 I'm very happy to start this day, where we're going to be sharing a lot of stories from the global community around DHS2 and the global COVID-19 response. So I'll get things kicked off with a small presentation around how we've achieved speed and scale through our global goods and local innovation. And then most of today will be dedicated to our various implementers in our global community to share their stories. So a couple of snapshots here, but today I'm just very happy to be able to share and I'm having a little trouble with the changing of the slides. Okay, so our global deployment of DHS2. So to open today, I will talk just a bit about our global goods and also around our local innovation. And so this is built around a long history and the foundations that we have built as a community over the course of many years. Then I will go into a little bit about how we have highlighted the local innovations that are at the very heart of how we have worked for decades and looking at a persistent focus on meeting the needs of end users in countries. So looking at district level, national UNOZERS, but also where health services are delivered in facilities and communities. So this first slide, it really is intended to just highlight what we consider to be our global public goods. So there is the DHS2 platform itself, the DHS2 Android capture app that has fast-tracked minor releases and critical support for the global deployment. We have our COVID-19 metadata packages. So this is a part of the body of work with the health organization around taking global standards and developing DHS2 products to help disseminate those standards. And last but not least, we also have our DHS2 Academy curriculum and that includes end user training templates, remote training support and moving a lot of these in-person academies into online webinars and academies. So a lot of innovation in how we continue to support countries during the time of no travel. So taking a bit of a step back, not as far as the birth of DHS2, but at least back to 2014, we had a lot of learning from the Ebola outbreak response in West Africa. And I believe it was the Ministry of Health in Liberia who first contacted UIO to send a delegation to the country to see how they could support the use of DHS2. So this was the system that was already being used in country and many users were familiar with it. And we also learned that even with the health system under duress in several of these countries during the Ebola outbreak, reporting into DHS2 was sustained. So we still had access to data through an established system. So what we've learned is that we need to be strengthening existing systems when these crises happen. We shouldn't be introducing parallel systems. We know that we need flexibility to facilitate these rapid transitions between detailed case-based surveillance and line listings when the outbreaks start to happen and then also being able to move to aggregated daily data collection when the burden is just too heavy. We know that we need simplicity collecting only the data that is needed to ensure that we have good quality data to be used and that we're not overburdening the healthcare workers from their real task which is providing the healthcare and the response. We know there's a lot of work to do around decentralization. So distributing the workload to subnational levels to facilities and even to community health workers. And these are the people who are really the source of data when it comes to early warning. We've learned a lot about data standards, the extent to which we can preset these and be able to disseminate these so that we can mitigate the proliferation of tools in the field and also be thinking about data exchange principles long before there is an urgent need. And lastly, we've learned a lot about making sustainable gains. So using these emergencies to step up surveillance capacities. So not just being able to respond to Ebola but to be able to respond to the next emergency outbreak. So we'll hear from Sierra Leone today. They have really honed their experience in disease surveillance and over four years they've been scaling decentralized case-based reporting. And they've recently introduced DHIS-2 as a national electronic case-based disease surveillance system. It helped them to detect Lassa fever outbreak in 2019 and it's being further leveraged now. So we have some really great stories around how countries who have made this happen. And lastly, this is also work that had sparked our first CDC partnership to further develop DHIS-2 and the software to be able to respond to the functionality that's needed for disease surveillance use cases. In 2016, the health data collaborative was established. This was a response to the development of the sustainable development goals. So this platform aligns technical and financial resources. So many, many partners that we work with and others, Gavi, Global Fund, Norad, the Gates Foundation, they have really brought themselves together around a common framework for strengthening routine health information systems. So this gave us a global platform to align our resources and really be able to dedicate several years of work into helping countries to improve their own M&E systems for health and also being able to emphasize that national ownership of those systems. In 2017, the University of Oslo became a WHO collaborating center for innovation and implementation research on health information systems strengthening. So we've partnered with the WHO for many, many years, but this gave us a place to work where we could expand upon the WHO Health Facility Data Toolkit and be able to develop these DHIS-2 metadata packages. So it's like an extension of those WHO standards that can be installed into a country's local DHIS-2 instance. So we're really looking at using DHIS-2 as a platform for disseminating these types of data standards. It crosses facility data, but also with linkages around civil registration and vital statistics, as well as integrating other types of data, mortality databases and population level data for better analysis. In 2018, we saw some major investments in malaria elimination systems. So the Gates Foundation launched the Digital Solutions for Malaria Elimination Project, and that helped expand the DHIS-2 core platform, as well as the DHIS-2 Android Capture app with new functionality that supports malaria elimination surveillance. And much of this functionality has now been repurposed for COVID-19. So many of these disease use cases, the software requirements are very similar. So we're looking at one screenshot here, which is some enhancements to relationship analytics that were built out to analyze the relationship of malaria cases with foci in an elimination context. But now we're able to re-conceptualize and repurpose that functionality for COVID, as well, using those same principles to be able to link index cases with their contacts and with clusters of cases. So when we develop in a generic way, much of the functionality has a life and a benefit beyond the specific disease use case. We also have a screenshot here of the Android Capture app, and a lot of improvements have gone in here to the Android app to really help the operational activities among field workers and helping them to answer the question, what is it that I need to do today? Towards the end of 2019 in Athens, there was an advisory group convened with experts from WHO and CDC on surveillance, and they joined a delegation from the University of Oslo and our HIST partners. And this entire week was designed to really develop and understand the requirements for vaccine preventable disease surveillance. And so this work, we are working on vaccine preventable disease case-based metadata packages and aggregate IDSR packages, but these design prototypes actually became the foundation for our COVID-19 metadata packages. So we were able to pull on years of expertise and experience, and many of these designs have already experienced some field testing and some validation in countries like Sierra Leone and Uganda. We will also have Dr. Ellen Poy, who will be sharing how the WHO African Regional Office has capitalized on this with many, many countries in Africa using DHIS-2 already for the aggregate IDSR reporting and being able to implement a surveillance system at a regional platform level. So now we can skip forward to 2020, this very interesting year. You will hear from Pamad next around Sri Lanka, but I wanted to emphasize here that from January, Sri Lanka customized DHIS-2 for COVID-19 surveillance. So there's this huge importance of having a global network of regional in-country expertise. And there are many countries who are able to move faster than we did at the global level to mobilize their systems for a COVID-19 response. A few more that come to mind include Bangladesh and Indonesia who were quickly able to update some of their aggregate daily reporting forms, as well as Myanmar who was able to update an event-based patient registry to capture COVID cases very early on. So this type of national capacity and ownership is critical to what we see as a successful response. March 11th, 2020. So this is the day that we officially released our COVID-19 metadata packages. And this is quite interesting because we have our tracker implementers here, Sherjeet and Yuri and Enzo at the Ghana Tracker Implementation Academy in Accra during this time. So they were working day and night to develop the first version of the COVID-19 case-based surveillance tracker package. And it also gave us this possibility for real-time validation because we had several country teams at this academy bringing their critical insights from their own implementation experiences to help us understand if this design is something that matches what their experience shows about what works in the field. And so all of this happened just as the academy was cut short and borders began to close. In April, 2020, we saw the Norwegian Municipality Organization launch DHIS-2 for contact tracing. So you'll hear a little more about this in one of our parallel sessions, but it just emphasizes that the challenges we face are not unique to low and middle income countries. There's a lot to be learned from the disease surveillance expertise across Africa and Asia and Latin America. So there's some really interesting use cases here at Municipality, a very more local level organizations who had switched from using Excel to DHIS-2. And finally, here we are in September on a virtual conference because we can no longer meet in person, but you can see that 36 countries have now operationalized DHIS-2 for COVID-19. And when I say operational, we mean that there's actually data actively being entered into the system for analysis and use. So I think at least from my experience is one of the fastest scale-ups I've really ever seen. And I think based on this presentation, you can see that it was really, this was built on years of collaborative work with our global community that helped us to respond. So now let's switch gears just a bit to tell a little bit more about some of these global goods. So there's the COVID-19 Digital Health Data Toolkit. So this was designed in a modular way. We have currently five different modules, case-based surveillance and laboratory reporting. We have a points of entry, screening and follow-up program, a contact tracing program that has relationships built in to those case-based surveillance. There's an outbreak line listing for when some of the caseloads get too high to do proper decentralized case-based surveillance. And then we also have daily reporting of cases of transmission status at some national level and key resources. So we have designed with the idea that we should be optimizing data collection and field-based workflows at the bottom, but also we need to be having a rapid data-driven response at the top. So being able to bring all of this data together and comprehensive dashboards to support the analysis and use. I'll talk a little bit more about what's actually in the toolkit. I think many of you have heard of the WHO metadata packages. So these are installable JSON files that contain all of the preconfigured metadata. And the idea is that every country doesn't need to start from scratch and redesign DHIS too. We can provide a bit of a template and we can match that template to what the global standards are. And in this case, this was all aligned to the WHO COVID-19 guidance, the technical guidance that was published publicly. So at that point, a country can take this package, they install it in their own national instance, but then they're able to adapt it to their own use cases. So it's a bit of an accelerator that way. In the interest of data exchange, we've included coded mechanisms for the WHO case-based data dictionary. And we are looking at SNOMED, global patient data set codes being incorporated in the future. We also supplement this with documentation. So detailed installation guides, how do I actually get this into my instance? System design guides that tell you how did we make certain design decisions based on the technical guidance we had and what we know about design practices. And finally, all of this, we need to be able to find new ways to train users in the field, particularly with travel restricted. So we've been working with a lot of these end user training templates to make it a little more ready to go. And I know many of our countries have been supporting virtual trainings down to facility and district level. And these are also developed in collaboration with our regional HIST groups. So we have a lot of field-based knowledge being input into these products. So these packages, as I've mentioned, the whole point of collecting data is being able to use the data. So we really want to emphasize having data at the fingertips of decision makers. So all of our packages come with DHIs2 dashboards out of the box. To the best extent possible, they are being updated for emerging COVID analysis practices and new KPIs, particularly on contact tracing that are coming on board. But we've also looked at expanding existing WHO health data tool kits for DHIs2. So for example, we've had a cause of death package for a while that supports the WHO SMOL codes to be able to support countries in better capturing the medical certificate cause of death data. But we've also expanded this with some prototypes for rapid mortality surveillance. So where it can be very difficult to capture cause of death in the community, we have a more simple prototype that allows capturing all cause death and being able to do key analyses around excess death, particularly when we know that it's very hard to get good numbers about what deaths are truly attributable to COVID-19. We're looking at the expansion of non-communical disease registries and trackers with WHO and others. And these will become really critical as the analysis of comorbidities and really understanding what are the vulnerabilities in different populations are as you plan COVID response. And lastly, we have some really great sessions around secondary impact monitoring. So this is around measuring COVID-19 impact on health service delivery. So we know that COVID-19 cases and deaths are not the only ones affected. There are many people who are not receiving the key health services they need. So Global Fund and UNICEF and even at country level have begun to explore some frameworks about where we can use this very robust HMIS data that has been supported and strengthened over many years. It provides us a baseline for doing these types of analyses. The last little piece of my presentation is going to be the focus on local innovation. So I had told you we were able to achieve scale rapidly around using these global products where I've showed you but also being able to really tap into a very long tradition of the University of Oslo through action research. So again, this is the idea of being able to learn by doing and we develop a global product. So say that is the DHIS2 software release but then through local use we're understanding how our country is adapting this and what are the new requirements that they need. And in the perspective of COVID-19 what are those new emerging requirements as people are really testing out this platform for new use cases. And it's this virtuous cycle of global standards coming top down and local innovation and best practices moving up that helps us to really develop a product that's going to meet the needs of our end users. So I'm going to share a couple of examples here around how our national and regional experts have expanded and innovated on the DHIS2 platform but these are really just teasers for some of the other sessions today that I hope you'll be able to participate and learn more. So you have a snapshot here on this is a custom dashboard that was developed through web apps. DHIS2 has really invested in leveraging itself as a platform and making the app framework as a way for countries and implementers to be able to innovate more easily on top of the core software. So here we have a custom dashboard used by the LOW-PDR epidemiologists and in their emergency operations center for being able to analyze more quickly the relationships between index cases and contacts and where those cases are moving around the country. I think one of the most interesting aspects from the global package was the wide adoption of points of entry screenings. So we've talked about case-based surveillance for many years, a little less emphasis on points of entry, but this has really taken off with incredible innovative examples from Sri Lanka, from Uganda using Android apps and travel passes at the land borders from Guinea-Bissau generating travel passes based on validated laboratory surveillance data. So this is really fascinating and it shows a bit of an ability to be able to cross sectors because points of entry, they are generally not controlled by ministries of health. So we are seeing sectors work together and bring data together in a way that we haven't really seen before. For many, many years, the ability to link case data with laboratory data, so laboratory data coming from one source, case data coming from more of clinical points of diagnosis, it's a challenge to link this data not only in low and middle income countries, but also in Western countries like the U.S. So we've seen some very interesting solutions that really support complex workflows and they really are complex workflows. So we have some presentations from Rwanda Ministry of Health and from Hismose Ambique in Guinea-Bissau, how they've developed some tools to be able to bring these different data sets together. And last but not least, we've seen the importance of getting data out of DHIS2. So data from DHIS2, it's a source for national program planners for the national response teams, but also we need to be able to support risk communication to the public. And so increasingly we are seeing solutions and innovation around how to better get that data out of DHIS2 and put it out there for communities and the public to understand and feel confident and feel some transparency with what's happening with the epidemic situation in their country and locally. So I will stop here just with a small reflection after the Ebola crisis. So there were ministries of health and finance in Ebola-affected countries in West and Central Africa. They convened in Geneva and the Lancet wrote, the lesson painfully learned shows that we don't need another vertical program for a specific health condition or challenge. What we need is to build resilient health systems. So I've summarized a bit of our roadmap this year, but what I'd really like to emphasize is that we are very much on a pathway forward together. And when we close with a plenary session at the end of the day, Gavi and Global Fund and CDC will join us to share some perspectives as global partners around how we can work together to really build resilient health systems and to be able to know that when the next emerging disease X appears that we're going to be ready for it. And so with that, I thank you very much for letting me open the day and I'm very pleased to hand it over to my colleague Pamad Amarakun, who will share the experiences, the pioneering experiences from Sri Lanka in developing DHIS-2 for the COVID-19 response. Thank you. Thank you so much, Rebecca. So good morning, good afternoon, good evening, everyone from wherever you are joining. I'm Pamad Amarakun representing his Sri Lanka and I'll be talking briefly about COVID-19 response with experience from Sri Lanka. So let me just start with some background about history. We are all aware that COVID-19 started off somewhere in late December. In fact, on 31st December, China reported it's the first cluster of COVID-19. And then with regard to Sri Lankan context, it was not about whether we would get COVID-19, but we were more worried about when we were going to get it because we had so many Chinese tourists and employees who were working in Sri Lanka and we were not sure like when we would be getting this disease into Sri Lanka through one of the tourists who were entering the country. So in fact, Sri Lanka got its first case of COVID-19 on 27th January. And interestingly, by the time we got the first case of COVID-19, we had already thought about what to do with regard to information collection and surveillance on COVID-19. So how it all started was on 20th January, 2020. So on 20th January, so about one week before we got the first case of COVID-19, we had an initial discussion with the Ministry of Health Sri Lanka. So what did they ask? So they had few specific concerns about setting up the information system because the main issue was that we did not have an integrated disease surveillance system, digital one, which connects various institutes of under the Ministry of Health as well as other stakeholders such as immigration department, the ports of entry. So one major issue they had was to share this information that is coming with different stakeholders. So these stakeholders include Ministry of Health stakeholders as well as non-Ministry of Health stakeholders such as those who are there at the ports of entry. And then whatever it is, like we were certain that we are going to get this disease in like a few days probably. So they wanted something to be developed really fast, not about weeks, so usually it takes weeks, but this was to be developed in few days. And then of course, usually the Ministry procurement process even when it comes to information system, it's a really lengthy process, but they did not want to get that process involved, but rather it had to be like a really fast procurement or establishment of the system in the Ministry setting itself. And then of course, they were not sure because nobody was sure, like we are talking about early January, no one really knew how the disease was progressing and which I mean, like when you consider about a country, what's the scale it will be affecting. So they were not sure where we are going to implement the system. So what they only knew was like we may start with a few facilities, but we may really need to scale it up as time passes. And then of course, the scope of requirements, we were not sure. I mean, it could have, it could change rapidly. So you can't go for a detailed SRS at the time of designing the system, but it has to be agile that there'll be requirements that are changing and we had to incorporate modules even after the system has been set up and is functioning. And then because we had so many stakeholders joining and entering data, sharing data, weaving data, they wanted some sort of access control so that say, for example, a particular department, they will only have access to a particular set of analytics or data. And of course, like the training, because now it was COVID-19, we could not get people gathered at training centers. So the training was one major issue. So they preferred a platform where the health staff was already having some experience. So the training, the learning curve of the system was not that great. And of course, there was some concerns whether they would prefer to have some mobile data entry as opposed to entering data from a laptop or computer. And also to integrate with existing information system because like already they knew, like we had to start off with somewhere about the port of entry, the airport, so that itself had its own information system. So there was scope for integration as well. So, I mean, after the discussion looking at all these requirements, what we felt was DHIS-2 was the ideal candidate even though at that time, talking about third week of January, this was not tested anywhere in the world. But then again, we took on the task and in like three days, we were able to get the first version piloted. And in fact, what you're seeing now is an extract from one of the popular newspapers in Sri Lanka where the Director General of Health Service informs the parliament that this kind of system has been set up and we have piloted in and it's ready for implementation at the ports of entry. So in fact, like there was so much of support from the ministry administrators all the way up to the Director General of Health Services in getting past approval to the implementation of this system. And then about the community, right? So this, as you can see is a screenshot from the DHIS-2 Slack. In fact, this was on 29th January. So this was in fact my official, the first official communication with the DHIS-2 community. So what I did was after having the first pilot, I mean, so we were ready around 25th January, I informed the community about what we have done in Sri Lanka and that we have launched it. So as you can see here, it was that time it was novel coronavirus, it was not COVID-19, this January. So with this communication, of course I received so much of feedback from the DHIS-2 community, from University of Austria especially and even from other, his notes as well as the community, right? So about the functionality of what we developed. So it was mostly about customizing DHIS-2. So initially the first version, it was about the port of entry, which was just a DHIS-2 simple customization. But the thing was, it was getting more and more complex because there were so many user requests that we had to cater because of the urgency of the situation where we had to think of some custom development. So this custom development was required for certain functionalities, which is not possible by using code DHIS-2 applications. Sometimes there were like the customizations we have already done, which also required some kind of development on top of it. This was where in around mid-March, we had a hackathon developed and so many freelance developers, Sri Lankans who were joining from Sri Lanka as well as outside were gathered along with all these stakeholders mentioned, including the government ICT agency who did a major task, as well as the University of Oslo who provided support and guidance all throughout this process. So more about this hackathon and the local innovations in this symposium that we are having on local innovations. But we had the customization plus the development component also, which ran parallel. So what you're seeing here is the entire ecosystem of the modules that you have in our COVID-19 surveillance system. So the first component that was developed, of course, was the point of entry program. So this was very simple initially where we wanted all the tourists who were entering the country registered there and that data to be available to the field health staff so that they can perform a visit while they are in the country within the next 14 days. But then again, it was always changing. The requirements were changing. So by about first or second week of March, the country's policy changed and they mandated everyone who was entering the country should go for mandatory quarantine. So everyone was put on government quarantine center. So this was when they wanted the system to be customized so that all quarantine patients or persons information should also be there in the system along with what's, I mean, they are their symptoms and the tests they have undergone. So this is where the quarantine health center information module also came into the system. And thereafter, of course, by about the third week of March, we had a huge rise of cases. So this was when they wanted to have the case information also integrated into the system and the suspect information. And then also to go along with this, they wanted different kinds of mappings about case to suspect. So these components also had to be developed in addition to the routine laboratory and the hospital information that they've required from the cases. And then, I mean, it's the same in almost all the countries because of the enthusiasm, a lot of people try to contribute to the ecosystem of information in COVID-19. So there were so many third party applications, mobile applications that were coming up. So the government also required, the ministry also required some kind of support to integrate the information that is coming from these third party solutions into the system. So we had to work on that part as well. And then once we started seeing a sudden rising cases as well as the deaths, they were more concerned about having an idea about the ICU beds, the level of ICU beds. So this was when the ICU bed monitoring, another custom application was developed. And then we had requirements about, you know, like some barriers about taking too much time to enter data. So this was when other integrations such as integrating with the immigration system was required on top of already existing functioning modules. So I just wanted to briefly highlight, it's not about just one module that was there in the system, but it was catering a wide range of requirements. And what you're seeing is the timeline of how these modules were developed along with how the COVID-19 progress in the country. And you may be able to see that from late January and by about the late April, within that three months time, we were able to get all these modules developed as well as share it back with the community. So what you're seeing here is a contact mapping visualization, which is of course a custom application, custom web application be developed based on the requirements, because the core DHS2 system does not support this kind of visualization where you wanted to see how this is progressed from a confirmed case to suspect. So this mapping was required and this was done, this was made in fact as an output from the hackathon we had. So more about this in the next symposium. But what I wanted to highlight is that this local innovation about the contact mapping visualization, we share it with the community and the University of Oslo took it up and identified the generic requirements and with the help of the University of Oslo developers as well as local developers, we were able to come up with this generic contact tracing application, which was then released in the DHS2 app store. So this was in fact contributing back to the community. And then again, we further expanded the contact tracing application by like they wanted to check where are the persons, if someone is confirmed, they wanted to check where this person has visited in the last two weeks. So for that one, they wanted to take data from mobile tower, of course with the consent from the patient as well as with government authority. So there was an integration component that was developed which kind of pulls data from this mobile network information to the DHS2 which shows where the person has traveled in the last two weeks. So this was again another custom development we did on top of the contact tracing model. And then again, this is the ICU bed tracking which is in fact a very simple tracker implementation but due to the prevailing situation where they required some custom visualizations and very simple interfaces, we had to develop this ICU bed tracking simple web application within like two weeks time. So there are a lot of challenges in this entire procedure. The thing is like the biggest challenge we had was uncertainty of requirements because we were not sure we never thought that we had to incorporate all these modules when we first developed the initial version with the port of entry program in late January. But now when you look at the system, it has about six or seven components and some of them are even custom made. So the requirements were always changing and we had to be agile to the changing requirements. And then sometimes because the health staff was too much burdened with data entry and even at the ports of entry, they had other tasks to attend to so we could not allocate too much of time for the data entry. So for that one, there had to be some solution. And then again, there are a lot of other requirements that were coming which were not possible using the DHS to co-applications. This was also a challenge we had during the initial period. And the biggest task, one of the biggest tasks was training of end users because not only the other biggest challenge with the COVID-19 was that mobility of everyone was limited. So we could not bring health staff to usual training centers that we were used to do. So we had to explore other means of training and that was a major task in the first couple of months. And then again, there were a lot of applications, third-party applications. There were a lot of mushrooming of applications, but some of them, they really had a lot of good things about them and we had to integrate with them so that there has to be some kind of data sharing. So we had to think about integrations. And then the strategies, a lot of them. The first strategy, of course, was using the DHS to itself because it was a customizable platform. Had we grown for a custom-made third-party software, with all these changing requirements, it would have been a nightmare. So it was one of the best decisions that we took early in the early days of COVID-19. And then we had to integrate with existing information systems in the government sector, such as, for example, we had the immigration system which already had passenger information there before the flight landed in Sri Lanka. So that information, we had to push to the DHS to instance so that they only had to enter data about the health conditions. And then again, of course, what we did was, we designed a few web applications. Of course, with the concurrence of the university was slow because like the thing was, there was too much of expertise required for a totally new set of developers. And without their support, of course, this would not have been possible. But with this web application, we were able to quickly address the issues that were not possible with ODHS to applications. And then we had to support third-party solutions. And also we had to think about the country, had to think about the roadmap for the personal health application. So there were some discussions about the country's information system as well. Now that the country is even thinking about going for a central HMIS, which gets these all the vital indicators from all the programs so that dashboards are visible, which we didn't have before. And then of course, the training. So we used so many technologies, especially the Zoom. So we thought it would be a very difficult task, but it was not so. So we mainly use Zoom platform for most of the online training. And then for troubleshooting, we had to use remote desktop software like TeamWeaver. So these kind of tools, which we didn't use much before, especially to provide end user support and training, we had to use during the COVID-19 era. And of course, I must definitely highlight the multi-sector collaboration because this was not just a task possible with health ministry or the history Lanka. There were a lot of parties, the government entities, as well as the private sector and the freelance volunteers, as well as the health staff who were always there to support the information system. So I would just stop here, but I must really thank the health staff of Sri Lanka without whom this would never have been a success. So thank you so much. Yeah, thanks very much, Pamod. Take it on from Pamod to also again, share experience from COVID response with support of the HIS too. This is a presentation from Uganda, HISP Uganda, appreciation to a team behind the COVID response support at HISP Uganda. Pamod and Rebecca have shared Uganda has not been also left behind in the COVID response. My background picture is at the border of Uganda where we did emphasize use of DHHIS too for COVID response. For Uganda, I'm going to focus on our approach to all this. Our approach was mainly to help with the data collection at source and be able to visualize. And so is the map, is the dashboard I'm sharing here that Rebecca has highlighted here before as a local innovation to be able to support the COVID response. So what you see here as from our government server is a replica of what is currently being used at the command center to be able to respond to a response. And what it does is it allows to bring data from different sources, from different tools that is all reported into DHHIS too and display. And particularly what you would be able to see that the high level visuals that really allowed the decision makers to be able to take a decision on where and how the outbreak is progressing and what measures need to be controlled. And you will also be able to see that we do support quite a number of pillars in the COVID response. For example, you have the laboratory, you have the surveillance, you have the case management and logistics dashboards. And again, you also, our point of key, point of entries have been our most focused and we will see data scrolling down and showing the different data from the different points of way. So this attempt is to really bring almost near to real data representation at the high level senior management for COVID response. So our journey started way by looking at what the preparedness in terms of data management, in terms of data transmission, in terms of data collection were laid out by the ICT COVID response pillar. So you will see that this picture or this diagram of flow shows the different sources and how data is exchanged and interlinked with the different response pillars and also visualized. So here I will highlight more where the DHHIS too has played a key role in terms of capturing data and also in terms of being able to visualize. So one of the key areas in this COVID response was the self-reporting or the reporting from the community. And that was through the rumors, alerts and signals as many of you may know them as. So particularly at this point, our DHHIS too allows us to receive SMSs from anonymous users. And for particularly for Uganda, the system was being configured to be able to allow community, Uganda to be able to send notification to the send pro team to be able to follow up. So under this point, the DHHIS too again was configured to allow that messages around COVID symptoms, COVID suspects would be reported by the community. And this also worked alongside with other tools that were put in place. Another area that was key to COVID, that is very key to COVID response is the different sources where this data is coming from, where the suspects are. And particularly for this, we're looking at the points of entry, which is our borders and airports, the health facilities where the patients would have contacts and the community, plus the quarantine centers for those who have probably been exposed and the isolation center for those who are positive. And at this point, we were able to reconfigure our EIDS as we called it the DHHIS to tracker to be able to support the investigation at this point. The other key area that we also have supported with the DHHIS too is the investigation and outcome in the isolation centers. Over here, you will be able to see that for all the isolated cases in data is collected from these cases, aggregate and individual level. And the DHHIS too has been configured to be able to support that. And lastly, we were also able to allow the DHHIS to visualize this data integrated from the different systems. And so the dashboard I shared. As cardboard shared, when everything shut down, of course, for Uganda, the borders did not shut down because we highly depend on imports through load, by load from Tanzania and in Kenya. So in the picture here is one of our busy points of entry where we deployed the DHHIS to Android tracker to be able to capture information real time from the travelers. So at this point, the tracker is where we really started from in terms of our COVID response implementation. And slowly by slowly, we've been able to reconfigure our tracker to support investigations at the health facility, community, hunting centers and the isolation. And purely here, we used the Android DHHIS to be able to collect data in real time. The alert notification process was continued where the command center and the teams responsible for follow up were able to follow up the notifications or rumors that were coming through the system. Again, at the points of entry, at this point, we are able to collect all the information from the travelers regarding their bio data, regarding their travel history, science and symptoms and automatically integrate it with the lab information management system so that we'll be able to reduce the lab, the results turn around time. And over time, the East African has also developed a track driver tracking system that we've also been able to integrate our EIDSR with. And then also for the community, the module has also been configured to allow for investigations within the community and also the returning Ugandans who were in abroad. During the, in the beginning of the COVID in Uganda at the borders, we had a process that would allow a track driver be sampled. And after sampled, it would be allowed to travel. And once the results have come back, then you would have to locate where the driver is so that we can be able to either isolate them or give them the results. In case they're positive, then they will be isolated. So we did develop a tracker app, DHS2 integrated that allowed us to be able to scan the QR code for this driver on different checkpoints so that we were able to identify whenever the results were received, we would be able to identify the point at which this driver would be. And here we use the GPS coordinates of the scanning points so that we can be able to locate where the traveler was. And this would give us the point and the time when the driver would be at that station. Slowly with the outbreak now shifting to more numbers and then getting to more aggregate cases and also being able to expand to more COVID treatment units. We have also remodified our implementation to be able to support investigations and outcomes within the treatment site. And at this point, we're able to capture the details of all the patients who are in isolation and then also at admission but also during admission and also at discharge. The DHS2 has slowly become the central repository for data from different systems. So now it serves as they have for when data is supposed to be analyzed and picked into other systems or analyzed and also displayed on the dashboard as we've shared. In terms of visualization, we use a combination of visuals. We do have, of course, the core DHS2 dashboards that do help mostly at the implementation sites for the teams to be able to appreciate the data and see the progress and also be able to identify some of the challenges they have with the response. Over here, we are moving now towards a tool built on the same dashboard to help the command center to be able to narrow down and drill down to the individual level. For example, for any given CTU, which is a COVID treatment unit, we're able to see the cumulative numbers in admissions and death and more information. And also we're able to drill down and be able to see individual level data for the patients. So at this point, once you click on the view cases, you are able to drill down and see the individual data in the line list but also as an individual patient chart. And lastly, in terms of the achievements we've done, we've been able to create a repository for COVID data. And as you can see here, we've quite a number of data sources and datasets that have been created both at the individual level and aggregate level that are currently being updated routinely either by direct import of the data into the system or direct entry of the data into the system, but also using exchange from other systems, especially the lab and ODK. With that, I come to the end of my presentation and I wish to appreciate the teams that have been supporting this implementation not to not forget Minnesota Health that is at the forefront of this response and use data from the system to be able to make decisions and they manage the outbreak. Finding from CDC through infectious disease control that supported the development of these pieces and the rollout of the system to many points of entry but also supporting the team that has been supporting the Minnesota Health to build a dashboard and not forgetting the HIST team that has worked tirelessly day and night to make sure that we are keeping the team informed of what is happening in the field. Thank you very much.