 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. 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. 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, 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. It's really 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. We 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. Like you just plop someone down in front of a map, you know, a blank maps app and expect them to, you know, get it right away. 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. Sometimes it 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 this even easier than the other analytical apps. It's 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. Then you have thematic 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 all units, one specifically specifically tailored towards the facilities the lowest level, and one that can show the full hierarchy. In addition, we will 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. I'm going 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 thematic. 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 the some of the features build on the others. And now we have a full package that we would like to present often also I've some 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 it maps you don't need to wait for 240 to be able to do this so just start playing with the maps up. The, the most important feature for 240 was a feedback we got. We had a workshop in Nairobi you will hear more about it. And that was that printed maps are the main way of sharing informations 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 SS2 maps was very limited. And we have improved that greatly in this version. Another important feature I know has been request by many was that it was only possible to display the name of the argue and it's 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 lots 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 is 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 in set 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 in the maps that you have the power of adding at as many layers as you like. So that can be a great feature, especially if there is a linkage you want to show between the two layers, but in instead of the 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. The second 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 this thematic mapping technique which is called a corraplets supporting supported. So one here the districts are colorized according to a statistical value, and this is the great map to use. If you want to, to see data that is normalized per capita percentage, but it's not the map you should use if you want to show raw number total population, or the number of birth in the districts. 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 going to 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 and the value here is only room for the for the values for the district but here is much more much much easier to compare the districts and the different elements 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 from a program and it has a data element attached it you can decide to style by this data element. Instead of just showing the events at black dots you can hear 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 man for example the diagnosis you know that can be a 1000s so trying to style but 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 of thousands hundred thousand events. So that's why we have 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 not the maps up it's 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 with the with the filter. And then this one is that if you have if you have many events you can decide to group them into these these clusters that are lying close to each other. And you'll 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 over 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 will show you different ways you can easily import this catchment areas into the system. But when you have catchment areas, you will see in this audience when you select your audience for your layers you will see you have an extra drop down 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 audience it can have multiple geometries attached. So normally a facility will only be a point in the version you're having but they can now also be a polygon or the area where so, 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 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 339 where 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 also like the catchment area instead. So this one is showing a thematic map, whether 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. And especially if you're a bit uncertain, because you know your districts. You can see all the way in you can see the individual neighborhoods and housing, and you can see where the areas are drawn on top. 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. And then 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 and 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. 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 DHS2. I created this mapping QGIS in another GIS 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 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 with vector-borne diseases and health. This one is showing land cover or land use. It will show the whole the landscape varies within the districts. And this one is showing a state there 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 chieftains. You can see the chieftains with the most percentage of wetlands. So you can see there is BMC state. No chieftain 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. This is three map layers here. You have the population density at the bottom. Then I've added chieftains, 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 every 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, WorldPop has many different data sets. We have added two 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 we import to the system. This is only for the youth to view. It's not taking over the population data you 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. Now we get a lot of requests because they want to data for this year. The good news is that WorldPop is currently taking even more newer census data, where they have been in the recent years and they will not produce these 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, previously use the data table much more. You can sort by them 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 you would like to see the number, the population living within 3,000 meters, for example, from a health facility, you can use this feature. So you will see here 3,070 lives 3,000 meters within 3,000 meters from this facility. If you have catchment areas, this can be defined much more accurate. So here we have the same district with the catchment area. And you will see that the population is then much higher, more than 9,000. Another thing we have added, this is in 237, is that the Maps app is probably the best app to use to have a good overview of your facilities. And there has 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 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 tried to cover many use cases with the DHS2 Maps, but we will never be able to compete with the 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 we made it very easy to get data out of DHS2 into another program. So if you click on that menu when you have your layer, there is a download data button. An important thing here is that 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 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 settlement extents from Grid3. 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.