 Okay. So let's get started. So let me first of all thank you for joining this DHIS2 webinar. Today we're going to be talking about some advanced population mapping that you can now do in DHIS2. We'll also be talking about some of the kind of tried and true methods of assessing population or getting population data in DHIS2. Let me introduce myself. I'm Scott Russ Patrick. I'm the DHIS2 Analytics Product Manager. I'll be doing the first part of the presentation today. I'm then going to be joined by my colleague, Lloyd Manuel, and he's coming joining us from Crosscut. He'll be taking us to the second part of the presentation. At any point, if you have any questions, I just always put my email here. I'm always happy to follow up with any questions. If you need any more specific detail or you want to go into something, so here's my email scott at DHIS2.org if you ever need to get in touch. All right, let's just start going through it. A quick overview of what we're going to do today. First, I'm going to give you a quick introduction to DHIS2. I know that many of you are probably very familiar with DHIS2, but we saw from the registration that there were quite a lot of folks who were joining today that were not using DHIS2 or not in countries that currently use DHIS2. And so we want to just make sure that everybody's on the same page. I'll do a quick five-minute introduction of what DHIS2 is. Then we're going to get into the actual meat of the presentation. We're going to talk a little bit about the initial problems that we're seeing with various population sources in countries that are using DHIS2 and how those issues are affecting the types of indicators, calculations, analyses that we're able to do. Then we're going to get into a couple of solutions. We're first going to talk about how we can use clinical service-based denominators as populations to calculate some of our indicators. This is not an incredible technical innovation. This is just a very tried, it is increasingly a tried and true approach to using the data you already have in many countries, DHIS2 instances, to be able to calculate more accurate coverage-based indicators that you need for immunization campaigns, for example. And we'll look at a couple of case studies of that. Then we're going to get into some more of the technical innovations. We're going to look at some of the alternative population denominators. Now they were able to see in DHIS2 coming from third-party sources. And we're going to see some of the latest and greatest technology that we have to be able to build or produce catchment areas for facilities and attribute population by gender and age to those catchment areas. So after that, I'll give you a quick demonstration of these new features. And then I'm going to hand it over to take us through how his organization Crosscut is actually enabling DHIS2 users to build these catchment areas and how you will be able to deploy these catchment areas in your own DHIS2 instance if you wanted to do that. Now we're planning to take about an hour for the entire presentation myself and Chloe combined. So we will have a little bit of time at the end for Q&A. The Q&A can happen here in the chat, but it can also happen on the community of practice. So here's a link to the community of practice. This is where we're currently live streaming this event as well. And the community of practice is a great place to share your thoughts, impressions, opinions, ask any questions that you have, maybe answer some questions that people are posting there as well. And it also is a place where we can continue to follow up on the conversation. So after the webinar is done, we'll all still be on the community practice and we can all still be sharing ideas answering questions there. All right, so quick introduction to DHIS2. So DHIS2 is essentially a data capture management and analysis class. It is extremely generic and flexible and is supplied to a wide range of use cases. For example, health, education, agriculture, it's even being used to monitor pro-goffing in the US PGA tour. So it's extremely flexible. It is a completely open source product. Everything about DHIS2 is free to use. This developed from the University of Oslo, at the very least. Of course it is not free to necessarily host DHIS2. And since obviously there's costs associated with hosting servers and having the proper infrastructure and that kind of thing, but there is no license or fee to use the software. DHIS2 is an application-based ecosystem. So just like you have Android or you have your iOS, the operating systems on your cell phones, DHIS2 is the same in that when you look at DHIS2, you see an app menu and all of these apps do different functionalities. Some apps are used for data capture, other apps are used for system management. Many apps are used for data use and analytics. So many, many apps. The University of Oslo, we maintain about 30 core applications, what we consider core applications. These applications are the bare minimum necessary functionality for some of our key use cases in health sector, in education sector, supply chain logistics. But there exist thousands of DHIS2 experts around the world and these experts are also producing their own applications. And many of these applications are very generic and can be applied to many countries or many different use cases. Other applications are very specific. They can maybe only be or are in one specific language or are hard coded to a very specific use case. But the DHIS2 platform enables people to innovate, build new applications, and then you can also post these applications to our app hub. So we have like an app store just like you see with like Android, for example. We call it DHIS2 app hub and you can see the community apps that are available there. All of this to say is that DHIS2 is a place where has a lot of native functionality. If you don't have the functionality that you need in your DHIS2 deployment, you should check out the app hub. Maybe someone's already made an app that does it. There's a good chance there's dozens of apps that are there. Or you can develop your own app. That's a distinct possibility and we maintain resources, guidance, documentation, technical support to folks who are building their own apps as well. We have academies and trainings on that as well. So DHIS2's principal use case is that as a national health management information system. And a national health management information system is used to capture data from all health facilities, all clinical services, health data, disease surveillance data, supply chain data, HR data sometimes. And all of that data is in a single data warehouse in which you're able to build analytics and dashboards and charts, maps, graphs there so you can visualize and use this data. DHIS2 is by far the world's largest health management information system platform, HMIS. You can see the countries that are currently using it. We estimate the DHIS2 is covering about 4.2 billion people worldwide, so a little over half the world's population. Health data is represented in DHIS2. Again, the core development here is at the University of Oslo, but we also have a very large network of DHIS2 experts around the world, which I'll point to. More information on that in just a couple slides. I did want to point out there was a UNICEF video published today about how DHIS2 has gone to national scale in one of the most densely populated countries on Earth, Bangladesh. So it's a really interesting story to show you kind of how DHIS2 can be implemented and scaled across an entire country with as much diversity and challenges and even expertise as a country like Bangladesh. So there's a link to that if you'd like to check it out. Maybe we can post this in the chat as well and you can kind of see DHIS2 in action. So because this webinar series focuses quite a lot on immunization and how DHIS2 is being used or can be used for immunization, I also wanted to point out, of course, everyone here has been very much focused on COVID-19 for the last couple of years. I'm sure you have as well. And DHIS2 is being used heavily for COVID-19 surveillance, so about 43 countries currently with additional 12th scaling. If you go to our website dhhis2.org backslash in action, then you will be able to see these maps of the screenshots that I'm showing here and you see that some of these countries, actually many of these countries have a little icon over them and that's saying that we have a user story from those countries that we've documented how they're using DHIS2 for COVID-19 surveillance. And then you can read these user stories and it's actually a really incredible thing to see how countries are innovating, how countries have set up DHIS2 to monitor for COVID-19 surveillance and even more incredible how countries are sharing knowledge, sharing resources, sharing expertise, sharing applications and innovations between each other for DHIS2. So when you're part of the DHIS2 ecosystem, community, you're not just operating in isolation, you're part of this very large global network with innovations and experts all feeding into one repository, one platform that everyone's able to benefit from. Same story goes for COVID-19 vaccine delivery, so about 41 countries currently operational and another four currently in deployment or development. And again, lots of interesting stories here, so I do encourage you to check it out when you have some time and see how DHIS2 is being used. If you're a country that's not currently using DHIS2, please do reach out to us. Like I said, there's probably an expert or an organization that has DHIS2 expertise either in your country or near your country that would be able to support you. Of course, University of Oslo can kind of be a bit of a guide to help getting things set up. Whether you already have DHIS2 or you want to apply DHIS2 to another context like COVID vaccine delivery, again, we have resources to help out with all of these. All right, so to put it a little bit in context, how big are some of these systems? Well, we obviously just mentioned Bangladesh. Bangladesh was a huge country, but specifically for COVID-19 surveillance and vaccine systems, we see some countries are really massive. So Sri Lanka, for example, has 19 million people enrolled in their COVID-19 surveillance system. Rwanda has over 10 million. Nigeria nearly 8 million. And you see that these systems are really, really big. Sri Lanka is handling 25 million COVID-19 related events and data being stored in the DHIS2. And so we want to make sure that DHIS2 is, at the University of Oslo, a big focus is making sure it's robust, it's strong, it's secure so that DHIS2 can perform when this much data is being put into the system. And then that data is secure and only accessible by those who need it, and it's not vulnerable to any kind of malicious acts, especially since we're having now DHIS2 storing individual level data. And which brings me to my next point, what kind of data can we store in DHIS2? Well, there's really three types. The first one is aggregate, so starting at the left of the screen. Aggregate data is kind of your routine data captured from health facilities, your monthly facility reports, that kind of thing. That's where DHIS2 started about 25 years ago, is capturing that data. But now we are also able to capture event data. So event data, think of like outreach campaigns, supervision and support visits, educational events, so data about a single individual event. And we are also able to now monitor individual individuals, we call it tracking or tracker. And you're able to monitor that patient through a healthcare program, maybe it's COVID-19, testing and vaccination, maternal health, other immunization campaigns. And you're not able to just track people, you can track basically anything, you could track equipment or drugs, commodities, buildings, infrastructure. You can monitor these longitudinally through specific predefined programs. All right. So that data from aggregate event and tracker is then all stored in a single data repository, data warehouse, which DHIS2 supplies that. And then it's available through various analytic tools, so maps, charts and dashboards. And we'll show you some of those analytics tools later in the presentation. DHIS2 is a massive community, global community. Our principal or primary points of support to countries are through these ISP groups as health information strengthening program groups. There are, I think, now 17 ISP groups around the world, spread out Africa, Southeast Asia, Central and Southern America, yeah, all over the world. And they are able to support countries, support local DHIS2 users in whatever they need to do with DHIS2. You can find a link to and a list of all of our his groups on the website, on our website, dhis2.org. We also obviously work with many ministries of health. We work with many donors, hundreds of NGOs are using DHIS2 for various projects. And the list goes on and on and on. A large pool of software developers, just a really massive community. And all of that community is coming together in a single virtual place. And that's our community of practice. So community.dhis2.org, this is where anyone can get information about latest DHIS2 innovations, you can ask questions, you can answer questions, you can share insights, you can see announcements, you can give us feedback on features that you like or more importantly features that you don't like or that you want changed or you want features added. It's just a huge community with thousands of people interacting on the community of practice. You know, you can see 10 years worth of knowledge is there on the community of practice. So if you have a question about DHIS2, it's probably likely that someone else has had that question already. And you can find the answer to it on the community practice. So, you know, my principle rule with DHIS2 is don't suffer in silence. You know, if you have an issue, you have a problem, please reach out, be on the community practice. And there are people there that are able to support and help you through any challenge that you have. So we can use other population estimates now, or we have other population estimates available to us. And there are several sources of these population estimates. WorldPop has been one of the primary sources for quite a long time. They have now partnered with a organization called Grid3 to be able to derive from a bottom's up data sets very accurate, very granular population figures. You can see here on the slide, there are two different approaches, top, down, and bottom up. I'm not going to get into these approaches. I'm not the most qualified person to talk about it. But the good news is that we actually, in our last webinar, which you see a link to here, back in December, we had folks from Grid3 join us on that webinar. And they explained in detail their various approaches. They also have it on their website, both WorldPop and Grid3 have a very good explanation on their website. But you can also go on YouTube and watch our previous webinar and you can hear it straight from the horse's mouth, so to speak. We also get population data, can get population data via Google Earth Engine. So Google has their own algorithms, their own approaches. They are able to feed us both data from WorldPop, as well as their own sources. And there's also Facebook's data for good initiative, which also derives very detailed population data. Now, we don't have Facebook data available to us and DHIS too just yet, but we are talking to them and hopefully we'll have that very soon. Sorry, went a little too far. Okay, so let's look at this in action. Now, I know we're all kind of tired of looking at charts here, but I just want to tell a quick story about Tansali District in Zambia, how they have been using these populations that are coming from these other sources, specifically WorldPop and Grid3. So here we're looking at Tansali District, all the health facilities as a row. And we can look at their, the first column here is the Ministry of Health Population, so the total population for each facility they've calculated as the catchment. The second column is the population under one year of age, so zero to 11 months. And then we look at the percentage of the total population that is under one. And we can see that in some health facilities, it's quite high. So they're saying that in Tansali Hospital Affiliate HC, they have 11.5% of their population is under one year of age at that facility. And what you see highlighted here in green is when they conducted this work, it was in partnership with UNICEF, Global UNICEF, Grid3, and our local partner in his South Africa conducted this work. And they said that these population figures in green here are incorrect. So these percentage of total population under one is way, way too high. And so what they did was they revised it down to 4.1 to 4.2 for every single health facility. And they found, they got the number of 4.1 to 4.2 based upon reliable surveys that have been done in Zambia for the total, the percentage of population that is under one year of age. And so you can see that the population revised down is the second to last column here. And so you can see that it actually goes down quite significantly from 11,000, which is what the Ministry of Health had down to about 6,000 once they revised the percentage under one. But they went a step further, right? So they didn't just revise it down, but then Grid3 in partnership with World Pop, UNICEF, and his South Africa came in and they applied their bottoms-up population approach. And the bottoms-up population approach for Grid3 came out with a new population for each individual health facility. You can see that in total for the entire district is very similar to the revised population. So the revised population was 6,241. And what Grid3 came up with their more advanced approach looking at the various population sources, population densities, household enumerations, their very advanced approach came up with 6,171 as the population. But Grid3 is able to go a step further, right? So Grid3 was then able to look at what was the population that was in 30-minute walking time of a health facility, right? And so within 30-minute walking time, that was only 4,472 for under one population. Then they go a step further. The last column here is looking at within a 60-minute walking time. And there's quite a lot of data to show that if someone has to walk longer than 60 minutes to receive routine health services, they probably won't seek those services out, right? And so they say within the 60-minute walking time, they have a population of 5,483 to each one of these health facilities. Okay, so let's look at these different population sources side-by-side comparison for pentavalent three coverage. All right, the first column here is the entire country of Zambia, Ministry of Health projected pentavalent three coverage rate. The second one column is the pentavalent three coverage rate based upon the revised population denominator. Again, this was the population denominator that they applied to 4.1 multiplier 2. The third column here is that grid three pentavalent coverage rate. So grid three is approached to population estimate. And you can see that the revised population and the grid three are very close to each other, 76.5 versus 77.3. Now, very important is grid three's next step, which was, which is the third column here, which is looking at the pentavalent three coverage from within a 60-minute walking time. So that is 87.1. So 87.1 percent of the population that is within a 60-minute walking time of these clinics is getting the pentavalent three vaccine, right? That's what that indicator is saying. Now, the last column here is when they applied a service-based denominator to it. Now, this is very interesting. The service-based denominator, which we had just been talking about using the service-based denominators, gave an indicator value of 98.7 percent. So quite a lot higher. Why is this? Well, what this is probably telling us that in Chensali district, you actually have a large proportion of the population that is not receiving clinical services in Chensali district, right? Or they're just not receiving clinical services at all. Maybe they live very, very far away, maybe a two-hour walking time away from the health facility, and they're not getting pentavalent three shots at all. So that's how we can kind of start to interpret the difference between the service-based denominator here for pentavalent three versus the grid three or the revised indicator calculation for pentavalent three. All right. So let's now talk, let's shift gears a little bit. That was service-based denominators. Let's talk and Google Earth Engine talking about kind of the theoretical approaches or processes to apply these population figures. Let's now look at some of the features to support these processes. So I'm going to talk about five new features here in DHS2. These are our facility profiles, the world-pop data that I was just showing through Google Earth Engine, a structures map through Google Earth Engine. That'll help us figure out where people are actually living. We're going to talk a little bit about the facility catchment that's being provided through Crosscut. I'm just going to give you a really quick overview of the facility catchment, and then Quinn's going to come in and give us a lot more detail about it. And then I'm also going to mention the offline mobile dashboards. So let's just jump right in. So the first feature that I'm going to point out is the organizational unit profile. And you see under where it says organization profile on this slide, I have the release number for DHS2 where this feature was made available. So this feature became available in DHS 2.37. That is the most recent release. And next month, we will be releasing DHS 2.38. But the most recent release currently available is DHS 2.37. And in 2.37, we have this new feature called organization unit profile. And essentially what this allows you to do is to click on any org unit in your country's database, in the Maps app, and you will bring up a profile of that org unit. So you can have things like a picture. You can also have key data. So you can have a population under five or population under one or total population. You can have total vaccine coverage rates. You can have any kind of attribute data that you want to see. So facility type coordinates, whatever it is that you want, this organization profile is completely configurable by you and by your system administrators. And you'll be able to allow for anyone using the Maps app to just click on any point, any facility, even districts as well, anywhere in on the map and bring up these kind of key information that you need to know kind of at a glance. So a really useful practical tool to looking at facility-based data in DHS 2. The other one here is now we are able to use get fairly detailed population estimates from World Pop and Grid 3 via Google Earth Engine. Now I'm just going to mention this. I'll show you in a demo live here just in a second. The other one that I want to mention is that now we have building structures layer and this building structures comes from, again, Google Earth Engine. And this dataset contains 516 million structures in Africa, which they estimate to be about 64% of the total African continent in terms of structures. So not 100%, but it is getting better every day. As soon as you know, it's hard to give a time frame, but eventually it will be a very comprehensive structures map. But even as it stands now, you'll see that it's quite detailed and what you actually see is these orange outline of every structure that has been detected. And they use aerial photography, machine learning to be able to identify these structures. And now we are able to pull that into DHS 2. So I'll give a quick demo of that as well. Catchment areas. Catchment areas is a big advance. It's coming out in the next release of DHS 2.38 that comes out next month. So it's not available in any of the current releases. It's coming out next month. And essentially what we're able to do is we're now able to have multiple geometries per org unit. Sounds very technical. Essentially what it means is health facilities, schools, community health posts, any kind of point location in your country can also have a catchment area drawn for it. So you can finally start to get population estimates or understanding of settlements that fall within a catchment area for a health facility. Now again, Coyt is going to come in and give us a lot more detail on this, but I'm just mentioning that this is a feature that's coming out in the next release. So I have got one more slide here. Now this next feature came out in DHS 2.36. So it's been out for about a year now. We now support offline mobile dashboards. So dashboards on your cell phone. Now obviously not specific towards population mapping, but what it essentially means is that if you make any maps in DHS 2 that show populations or building structures or any kind of thematic map that you're using for any kind of outreach campaign or site supervision or any activity that requires you to go out to the field is now you can have that dashboard. You can view it on your smartphone. It works for iOS and Android just through your web browser on your smartphone. And you're able to save that dashboard to be available offline. So you bring up your dashboard for the district. You jump in the truck. You drive out to a health facility. You're doing supervision support at that health facility or maybe you're organizing an outreach campaign from that health facility. And you're able to visualize, use, share your data even while you're offline. So everyone can huddle around your phone or tablet. And it also of course works on your computers and your laptops. And you're able to sit there and look at the data, talk about the data, share the data even if you're not connected to the internet. So this is a really exciting advance in DHS 2 and essentially means that you can take your DHS 2 dashboards in your pocket anywhere and any time have them available to you. All right. The last thing I want to point out is I'm talking about some pretty cool features I think specifically how data is coming into DHS 2 via the Google Earth Engine. Now I'm going to just quickly point to the fact that this data can also be available to you outside of just the Maps app. So everything that I've been talking about is confined to the Maps app. But you can also have this data in your standard data sets, your standard indicators, your other analytics tools. But you have to import it. And there is an app in the community to support data imports from Google Earth Engine. It's called the DHS 2 GEE Data Importer app. It's in the app hub. There's a link to the app hub. I was talking about what the app hub is earlier. It's just a repository for all the DHS 2 apps that are developed outside the University of Oslo. And so you can go get this app, download it to your DHS 2 instance, and start importing this data from Google Earth Engine. We also have the plan to bring in this functionality to the core import-export app of DHS 2 in the release at the end of the year. That's DHS 2.39. So that will be a native functionality towards the end of this year. But as it stands right now, if you're using DHS 2.31 all the way up to 2.37, you can use this application that's available in the app hub. All right. So I know I'm running a little over time, but I think that we're still doing okay. I am going to now just do a quick demo for this. Can someone just confirm that you can still see my screen, please? Yes. Great. Thanks. All right. So I'm now looking at the Maps app. And I am going to add a layer. So click Add Layer in the upper right corner. Maybe I can zoom in a little bit here. So add layer upper, sorry, upper left-hand corner. And you see that we have some new thematic layers here. So we have population, population by age and gender, building footprints, elevation precipitation, and we have some other temperature land cover. So what I'm going to do is turn on population by age and gender. And let's say I just want to see my under five population. So I'm going to click male zero to one, male one to four, scroll down, do the same thing for female. There we go. And we have different aggregation methods. So I can say some or mean. I also have all of these others. Just to keep it simple, I'm just going to turn off mean and just have some. I am now going to switch over to my org units. And I'm going to do this quickly, but Chloe's going to take us through a little bit more slowly so that everybody can kind of appreciate what's going on here. I'm going to just turn on my facility layer. I'm going to turn on my catchment areas. And I'm going to turn on for just one district, Bambali district, because this data is going to be pulled from Google Earth Engine as soon as I click add layer. And if I turn on the whole country, it would take a little bit of time because it's pulling in a lot of data. So I'm just going to do one district. It's going to take a second to load. All right. So here's our catchment area. So the district, you can see that each spot is a health facility. And then we have a catchment area drawn for each health facility. I can click on one of these catchment areas. And I can see the total under one population that's coming from WorldPop via Google Earth Engine. So you can see that this has a total under one population of 816. And I can click on any of these health facilities from catchment areas and see the population under one population for that health facility. Now, let's add another layer of complexity. Let's add the building footprints. And so I'm going to leave my irrigation method to count. I'm going to turn on just again Bambali districts. I'm going to turn on my facility layer level and my catchment areas and click add. Again, it's going to take just a second to load. Again, so we're pulling this data in real time from the catchment, sorry, the footprints layer. So you can see it's starting to circulate. And you can see these orange dots are kind of orange heat map showing up. And these orange heat map represents all of the facilities. So I'm going to toggle off the visibility of my population. I'm going to zoom in. You can see as I zoom in, the content of the work detail and I keep zooming in. Eventually, I get down to individual structures. So I do things like turn on imagery and then you can see all of the all of the structures here are actually showing up as orange. And if I zoom out, it will just resolution out. I zoom even further out and click on the site or sorry, the catchment area. It's now giving me the total number of structures in that catchment area. So this catchment area for this health facility has 1,911 structures. So very important information to know for outreach events. If I talk about my population and switch over, then we can start to see some of the interesting analysis where we see where our population is and our structures. We can go, we can see that there are structures out here, usually structures in this area are usually indicative of actual villages or huts where people are living. So we can see that the health facility is over here, but the catchment goes all the way over here across this river. Maybe this area is a very far away from the health facility. So outreach campaigns, that kind of thing, for this area, if it's, you know, less accessible. So that's all I was going to do for the day. He's going to talk to us about how we actually make these catchment areas in DHIs too and how you'd be able to get that set up in your instance if you'd like. So that is it from me. I will hand it over to you. Excellent. Thanks, Scott. Can you guys hear me? Yeah, loud and clear. Okay, great. So I will try to go relatively quick here. So my name is Kuwait Manual. I'm based in Washington, DC with a company called Crosscut. We're focused pretty heavily on geospatial micro-planning. Our primary area of focus is in supply chain analytics. So what I'm going to show you today is essentially Scott talked a lot about the use of population and some of the new visualizations with the building and things like that that can be used in DHIs too. Really the main focus and the point that I really hope that you hear today is around creating the catchment areas to be able to use in DHIs too or in other systems. So that's what I'm going to show you today. So just confirming you can see my screen. Yes. Okay, great. Okay, geospatial micro-planning. So what does micro-planning mean? A lot of times folks mean different things when they refer to micro-planning. Generally speaking, and for the purposes of today, it's referring to the processes and tools for public health planning below the district level. So the focus is below the district level. A typical elements are around estimating the target populations and identifying the settlements. A lot of what Scott was describing and showing you. Creating area maps or catchment area maps, and then estimating the supplies and resources that you need for routine services or for campaigns. So geospatial micro-planning just refers to using geospatial tools to help support that process. So there's two typical types of area mapping that's done to support micro-planning. There are site-based catchment areas which is what Scott was describing and kind of what you can see in this map here on the top right where you're essentially identifying the area that is served by a nearby health facility. The other one that's typically used is we call this population-based catchment areas or essentially ways to divide up an area for supporting a door-to-door style campaign where it's not necessarily delivered via fixed posts but is more set up to be sized by a number of buildings or a number of people. So catchment areas, why are they important? They, as Scott was sort of describing, help you estimate the target population and measure coverage. It becomes very important for forecasting supply needs and in terms of accessibility, it helps you look within the catchment area and identify those settlements that maybe have poor access to the to the health site. So it helps you sort of plan, do the session planning and outreach planning to cover all of the sites for a campaign or for routine services. So Crosscut is essentially an app you can use. It's free. It's available online and that's what I'm going to show you today, essentially to here's what it looks like to create catchment areas that you can use in DHIS too. So this is our application. So I'm just going to do a demo here. Okay, this is my list of catchment areas. So essentially this is kind of where a user would start off, where any catchment areas that get created get listed here. So the actual creation process, I'm going to show you that now. So it's fairly straightforward. The two types that I mentioned were site-based, where you need the latitude and longitude of each site. Or the other one is where you're setting up catchment areas for a door-to-door campaign with roughly the same population. The third option that you can do is essentially just draw your own catchment. So typically, many programs just will have literally take a paper map and then draw lines on it. That's part of the concept of what you can do with this. We call it the digital sharpie. But for today, I'm going to show you one with latitude and longitude. So we've got a handful of countries loaded on here. I'm going to pick a small one today with East Wattini. So basically what this is saying is you need to load a file with all of your sites that have the latitude and longitude. So this is me doing that. Then you tell it which column is your latitude and longitude, which column is your site name, and that is it. So my point in showing you that is mainly just to say that this is a very easy, fast process to be able to do. So that's a key message that I want you to be able to take home today. So while that's running, which we'll see, we'll just give it a second. So those of you that are involved in geospatial planning know some of what it takes computationally to be able to draw catchment area maps. So what you're going to see here are catchment areas. So the yellow lines are actually the administrative districts. So essentially what this does is carve up the administrative districts and assign it to its nearest site. So what you'll see here, if we zoom in, you can see each of the catchment areas here. And just as Scott was showing, it shows the breakdown of the population. This is coming from Facebook, the number of buildings, the estimated number of buildings. This is actually coming from OpenStreetMap. So again, we just pull from the sources that are available to us. But that's that. We do have the apps available in English. We have it in French. If that's a preference, we actually have it in Arabic also. And it's partially translated into Amharic, not completely. We'll stick to English to help me. So looking at this map here, a couple of layers, just like what Scott was showing, the population is there to be able to look at where there are actually buildings and the suspicion that people are actually living in these areas. So fairly straightforward view. The travel time is nice. It lets you, this is walking travel time estimates here. So this shows you a particular district here. It's divided up into each of the catchment areas. The green shows one hour travel time. Yellow is roughly one to four hour travel time. And you can actually adjust those. So if you want your red to be anything above two hours, then you can actually change it and get the adjustment there. So that's helpful. One thing that we found that several immunization programs have been interested in is actually the combination of looking at travel time and population. So we have a slightly more complex view that usually takes a little bit of explanation where let's just zoom in here and just look at one for right now. So this shows a single catchment area. We'll say green is anything less than 30 minutes. And red is anything more than two hours. So what it does is it looks, the purpose of this particular view is to identify areas that are both densely populated and far away from the actual site and the value there. So what I've done here is if you look at the red, anything that's red is more than two hours from the particular site. And then anything that's dark red is essentially a more densely populated area that's also far away from the site. So that might be a good area to target or include in a particular outreach. So that's kind of what I wanted to show you. But really the core point here in the main DHIS tie-in and the purpose of the day is around the catchment areas. So kind of looking back at our list here, this is a viewer we have on our actual application, but all of this is available for loading into other systems. So this is literally the catchment area file. It's that easy to be able to download and use. It can also be integrated with other platforms via our API if that's a preference. So one thing to note is that some folks may want to actually have paper-based maps. So in that case, we actually have a generator that generates a set of PDFs that can be used to either print out and put on the wall of a health facility or passed out to a particular team to carry out a campaign where electronics not an option. So just kind of, you can see that that's essentially kind of what you're looking at here. So just to give you an example, so a little paper-based simple map here. Yeah. So I showed you East Wattini. There's a handful of countries currently loaded onto the app and we're attempting to load more. That's a major focus of the work this year is trying to load additional countries into the application. What I showed you with East Wattini were site-based catchment areas. I want to show you just very briefly for door-to-door campaigns. There's essentially no dots on the map. It just carves up the territories into roughly equally sized by population. So the one thing to note is that the catchment areas are these little area maps here line with road boundaries. They align with the rivers so very able to be actually implemented and used by field teams. That was a key feature that was requested. But one thing we did find too is that all these catchment areas are automatically generated. So we inevitably find that there's people that want to make changes to the map. They don't like it for a particular reason because they know the area better and you would never divide up the land that way. So we did create a fairly simple way for them to be able to change it. So if we say that the users here wanted to change this catchment area, they could actually make that change directly here in the application. So here you can see the building estimates around 1200 buildings are estimated in this particular area. So you can actually just kind of color and change those as you need to. The building count goes up, which is typically how someone would use this. They would try to size it for workload to support a team. So we think it's pretty cool to be able to get to a certain level of precision with automatically generated maps, but then where it's necessary to give the user the ability to actually change those on the fly as they need to. So you can see here now the catchment area is bigger there. Okay, so that's essentially our application. So with DHIS-2, the idea here is you can actually import those catchment areas files. So I showed you kind of what an electronic version of those files look like. This is what you need to actually be able to pull into DHIS-2 to get this kind of a view, but I also showed you that it's actually not that difficult to be able to produce that type of to get these black line boundaries and also to be able to edit them manually if that's a desire. So yeah, that's catchment areas. The key thing to note there is really we tried to stay very focused on a very singular use case, which is creating catchment areas. We're attempting to provide something that's very easy to use and fast. It's a very sustainable in our perspective in that it doesn't take a large project or major technical assistance to refresh these. You can essentially just add sites, remove sites, or make adjustments and then refresh, and then they are refreshed. So the other elements are it's a combination of automated and customizable and it can easily be integrated. So we know that there are several folks that probably won't want to use our app or solely consume catchment areas on crosscut.io where they're created. So the idea is that you can very easily use these in other platforms. So we are currently developing an actual app to go into the the DHIS2 app hub just to make this a little bit easier for DHIS2 users. So instead of even going to the crosscut app at all, you could essentially sync your DHIS2 sites and run crosscut to pull the catchment area lines back in and then publish them into your DHIS2 app. So this is what we're currently building and we anticipate that this will be available in May. However, you can go today and check out the app at crosscut.io and try it out for yourself. We only have a few countries. So this map here shows you where we are and where we are going. So the countries in dark green are the ones that are fully in the app and available ready to go. The ones in light green that you see there we've essentially turned on a portion of the country where we've had users interested in just a particular area. The purple ones we anticipate having available for DHIS2 users in when we make that app available in May. So we'll turn those on in April. And then the yellow ones are the ones that we're planning for 2022. So if you notice anything you probably notice that the bigger ones are for 2022 and the smaller ones are for April 2022. There's a reason that that's the case and essentially the geospatial processing involved in creating these catchment area maps is actually fairly sizable. So the way that we make it fast for the user is we do heavy preprocessing so that the user can have a fast experience. And what it takes technologically to pull that off is it's more complex for larger countries as those of you who work in this area very well know. So this is our current plan but honestly if you have a particular interest and you're like I really want to be able to use this or do this sooner please reach out to us. You can email me directly here. My information is here on the slide. This is sort of our call to action slide here. So we will be making some, we're going to be hiring a couple of folks this year. So if you are looking, if you've got expertise in this area and looking for something new please reach out to us because we are going to be hiring. If you would have any interest in partnering with us, other technology providers we would love to make this available to be delivered in other technology platforms, VR APIs. Or if you're an implementing partner and want to use something like this in your actual implementation programs please reach out to us and we can talk about how we could customize some of the features for you. If you want to try it out you can actually just go to the website today and try it out. If you have any questions or additional feature requests or things like that or if you want to add your country please just email me. And then lastly to be able to make all of these available sooner we are actively seeking funding to be able to scale this technology to larger countries so that it can be delivered affordably. And so if you're interested in helping us to be able to do that faster please reach out because we are trying to raise support for that. With that I will stop, I know that was very fast but I wanted to allow a little time for questions. Thank you. Great thanks so much. That was a really incredible presentation and I just do want to iterate a couple of your final points here. The first one is that we want to work with countries implementers, NGOs, projects that want to implement this soon. You know as Chloe pointed out we are able to update, change, improve these features based upon real use cases. And we're able to do that in very, very quickly. We're able to rapidly improve things. If we have specific requests and requirements coming in from implementations in the field. And that's what we want to identify. We want to talk to you to support your implementations, to understand the issues, to understand the user workflows that will help us improve our features and our services. Not just to you but to everyone in the world who needs to use it. So please do reach out. If you're a country, an NGO, a project, a donor that wants to implement any of these features that we've been talking about, do reach out to us and we are very, very eager to work with you. And at least to hear your story and your use case that really helps us improve these products, these features. The other thing is of course things can move faster if we have more funding. And it's always working in the development sector, it's always a little bit of an elephant in the room but if you are a project that needs these services I think we would be able to respond relatively quickly if we were able to have more resources. So there are a few questions in the chat. I think I will start with my good friend Jillian Berkowitz from App Associates. She is saying, is there any plan for these mapping layers to be available on the Android interface? So on the maps that I showed Jill, you are able to show anything that's made in the Maps app in the dashboard. And now the dashboard is able to be viewed on a smartphone, whether it's iOS or Android. So all of the maps that I showed you that were DHS2 can be on a phone. We have rendered the maps and the dashboard to be mobile friendly. And again they are also available offline. I don't know if you want to say anything about your technology and being available on mobile. It's easier to consume via computer but it is available on the mobile, Android or iPhone. Great. Yeah, people are asking for a contact if you want to reach out. So here is my email again. A couple more questions for you as they were coming in on your presentation. So what could you explain? This is coming from Samuel. He is asking, could you explain the parameters that determine the number of catchment polygons in a particular administrative district or how a particular administrative district is divided up? Is population estimate or simply entering the number of catchment polygons what you do or you factor those in? Does that make sense? Yes it does. So I mentioned that there's two core types of catchment areas. There are site-based catchment areas and population-based catchment areas. So for site-based catchment areas, if there are four sites it creates four contiguous catchment areas. There's obviously complexities with catchment areas, especially in urban areas where there is overlapping and things of that nature. This is a focus solely on the use case of having contiguous catchment areas. So yeah, the answer is if you have four sites it creates four catchment areas. For the population-based, the number of polygons, the number of catchment areas that get created are dependent on how many people live in that district. So these are census projection numbers that are pulled from the Facebook dataset. So essentially it creates if there are 10,000 people and you size each one around a thousand then it creates about 10 catchment areas. So that's how that works. Great. Okay, thanks. A little bit of a refining question. Jill earlier was asking about if these catchment areas would be available on the Android capture app, so the data entry app for Android for DHS2. And I think she's specifically asking because she works on indoor residual spring activities, so door-to-door household spraying with insecticide. And the answer to that is in the capture app, no, it is not currently available in DHS2. But it can be a very, it can be a next step. It is something that we definitely build and enable it. If you need those kind of functionalities, Jill or anyone else, please do reach out so that we can understand the user stories. We can't develop these things in the blind. We can't develop them without understanding how people are going to, why they need them, and how they're planning to use them. So if that's a functionality that you need to be able to have catchment areas in the data entry app, then it's definitely technically possible. We just need to know exactly how to enable it. And that's where you come in as experts in the field, implementers with your experience and user stories to help tell us how exactly to do that. So please do reach out. Scott, the only thing I'll add there is that starting next week, we're releasing the feature where just like you can have a PDF for each individual catchment area, you will also be able to have a Google Earth file for each catchment area. So if you do want to load that on and Google Earth application on your mobile device for navigation for teams and identifying where the catchment area boundary is, you would be able to do that. Okay, great. Rika is asking another question for you. Travel time scenarios, are there options for motorized vehicles and road conditions as well as or as well as walking or what are the options there? Yeah, good question. So the options right now are walking only. So what you see here, what we currently have available is only for walking. The reality is that when you look at the travel time for mobile, obviously it's going to show kind of green lines that run along where the roads are. I do know there are some APIs that make that available from other providers. I think even Mapbox potentially offers one that we've looked at a little bit. This one's just focused on walking, but I do think that those are available if that's a thing that you want from other providers. Yeah, and yeah, that is true. And I think that grid three is also produced some maps that include travel time by different modes of transportation. Those maps are not, one functionality of the map app in DHS2 is that you can upload your own external layers and have those as base layer options on your maps. So if you had a travel time map, say by motorcycle or by car or something like that, then you could upload that to DHS2 as a custom layer and then turn that on for any map that you want to see and then build additional thematic layers on top of it. So the same catchment area is the same thematic layers, data structures, any other layer that you want. And so you can layer these things on top of each other. So if you did have other map layers that factored in like driving time, then you could put those on your DHS2 maps as well. Another question is how dynamic are the offline dash mobile dashboards you presented? When you use the map online or offline, can you calculate distances between GPS coordinates? Does DHS2 support distance calculation? So yes, the short answer is when you are online and it's online only, you can calculate the distance between any two points in DHS2 maps. You can also calculate the area within, you can draw a polygon and calculate the area within that polygon in the maps app. Now you can't do things like what Google maps does with like routing or directions or that kind of stuff. It's not that advanced. We're not trying to produce a turn-by-turn driving navigation tool, but you are able to just look at kind of as the bird flies straight line distance between two points and draw simple polygons to get area. That feature is only available online. It's not available offline. So if you're looking at offline dashboard, you're not able to do that. Just scrolling through the chat here and keeping an eye on the community of practice. I think we can just take maybe a couple more minutes and round out the half hour. There's a question there about tracker and the maps scattered around the three o'clock. Around three o'clock. Scrolling up almost there. Is it possible to integrate the DHS2 tracker functionality, i.e. individual immunization information with the catchment area mapping to do things like generate a list of children that are due for immunization within a health facility catchment area? Yeah, it's interesting question, Mark. So the answer is you can generate lists of children due for immunization based upon the children that you know should be coming to that facility because they have visited it in the past or their mothers had delivered or enrolled them there. We are not able, you can potentially from the catchment area derive target populations. So, you know, this is how many children I expect to come. But you're not able to say explicitly these are the children that should come unless they are known entities to that facility already. If they are, you know, if the mother has delivered at the facility and automatically enrolled the child in an immunization campaign or the child showed up for their first vaccine visit, then once they are known, then they can be followed up explicitly via DHS2 tracker. DHS2 tracking consent, automated alerts, notifications to them. They can also alert the clinician if there's missed appointments or scheduled appointments, that kind of thing. But that's only if the child has already been like registered at that facility. But of course, from the population estimates and approaches that we've shown you could get like a target population and, you know, measure your total children immunized this month against what you'd expect based on the target. Looking for other questions. There are quite a lot of questions if we, and we are now at the half hour. Should we keep going with questions, Max, or should we call it a day and follow up on the community practice? Okay, guys, if you want to stay on, welcome to. Okay. I think I, we've taken enough of these good people's time personally. So, I just wanted to reiterate that if you do have any questions or concerns, do reach out in the community practice. If you want to get in touch with us, if you want to deploy any of this, use any of these new technologies approaches, do please reach out to me. We're very happy to engage with you. We want to get use cases so that we can continue to improve these functionalities. One last, well, I think we'll call it a day. Everyone has my email. We're always on the community practice. So, again, if you run into problems, remember not to suffer in silence. We, there's someone here to support you. And any last words before we go? I really appreciate the opportunity. That's great to get to speak to such a large group and please do reach out. We love working with new people and we really want to help you make catchment areas. So, if that's at all I think you want to do, we would love to help you. Thank you. Okay, great. Thanks. So, we'll call it with that and we wish everyone a good rest of your day and we will see you all on the community practice.