 We will introduce the micro and react teams, which have been put together as Mike mentioned. So, my name is Gisela, and I will introduce the micro team, which is stands for antimicrobial resistance consumption and burden estimation. And then cherry will take the lead on the drug resistant infections and disease dynamics. So, the micro team has led by Ben Copper and Christian Delochec, and our flagship estimates are the global burden of antimicrobial resistance, which is estimated by a team based in Oxford in which I will concentrate in this presentation. But it's really a team effort from people joining in the institutes for health metrics and evaluations and also in Australia and Croatia, and we have Jesse Commendas joining next week or she will be our newest member. So, Barney is the one who, well, our senior communications officer and public engagement officer, and he's the one who keeps us together in this effort, huge effort of collecting data, which is the cornerstone of our estimates. It's the network of collaborators have grown massively in the past five years, so I remember this map being empty in 2018, and now we have really collaborators in all continents, or data comes from a huge variety of sources from vital registration. Laboratory results antimicrobial susceptibility tests, and, yeah, literature studies as well. Data sets that allow us to understand the pharmaceutical sales and antimicrobial and antibiotic use. So, our most recent member of the team that joined ball is it's here with us in the front row, and he's been tracking households that use antibiotics when their children have infectious diseases such as restricted crack infections. He's also updating the consumption of antibacterials in across 30 European countries and national antimicrobial resistance that across 14 countries in Africa. Tilly, who is sitting in the middle row over there is looking at the most recent IQ via data, which is the largest source of information of pharmaceutical cells. Across countries, some countries even request official data from IQ via to to have their own estimates of a standard units concentrations variations of all doses of antimicrobial sold in in the countries analyzed and he's documenting all the findings and estimating the antimic antibiotic consumption. Freddie is also helping with all these estimations and pursuing the invasive non-time folder Salmonella resistance estimates into the into a paper that will be presented very soon in in in a conference. And finally, I also focus on the estimation of relative risk of resistant infections, compared against both no infection what would have happened if we didn't have any and resistant infection. But on or what would have happened if it if it was compared to a susceptible infection and the outcomes in terms of mortality and length of stay for patients. We disseminate our results in a global estimates, but also in regional estimates now published for in Europe and Americas, and we are in P reviewing the Africa and is Eastern Mediterranean results. So I now pass the microphone to cherry. Thank you. So, I'll bring you through some of the projects that we are working in in the dry up group drug resistant infection and disease dynamic and this is Ben's oak tree. And we are acorns on the oak trees. And this is just a give you a brief overview of the type of projects down the rose that research areas that we are doing and across the columns the methods that we are using and the acorns take care of different projects. And I'll bring you through some of the examples under each of the research areas we are working on so for Emma burdens. The robot project which stands for rethinking how to understand the burden of antibiotic resistance bacteria is aims to look at the existing statistical approaches to estimate the burden of MR and also look at the underlying assumptions of those methods. And one of the method, one of the assumptions sorry that is making is the core existence of different strength of bacteria, and we are using math models to look at the within host and between cohorts of host transmission dynamic of coexistence of different strengths of bacteria. And we have been contributing to the mass oblique mass application development. So this is a project with Professor direct in my doctor research unit in Bangkok, and the idea of the tool is to support the local hospital to analyze their routinely collected hospital and microbiology data. So that a mass events report can auto can automatically generated within the hospital. And recently it was implemented in over 1440 hospitals in Thailand. Then the flaming fun has been investing on increasing the capacity, the microbiology lab capacity in all resource limited settings. And so the question that we're interested in next was whether or not maintaining the active microbiology lab services is cost effective and whether it's worth for the government to keep the capacity to maintain the services. So this one of the analysis that we have done, and it's a project collaborating with the men's school of health research in Australia. Based on our model, it seems as very likely that maintaining microbiology lab service is safe costs with safe costs and safe lives. So this, the paper is in preparation the manuscript of this is in preparation. And we just started a project, trying to develop machine learning algorithms to optimize antibiotic prescription and reduce resistance. So we just started we just got our ethics approval granted to collect data from tertiary hospital in Thailand, which will then use to build the model and then use another hospital data to do external validation. So we've been working on the project with St. George's hospital. And in particularly we are leading on the component looking at the antibiotic use in hospital, trying to quantify the impact of different antibiotic prescription strategies on patient outcome, as well as to evaluate the observed antibiotic use in the hospital and then compare that against to what will be expected of the antibiotic use given the distribution of the disease in the hospital, as well as the assumption that the hospital would adhere to what the Agile Aware Antibiotic Guidebook says, and for the precise methods, NIOs and their poster will be the best person to talk to. And the previous work by Moyin, Sharon, we got the AP trial comparing the short duration antibiotic versus long antibiotic duration more than eight days. The trial is done, is completed and the manuscript is under review. And at the same time, we also did a bit of modeling exercise to look at how reducing duration of antibiotic can impact the prevalence of MR in hospital settings. And this project started in a group retreat event a couple of years ago back when we were all in Bangkok. And Renim sitting in the middle has just joined us a month ago and she'll be leading this project looking at the waiting household and between household transmission dynamic of MR using data from cluster randomized control trials from Burkina Faso and DR Congo. Sean, a project with Professor Paul Newton, looking at sub-substandard and falsified drugs. And Sean will be leading on the analysis looking, quantifying the direct health impact of SF medicine, and also his paper looking summarizing different possible mechanism of SF medicine on spray of MR was just published actually very fresh just yesterday. And the pre-Marvera project which stands for predicting the impact of monoclonal antibodies and vaccines on MR. And it's essentially the aim is to evaluate the effect of vaccine on reducing MR. So we'll be building models and fit that into cost effective analysis. And this is other examples of projects looking at emerging infections. This is a project by Ben where we'll estimating the burden of hospital acquired COVID using acute hospital data from the UK. And the home message is there's around one to two percent of people who admitted to hospital will acquire COVID will have hospital acquired COVID. This is the second wave and that's before the vaccine implementation in the UK. And also, you will be hearing a talk by Mark, our diffuse student just before lunch about his work on respiratory infection and he'll be also using trial vaccination to ask questions on treatment impact of treatment during outbreaks. And here are some of the direction future directions will be continue working on MR modeling, and there will be a project. And now it's preparing the proposal and what it's about to submit collaborating with the UK HSA looking at a hospital network model for MR. And there are a couple of projects that will be happening on relating to trial designs. We are recruiting a postdoc to work on Lhasa fever vaccine with Professor Sarah Gilbert's group. So if, if there's anyone interested potentially that you know, please spread the news first. And also collaboration with a Luvara from Professor Mike English Group looking at MR in the new net. And we are also hoping to work on genomic data and see how we can use leverage such data to support interventions to control the spread of MR. Thank you.