Okay. So let's go ahead and get started. Good morning again. So we're going to start this session start today off with a presentation on maps. And I know that a lot of you probably a bit tired we're starting early and some of you probably woke up this morning at 3am with the sun shining directly on your face. Or maybe you went out after beer and pizza yesterday and didn't get back to your hotel till 3am, which is probably more likely. So I'm going to give us a quick introduction to this and give you some prompts to think about while we're going through this presentation. So, yeah, sorry, my name is Scott. I'm the analytics product manager. And then we're also going to have beer and our lead maps developer come up and give us an overview of the new functionality. And then we also have Maria Munez and Sylvia Ren from UNICEF, joining to give us finish off the presentation with a little bit of information on how people are using maps and how we can encourage people to use maps more through capacity building. But to the prompts. So we know that the maps app is probably one of the most underutilized analytics apps that we have in DHS to which is a true tragedy because it is an incredibly powerful tool of all of our apps that we have. It is probably the most advanced in terms of functionality. And because it's so advanced at this point. It's actually somebody somebody's still waking up. But because the maps app is is so advanced. I think that it's actually been very hard for people to keep up with the functionality, because we've been pumping out a lot of functionality continuously. And so we're going to catch you up on that. So we're going to look at the new features. So please pay attention to the new features. This is not the maps app that your parents were using. This has really advanced quite a lot over the last years. But I also want you to think about as we're going through the maps app, think about why many of you many countries are under utilizing the maps app. Is it that the functionality is not there. Is it that you don't have the capacity building you don't have the strengthening you don't have the use cases. What is it that is preventing you from using the maps app and then I would love to hear about that we have a session this afternoon this afternoon. Wednesday afternoon, where we're going to go into more detail around map use and we'd love for you to come to that session and talk to us about why you think people are not using maps and we'd like to figure out a way to move forward together as a community. You're going to see some examples of how people are already using maps, especially from Sylvia Maria. And I think this should be inspiring to you. I think that you should see how some of these countries have adopted maps and know that you can do the exact same thing. There's no reason that you can't then I also want you to make sure that you understand how it takes a, you know, a bit of more understanding on how we build capacity around maps.  Maps as a concept is a bit more advanced and say like a bar chart or a line graph, you know, these are really simple things that most people can understand right away. But once you do build capacity around maps, it can be the most powerful analytics tool that you have. So with that, I think I will go ahead and hand it off to our lead maps developer Bjorn, and he is going to take us through the latest functionality. Thank you, Scott. We like the maps app is underutilized. And sometimes we hear that maps are looked upon as being more complicated, even so complicated that people are sometimes just afraid to, to go into the maps app and try to make one. But just to get everyone here on the same track the maps app is super easy. I would say argue that is even easier than the other analytical apps. Very, very few selections you need to make before you have actually created a map and I will show this, but this is just to get all of you on the track if you haven't opened the maps app before. I hope everyone has. This is what it looks like you can select the base maps you have the legend to the right. And the most important button is the add layer button where you have these layers presented. So if you have an automatic you use for your aggregate data, you have events and track entities you can use for individual data. And then we have two layers that you can use for your, your audience. One, specifically specifically tailored towards the facilities the lowest level, and one that can show the full hierarchy. So spend quite a bit of time of these external layers here, which are from fetch from the Google Earth engine but they are from various sources. And just to show you the proof that you can create a map in 15 seconds. That will be showing now. I had an issue that set the base map if you need to change it. Click on add layer. The only thing you basically need to select to have a map is to select an indicator and then go with the default. And you have the map here and you can interact and click with it. So it's that simple. And then of course later on you can go in and change the different period change to different, different org unit, different districts, and you can change the styling and you can even filter the data if you want to look at part of it. But just to get started, select an indicator, click add layer and you have a map. We've added quite a few features. I'm not going to go through this list. I'm going to present some of these features today. It's not only the latest features because we have been building some of the features built on the others. And now we have a full package that we would like to present. Often also quite a bit of quite a few times I'm presenting the latest features, but I also see very often see that is of no use because you are maybe two or three or four or five versions behind. So the good news here is that most of you yet later today can go and create its maps. You don't need to wait for 240 to be able to do this. So just start playing with the maps up. The most important feature for 240 was a feedback we got when we had a workshop in Nairobi, you will hear more about it. And that was that printed maps are the main way of sharing information in many countries. So if you have a maps you would like to share with others, you could even make a PDF, but very often a printed map is what you would like to share. And the printing functionality in the HS2 maps was very limited. And we have improved that greatly in this version. Another important feature I know has been requested by many was that it was only possible to display the name of the org units on the map, but you also wanted to see the actual value. And we have added that support in now in 240. But what we have what's different in this 240 is that you can click on the download and then you are entering this download mode. And here we have a lot of more possibilities to present your map. And very often the one who are going to read your map is a different person than you who produce it. So it's important to tell the story around the map and not only present the map in itself because it can be hard to interpret. So what we've added is you can add the title and the description. This map is showing birth by attended by skilled health personnel. It's in percentage. This is from the serial on the database. So it's only demo data. And then you can select which kind of elements you would like to have, but these are like the basic so you can have a title. Description legend and inset map can be important for people to realize where in the country it is. We have a north arrow scale bar. Yes, that's it. Here also if you get please get feedback. Give us feedback if you would like to have more elements to this print layout and we can add it. So this is the result quite clean map with a clear message. Often you have this. When I see maps that are produced, some of the maps are often too busy because in the maps that you have the power of adding as many layers as you like. And sometimes that can be a great feature, especially if there is a linkage you want to show between the two layers. Instead of they come to it across because it gets much harder to read. So instead of trying to put everything in one map rather make many several multiple maps like this, which is easy to read and maybe put them side by side instead. An important feature we added in through 35, which I think most of your should be on now is that we only for aggregate data we only had. So this is this thematic mapping technique, which is called a corrupt let's supporting supported. So this one here, the districts are colorized according to a statistical value, and this is a great map to use. If you want to to to see data that is normalized per capita percentage, but it's not the map you should use if you have show wrong number total population, or the number of birth in the district. And the reason is that you you will easily start to compare the different districts here with a performance across the boundaries. But it's not really telling the true story because often the raw data is connected to the population to the numbers. And that's why you should also always use these we call it the bubble map is often called the proportional symbol map. So please use this one. Normally this is the one you use technique you use for data elements, and this is the one you use for an indicator. Changes are not only in space, they're also happening in time. So we have added two methods to show difference in time. So the first method is to have a timeline showing under the map, and then you can see this is for the last 12 months. This one is just playing, but you can also click on this different to move back and forth. I think the problem here is that if you're interested in one district, you should be able to just focus on that district and see the changes. But as the map as a whole, I find it very hard to remember how it was the last month when I go into the next. So that's why we also added this we call the split view, which I think is much better. It comes with a cost because it's less room for each map. So for example, on the last map, I could also show the name and the value here is only room for the for the values for the district. But here is much, much, much easier to compare the districts and the different performance throughout this six month period. Another feature we feel is underutilized is the event layer, which has many more styling capabilities now. So when you select an event from a program and it has a data element attached to it, you can decide to style by this data element. So instead of just showing the events at Black Docks, you can here see that the style by the mode of discharge as an example. So you can also try to get patterns out of this. It works for some data events. For example, the diagnosis, you know, that can be a TOSNs. So trying to style by that element will make a legend part too big. But for most data elements, that should be something you can do. And also another thing with these event maps is that you can often have hundreds, even hundreds, TOSNs, 100 TOSN events. So that's why we have, oh, sorry. One more here. We have made a data table for most of the layers. So this one is showing for event layer. That was the last layer we supported. So the data table is a table view of the same data you see on the map. It was added in through 35 for the event layer. And it's a great thing to, the maps app is not only to show the data. It can also be a way to drill down and investigate and look for specific cases. So what we see here, you have this filtering capabilities. So here mode of discharge is set to died and then age is less than 10 years. And then you are left with two events only. So you can see as you type here, the maps updates automatically as you type and you're left with the filter. And then this one is that if you have many events, you can decide to group them into these clusters that are lying close to each other. And you see here too, also we are keeping the styling. So we call these donuts, but the outer circle is showing the representation of the events inside of that bubble. And then in the last couple of releases, we have worked on a lot on catchment areas. So as you know, catchment areas are the area where the where the hospital is getting their patients from or where the school is getting their pupils from. And often that could be good to define to have, for example, an approximation to know the number of population, for example, living within this area. So if you have, we don't have any build in support for creating catchment areas. This is a very complex thing to do to create these areas. But you can easily import, we'll show you different ways you can easily import these catchment areas into the system. But when you have catchment areas, you will see in these org units when you select your org units for your layers, you will see you have an extra dropdown called associated geometry. And there you might see catchment areas or other types of areas defined. So the new thing here is that if you have an org unit, it can have multiple geometries attached. So normally a facility will only be a point in the version you're having, but it can now also be a polygon or the area where which is the catchment area for this facility. If you have 238, the research app, I would advise you to check all this called the micro planning app from Crosscut. It will help you to automatically create these catchment areas. So it will use your facilities and it will also use your districts and then within the district boundaries, try to define the catchment areas by based on factors like travel distance if there are a big river blocking mountain ridge, land cover, all these kind of factors. And this can be good as a starting point for your catchment areas. And then later on you can go in and edit this manually if you see that this is wrong for this area. And then in 239, you can also import from any tool the catchment areas you would like to use. So this one shows two example with catchment areas, what you can do when you have imported it, whatever you select the facility points, you can now select the catchment area instead. So this one is showing a thematic map where the catchment areas are colorized according to the statistical value. We will later show you how you can calculate the population within the catchment areas. But this one is also can be a useful example, we have this detailed imagery from Bing.  So you can sort of ground through thing we call it and see, see how accurate they are. So here you will see that the catchment areas clearly defined along a road. Then we are moving on to the earth engine layers. I know quite a few of you have signed up for Google Earth Engine now I really recommend the rest of you to do it. I think I have 20 countries been signing up last few months. The process it used to be a complicated process you had to do the sign up with Google yourself. Now it's super easy. It's easy is to send them an email to maps at dhs2.org you can you will find the slides and we'll find everything information there. But you only need to send an email ask your system administrator to do it, and we will fix your access. So it's done in a few minutes. And then you will have access to these powerful layers. So what's special with this Google Earth Engine is called an engine because it's not only like a repository for data. It's also they provide all the computing power in the cloud at Google. So you can do a lot of interesting stuff with this data. But they do this dhs2 is supported for free no extra cost for this is for a good project for Google so you don't need to pay anything. What they are providing is a way for organization to upload a data. So we have data for example from these three organizations. They added to Google Earth Engine. What we do is that we pass in the organization unit from the instance, and then we use this data to calculate for example, we would like to calculate the population within the district on in your country. And then we get that result and present it. So and all of this is happening on the fly. When you click that link. This is an example of elevation in Sierra Leone. So you can see you have the base map showing the elevation with the color scale. Also we have access to the raw data. So if you right click anywhere on this map, you will see the elevation at exactly that point. You will also if you click on this you will see aggregated values you will see in this district the max value is 1933, which is almost the same this resolution is 30 meters. So it's almost the same as the highest point. And you can also have the mean a max you can decide how you want this data to be aggregated. This could be used for malaria risk mapping, not in Sierra Leone because it's a low altitude country. So there is malaria risk all over the country is not connected with altitude. But this is just shown an example, because you can set the mean and the max. And for example, you can define that the dark color is a high risk area and the orange color is a medium risk, for example. And I did this for an academy we had in Delhi where there were participants from Bhutan where malaria is very connected to altitude. So then this is not created in the data is from the issues to the I created this mapping to guess in another years program, but here the red areas mark the area where there is malaria risk below 1,700 meters. And this is also an example of thing how effective maps can be you're trying to describe this in words where these areas are. It is hard and you can also see easily that there are at least four states where basically there is no malaria risk. We also have added a land cover data sets, which also might be used in with vector born diseases and health. This one is showing so land cover or land use it will, it will show the whole the landscape varies in within the districts. And this one is showing us as data where the permanent wetlands is almost 18%. And then again if we take up the data table, you can click on the titles there and then you will sort the results. So here you can see these are chief dumps, you can see the chief dumps with the most percentage of wetlands. So you can see there is BMC state know chiefdom here is having more than 50% of the land area is considered to be wetlands. Then finally we're moving on to population, which is probably the most interesting and useful. We are using population data from WorldPop did one show some map. This is three map players here, you have the population density at the bottom. Then I've added chiefdoms boundaries on top and then the health facilities. So this might be useful to see if there are areas which is not covered by a health facility, but where there is a high density population. So for example I just added a circle in the middle there might be a candidate for where to add another health facility. A little bit behind the scenes what's special with this WorldPop dataset is that it's very high resolution. It's 100 by 100 meter is the resolution and within everyone cell 100 by 100 meter cell there is a population estimate. This slide is from WorldPop. I would advise you to go into WorldPop and see a presentation there for how this is created. But based on a lot of data, satellite imagery, roles, building, footprints, land use, they are able to create this model of the number of people living there. It's not necessarily completely accurate within a cell, but within a larger area, these estimates have been proven to be quite accurate. And then so this is just a small area and you can see the cells with a number of people living there. And then what makes this so flexible is that we can add every layer on top. And then what we basically do is just to count the number of cells that falls in catchment one and two and then we get the population estimate. And all of this now is built directly into DHS2 maps. So the two population layers we have is this one with a total population and then during COVID-19 we understood or got feedback that it is crucial to have the different age groups. So for example, to find the elder population. So then we also added the population age groups layers, which is divided into a gender and sex structures. So here you can see that you can select, for example, male and female under five years if that is what you're interested in. Just mentioning here a well pop has many different data sets we have added to that are globally available. They are based on a top down approach, which means that it's taking your census data as a starting point. So when you add up the number for the year of the census, it should match the numbers. And then there are projections from that census into the future. I also know that the population data can be very disputed. This is not the we import to the system. This is only for the youth to view. It's not taking over the population data you already already have in the DHS2 instance. This is only on the fly measurements in the maps app. Also, the data we have is for 2020. We know we get a lot of requests because they want to data for this year. The good news is that will pop is currently taking even more newer census data whether have been in the recent years and they will now produce this population numbers for 2020 until 2030 with projections. So what you can do with this data then is that you can try with your own districts. Select the population layer and you will instantly get an estimate of the population within. So you can see in this Gaura, you will see 24,000 in estimated population. And you can also, like I said, preview the data table much more. You can sort by them by the by the value and have it presented like this. And then again, this is the age groups. You see you can both see the individual age groups and also the total for the group selected. If you don't have catchment areas defined, you can select a buffer. So if if you would like to see the number the population living within 3000 meter, for example, from a health facility, you can use this feature. So you will see here 3470 lives 3000 meters within 3000 meters from this facility. If you have catchment areas, this can be defined much more accurate. So here we have the same district with a catchment area. And you will see that the population is then much higher, more than 9000. And another thing we have added this is in 237 is that the maps up is probably the best app to use to have a good overview of your facilities. And there is also been a lot of discussion on the master facility list. So you are collecting a lot of data about these facilities. And what we have made is something called the org unit profile. So whenever you have a facility on your map, you click on it, you will have this view profile button. And then you will see all the information you have about the health facility. This is can be configured so you can decide what you would like to see. You can even add an image to the health facility. You can see the name contact person. And you can also see select what kind of statistics you would like to see for each health facility. So please use this one more. My last slide is that we try to cover many use cases with DHS2 maps, but we will never be able to compete with a proper GIS system. And also I don't think you want us to be a proper GIS system as well because these are very complex to use. So we want the most common task, especially if you're looking at your own data. DHS2 maps should be the app you should use to make a map. But if you would like to combine your data with other data, we might in the future add more possibilities to bring on other data sources. But very often you will need to go into another program. And we also had academies and so we see that people are learning quite fast the other programs. And then we made it very easy to get data out of DHS2 into another program. So you have an, if you right click, if you click on that menu when you have your layer, there is a download data button. An important thing here is that the download, when you download the data for a map, for example, you're not only getting the org unit or the facilities. You're also getting the data attached that you see on the map. We see that some of people use a complicated process of going into matching data, linking the statistical value to the org units. If you use the maps app, you don't need to do it because it's already attached. So just download the data and style it again in QGIS. So this is just an example. Download the facilities. Then we have a settlement extents from Grid Tree. So this is showing where there are settlements. And then we are combining these two in QGIS. And here also you could see if there are areas that are not covered by a health facility. So for example, on this map I saw this seems to be a larger settlements there to the right where there is no facility. That was my last slide. So we'll move on on how we can build capacity on using maps. Thanks. Good morning everyone. So you've heard that making maps and DHIS is easy. You've also gotten to see a lot of the really fantastic features within the Maps app. And you've also seen that there's a lot of really powerful data that's made available to DHIS to users through a tool like Google Earth Engine. So population data and earth science data, which coupled with the routine information that you have in your DHIS to instances can make very powerful maps. You also heard though that the Maps app is one of the analytics tools that's the most relatively least used within the DHIS to platform. So we wanted to learn more about what are the reasons behind the limited usage by gathering insights from the field. So we started a collaboration about a year and a half ago, including UNICEF grid three, the HIST Center, HIST South Africa and ministries of health and HIST in five countries in eastern Southern Africa, Kenya, Uganda, Rwanda, Mozambique and Zambia. And again, the idea was to understand why the app is relatively limited in use and also what are some of the current practices in the field and how can this be supported better within the existing functionality. The results today reflect the inputs of many individuals. Some are captured in the slide pictures, some in the room today and some that are joining remotely. And so we hope you'll be inspired by some of what you see today as a result of what you can do with some capacity strengthening and leveraging some of the functionality within DHIS to. And then you'll be part of the community that we're building here to strengthen map use. A strong motivation behind this collaboration. Bjorn shared some of the data that's made available, for example, through world pop innovative data that's very granular and can be aggregated to different units of analysis. And we see that there's a strong demand to represent data spatially. And again, we heard from Scott that this does require special skills around how to represent data spatially and how to use and interpret that data. Again, we understand that there's limited use of this information. So we wanted to get insights from the field and identify what are those opportunities to strengthen map usage. So we convened in Nairobi last November, and we brought together Ministry of Health from Kenya and Uganda, including program staff and HMIS staff. We brought together DHIS to developers, and we brought together population modelers, along with HISPs that support implementation in these countries. And we used a range of different modalities to facilitate dialogue, the dialogue and discussion was really important. Again, to find out what are some of the current practices in the field, what are some opportunities to improve and where users were having some challenges or constraints and using the DHIS to platform maps out. So what did we learn. As you heard earlier today, we know that facilities in terms of using data and also in districts like to have map printouts. And we found out that the functionality and DHIS too in terms of downloading and printing maps had opportunities for improvement. Specifically around some of the labeling, the download options and the layout. And so as you heard today in the latest release of DHIS too. This was one of the features that was prioritized. That was a direct result of some of the consultations that happen. Again, having the diverse group of people, the ministries, implementation support teams, and also with the exchange of population modeling team and others. We also found out that the process for signing up for Google Earth engine was very cumbersome. And so again, while many users may have known that these features existed just as you learned today. There were challenges in setting up the access the sign up for Google Earth engine and DHIS to in the national instances. So again, this became apparent from the dialogue that took place. And now the process is simplified and since November there have been 18 countries that have now enabled these this feature in the national DHIS to instances. You also heard earlier today about the need for capacity strengthening around map making interpretation and use. We learned from the field that users would like to have more skills development in this area. And also that they were not always clear what are the possibilities of representing data spatially and how this might differ from analytics and charts. We also learned that users wanted to have ongoing capacity strengthening, given turnover of staff, and also the need to scale and sustain. This isn't a one off thing. One of the things that we did working with his South Africa was to develop an online Moodle course that can also be further adapted for national year. If you happen to use MOOC and Moodle in your countries. That provides some principles around GIS and introduction around how to use the maps out. We also developed a level two maps Academy and Sylvia will be sharing more in a little bit around what's possible in terms of with in a short amount of time, some fantastic maps that I hope you all will be inspired by. We also learned that there's a challenge of data. So data availability, particularly population data at the lowest levels of the system and issues with missing facility coordinates. And also with misplaced coordinates and having updated shape files or administrative boundaries to represent changes over time and, for example, district formation. So all these things are realities that will come up when, for example, making maps but one of the important lessons that emerged is that by highlighting these issues by using the data. It's created greater demand in terms of improving the geodata and DHS to and also a greater demand for using some of the innovative population and earth science data that we have been sharing. So with that, I'm going to turn over to my colleague Sylvia who's going to be sharing more about the maps Academy. Thanks Maria, and good morning everyone. My name is Sylvia Ren. I'm a GIS consultant with UNICEF and grade three. So if you have any GIS related questions around data or GIS come see me. I'm around. So I just wanted to give you a quick overview of the level to maps Academy that we did in Cape Town, which was maybe a little bit different than some of the other academies that have been held. So first of all, we spent a lot of time trying to make sure we get the right mix of people to attend. And this was not just the technical teams. We really wanted some program staff and decision makers within the programs there as well. And we wanted them to come from the same country. So if a country was present. It would be both the technical and the data use teams that that that were invited and that came to this level to maps Academy. So we did some pre course requirements. And one of them was that they needed to have done a level one Academy, and that they took a Moodle, which was an online maps course so that they already had some foundations before they came in to this Academy. And we wanted to make sure that the use cases were based on on use cases that they were using or needing in country within the next few months. So, so the maps that they produce and I'll show some examples in the later slides were some that they would be using back home. The country databases so we didn't use Sierra Leone or Laos, we used all the country teams were able to use their own instances. We had some really fun activities so we also tried out the tracker where we mapped ice cream shops with in Cape Town. And this was mainly because a lot of people they see these these roster layers with population in them and they don't really know what to do with that.  We also have supported with the online learning so that was the Moodle I mentioned and we will be following up with participants as well. If you're more interested in this level two maps Academy and and some of the things we did then Nora will be talking about this in a lot more detail in tomorrow's session. Sorry, everyone, we're having some internet instability and if you're not. You don't have something essential you have to do with your computers are depreciated if you're not doing it's high bandwidth, because we're trying to make sure we keep the stream going which is crashing at the moment. So it's appreciated you shut down any high bandwidth activity that would be great. Thank you. Okay, thanks. So I just wanted to show a few maps that were made by the participants. And please keep in mind that while some of them have done the level one maps Academy these are not GIS experts. They're people that are using mostly that the DHS to maps up with some of their data, and based on discussions that they had with their program staff that were also within this maps Academy. So this is a map of Uganda. That shows the women of childbearing age and the ANC for coverage. And here you will see the black is in the gray is the women of childbearing age per hectare and maybe just to add to that. This is really powerful because it shows you the location of populations, whether it's six or 10 women there is isn't it's not that accurate. This is 2020 data it's it's kind of a top down approach which you can look at more on the world pop website. But for the first time I think some of the DHS to users can actually see where people are in in their catchment or in their districts. They've they've put facility distribution on there as well. And then they can kind of see the ANC coverage. They've also then made a map to look at the number of deliveries and saw that a lot of while we do have women who are doing ANC visits. There's a good possibility that they're traveling quite far up to the north there to actually have have the babies. For example, of the suit to this one actually won the maps competition. And here you can also see some of the level of detail that these maps can give you. We're getting a lot of requests from countries to do geo enabled micro planning. So to kind of get catchment area maps that do have a lot of detail. And here you can see, you can see a lot of detail in in in the, in the yellow, the yellow boundaries I think I'm hoping you can see them. Those are the catchment areas that were generated by the cross cut app. They also showed the home deliveries by, by using the bubble map there so you can see, St. Joseph's catchment has a high number of home deliveries, and then they use the new ANC clients data as well to show how many new clients are there actually within that catchment area that's showing a lot of home deliveries. And then they also use the, how many of them are under 20 years of age because there's a high maternal mortality in that district and in general. And here's another example of the map where they used the Penta one data together with population, and they used two kilometer buffers to look at where our population that are over 10 kilometers away from our health facility. And again, these are basically map newbies, you know, being able to do this in the DHS to here we have an example from Zambia, where they're just kind of drilling down to say well northern province actually looks pretty good it's in the green, but when we then look at the districts of that northern province we can see that there is at least one district who was was underperforming in the coverage. Here in Tanzania we have an example of MR one coverage, where we can also see, you know whether where there's increased coverage in the blue, and then low coverage in the areas around where we have increased coverage which which may be an indicator that the people from those areas are going into, for example, kbt to get there to get their vaccines. Here's an interesting example from South Africa, where they were exploring the population data and in an area which they thought they knew fairly well. And you can see this is a very remote area you don't see a lot, you don't see roads or anything. And they actually did find populations in that area that they said when they went home they're going to need to explore that because they've never actually gone out there. Here's an example of the population data in an urban area. Also an example from South Africa, where they were looking at the TB rates and they looked at the population under five years of age, and just kind of looked at that together in the urban area. We had a follow up from Zambia. They wrote into the community of practice, I think, which, which is great that they have been showing the districts how to use the maps app to understand performance within their districts. So here we can see them in the district office. And one of the people that attended the maps Academy just kind of passing on that knowledge and using the maps app. Next, come to the session by Nora tomorrow afternoon. And we can discuss this further. Please also join the maps community of practice on the DHS to community. And here you can upload your maps, or if you have questions on making maps it doesn't just have to be on DHS to it can be in QGIS as well. If it's kind of routine data related. Then please do join that. There is also a maps, a really great maps app Moodle course developed by his South Africa, which you can sign up to and do in one or two hours, and it will really show you the features that are available. If you would like to sign up to that you'll get a certificate. Please contact Nora Nora. I don't, I think most people know you but maybe you can wave or stand up really quickly. Please contact Nora and she'll make sure that she can get you signed up. There's more to come so we'll have some more e learning Moodle's videos and jobs aids. And since the health facility locations are so important to a lot of the maps that we see that are being made and requested. And there'll also be a health facility coordinate checker. That's coming. That's it for me. Thank you. Okay, so that was the, that's all the presentation we had just one thing I wanted to emphasize about the last presentation was a lot of times people ask us how do we come up with the features that we put into DHS to sometimes it's very opaque process. So it's not this is not the Willy Wonka chocolate factory where we just kind of dream up our own movie book reference that maybe not everybody gets. But anyways, the point is that I hope you noticed from the presentation how we actually tried to convene a workshop to understand where the barriers were, and to then immediately bring those barriers back into new functionality. And that's kind of what we try to do for all of the apps and everything we develop in DHS to we don't know, we don't just dream it up. There has to be a real need. There has to be an actual implementation. And we don't actually even have the resources there to do like cool fun things that we think would just be interesting. There has to be a use case there has to be someone specifically asking for it. I need this functionality because I need to use DHS to in this way.  And if you'd like to be more involved engaged in the say the development of the maps up and giving us requirements. We're the folks that talk to we can bring you into the community practice where we have a continuous dialogue about the latest functionality and things that you think need to be there and what other folks are using the maps out for. And so we're very happy to invite anyone and everyone here to join that community. And if you go on to the community practice community dot DHS to dot org, there is under the implementation thread a link just for the maps community. So please join that and and we'll we'll have we'll keep the conversation going. Now, somehow, by the grace of God, we've ended early. And I think that gives us a very unique opportunity to have questions. So, yeah, sorry, we should have warned you Max, Max. So we we covered the new functionality, we covered capacity building and we covered some examples. Does anyone have any questions. Raise your hand. Someone's got to break the ice. Yeah, oh, sorry, Joseph, right here. You're probably going to reference a bug that we haven't fixed it or something. Yeah, thank you, Joseph from a lie. Yeah, it's a great new development, but we got the GIS. I think the key thing is about the whole data source and how we are going to manage the shape file and all the metadata. I don't know, do we have some somewhere that like a global repository where we can easily access all sort of like population and even with the climbing weather data, and then that we can further use it. And also like from the country's perspective, like we also generate the local, the local maps and the local data like the health facility we have our master health facility registry. So how how we can sort of like creating the synergy and not only within the country but maybe within the region and also the continent and even worldwide, so that people can benefit out of this. Thank you. That's a tricky question. There are various resources to finding good, good data. Speaker. So, there is a site called garden g a g a d m, which have boundaries. I would also advise you to come to the will be more specific about resources. When we have the meeting tomorrow to finding this shapes file for example. I can also say you that the this process of getting new boundary data into the issues to has been quite complex. If you have ever dealt with it in 339 is much easier. So we have improved that workflow. So I see some happy, happy faces here. Thanks. Maybe if I can add to that as well. So there are various global repositories and geo boundaries is a really good one. It has got them data in it. But here you can compare boundaries from different resources and a different administrative levels. So you compare them directly to see which ones match your country best. We have the grid three website which has settlement extends for all countries you have hot OSM for health facilities. What I can do on the maps community of practice I can maybe add some of the global repositories that we would recommend for you to have a look at. Please do remember that if they are global repositories they may not match the national data that you might get from your health facility master list, or from your ministry of lands in terms of boundaries. So that's just something to keep in mind when using the global data sets, but there is a lot available. Yeah. Just to add one thing is that as part of this collaboration we have been working with a number of different countries to create what we call bespoke model population data sets. And there are also other layers of interest, for example, like the roads that are not available in Google Earth Engine you may have your local data so I do think that that is still something that we need to sort out is how we can make available and some kind of repository. Some of this data so that you can use the data from you that you would prefer from your countries for example if you want different data than the one made globally consistently available through world pop. So again something that we would like to explore in the near future, working with DHS to team and others. And this is also something we will cover in the session tomorrow. So it's at two o'clock. It's in the technical track. Don't be afraid that it's too technical. It's basically more how to learn about maps than actually learning to complex yes and tools. So don't be frightened for joining. All right. Thank you. My name is Lawrence flank Niambello from Malawi. I'm from the expanded program immunization. I was interested when I heard about micro planning. And I just want to compliment on what my colleague has actually said again on the same. So in the immunization, we are so much interested in access and utilization. So I was also considering to say on the geospatial tracking system, where much we are using again geospatial micro planning to say, don't you see that also as a need to say, maybe if you might also bring in a system, the gts where you'd be able to actually track to look at maybe the vaccinators as they are trying to reach out to the, the children, maybe you've already done your micro planning and then you have to find out to say, would the vaccinated be able to try to reach out so that we really work again on the utilization and, and of course accessibility. So I don't know on your micro planning geospatial micro planning. How do you plan to get to those levels where you have to also consider the geospatial data. I don't know. Don't you see that as a need in the near future. Over. Thank you. Yeah, it's, it's, it's a good question. Thank you for that. I'm not sure how far the tracker app can be used, like the, the gts I know the gts has a has a dashboard that can be used and that shows you how to track. And it uses some of like, I think it uses the settlement extents as well to show you where you've been and areas you've covered. You can obviously use that data and bring it into QGIS and then take data from from the DHS to and then also add that to QGIS so that is possible now. In terms of linking the gts with DHS to maybe that's something to ask for. Now it's good feedback and, and we have been looked more into aggregate data than to individual base data. So far, I think that there is a track entity layer also in maps up but it should be really get some more love and focus. So there are possibilities and people are using it and you have the, the, the, the app where you can capture coordinates, even multiple coordinates for the for some like content tracing and so on, but it's still limited. So I think often still you depend on on moving into another system to do to do this analysis. Would you like to add some. Yeah, just to point out that planning and micro planning is one of our. Be careful with your toes. Everybody. Sorry, Kristen. I think there's quite a few doctors in the room. We need it. Okay. So what I was going to say was that micro planning is a key use case for us. It's a specifically we are really analyzing the functionalities that are required to be able to conduct micro planning, all the way down to health facility community level in countries and making sure that DHS to has all of the necessary functionality. And there's different ways that there are different types of micro planning so you have different plans for like immunization may also have different kinds of micro planning approaches for other types of outreach services like like insecticide net distribution or maternal follow up, etc. But we are part of a global community that's analyzing digital tools for micro planning, and, and if your country is going to do any micro planning and considering to using DHS to for it, please keep, please talk to us. Tell us what you need, what you have what you don't have, and then we can kind of go through the process together, but it is a key use case that we're we're aiming to cover. I do want to mention two examples that we have presented earlier. This one's from Uganda. And if you remember, and Uganda is actually able to use this map to inform micro planning, they have micro planning coming up and they have used DHS to for micro planning in the past I think some of the Ugandans in the room to probably prosper certainly could elaborate more on that. And the point is that with these maps, you're able to see where people live. Right. And you can see that quite quickly. This is quite zoomed out but if you can zoom in, and you can see where the actual structures and buildings are where people live. And obviously that's a critically important part. You can also see where the health facilities are. And so you can very easily just like they did in. Ethiopia here. You can see all those populations that are quite far away from health facilities, you know, 10 kilometers. And we know that that is a barrier to access that distance. And with these maps, I mean it makes it as obvious as you could possibly get it. Certainly. The other one here that was promised to is also extremely interesting because you can see the health facilities those are the big dots. Right. And you can see the catchments and you can see that some of these catchments are gigantic. And when when they were presenting it, they told us we didn't even know people lived here. You know, it's so rural, it's so remote. And now we know we have to go do campaign planning or we have to do outreach to those those places because there's clearly people there. And it wasn't something that they had an insight into until they built those layers on top of each other started with the base layer, added the building footprints add the population, and then it's clear that the that it's there. Okay. Yeah, maybe we can.  And we have a session tomorrow as well. I think the brakes at 10. Oh, sorry. No, we still you still have to sit here. Well, we can answer some questions off as soon. So there was a sorry breaks at 10. This communication there's a question here in the middle. Well, maybe, and then we can come back to Malawi. Oh, sorry. So I find interesting. Otherwise, I just want to compliment our leader on what I actually said. So I was looking at a problem at hand here, because you'd see if you get into the HS to generally in terms of coverage, it's generally it's a problem because each time maybe, like our site, our scenario, that maybe we want to come up with a campaign. So the times we want to get the data. That's when we're coming up with a macro planning. We have to get data from the districts. In this case, we want to get them. We want them to provide us with the national statistical figures and the headcounts right now with the Joe special micro planning in my thinking I was thinking that if they just to be able to provide us with this approach. It means issues to do with coverage is not a problem because in this case will not have all these headaches that come in when we are trying to reconcile the figures that time people would say no. Maybe we want to use the NSO figures, the national statistical figures and the headcount figures. So these don't do not actually reconcile. And then you will see that we want to create the coverage is now that even us as we are working with the coverage is actually tough because at times we need to sit down and say okay, can we work on the proportions and then come up with these coverages and you'd see that some districts do not even manage to reach out to those coverage is because they just don't use on doesn't provide coverage is we have to calculate separately we're going to the population, the proportions and then we are able to give feedback so I was of the concern of the mist open it for vaccination in comes to children that most of the children are telling me it's either we underpopulate or we overpopulate and then these proportions are not always realistic. So I was thinking on assumptions would say okay, if we are to assign to district by district, how do we ensure that we are really giving real figures. I was thinking that maybe if we, we may adopt the geospatial micro planning is going to be easy will not have issues to do with coverage is because be able to actually track the children that are really supposed to be tracked according to the coverage generates I was thinking that if we might come in with the idea of geospatial analysis in this case is going to be easy because it will be direct, it will not be these two way where the office has to ask for data. That's the cow, I mean the population figures, these two, the national statistical figures and at the same time, the head count figures so to populate these maybe to reconcile is always an issue. So I was thinking that maybe if we can have that system in the highest to it's going to be easy. And the GTS thing we hope us to actually reach out to the gap that we still feel it's always there over time because we don't have those realistic figures we make on assumptions over time and we really don't speak what happens really on the ground over so I thought maybe we can still talk a little on the same. Thank you. The sad reality is that I've never worked in a country that wasn't struggling with their population. Most countries are struggling with this. And I think the important thing to appreciate is with the maps you can see where people live. And this world pop data is a projection. This is not a head, it's not a head count. Right. It's a model. So it's not necessarily exactly what you see it's also from 2020 and as you're pointed out they are updating it and even providing some new projections, but it is not your national statistics necessarily. But it is a really good place to start and we and it makes it very easy now to use it in the mouse out. So we have we have actually done a series of webinars on different approaches and methodologies to available. It's available on our YouTube channel but I'm happy to share some links but there are, and it's certainly some of the WHO colleagues here have a lot of experience in this as well. If you're struggling with coverage indicators just know that everybody else in the room probably is too. And then there are different methodologies to use to calculate them. And then of course the maps out can be a, you know, when you put on the building footprints layer, it's kind of hard to argue with it. Because it's just, you see where all the buildings are. It's very, very clear. So it makes it quite easy. Maybe also just to add on, I think one of the things that we're seeing a lot of is how important the actual boundary of the catchment area is when you're trying to reach people. A lot of times the facilities have hand drawn maps. So, and when we ask them to digitize that, we see a lot of gaps and overlaps and what the facility perceives is their catchment area. So, when they say, this is my facility headcount or my catchment area, they may be under over estimating what is in their, their catchment boundary, just because it's never been properly mapped. So, starting with just properly mapping the catchment area, and you can use a tool like cross cut to get kind of a first iteration of that and then sit with the facilities to make sure they are happy with that. That can go a long way. And then you can use your census population to see, maybe it does actually add up. It's just that the boundary was wrong. Or you can, you can sit with your facility and then go through that again, use settlement extends that you can write populations to and then look at that. Look at the population again, but the actual boundaries around your catchment area are really, really important to make sure you get the right population. And that's often an issue that we've seen. Maybe just to add, in some countries, we've done extensive micro planet maps, where we've put three different populations. We've put the one from the statistics office, a bottom up model which uses a more detailed data, like from a census cartography, and the facility headcount data and then the facilities could choose what they felt was the most accurate. So, so countries are requesting that as well. Hi, my name is Lily signs I work on the PMI vectorling project. And on our project we collect quite a lot of entomology data. And there's a lot of interest in being able to map our entomology indicators like vector density and vector composition, along with climate data. And mostly, that is, you know, looking at monthly changes to climate data at the district level with our entomology indicators. So far we've noticed that the climate layers. We're seeing a lot of data at the weekly level, and their differences in what that time period is based on the source of the climate data that's coming through. So we're just wondering if there's any possible or expected functionality of kind of aggregating climate data at different time periods or flexibility in in those time periods that are available within maps. So, so I need a, I need help on this one. The answer is, yes, it's something that we're taking we're looking very much into having more granular climate data but maybe, Kristen. So, so we have a, we have an own session on climate health tomorrow. Actually, so, so please join that one. We have several initiatives around in the countries. And there is a growing demand for combining climate data with health data to be able to predict prevent understand the impact of climate on health issues. We are in the process. I mean, we could say that I think it's not a secret. We are in the process of we actually just handed in and proposal for welcome trust on a big project eight years project with the 12 PhD students involving many countries on investigating the impact that the climate health has on health data so we hope we will start a big initiative but we don't know yet it will be decided during summer so cross all the fingers, but we really believe anyway, even though we're not getting funds, we believe that that's a growing demand and it's very important to address issues when it comes to weather data, climate data, meteorological data for the first impact on and we know already we have done it on malaria and nutrition. So we know already there, there's evidence, but we will encourage people in countries to take contact with climate communities at the universities at meteorological stations to start the discussion to see how can we combine data from various sectors in order to to address social challenges such as climate health. So this is a kind of a call for action. And we will have some examples in the primary on Thursday when we are talking about cross sector monitoring. So there will be examples and we actually have a session at three o'clock today, monitoring progress progress across sectors in auditorium one, where we actually look at this to these to see how we can combine data analytics, analytics across sectors, and many of these indicators are climate relevant indicators. So yes, this is a very much an up and coming topic for for us all. Maybe I could just add one thing about that specific question. I worked fairly extensively on a proposal on climate health and the issue of granularity and matching geographical scale comes up in every climate health use case. And the way to address that is by creating customized climate services for use case which we're planning to work with a few new partners in the climate sciences demand to do. So probably be a combination of local climate data were available globally modeled climate data, but designed to match a given health use case. So we're, we have discussed that with a few different climate partners that we're hoping to join us the welcome project, and once those become available, to the extent of those can be made generic and made available for different countries in different contexts that's obviously the goal as many DHS to product product. If you're interested, I definitely recommend getting in touch with us because the first step of that if we do receive the approval for a project proposal will be selecting countries and use cases to work with and trying to move forward and develop some viable systems. And just to add, if there are any knowledge about where ministries are sharing data, we are very interested to kind of leverage upon that to see what can we do in order to show or as I usually say create hope, show examples where we actually can do see the benefit from from matching data from local weather data with climb local health data, because for in on satellites that has been available for quite a while, but it's the same as with maps.  So, so we need to think about that in in when it comes to climate as well. I would also advise you to have a look at the Google Earth engine just Google it and see the data repository it's a vast, vast resource and that's climate changes a big issue for them as well. And they are constantly adding new data layers. So, but it's if someone you could have a look if you're working within the field and see if there are more data sets that we could also add to the DHS to instance to the maps up. So please have a look and and give us feedback. Okay, I think we have time for one more question before the break. This side of the room seems to be a bit more tired than this side of the room. Are there any questions over here. Yeah, of course, George always. Thank you very much so I have one comment and one question. So the organic profile is really spectacular. I've come across it recently. The other thing that is impressed me what from beyond said is that I realized that you could have like the data table at the bottom of the map. But you were just clicking around with the filters and I realized that you could actually use it for real time analysis. That's really interesting because now I realized that instead of having to create 567 different maps like, you know, all the zeros or the ones you can actually just have one map and give an explanation to dynamically use it like on the fly that's great.  Currently, because this is a one time job, we have not prioritized to make this into a nice unit. So there is an API, you need to set it's fairly well described, sending a request to this API and it's done as a one time job and it will keep and it will be there. So this one basically selects which sort of elements and like meter data attributes or you need groups, what kind of indicators and data elements you want to see. But I see we will, I will take a second round of getting a user interface for this as well. Yeah, we have to. Yeah, we pointing out an API link is, is a bit tough. Okay, we're still, we're still just a few more minutes away from T. Any other questions last question. No silence is acceptance. Okay. One thing I just want because this was this been a great process this last half year, having a workshop in Nairobi and then leading up to the academy at the same time working on the maps up trying to improve features. So I just want to specially thank Sylvia and Maria from UNICEF, and also Nora from HIPAA South Africa for organizing the academy which was a lot of work. It's super useful also for us as developers and also people sitting in Oslo, come out in the field, learn about the use cases, see how this is used. We were 2014, this weren't his group represented on this and it is super useful. And sometimes someone from the outside needs to come and bring us together. So I'm very thankful that you did this job. I hope this, we will continue this great cooperation for the future as well. Thank you. All right, so thanks so much. I think we'll go to our coffee break and Okay, welcome everybody we will get started now with the next plenary session. My name is Anna Tursang I work at the implementation team here at the HIPP Center. My name is Ola Titlista. I'm also at the implementation group here at the HIPP Center University Oslo. Welcome to this session. Welcome everybody. So I'm very excited about this session. We have a good panel here on stage with representatives from governments and WHO office from different countries. These are countries, many of them have been doing DHS to for many years. And we think we have a lot to learn from all of you. So next slide. Is that not working? Oops. So up here on stage, we have Rana from Mozambique, head of HIS and Ministry of Health Mozambique. We have Macha from Tanzania over here, Assistant Director, Ministry of Health. We have Masood Ahmed, Deputy Director of Strategic Affairs from Ministry of Health from Ethiopia. We have some little bit newer countries we have from Angola Pedro Duarte Gabriel, Head of Planning and Statistics, Ministry of Health Angola. And we have Amar Babani, Health System Officer from WHO country office in Iraq. So all of them represent countries that are on various stages of how long they have been doing DHS to ranging from Mozambique for over 20 years soon to Iraq starting this year or last year. So we hope it will be an interesting discussion. We will open for questions at the end of the session from the audience, but first we will hear a little bit from the countries on what they think have been important to sustain DHS to up to now. Should we introduce our friend Emilio? Oh, I forgot Emilio, sorry. So Emilio Mosahir is from, he's the head of research at Sao Digitus, his group that is supporting the Portuguese speaking countries. You are a former PhD student also from University of Oslo, and he will help a little bit with translation from Angola. Okay, thank you. Good points. I will leave the floor to you. Next slide. So let's start with Mozambique. So Brana, we can see on the slide here that Mozambique has been using DHS at National Scale for almost 10 years now. And I also remember that you started I think in 2001 with the early version of DHS. So it's been many, many years. We can see that the scope of the system is quite advanced with many health programs, integrations with many key systems. Can you share some insights into the governance and coordination processes that are needed to implement and sustain DHS at this level over so many years. Thank you. Hello. So DHS 2 is now the since 2015 has been the official platform for data management. We still have some challenge because we have a lot of systems parallel, but we are trying to more and more bring that data and integrate with our system. So I think the key issue with Mozambique experience to sustain over 10 years, the DHS 2 is to have a clear national policy. So we try to make the DHS 2 the official platform and all the partners must be aligned with this vision and also reinforce the ownership of the DHS 2 in the provision and district and health facilities level. So there is already, can I say, movement about the use of the DHS 2. Of course, we still have challenged to ever come. The implementation of a system and more than 1800 health facilities. So we have the same uses as many of the African countries like infrastructure, communications, the stuff that we need skilled in the informatics and so on. But we're trying to build this with the help of our partners. The University of Oslo, the University of Eduardo Moundland. So it's a common effort to really make it happen. Thank you. We'll hear more from Mozambique later. So Marcia Tanzania has recently celebrated 10 years of the DHS. Congratulations. So the key lessons learned that you can share with other countries in terms of building country ownership and sustaining a system over so many years. Thank you very much. My colleague have already mentioned also in Tanzania, we strengthen the governance component of the DHS 2 and we take that platform as the government platform for data collection. And also, in Tanzania, we decided to use the local institutions, like I mean local university, like University of Jerusalem, and also we use Oslo, I mean also group, I mean his group in sustaining the platform. But during the rollout of the DHS 2, we invest a lot in training at all levels, because in Tanzania, we have almost 11,000 facilities. So we involve all many employees at the facilities during the rollout. So by doing that, it make many DHS 2 to be a platform which have been owned by all implementers, I mean all service providers at the facility level. But on top of that, we build up, we develop the roadmap of implementing that many DHS 2 platform. So doing all that help us to the ownership of that platform. And right now, we have already started to be used by other sectors like agriculture sector and other sectors are interested in using that platform. Thank you. So over to Ethiopia. It's impressive to see how Ethiopia has managed to scale up the DHS 2 implementation across all facilities in such a big country. Can you share with us some insights into the structures and processes that need to be in place in order to manage such a challenging implementation in low resource setting. Thank you. Thank you so much. So, when I talk about our DHS 2 implementation, I'm talking about the countries that can populate the country in Africa, next to Nigeria, having more than 4,000 private health facilities, 3,600 health centers, more than like 500 hospitals. And the DHS 2 implementation is started in 2017. The implementation touches the ground within six months. So what makes, you know, you know, sustainable and the leading factor, there are a lot of issues at the country. The first one is we had strong HMS paper based system. So that system is, you know, the foundation for DHS 2 implementation. We designed our health management information system. We have designed it in the way that it will be sustainable. So our health management information system, which is designed in 2008 has four principles. The first principle is, you know, standardization. We have standardized everything, the reporting format, the data elements, the communicators, the denominators, the denominators, who are to report, who are to report, for whom to report, who are to report, everything is standardized and documented so that everyone will abide to that principle. The second principle is simplification. So we don't have to respond each and every need of the health system through DHS 2. So very simple data elements in order to be reported from the grassroots level to the next level. The third principle is integration. So before our health management information system, data were coming from the grassroots to the national level by the program. There was, you know, parallel reporting to the national level. TV were reporting directly to the TV unit, Malera to Malera unit, HIV to HIV unit, but we make a kind of decision to make it integration. So we have an integrated system. Another, the fourth principle, when we implemented our health management, in the words, initialization, the first team of sending the report is not to send the report for the purpose of sending. So the data is as a point of data collection, the need to use that data as a point of data collection for sending to the next level. So these are the four principles. The second one, in terms of having good DHS 2, we invested on human resource. So at the time, when we implemented our HMIS, there was no designated responsible person working on health management system. So we have created a category called HIT, Health Information Technicians. They are many responsible for data management, data collection, analysis, interpretation, and same as a report. There are now some capacity of HIT, I mean technology. They have now some capacity with informatics and some capacity with health and some knowledge and skill on bio study. So we have created this position and we deployed within five years so that you'll take over. The second one is we do have a special funding mechanism. So since we are living in a resource limited country, we have a funding mechanism called pool fund. So whenever a donor comes to the country, we mobilize different resources put in one basket so that the country is responsible in terms of assigning the fund based on our priorities. So that mechanisms help the country to invest a lot to push the DHS 2 implementation forward. The fourth one is the government's system. We prepared manuals, guidelines, structures that can facilitate and support DHS 2 implementation. The fifth one is, you know, we don't allow our system to revise it more frequently because, you know, whatever we revised in our indicators, since they didn't need to include it to our DHS 2, we don't allow to revise it within two years, three years. So at the minimum, we were waiting to revise our DHS 2 at least four years and five years so that the resource and other things will be minimized and will be more efficient. The sixth one is government ownership and commitment. So, you know, from the day one, the government is very committed to lead it. So whenever you are sitting in the driver's seat, whenever the partners, the donors are coming to the country, they align based on our priorities, we have the principle 3-1 principle, one plan, one budget, one port principle. So when we have the resource, they are located based on our plan. Whenever they want to have a data, they are taking the data from our system. Whenever they want to, you know, have a plan, they are laying with us. So with this principle, the government is leading and the government is, you know, you know, and, you know, the commitment to invest in some infrastructure like we invested a lot on infrastructure, buying computer, having health needs, human resource allocation. At the same time, we decided to use DHS 2 beyond the routine RHS, routine health information system. Currently, you know, the last three years, we were using DHS 2 for COVID response. Even we were using it for data entry at the laboratory, because it minimized a lot of resources, because human resources working at different levels, no CDHS 2, so that we went to use that capacity in terms of implementation. So this is a government commitment. The other one is collaboration. We wanted to collaborate with people on this area. The last one, I can share my experience is we have to have a strong immune system, which means we have regular programs to do self assessment. We let them conduct self assessment as facility level. You know, we call it LQS. There is a system to conduct from the district to the facility RADK every quarter. There is a supervision. There is a performance monitoring mechanisms. There is annual conference. There is JSC regional health bureaus with the ministry. So we established a kind of strong MND system for the HHS 2 platform. These are some of my experience I want to share to the committee. Thank you. Thank you so much. Thank you so much. Yeah, sorry. Okay, so now we are moving to the countries who have a little bit fresher in the DHS 2 worlds. I think maybe I will start with Angola. That's okay. Going by a number of years with DHS 2. Hello, Angola. You have been doing DHS 2 since 2016 and then 2019 you went full scale. So I understand you are working mainly with aggregate data, but you have a priority to move to individual level data soon. Do you want to talk a little bit about your journey and your goals for the future and what you can learn from these other people? Hello, everyone. My name is Pedro Duarte. Angola had its beginning or the first steps related to the DHS 2, as it was already well said, in 2016. And from January 2019 we adopted the DHS 2 as a health information system. So, sorry, Angola started the first steps in the implementation of DHS 2 in 2016, but in 2019 it was kind of official kind of roll up in some other districts. The management of the health information system in Angola is done by the study cabinet, planning and statistics. And there is also the support and the work together with the technology and information and communication, the GTCI, which is responsible for the technical support at the level of the platform. The implementation of health information systems at the Ministry of Health in Angola. There are three institutions, one is for management and another one is the one that deals with the technical part. The GTI stands for the Cabinet of Information Technology that is providing technical support and GP that deals with the management of health information systems. So, the DHS is rolled in all 162 municipalities in Angola, they are using DHS 2. And fruit of this, we already have almost all the public health programs, it is also part of the technical team of the DHS 2 together with GP and the GTCI, the public health programs. We have aggregated data for various programs such as malaria, tuberculosis, HIV, the PAV program, and steps are being taken to improve. We still have this information aggregated. So now we are moving slowly to individual data. And for the specific case of malaria, you are already making the pilot in a province to be able to implement the tracker for malaria. Currently we are implementing slowly the tracker, but the tracker for malaria for HIV and tuberculosis. Currently there is a kind of a piloting in malaria in terms of getting this individual data. So currently there is an institute fighting against HIV, so now he is using the tracker capture to collect individual data from HIV. But what we want is that really to implement the full tracker in order to get this data. It is important to note that there are also other systems that, in a way, serve as a support to the system of information. And that we need to have them connected to the DHS 2. And that is why we have several challenges, several challenges in Angola, in terms of implementing or being able to follow some countries that we have already heard here. As in the case of Mozambique, we have been using it for a long time and we have had a vast experience in Tanzania, as we have heard here. And as well as we have heard here in Ethiopia. And by doing this, we intend to implement the tracker for the main programs or for some diseases, as we have already done here. As challenges like malaria, TB, HIV. We also need, in terms of the various systems, to have interoperability in the systems of the DHS 2. And we are collecting data for different data in different programs. So what we want now is to integrate all this program to DHS in order to get data from DHS. We are still facing different challenges as we have from Mozambique, Tanzania and Ethiopia, because they have kind of a long experience in implementing different kind of stages of implementing the DHS. So what we want is to learn how we can also be able to implement the tracker in order to get this individual data. And we also need to start the aggregation of the files for other programs that we still don't have. As challenges, as in the case of the anti-drug struggle program, we still don't have the files that we are going to implement, the aggregation for these programs and some. These are the main challenges, as a summary, that we have in Angola. Thank you. So the other programs, like this one that is mentioned here, against drug that is collating in paper form, so we need to put it in DHS. So in summary, that's what we can say from Angola. Thank you. Thank you so much. And lastly, I will, and not least, hear from Iraq. This is one of the very new DHS two countries started in 2022 and operational now, slowly in 23. So I would love to hear from your experience and what do you think you can learn from these countries that have been working with DHS for a long time. Yes. Hello, everyone, and thanks for giving us this opportunity. I'm in leading health system activities in Iraq, WHO Iraq. So I mean, more or less Iraq's situation, similar or a little bit different from the other countries, like for Iraq is a rich resource country. And it makes some time more than some other donor country donors, like for example, 10 billion every month from the oil price. The approach that we supported Iraq.  This is not the first attempt or for Iraqi Ministry of Health or embarking on digitalization. It started actually in 2015. And, but it didn't go as it was wished for. So for us in WHO Iraq, it was important to to understand the health system main challenges so we linked the information. The digitalization worked the team of the information management with the health system work together to understand what is the main challenges of the health system and how can we, we generate interest of the the the decision makers on investing in health information system one digitalization. Like other countries Iraq developed its health information system paper based in 1983. It's very well structured. It captures all the HMIS data and then there are other few digital or semi digital programs running but they are very much fragmented. So, the first thing in Iraq. I mean, after 2013 we need to understand that the decision in Iraq is mainly mainly politics driven by political interest. So that was very important entry point for us to generate that political interest and commitment and digitalization so that that commitment that interest generation it started from the highest level in the country. That was above the Ministry of Health. That was one of the the success. I mean, factor helped us. The second was actually collaboration with the University of Oslo, it give us a lot of power when we had this political commitment to start it is to show them our collaboration. It was very effective to effective tools. I mean, and way to work with the ministry and demonstrate how we can approach because digitalization is not an easy. It's a long process, but where to start how we start. That was very much. It was very important to to address and University of Oslo gave us the power of putting things on on on the right track. Because in 2015, they started individual level and few centers few variables and it was not sustained. So we had to understand the whole context where to start and how to start. And the sustaining the digitalization, we needed to very much pay attention to the leadership and governance because the system is fragmented. They are not collaborating with each other. And there are a lot of ways of resources and duplications. So, for that, for that many reasons. For example, I will just give you an example the ministry decided to go with first with expanded program of organization individual level. So, I mean, given the situation of Iraq having like about 1500 health facilities, providing the service with thousands of employee it will be very difficult. We look into what are the risks. I mean, when we had to take what are the risks that might impact the progress. So, for example, I mean, we know the resistant to change is one of the biggest challenge of from the previous previous attempts. We know that plus that risk, the transition time because I mean you don't want to you don't want to create more boards and add more burdens on the people that they are doing the job on the ground. So, so to convince to I mean to change the way. That's how we will collectively with the University of Oslo expert from WHO and other partners. We made it shift to the aggregated data, and then we can slowly go. So, we set the strategic vision, but the way the strategic vision was entering the data once at the facility level. So how to get there. It's a long long process. And we, we were very lucky. I mean, preparation it took us almost a year from January 2022 to January 2023. It was just a preparation to to to set up the enabling environment for digital solution. And that was very, very important and most importantly was how to create that governance model with at the Ministry of Health to ensure its sustainability. And, you know, addressing all the other areas of strategic strategic investment standards interoperability infrastructure, the policies regulation and then capacity so similar to my colleague here we had, we have some principles and these principles lie in same creation of standards because it's not the DHS to we have other system we need to ensure that interoperable. And we, we ensure that local capacities are built. It's very, very important to have a local capacities for DHS to unfortunately in the region we don't have a test, but with the API program. So we started the API implementation for a segregated monthly data at the health facility level in February. This week last week I mean beginning actually on 7th of June, we finished all Iraq, I mean from in the Kurdistan region of Iraq and the rest of Iraq we finished it. It was very smooth. And we are very happy and proud because we have now like a local team within the Ministry of Health from API. They have the capacity for data entry validation and quality check. So, one of the big issue in Iraq was the data use so I mean to ensure that this is sustained they need to use it if they don't use it they will not be providing feedback and the quality of the data can improve the more you use it the more you monitor, develop your monitoring and evaluation and the more data can be improved. So here my question to other countries. I mean, actually, we have this issue of server, local server versus cloud based server. The ministry I mean, I mean we take the issue of data security and ethical issues. So, it's still not easy for us as an Iraq to to justify the cloud based service so we anyhow we managed to temporarily for three years support the ministry with cloud based server but at the same time, we are in collaboration with our partner UNICEF was working on on building data center for the Ministry of Health. And saying that I mean, has this problem faced any of these countries, I mean, the digitalization and how, how they were addressed that I mean, it's, I'm not a data, I mean, it person and server so to maybe help me and light us more to understand how we, when we talk to officials what to say. So that's my question to my colleagues here. Do you want to try to respond to the question around the hosting. Thank you so much for a nice question. Actually, we have the same challenge that he raised, but for the last couple of years, our host also it was in the cloud. Currently, we have, you know, a strong data center as a country level. So we are working on it and now it's working good and we have also collaboration because the data should be duplicated and put in different places and if there is some kind of problem somewhere so you should find that data from some other places so currently are collaborating with ETN telecom, the telecommunication service. So we are hosting also in another era. So we are, we are hosted the data into places. One, as a ministry level, we have a robust and an excellent data center. The second one is ETN telecom area. So it's also hosted there. If there is some problem in the ministry, we can access the data directed from the ETN telecom. This is the experience we had. Thank you. Thank you. You want to add anything, Marcella? Okay, I can share also the Mozambique experience. We had the same challenge. We still have because normally the ideal environment is when the minister of science, technology and communications set up the data center for all the ministries. So that way you have a local server with the capacity to store all the data. In Mozambique case, that was not the case. We didn't have a legal framework to support not even the means to set up such data center. So we came with our own data center within the ministry of health. So we have a physical data center with the servers because by law we cannot storage for long time in cloud. We can have the systems there if we are designed, testing, even pilot, but once you go to implementation phase, you need to bring that information to a local government server. Okay, thank you. Thank you. Also, in Tanzania, we had the same challenge, but when we start implementing, we were using the cloud. But after some times, as my colleagues say, in Tanzania, we have a data center whereby all information, all data are set to be stored there. So after that regulation passed by the parliament, so we decided all the information from the cloud to put that data center. Thank you. Thank you. Okay. Okay, thank you. The data is still stored in the cloud. And in fact, thinking about the security of the same is in a way very important. Of course, on a temporary horizon, do not freeze here, be it medium, short or long term, we should think in this sense of having the data stored in our own servers. We have a ministry of technologies that works in partnership with the various ministry departments, and in a way, they can create solutions relative to the conservation, so to speak, of the data that we have at the level of DHC2. Currently in Angola, the data are still in cloud, but this is a big challenge to bring the data to the country, I would say. So there is within the ministry, the directorate that deals with issues of organizing the security of the data, but still a challenge are currently now. Okay, thank you. I think. No, I have one now, but you can have a chance later. Thank you. I know that the one thing that was a big dance on the end of having common is a very strong collaboration with the local universities. And I think we've that have followed the chess in many countries have seen kind of the potential in that kind of collaboration. Can you share some insights experiences from your countries around that university collaboration and how that has helped your implementation. I don't know who wants to go first. Thank you very much. Thanks from Tanzania. During the roll out of, of, of the chess to platform. We get a very big support from University of Oslo. And that is miss that investment was done to the local institutions in Tanzania. To appreciate and to make that system sustainable. What the government decided is to use those local universities in Tanzania to maintain the system first. Also, to get the innovations from those institution for many higher education institutions. But also in building the capacity. Example in Tanzania. The old maintenance of the chess to is done by his group in the University of Jerusalem. And in the University of Jerusalem, what they've decided was to introduce the masters program on health informatics, which one of the component is data management. And the chess to is being taught. But another another hand, we have decided to. To introduce a curriculum. On middle middle health card on the area of data management. And that. The curriculum involve also the, the learning of the chess to platform. So by doing that, and by using that local institution I mean local university and his group help us match to sustain the platform because right now the platform has grown very much in the use of that platform has grown very much in Tanzania. Thank you. But I'm not. So do you want to add something. Yeah. In Mozambique case is more or less the same as Tanzania. We've been partnered with the University of Oslo since the beginning of the point of the choice to. And we had a very strong partnership with the local university. It's a Duarte Monday University. And this environment allows us to build capacity to do research innovation to have a guidance in terms of the policies, and also to start to train from early stage. Informatics students that can increase the, let's say the task force of the people, stuff that will in mid long term, being the system working with the health information system and the digital platforms that we have. So it's more or less the same. It's, it's been a very long partnership. So, and it's becoming more and more stronger and with the impact. Thank you. Thank you again. So, in 2017, we have, you know, health sector strategy plan, HSTP. One of the transformation agenda that the sector went to transform is the data area, which we call them information revolution. So that information evolution has two three plus number one cultural transformation in terms of data quality and information use number two digitalization number three governance. So if you want to pass and achieve all these areas, we understand that you couldn't achieve it through the conventional way of, you know, the system's implementation. So we designed a program called capacity building and mentors program we call it CBMP. So we announced a kind of call from the ministry side. We had you know we have like more than 30 universities. It was an open call. So out of the 30, we have selected six universities. So this is one of these collaborator is the ministry with a clear vision and goal to support it and health information system, not only the chest. So this is the main aim is to enhance localization and local capacity. At the same time, the university to breach the academia health sector linkage. So there are four collaboration areas actually we have identified number one. We want to them to be a capacity building hub. Since most of today's students are tomorrow's, you know, implementers or tomorrow's health professionals. So we want to implement I mean integrate health information related activities in their pre service training so that we did that. The second one is pre service training I think I mean in service training. So they are supporting a lot of things in doing that. The second one is they are engaged in selected district is into implementation of his to show cases like they create to demonstration areas. So we put a clear roadmap from emerging candidate model digital model demonstration for each case series and achievement to be done. So they do, they did a lot by mentoring providing supervision something like that. The center of excellence. So in center of excellence, they are supposed to be an academy for the chase to number one. They are supposed to bring innovations. They are tasting different softwares. The fourth area is evidence generation. So for the last five years, they have generated like 11 implementation research, more than 80 published and unpublished evidences from their students and other areas. So, as a beginning, as a beginning, there was a question that whether academia versus ministry link as a rocket or not, but we proved that it's working a lot of things. We are activating I mean the results, even as a beginning, their score was 60% on collective score for that is information data quality and information is, but currently it becomes like more than 85% is a big achievement as a country, and we are expanding the support and currently we are supporting more than 100 orders by six universities in in collaboration with the regions and other partners and a lot of donors are very much interested and they are supporting this platform as well. Thank you. Thank you so much. And I think we have one last question. We, before we open up from for questions from the audience. So we heard both from Iraq Angola and we know from working with a lot of countries using DHS to that this move from aggregate to tracker or to individual level data can be challenging. It's a lot more users more need for support, etc. And do you have any and we heard from both of you that this is something that it's, it's where you want to go. So some reflections so what do you think newer countries need to think about before embarking on collecting individual level data. Big question. But in terms of collecting individual data and implementing trackers. So currently we have relatively better infrastructure. We have good human resource at each level system, and we have a government commitment for the government side, and there's also collaboration from his API and other partners. So currently we have tested it in different programs, like we stated in the TV, we stated in tested it in COVID response. We are collecting individual data. So we are planning to expand in some programs like any city and others. Apparently, we are implementing electronic media are many characters currently the center at the side of the end of that as we are implementing. So we are preparing ourselves to have, you know, individual label data is using DHS to so in terms of coming to and then since the foundation seems now very excellent. I don't think the challenges will affect that much of the content because we have a good preparation and good foundation to go ahead with I mean track implementation. That's my thinking. Thank you. Okay, thank you. Tanzania mosque reflections on trackers. Yeah, in Tanzania. We use trucker and TV program. And we have done it very well in collecting those individual data. And right now we are moving to the community level to have that those individual data. But also we have used it in the humanization. So based on the foundation which has we are having Tanzania, we don't think that we can face the challenge but we are moving well on that area. Okay. It's a complex question because it's true that when you have the infrastructure already in place and you have the resources conceptual should not be easy task but sometimes it's like you said it's a big amount of users. And in our context, we have more capacity in terms of communications and network within the capitals of the cities. When you go for the more peripheral areas, then the challenge becomes even bigger, because you struggle to come with the data that are friendly user but at the same time you can connect easily and send the data. So the our experience with the implementation of the tracker is being very challenging. We are using now in TV for some statistic vital statistic information. We are now moving on the community health information as well. But I think in our case what we did to do the transition. It was because you, we already had the great information, but the programs officials. We wanted the individual data to to make sure that we are looking at the right completeness data, the quality of data time in this and so on, and also to track the patient accordingly. We tried to mimic the paper system already in place, because we also have a very structure paper based system. And in each health facility, there are forms and, you know, to fill each program intervention. So we put this on track for these specific programs, and that's how we started to build the information flow and the data that each program needed in the district provisional or central level to analyze them to monitoring the performance indicators of specific programs. So it's a journey. We are still in the process, but I think so far, we have some lessons that we learned that we're going to improve. Thank you so much. Okay, I think we have about half an hour left. I think we can open up for questions from the audience. So you can raise your hand before you ask the question great if you can say who you are. And also, if you want to address a specific country, let us know and if it's for everyone also make that clear so we can guide them. Thank you. As usual, I don't need a mic, but I'm Carla Hedberg, been working with this since time immemorial. And I've been working in a lot of different countries looked at a lot of different databases and I think there are two, there are two major elephants in the room that you barely touched on. One is data and metadata quality. And the other one has to do with use. And I have three very specific questions for you that anybody can relatively easily pull out of the edge rise to the first one is in your country. Yes, how many data integrity violations do you currently have, because that reflects the quality of your metadata. And as I tell you, I know the answer for most of you but that's another question. I just think it's, this is something that everybody who is managing the systems need to know. The second question is, on average, for your aggregated data, how many of your data items your data records are having data quality problems on average, just a percentage. And my third question is, out of all of your health information using managers, that's probably between one and 8000. Right, that all your health program managers, all your top managers, permanent secretaries up to your minister, but how many of them in any random week are at least logging into the tries to what percentage of your health management or health information using managers are actually using the system regularly. Thank you. Thank you very much. That's a very good question. Very good question, but very tough. But they mentioned three areas are the key areas where our countries are. Fighting a struggling to make it happen better. One. The quality of that. In Tanzania. When we started collecting data by using paper based then we transform to to the chess too. The quality of our data. Started in 90 many 2013. 14 it was almost 45%. But we struggle to make sure that our data. In a good quality and the minimize variation. And last year evaluation because in our country each year the internal auditor general audit our data. So in last year, the quality of our data and the very I mean the quality of our data was around. 96 95%. And and the variation. Was very much minimized. Now the challenge came. We have a lot of data. With a very a beta quality. That's come the last question. Who are using those data. Who are using those data. At the key many policy maker in the system use the information which we are collecting. In Tanzania I can say yes. We've managed at least. 70% of decisions in health right now are based on data which have been collected. Procurement of medicine. Much based on the data which we are collecting. A location of resources. We are much use the data which you are collecting. But also. All plans. When we are developing health plans and all many plans which are we are doing in Tanzania. We are trying to use the data. Now what effort which we are using. It seems that the data which you are collecting are much used. At the national level. And the regional level. Less used at the facility level. And the hospital level. So we are now struggling to make sure at the facility level. They are using data. That is why Tanzania and many of the government have already collaborated with his group. In piloting the excellence district on the data use. So that we think when we will be able to build the capacity of the facility level. District level. How many people to use data will we be able to achieve the last question. In short, that's what you can share from Tanzania. Thank you. I think we can take another question. You have. Thank you. Thank you very much. Good morning everyone. My name is a man. I'm the regional advisor. From WTO for the Southeast Asia regional office. Thank you very much for the presenters. Your testimonies and your insight is quite useful. I'm just going to be a bit cautionary regarding the understanding of using the tracker data, the purpose of it. It's a fantastic facility in the highest to it has come a long way. And my only concern is when I hear that you are trying to transfer registers to be mimicking the paper based registers into tracker. We are currently defining or in a way self defeating strategy to follow. We have faced many issues in countries to try and understand how well registers are doing, are they standardized enough, relative to what we call the service standards from the service delivery point of view. And what we were challenged with is that many of these registers are sometimes collecting the wrong data. For me, we need a dialogue on what exactly is the purpose of collecting tracker data. It's not an electronic medical record it's not for us to measure every small detail that's needed for the patient care. It's so actually think strategically about a subset of the most essential data elements you need to follow up or at least to understand how well care is being delivered. So it's a huge investment. It's almost a different type of skill needed. So what we need to hear from you is that you have conducted enough of a national dialogue on what exactly is needed to be measured at the patient level on account of each episode or each encounter that would be useful to exactly what my good colleague and brother from Tanzania said the fact that I need the policymakers, the program managers to understand how well or not care is being delivered. Rather than I calculate or at least measure every encounter from a lab based result to an imagery result to this and that because not even in high income countries. Do you find at any form of facility based system that behaves as an electronic medical record and as well as the sort of the top level facility based reporting of aggregates of encounters allocation of resources medicines that doesn't exist and the data is voluminous. You want to try to formulate the question. Yes, the question is yes. The question is just, it's a very significant undertaking. And I would like to hear from each of the panelists. How well do you really understand or can articulate the need for the tracker data to be measured, given the cost of the skills needed and the quality exactly what my colleagues have said the data quality implications that will follow. Thank you. Thank you. Who wants to go first. Thank you so much. So, in Ethiopia, I think implementation of tracker is tested I think at least in in three programs. Number one, in COVID response. So all tested individuals, vaccinate individuals, and others are no coming through their, you know, and we were collected it individually so it has many purposes I think the second one is for any city. So we went to focus those individuals since they are lacking behind to get the service. We are not, you know, removing the paper that we are working thoroughly. So the third one is for TV program, since they are in a dropout so we could manage using this program, but we have an excellent example implementation of electronic medical record. So we are in at least currently in two big hospitals in the city. I mean, in the capital city in a day so they are totally paperless. We're implementing the for the last, like, two years. So, we understand that to implement electronic medical in the whole setting. The first thing is that leadership commitment is very important. That's that's hospital matters. The second one is, you know, the capacity to have good infrastructure and other things if you have good leadership. That is the first thing. The third one is currently the mayor of a dissident is committed to implement electronic medical record now look at a resource or all facilities in the, I mean, in the capital city. It will make us to be, you know, getting the data individually, you know, improving the quality of data and facilities and information. It has a lot of benefits, but what matters is leadership commitment matters, whatever, whatever you have the resource at hand, if your leaders are not committed, you'll not do anything. So, but the question is whether it is scalable. So the remaining setting or not. As a big country. I don't think we'll implement electronic medical record at each corner of the country that is the main challenge because we have a lot of infrastructures and leadership and resource coming in gap. Thank you. You want to respond. I think I don't have a different answer. From what my colleague have said, maybe we can hear from Iraq. Yeah, thank you very much. It was very important questions and when when I talked to about the governance model it included a special team to be institutionalized reviewing all these forms so we because we know existing paper. It's important to mimic it to be user friendly, but need to ensure that the data there are not garbage and garbage out that it's useful for the whether it's aggregated or case based. So for both. I mean when I when I link it to health system so we need to prioritize phase where is where are the problems so for Iraq is the planning is ad hoc. The resources are not. So what do we need now we need to prioritize for example the aggregated that gives the picture to do a high level policies and plans for the country. But there are other low hanging fruits in the country if you feel it's feasible for example TV. We started it because we have 155 centers and we have the resources we have the partner and we building the capacity but it's a long process and it's not just the plan you said implemented it's evolving changing every day you learn from a facility to a facility. So, the points you raise are very important and it's a very contextualized answer to be, but we need to look at the root causes and how we can improve the service provision of that certain tracker if it's a major challenge or priority for that country. Thank you. I think we can take another question. Good morning everyone. I am another from Mexico based in Pakistan. I have a lot of questions but I would limit myself to only two. The one is what is the key. Basically you followed for the political commitment. You followed in everything for the successful DHS to implementation.  So how did you cater their thing and the third question from my side.  Is there any central authority covering that are looking after the DHS to the information system for the multi sectors like wash and climate change. I must say, and the health information system at the facilities as well. Thank you. Thank you. Any questions, any takers. The first question is one of them maybe. Yeah, the first one was about the political commitments right. And can you repeat the question and can you Yes, and the success you did achieve. So I wanted to ask about for our clarity what was the key to involve these political people and the ministries that you successfully implemented the DHS to and they're located the funds and then providing the technical support and there's only a few questions from them. So, I think, let's start with the first. Thank you very much. I mean, Iraq is context. I mean, it's a very complex geopolitical situation. I mean you have a very rapidly changing politics, and then the country, whoever comes to the government wants to to demonstrate some successes on different sectors, including the health sector. So we advocated on, I mean, with the higher level politician politician in the country, I mean, they already have the when the government agenda or the program. It's a digitalization so all our role is to go there and demonstrate how digitalization will strengthen their political and enable them to demonstrate good success so for example Iraq, they decided to go with API case based. When we linked it with the politician decision makers okay we can achieve in six months aggregated data that gives you some visibility okay let's go for aggregated no case based after two three years for example, but it's a context specific but not easy. And then, for example, it's not just DHS to answer your other question about wash. So, we, we have another system we are working on capturing all that information for the decision me and we call it the low hanging fruit. Why this, because we need to demonstrate some successes so that keeps the momentum and the interest of the so and on 7th of June so we had launched at a tool, it's a WHO here I'm still. It helps us in DHS to actually because all the organizational unit was brought from there and so some because of the DHS tools interoperability. There are ways to. They are all component of his health information system. So that keeping that interest and involvement of politician. So the prime minister was invited the whole members of parliament were invited. And my colleagues I mean from headquarter and they were showing bro. So this kind of events helps for case of Iraq, it helps a lot to keep that political support. And then there are many other stories, maybe we don't have time to explain but I'm happy to share it with you. Thank you. And we have days to connect in the breaks. I think I just want to see other many people that have questions so we can kind of maybe limited to one person. Yeah, let's do a few more. All right, just a quick one. Kenneth champion from Malawi senior degree advisor. So I just wanted to learn from everyone, especially those that have done interoperability, especially with the tracker. So how did you work with the unique identification to make sure at least the systems are talking to each other, especially on unique identification. Also, I was also interested for those that one question. You want to go first. Okay. I think it's a very interesting question was ambiguous in the, in the process of starting this is adoption. It's one of the experience of with interoperability into into the ability that it's a difficult work that we have with the HIs to eat the justice system that uses another platform so we established interoperability with them to share the specific vital statistics from the health facilities that same birds. And now they, they, they, they also whereas building their own system, and they introduce the, the, this number identification number. So, it's a recent project. So this year, we are going to start within the mechanism that that is already in place. We're going to start to collect this identification number to the tower system to HDI. So that we allow us to, to really use this number to the information system at the hospitals, and really be able to, to, to, to track, especially the chronic patients and others that we attend. Thank you. Thank you very much. You want to comment on the same or, yeah. I mean, this process, we are also on the, on the very preliminary stage on the unique identification. And also in Tanzania, we have one institution which is providing many identification ID, I mean national ID. We're trying now to, to make interoperability between the system of national ID with the system, how many of the, with the tracker which we are having so that we can have a unique identification of the, those client, but also we are now piloting also the biometric. Very, very, very infant stage. So it's a process which we are going through in Tanzania also in the unique identification. Yeah. Okay, have another question here. Yeah. Sorry, I have the microphone. My name is Giorgio Donga. I'm from US Centers for Disease Control and Prevention. I'm happy that we have a panel from composed of senior officials from the Ministry of Health. I want us to revisit the question of investment into tracker system beyond the human resources that you have explained. I do support many countries in implementing tracker system. I'm in tracker module for notifying submitting that a case level data for epidemic prone diseases, and I have good insights into what it costs to do that implementation Sierra Leone is an example. In terms of the tablets, in terms of internet, not just availability of it, but the cost of submitting that data. I want to hear from different countries that are there what strategies we are using to to meet those costs, whether there is concerted effort or commitment by the government to invest in those infrastructure that would facilitate tracker implementation in your countries. Thank you. Thank you, George. Take yours. Yeah, thank you very much. I mean, for Iraq, we are planning or, I mean, the goal is to implement the tracker. So, for that, I mean, we had to do our homework and see where we can succeed and get evidence on like when we applied here and very shortly in two months, we got the picture of where are the connectivity is like we have the connectivity in 95% of all the 5,205 for example, and then we identified where the communication is. We don't know. I mean, we know if it's working or not working, but, but that's a very good preparation. We do it so for sustainability. I mean we have principles the principles as you said, we build on existing resources. That's our principle. So it's built on existing resources and utilize it to to use the on that. For now, we are working also with the Ministry of Finance. I mean, what the Ministry of Finance in Iraq is exactly, I mean, is highlighting the government, as I said, it's a rich resource country, but you need to demonstrate a success story and you need to work and get the system is running well and increase the interest so that the government can sustain it and finance it. We know that Iraq is not, I mean, it's not the two part, Kursan region of Iraq and the federal ministry. So there are resources limitation in some part of Iraq. We need to consider this also. So it's a very mixed approach, but we, it's very critical that you take, as you said, these principles and apply it on ground to generate the interest so that it can be sustained by the government itself by the ministries. Of course, and collaboration between, I mean, I mean, you need an interest, you need an investment plan, strategy to make sure that it's sustained, but when that comes, it's a context specific and a program specific. But definitely you need to start where there are priorities and where there are good achievements can be demonstrated to get that interest. Thank you. I think actually we'll cut you there. I have some practical information, but before I do that, we should give the panelists a big round of applause. Thank you so much. Thank you. Okay, so I think I was perhaps not the only one that struggled a little bit with the agenda and all the parallel sessions starting and ending at different times, etc. So just to try to make it a little bit easier to navigate the afternoon and all the sessions. If you go to the homepage for the conference, there's a link here now to a table, a PDF. That looks like this. So now you have kind of the different auditoriums and then you can see when sessions are starting and ending. Okay, so that's on the homepage for the conference. Yeah, and then you can have this more tabular view and we'll put another one for tomorrow. This is only for today. So, I think Max also has some practical information. Sure. So just to let you guys know that yesterday we did some filming for interviews which went really well we had maybe 12 volunteers and we're going to do it again today since I know a few other people wanted to talk to us. So we'll be outside in this area here between the two venues at around five o'clock. So if you're interested in coming to share a story with us just come and stop by. And my colleague to quadro also be going around trying to look for volunteers for us. So do it today at five during the experts experts lounge. Okay. And I think with that we're done for the plenary sessions so now it's time for lunch. Please make your way over to the cafeteria. We'll see you at the parallel sessions at one o'clock.