what to test so that the human people and the animal people and the food people could share their data at the end of the day, by at least coming up with the core set that they could all agree on. If I go to locations, automatically, who knows these location types at the bottom, inpatient, outpatient, ICU, farm, food store. So for all the trainings I've done with you, these options have always been here. I just never pointed them out to you. So you can see a cafeteria, catered event, a food distributor, a zoo, a veterinary clinic, a veterinary hospital, slaughterhouse. So those have always been there. I just didn't point it out to you earlier. So for example, I can put in here, neurology ward, neuro, hospital OHTL, department, oh, let me, OHT, good. And department is medicine, inpatient. Diabetes clinic, diabetes, the same hospital OHT, medicine, outpatient. And then I can say farmer, brown, brown, farm. I can say McDonald's, number five, MCD five, restaurant. I can say, I don't know the name of the health, but Nile River, Nile River, I don't know the names of any of the rivers there. And I'll just call that environmental. So you can, in this list of locations, you can put a mixture of human animal food locations. I will click okay. So that's the only difference there. It's basically, it's always been there. I just never talked about the veterinary options. You don't do it any differently. I click on data fields. Here are all the human questions at the top. At the bottom, you see the animal questions, which animal species, animal type, food type. So this happened automatically. As soon as I collected here, if I say human, those questions disappear. If it's a human animal food, those questions reappear. If I click here on, for example, identification number, that is relevant for humans, animals and food. If I click on last name, that's a human question. I really don't need to know the animals first and last name, date of birth. An animal has a date of birth, but no people don't keep track of it in their laboratory database. So date of birth is a human question. Of course, I could check it off if you wanted the date of birth you could, but by default, people doing animal health don't usually keep track of the animal's date of birth. They might keep track of the animal's age. You know, how many days, how many weeks, how many months. If I go to the bottom, you see something like city, county, that's, let's see, animal type, food type. So food type is only relevant for food, market categories for food and animals. So you can, and you can change that as well. So you can put more on the left side of the screen. You can add more questions if you want, or you can delete questions that you don't need. If you work in a purely animal laboratory, you don't, you can just delete first name, last name, sex me, maybe you want to leave, date of birth you don't want. So date of admission, if it's a veterinary hospital, maybe yes, but you get to choose what you want to remove. You also get to put what you want to add. For example, we have a project with Vietnam, Animal Health. They would like to know in Vietnam, what is the region and the, the region, I lost it, there it is, the region, the province and the district. It is organized by Vietnam, like in the United States. We have cities, counties and states. In Vietnam, they have communes, districts and provinces. So they've customized it for their purpose. That's what they did in Vietnam. If I go to Norm Vet, this is from Norway, they do this for mastitis, bovine mastitis, lactation day, lactation number, type of disease, age of mother, anatomical site, there's a lot of ability to customize it, depending on what your needs are. We're doing one for Pakistan as well. I do not have that yet. Let me click on okay. Let me click on okay. I'm now going to click on save. So now I've saved it and later I can come back, file, modify lab. I can add more antibiotics. I can add more locations. I can add and remove data fields, just like I did. What happens when I go to data entry? I go to data entry, I say new data file. I say okay. And here you see the standard who not question that all of you who have not been on the previous calls have seen. Identification number, sex, age. It doesn't ask me the patients first and last name, why? Because three minutes ago I just removed it from the list. So when you remove things from the list, when you add things to the list, like you see region, province, so here you see the list of provinces. This is a Vietnamese list, districts. So here you see the list of districts. Here you see the list of their communes, commune one, commune two, I don't know what these words mean. And region, they just have northern Vietnam, southern Vietnam, central Vietnam. So we've customized it for their purposes and we could also do the same for Ethiopia. So if it's one laboratory, well, I'll come back to that after I finish data entry. These are the human questions and he's the antibiotic, ampicillin and refluxin. So this is what you've learned all along for human health. Animal health, very easy. At the top it says human, but just change it to animal. So now you see the questions have changed and now you see the animal species, swine, cattle, reindeer, animal type, meat animal, wool, wild animal, zoo animal, a companion animal would be a pet. We should change that proper word is a companion animal. Like horses, like dogs and cats, we call pets. A horse is usually not considered to be a pet, companion animal. Okay, market category, domestic import for export. So like in Argentina, they have cows that they import, they have cows that live there and die there and stay there. There are other cows that get sent out of the country. They're exported to elsewhere, especially the meat less more than the living animals. But of course they also export living animals. So these are the animal questions and these are the food questions. So we have a food type, that's fine. So here you see the FAO list. This is a list from the Food and Agricultural Organization. Cheese, fresh milk, fresh meat, spice, vinegar. It's an official FAO list. Of course you can make your own. Okay, and I'm gonna click on save. But yeah, so city, county, well those, so if I go back to the animal that I put in city, you know, I can put Northern Vietnam Central. Save, save isolate. View database, everything is here. So basically, it only took really, in this whole conversation today, you saw that who not an animal is extremely well integrated. All you do is you say human animal food on that first screen and then here you just change it to the one that you want. And let me go down and put an animal in. Let me put an animal like, I'm sorry, an animal is bacteria, E. coli. So here you see, ampicillin has human breakpoints. And Rufloxacin has poultry breakpoints. No breakpoints, human breakpoints. Pylacin, well, I think I just showed some bad examples, but you know, maybe I just choose, let me put Stephorius. Okay, good. So here there's a better example. So here you see the breakpoint for cats and the breakpoint for dogs. In fact, it's the same breakpoint, but you know, that's another matter. Okay, so you'll just see all the different relevant human or animal or well, obviously there are no food breakpoints because the food's dead already. These, everything you see here are clinical breakpoints. We have not yet integrated into HUNET the, we have not yet integrated into HUNET the ECBs, the Epidemiological Cutoff Values. We're now in discussion with FAO to put the, to put the Epidemiological Cutoff Values into HUNET as well. Exit exit, we've already started to do some of the work. So I'm going to data analysis, data analysis. And if I click on options, here we would like the user to choose between current breakpoints, veterinary, Epidemiological Cutoff Values, UCAS, CLSI, 2018 breakpoints, 2020 breakpoints. So as you can see, we put the, we put this button on the screen, but the button doesn't do anything yet. So you will see other options to allow you to select which set of breakpoints you want to do. Any questions so far? And I am not monitoring the chat box or someone else could monitor the chat. Yeah, no, we've been monitoring and there are no questions. Anise made a comment before about Vincent from the CDC. I think when you were talking about different entities that work on veterinary and surveillance, but, you know, there are no more questions. Sure, sure, sure. And I'm happy to point people to some of my contacts. And if you have other contacts, that's also great. Okay, great. I'm going to show you a few other things here. I'm going to do file open laboratory. When you install Hoonet, we automatically give you three configurations. There's one called Debiture Test Hospital. I often use that for teaching purposes. Glass, in fact, we're going to merge those two together for the Debiture Human Glass Project. We have this other one called Agisar. So I'm going to choose, instead of the, when I teach human focused groups, I just open the Debiture Test Hospital for my training purposes. But there is this one called Debiture Agisar. Let me open that laboratory. I click on data entry, open data file. And here you see, I think it's 300 isolates. I'm going to open this up. Debiture Agisar SQL-Lite database. So data entry, just like anything else, I'm going to click on view database. When you click on view database, you see here the letter origin A. These are 100 animal isolates, followed by F, 100 food isolates, followed by H, 100 hospital isolates. Let me go back to the top. You can also see that location. These are real data, but obviously I anonymized aspects of it because these are real data from a real project. So farm number one, farm number two, hospital number one, hospital number two, market number one, market number two, market number three, restaurant number one, restaurant number two, restaurant number three, restaurant number six, slaughterhouse, veterinary one. So we've given people a test database for teaching the one health approach. So here you can see the, I just made up the cities. So a lot of this has been anonymized. The specimen date, these are not the real specimen dates, tissue, and then if I go to the right, I see that this particular data file is, where's my organism? I think the organism's on the far left organism. So this particular database is mostly entire pathogens. C-A-J is campylobacter jejuni. C-A-M is campylobacter species, I think, just the species. C-C-O is campylobacter coli, E-coli, E-coli, E-coli. Enderopathogenic E-coli. Salmonella, more salmonella, more salmonella, more salmonella. And for the salmonella, I'm going to go to the right, and you can see the serotype of salmonella. I'm going to go to the right, and I see my zone diameters. I'm going to click on okay. I'm going to go to data analysis. I'm going to go to data analysis. Percent resistance. Let me put salmonella. Let me put data files, and I'll just choose that one. It's a database with 300 results. Okay, begin analysis. So here you see the percent resistance for the 346 salmonella. So for the 146 salmonella, you see the results for human, animal, food, average together. I'm going to click on continue. Let me just change that to a summary. Instead of doing the detailed report, let me do the summary report. When I do the summary report, I see average together. One row, human, animal, food. But instead of averaging them together, I can change the row to origin. So now I can see there were 32 animal salmonella, 56 food salmonella, 58 human salmonella. And you can see, this is interesting, that the food, so that the humans and the animals, it was a very similar percent resistance. The food was more susceptible. The, what is this drug? Tio, I forget what this is. It's up to you for. It's up to you for. The human and the animal is very similar, but the food is very sensitive. Chef Coraxone, this is the first time I've looked at it in this way. In this particular database, it seems as if the food is very sensitive. The salmonella from food is very sensitive. But the salmonella from the people and from the animals is very resistant. Why is that? I don't know, but you do have to keep in mind that food is complicated. The question is, where did the food come from? Where did the animals come from? If I'm sitting here in Boston and I'm eating chicken, is that chicken from Massachusetts? Is the chicken from Texas? Is the chicken from Argentina? So for this project, they would need to compare, where are the people? Where are the, so one possible explanation for this is just a simple hypothesis. It's my guess that this is a farming community where the human and the animals are sharing a lot of bacteria, but their food is imported from a different part of the country. So the food is more susceptible. That's just a hypothesis. But of course, what you could look at further is the whole genome sequencing to really do a detailed tracking of which salmonella do the humans get? Which salmonella do the animals get and which salmonella are you getting exposed to in the food? So whole genome sequencing helps in a much better way to track down the real epidemiology instead of these loose hypotheses that I am making. Okay. Also, I can do a stereotype. I can go, for example, I can say analysis, isolate listing and summary. I just want to do the summary and let me compare serotype by location. I say, okay, I say begin analysis. So, okay, and this is human, animals and food, everything together. So here, if you look at the graph, this is the graph for salmonella adelaide, the graph for salmonella agona. So, salmonella adelaide is mostly hospital number two, five patients, followed by farm one, follow, well, and the markets are all equal. Salmonella agona, I'm just seeing if I'm going to find a particularly interesting example. Salmonella derby is mostly in the slaughterhouse. Summon, let's see if I can find another. Okay, salmonella infantes is mostly restaurant number two and restaurant number three. I never even realized, I never gone to this database in this much detail, what's this? Salmonella typhomoreum was mostly hospital one, hospital two, and the slaughterhouse. So it's just generating hypotheses. Or I could look at farm number one. Farm number one is mostly salmonella adelaide. Hospital number one is mostly salmonella typhi. Hospital number two is the two, typhomoreum and adelaide plus some Ohio. Let me see if I find anything else interesting that stands out. Restaurant number three infantes. Slaughterhouse, salmonella typhomoreum and derby. Continue. That's human, animal, and food. I can go to isolates and I say isolates, I can say origin, what's origin, animal only. Whoops, let's click on that. Okay, and I click okay. And I click okay, I click on begin. And now we're doing exactly the same analysis, but this time it's only the animals. So you only see the farm and the slaughterhouse. So basically everything I taught you for humans is basically identical for the animals, except you have additional break points. Let me show an example of that. Let me put E. coli. Let me go to okay, and let me put E. coli. Let me get rid of the salmonella. Let me choose all of the isolates. Begin analysis. Okay, these were all human. One thing didn't work. The one thing that's, what I was expecting to see here is some of the veterinary break points. Let me choose, let me choose staph aureus and see if that makes a difference. No, there were no, oh, staph aureus, obviously. But actually I remember there weren't any salmonella, staph aureus in this particular database. What I was expecting to see here is some of these break point labels as animals. I don't see that. So either there's a problem. Oh, you know, I think I know why. I'm going to go to file, modify laboratory. Actually, no, I'm not sure why. Update break points. This is working. Because every time I think there's a problem when I review it after the call, everything works fine. But, you know, when something looks strange to me, I do want to double check it. E. coli, okay. Let me just choose that one month, those 300 islets begin. Okay, that's better. Now it's fixed because, you know, we were working on the veterinary stuff. So now you see human, well, that's somewhere. You're in human, human. Well, I guess these are human, anti-human. Yeah, I'm pretty sure it's correct. But normally what you would expect to see are the human break points labeled as human on one row and then the next row would have the animal break points. I'm just guessing that there are no septia IV break points for E. coli. It must be a grand positive or some other drug. So I think it's working fine. I just picked a bad example. Okay, other questions? Continue. I'm just looking at what time is it? We still have time. There are other things I could talk about. I said origin, animal, human, et cetera, but I could also go down further and say species, chicken, swine, cattle, fish. So it can be more specific than simply human or animal. If you want, I can think of more things to talk about, but if you have questions, I'd like to prioritize your questions. I have a question, John. So whenever we talk about isolates, obviously you have a pathogen that you're testing for resistance, but how about environmental samples that only account for traces of antibiotic? Is there a way we can enter those in one unit? Well, yes. Well, I mean, it depends on precisely what you mean, but let's say, if I found an E. coli, if I found an E. coli in water sample, I would say that either with this particular one's human only. Let me go to, let me open this up again to open lab, and let me just choose the one that we're doing. Ethiopia, one health lab, there it is. Open lab, data entry, that replaced what I did earlier. So for example, I would go to environmental. We don't have it customized, so you just put things where they belong. You could say where it was, you could say it's in Northern Vietnam, you could say it was in this province, in this district, and the sample type, I think we have water. You have water, so you could say it's a water sample. You could also say it's an environmental sample. I think that's one of the, well, we'd have to think exactly the best way to put it in. I'll just put water sample, and stepharius or E. coli is most designed with water, you're looking for E. coli, or of course, water pathogens, like armonis, you get it from putting your foot into contaminated water, and then you put the results in. So entering the environmental bacterial result is simple, it's no different from entering the human, and animal, and food. The only distinction is I could use your assistance on knowing what things I should put in the drop boxes. In fact, I think, let me go into that. If I search for the word water, who not actually has several kinds of water, I forgot about that. Lake water, municipal aqueduct water, sea water, fresh water, well water. So even we'd have to put in water for human consumption. So yeah, so it's really no different from what we've done. If you find some of the dropdown lists are incomplete, just let us know and we can add them to the list. That's how this list gets bigger. So there's river water. Yeah, my question was more related to when governments are trying to find reasons why a specific resistance is happening in an area, and they find traces of antibiotic in the environment. Oh yeah, that's what I thought you maybe meant, and I wasn't sure. So who not does not deal with that? Of course you can always trick who not, but in this particular case, I would just put it in the access or Excel or something. So you have a residue, antibiotic residue surveillance. I'm not sure what we'll find. Of course, whenever you have any meat, the meat should have, after you give an animal an antibiotic, you're supposed to wait a certain time period, I don't know, two weeks or something, to allow the antibiotic enough time to wash out. The main reason we don't want people to eat, the one reason why we don't want people to eat and food that has antibiotics, a small reason is because of the risk of resistance development. That's not the main reason. The main reason we don't want people to eat food that has antibiotics in it is because some people have allergies. If somebody has a severe penicillin allergy, you don't want them to have eating chicken that's full of penicillin. So the main reason we look for environmental, I'm sorry, we look for meat residues is this concern about allergies, severe allergies and a phylaxis. So this is a standard thing. Drug residues and microbial contamination in food, I guess this is an article from 1999, Drug Residues Monitoring and Enforcement. So I would just direct you to do a search on the word residues. Let me look for environmental, antibiotic or antimicrobial residues. Okay, this is from the British Medical Journal, an article, what's the title of the article? Antibiotic residues in the environment of Southeast Asia. So, let me get rid of all these cookies, go away, anyway, this one. So obviously a lot of people, public health and food laboratories have been doing this for decades, not because of resistance, but because of safety issues. So yeah, I'm sure there are methodologies and programs. It risks with antibiotic residues in the environment. So, right, and of course in the environment it does lead to resistance. I'm not so worried about somebody drinking water with a resistant, you know, gene. That's not, for all the other reasons, someone has to be resistant. Drinking contaminated water is not one of the big ones. People go swimming in the beach and rivers all the time. The main concern about the antibiotic residues in the water is that the bacteria in the water, the fish that we eat, those bacteria will become resistant and eventually this may become a human illness if somebody eats that. Or it might be a concern for the food producer, the fish producer. They're trying to grow all these fish for sale and the fish die because of resistant infection. Great, thank you very much. Yeah, I mean, you can trick Hoonet to doing this, but Hoonet really wouldn't have any advantages over other standard packages like Axis or Excel. Having said that, I don't like people doing surveillance in Excel because they're free tax, they don't type the word E. coli the same way. Have a database and they'll have like 50 different ways to spell E. coli. Yeah, no, I think there are, we could probably use DHIS too for those type of matching analysis. But thank you. Well, before that, just what you're describing, looking at antibiotics in environmental samples with a concern about antibiotic resistance is a relatively new concern. But looking for residues in the environment, looking for residues in food goes back many decades. So I would just suggest going out to some of the food laboratories, the environmental laboratories and see are there anything that they're already doing that might be useful. I think a lot of places would have their own local solution. I'm not aware of any commercial or non-commercial system that's used in multiple locations. But even if you want to do it in DHIS too, there are already people doing this for their own purposes. So you could learn from them what they have done and then copy the good, you know, copy good techniques and avoid bad techniques. We'll certainly do. Very important in Hunan. I'm going back to Hunan. I'm going to file. You see, I've done new laboratory. I've done open laboratory, I've done modified laboratory. I have not pointed out to you these other ones. Hunan, Argentina. Hunan Glass for Antimarchal Resistance. There's a new pilot project for fungi. Paho Pan-American Health Organization Blood Culture Study, Vietnam Animal Health. So my general view is that Hunan works very well with all of its default settings for hospital laboratories. But for public health labs and food labs and veterinary labs and research labs, they always want to play around with the data fields. Like when I go to new laboratory and I go to data fields, the list that you see here works very well as a default for the majority of Hunan users in the world working in the hospital setting. But people working in research or public health national labs, reference labs, or veterinary or food, very often come and modify the list and they start deleting things they don't want and they start adding things they do want. Because of that, we're now starting to put an increasing number of Vietnam animal wants of this. So if I go to Vietnam Animal Health new lab and I call this Vietnam, let's see, let's see. Vietnam, where is it? There it is, you know. And I put here, you know, Animal Health Lab, AHL, make the click okay. And I go to the data entry screen. This list has been customized for Vietnam. They want the veterinary ID. They want the region, the province, the district. They want collected by the name of the data entry person. It's something we certainly could do for everybody but they're the only ones who ask for it in a formal way. So, and that's human and I can go to animal, the questions. Well, in fact, the questions don't change because they said we only do animals. They just said give us the same thing for all. They're only interested in the animals. I can show you what they gave to me. I'm gonna go to this PC and I'm going to the C drive and I'm going to go to, where am I going? Countries, I go to Vietnam and I go to Animal Health and the specifications. Oh, I forgot about this one. So, this is from FAO. This is for the Food and Agricultural Organization. They're now starting to recommend HUNET but for the last few years, that's why I'm discussing with FAO. They have made their own Excel template. This is the list of, in fact, they've based it on HUNET. The list you see here is the HUNET list. Specimen type, this is the human list. So they made this Excel template because they thought it'd be easier for people to start putting data into Excel before they learned HUNET. I said, no, they should've just done HUNET to begin with because of course people, the nice thing is people know Excel. The problem is they make all sorts of mistakes on typing. You know, there's just even the name of the village. They'll type the name of the village 10 different ways with accents, without accents, with spaces, without spaces, with abbreviations, with hyphens. So that's the big problem in Excel, is people are not good at standardizing. Or the dates, if I go to the date, where's one of the date fields? Date, some person will put January 1, 2000. And then the next person, they'll just type it in different ways. So I don't like Excel for that purpose or surveillance. So anyway, so that's from FAO in Bangkok for RAP, the region of Asia Pacific. I've also brought together, so I'm talking with FAO for Asia Pacific and FAO for Africa. So actually I introduced them to each other. They already knew each other, but they didn't know there was all this overlap. So we're trying to come up with a global FAO view instead of FAO Africa and FAO Asia Pacific. So I'll show you the document. This is final draft June. Yeah, I guess I'll show this one requirement. Well, I doesn't matter which one for this purpose. So they sent me this document about what their wish list was. They said, John, we want three labs. That list is, this was the veterinary labs. They added on the humans. So it's now about 30 labs. And they said they want these fields. They want these dropdown lists. They wanted me to add a few things. Like Coonet did not have shrimp. Coonet did not have catfish. I learned that Coroyla is a special kind of chicken. They wanted cockerel. They wanted a sow, you know, a female pig, a swine. They wanted layered chicken. So you can see they took Coonet and then they added more things to it. They said, John, you are missing microplasma hyalpneumonia. John, Coonet is missing streptococcus NEA. So you can see here, not in Coonet. So with the collaboration, we're making it better. And they say these are the antibiotics they want. So we did a lot of customization for them. And then if I go to Pakistan, I haven't done it yet for Pakistan, but they did give us, I don't know which document is which. Annex, yeah, if I go to the Annex. So for their data collection, it's also based on Coonet. And also here you see sampling strategy. Humans, unless if you're doing a research project, there's no sampling strategy, you wait for the sick person to come to you. Of course, if you are looking out in the community, you might want to knock on households, but for typical human use, you just wait for the sick people to come to you. But of course for food and animals, there's so many options. Do you want healthy animals on farm? Do you want sick animals on farm? Do you want the animals at slaughterhouse before or after the slaughter? So these animals don't come to you, except for the sick ones, like veterinary clinic or the veterinarian goes to the farm. So there's a lot more on the food and animals side. For humans, we don't talk about sampling strategy very much, you just wait for the people to come to you. Of course, that has a lot of biases. So you might want to do a special sampling of humans, but that's in the area of research. But in the animal side, lots of times there aren't sick animals, you're interested in that. Even if there are sick animals, from public health perspective, you're not interested in the sick animals because you're not going to feed those to somebody. Whereas you're more concerned about the healthy animals and the healthy food, because those are the ones people are eating. So you need a sampling strategy. And then here are the data fields they wanted. They wanted the name of the farmer, they wanted the GPS. They want to know where is this animal, the farm because they have the veterinarian going out to visit the farms. They want the farm size. So some of these we wouldn't put into whoonad, we put into a separate file that we linked to. So that's not about the laboratory, that's about the sampling point. And then the sample details, the animal, the transport media. Think to hit one. Yeah, so this first one is sampling at farm. You can see that table one is sampling at farm. Table two is sampling at the slaughterhouse. And then sample processing volume. So this is about some of your questions. How do you get a sample of seagull? You know, you want 250, 25 grams, one gram depending on what you're looking for. What is this? This is a comparison of CVPs, clinical breakpoints and epidemiological cutoff values. So what I was telling you, they have sort of summarized here and you don't distinguish R, I and S. Well, you do for the clinical breakpoints but for epidemiological cutoff you're looking for it's either wild type or it's not wild type. They have the breakpoints that they decided that they would like. And what is this chapter? Methods for isla preservation. So this is more about transport, not about who not. I won't go into that in great detail. I'm happy to share these documents with you. So just let me know. I'd say a lot of things, but I do forget. So as long as somebody takes notes, I'm happy to send some of these resources I've mentioned. Yeah, for free to send me any documentation. Sorry, I think I think we were, I was talking as someone else was talking to. Can you repeat? It might have been Jabri, Jabri. Hello, John. Yes. Rodney here, Rodney here. Hi, John, hi everyone. I miss you earlier sessions, but in Uganda we are starting to do some MR in environmental health, in the environment. Do you know of any countries or surveillance system that advanced surveillance system for environment, for AMR? So I mentioned a project earlier in the call called the WHO E. Coli Tricycle Project. So there are a lot of people over 20 years that are doing this kind of research project for themselves. The tricycle project is one protocol that they're trying to do around the world. So this is an example of one new protocol for integrated surveillance, food, animal, human, environmental. So I would look up, you know, and so look for, if you do a web search for WHO, tricycle, antimicrobial resistance, you'll find some relevant documents, okay? And I can also give you advice besides that. I'm gonna go to PubMed. I'm just gonna do a random search. And I'm gonna do antimicrobial resistance environmental. My guess is that hopefully I'll find some relevant, I have to move my go-to meeting controls out of the way. New York State, so actually Martin Evans may know something about this. 20th century resistance, I don't know what is here specifically environmental. Plant pathogens, free range chickens, spatial exposure. The problem with environmental sample is it's so specialized. Do you mean environmental on the farm? Do you mean environmental in the, some people what they do is they look at the hospital, the hospital water supply, the sanitation area. They look at the river, they look at, and if there's a water treatment plant, they look at resistance in bacteria above the water treatment plant and after the water treatment plant in the same river and at the water and at the food or the sanitation treatment plant. So environmental sampling becomes very specialized depending on what environment you're talking about. So a tricycle is trying to be one standard protocol for the world, that's the only one I'm aware of. But there are a lot of research projects people have done over the many years but you just need to find examples. I did earlier look for UNEP antimicrobial resistance. I'm not very familiar with that website. In fact, I'm just looking at a press release now. The press release is not going to be very detailed. I'm just seeing if there are any relevant lengths. Let's see, even interesting, dust storms. Well, I don't know if they're looking at some resistance but resistance in one part of the world being transported to others, investigating the environment. So you'll just have to look around. I'm not very familiar with what documents may or may not exist, but there are obviously people who are experts and the experts might say there is nothing or they might say there is something. Here's an interesting document antimicrobial resistance investigating the environmental dimension but it's emerging issues in environmental, English, I don't know what we're gonna find here, investigating the environmental dimension. I'll just leave it at that. And someone else with time can look into these documents more. I don't know if this is a high level. It looks sort of high level theoretical but I do see several references. If I go to the very bottom, so you see there are references here that might be useful. John. Thank you. John. Did you see if there are... I'm doing a search now. Environmental resistance, third generation cephalosporins, oh, I'm sorry, ESBL, penguins and arctica. So antibiotic resistance change in the polar regions. So obviously there's an environmental component there. Did the penguins travel to South America pharmacy? So it's certainly a very broad topic. But John. But this year, I mean in 2019, there was an award from WHO, IOE and FAO on tripartite the project on MR. So some countries are selected. We have been invited also, we submitted our proposal that we didn't selected but there are countries who have been selected for this project and maybe this information can be a good source for the question previously asked. Yeah, so I've gone to this website before. There are Agnesar projects. Where can I find the projects? Well, I mean, just as an example, they used to offer these every three years. I'm not sure about now. This is all this from 2016. They have one year projects and three year projects. So they have had projects in Cameroon, in Burkina Faso, in Senegal, in Vietnam, in the animal health sector. Let's see. Devichro Agnesar projects. Maybe let me go on site agnesar.org. Agnesar projects. Integrated surveillance. I'm just trying to see if they have listed because several of them have been published. They've done some reports. I don't find it but I do have some of these reports. I'm just not sure what your public reports and what you're not. A lot of times I get the draft and I don't actually always get the final. So that's good to know. Actually, I had a question. I did see that CLAB, CLAB FAO, quote unquote exists in Ethiopia. Have any of you ever heard of it? Because according to the map it's there. Yes, we have it in Uganda. Where is it getting Uganda? Okay. That's in Ethiopia. If you don't know it, I could ask Eric Walay and he could say, he might say, oh, here's the right person. Or he might say we got started but then they stopped it. So you can't just go by it. You can't believe everything you see on the internet. But was there a comment there about CLAB FAO in Ethiopia? I don't have any information. Maybe I will look for that. Yeah, we have it in Uganda. We use it in Uganda in the animal health. And it's wonderful to have that experience because then you can tell them as an independent person, they like it, they don't like it. What do they like? What would they change? Because if I asked the, you know, if you ask the vendor, you always get the best view depend if it's a commercial system. This is not a commercial system. But you know, you wanna ask the company for their view but you also wanna get the view from some independent users. If we're after time, any other last minute questions or comments? For next time, please think of what priorities. UNED has a very nice analysis that we have not yet really discussed in great detail called resistance profiles. I've mentioned it, but this is also very relevant for the food animal human because we don't have the genotypes, but we do have the multi-resistance phenotypes. Does this salmonella and from the chicken have the same salmonella that we have in the human? The best way to know is genome sequencing. It takes time, energy, energy, expertise. We don't have that, but we do have the multi-resistance profile. So I can demonstrate this next time with the salmonella database to see, you saw it, we saw it some little teasers. We saw some things like the salmonella derby. We could see whether, we see that the salmonella derby in different places, but is it the same resistant, multi-resistance profile in the food and the animals? If it's the same zone diameters, the same multi-drug resistance, that's supportive that them being the same clone. On the other hand, if the salmonella derby in chickens is very sensitive and the salmonella derby in humans is very resistant, you know, then it's probably just unrelated genetic clones. So this is a very interesting analysis on the human side, but it has a particularly additional relevance for integrated food animal human surveillance when you do not have the genomic confirmations.