 What I'll be talking about is implementation toolkits. This is something we've been mentioning since Monday. Repeatedly how we have toolkits for different use cases, different health areas that we worked on together with WHO, UNICEF, other partners. But we haven't really had a proper introduction to exactly what we mean when we talk about implementation toolkits. So just sort of to clarify any misunderstandings about what these toolkits are and how they can be used in DJI's to implementations. I'll do a brief session on this now. So the purpose is to understand what these are, how they can help you when setting up DJI's to. So my colleagues have been making fun of me for being too serious when I've been presenting stuff. So now I'll have some photos of Lego bricks and we'll all have fun. So this is DJI's to. It's an empty box that you can use to build whatever you want, like with Lego. So when you start up with DJI's to, you don't really have anything. You have a software that can do lots of things, but it doesn't give you anything to start with. So what I wanted to do now, since there are some of you who have sort of very new to DJI's to in general, I will actually make a new DJI's to and I'll add some stuff to it just to show you the sort of this building process. So I will make a new DJI's to. This is of course always a bit risky to do this. Live and see if it's starting. Oh, sorry. So I need to use. I'm using now the latest version of DJI's to starting up a new instance. So what I'll do now is to show an example of how you use this empty box, build some build something from scratch. So I'll pretend we're setting up a routine immunization program. So let's say we're making a monthly report from health facilities on how many children are given. BCG doses, for example. Let's see if it's starting. OK, so we now have a completely empty box. They tries to. There is nothing here. No dashboards. I have no data sets. I have no indicators. I know organization units. So the first thing I'll do is just to make a little organic hierarchy here. So we have Norway. I'll add the. Also, and I'll make sure my user is assigned to the Norway organic. OK, so then I think I'm ready to ready to make my data set. So I know for immunization, I want to have my data disaggregated under one above one years. So the first thing I'll do is to make disaggregation, which we call categories in the tries to. So this one will be a certain 11 months. I need also to have one for 12 plus months. This I will combine in age group for immunization. This is a disaggregation. It's a data dimension. I want to use this in my analysis. So I'm picking these two for my category for immunization age. I know this is going very fast. I'll get to the point eventually of doing this versus use the toolkits. So I have my disaggregation under one above one years. Now I need to have my data elements, my BCG doses. So I'm making a data element. BCG doses given this be aggregate. I'm making a monthly form. I'm not making something for the case-based. It should be a positive or zero integer. I don't want to have decimals in my account of children. I want it to be added up over time. OK. What I need now is my reporting form, my data set. So this is my EPI monthly report. It's monthly. And I select BCG doses given. I want this to be reported at the facility level. So in this case, my only facility, I haven't really added any. But let's say Oslo is a facility. So I take this reporting form, which has one data element, should be reported from Oslo. Let's see if we have anything here. No, but it's public. No, but this is the OK. So I need to specify here that the user can actually capture this data. So of course, you would typically do this with a group of users, not with individual users, but just to make it quick. I'm doing it now directly with my account. So I'm sure Jit is now mentioning all the things I forgot. More tips, Jit? What did I forget? I think this OK. So I'll try one last thing. If it doesn't work, then I think, yeah. No, yeah. OK. So let's see if we can use the we're working on the new what this is. So let's give up the attempt to actually open the data entry on this one. The point being, yeah. I love my colleague here, she's asking. Sorry, my colleague here. She was asking because we saw that you spend, like spend DHS instance very quickly. So we are wondering how scalable, not how scalable, how much workload does it take if we really implement it on a country level? If I don't know like that, it's a silly question. But like, because you spend it very quickly. So I think you are using like a small database. Does this type of database accept many concurrent connections? We used it in a country level. This part one, part B, she's asking also, can we decide another type of database because for some reason, if we need to use our own, like a SQL database, for example. No, so that used to be the case before that you could choose between my SQL, Postgres, et cetera. But now we're standardizing around Postgres because it has GIS features, et cetera, that is used. I think so now I'm just running it on this. I would actually think for aggregate, purely aggregate reporting, you could probably run the national system on the laptop. So it's only when you start with aggregate, no with a case-based, that you need to really scale up in terms of the hardware. OK, so my point was to show sort of this process. Starting from scratch, you define your data elements, you define your data set, you define your org units. But of course, quite often what you're doing is something that others are also doing. If you're doing immunization registry, it's the same immunizations you're giving more or less in all countries. If you're doing TB surveillance, it's more or less the same thing. So that's sort of the idea with these implementation toolkits, that there are so many things we see that everyone is doing more or less the same way. So we can provide some tools to make it easier to do those standard things. So my initial attempt to make a simple immunization registry example wasn't so successful. Let's try instead to make a tuberculosis case-based system, but rather than starting from scratch with my Lego bricks, I'll go and download the toolkit for TB. So this is now a predefined configuration. This is the DHS2 part of the toolkit. It's a JSON file. It basically looks like this. So it includes some of the things I was doing now with making category option for disaggregations, making data elements. It includes dashboards. It includes maps. All of these pre-configured things comes as part of this toolkit. So if I now go back to my DHS2 and import this, so we see it's creating lots of stuff here. That was just a test import. I'll do the really import and we'll see what happens. Looks like it finished. See if I remember all the things I need to do now. I need to, first of all, make sure that I have access to this program, which is done through the user groups. So in this case, I should be an administrator who can change the program. I also want to show the data capture. I need to specify that we're collecting this tuberculosis data from my Oslo org unit. Let's see if I forgot something. Here we have the TB case surveillance. I can start registering cases. Here, diagnosis. I can start collecting information. So that's sort of the idea with the toolkits. I have my DHS. I can make my own stuff. But if I'm doing something that others have done and that people I worked on with WHO or with UNICEF on what are the standards, and we worked with the DHS2 teams looking at what has been done in different countries coming up with a good design, we can share them through these implementation toolkits and make it possible for others to use them by importing into the DHS2. So continuing with my Lego metaphor, the idea here is if I know I want to build this penguin or bird, I don't know what it is. If I know what I'm building, we can provide through these toolkits some instructions on how best to do that in DHS2. So working with WHO and UNICEF, others, to see what are the things that should be included, what are the key indicators, et cetera. And working with the DHS2 experts, what is the best way to model this in DHS2? We can put together a toolkit that has some guidance on how to do this. We can make a DHS2 instance available where people can look at the demo to see how it works. We can include these JSON files, what we call the metadata packages for people to use in their own DHS2. We can make training material that can be used along with this toolkit, et cetera. So what we say as a minimum for these toolkits is that we at least have some guidance describing how you address the use case in DHS2 and ideally also a demo. The metadata packages is what we refer to with this JSON file I was just showing, the actual configuration of the DHS2. So that's one component of the toolkit is the part that you install in the DHS2. So that could be what we call a common metadata library, which has some basic attributes like data birth names that can be reused. It can be just analytics, dashboards, indicators that you can link to your own data collection tools. Or it can be the full data sets or programs with all the data collection. So the idea is, yes, you have DHS2. You can build whatever you want. It's an empty box. But then we also provide these toolkits, which has sort of a use case, something you want to build. It includes instructions. It includes all the metadata, the parts you need. And then we have the demo, which is showing you how this works in real life in the daily use. So that's the toolkits. And like I said, it's something we're collaborating with WHO, UNICEF, others to develop. So we have this is just an example of the areas where we have toolkits, HIV, malaria, TB, community health, EPI, CRS we've talked about, nutrition, et cetera. So with this, we take the guidance that exists around the health areas, turn them into a toolkit that can be used in the national DHS2 implementations. So seeing that we're running out of time, I think I've covered most of this. So it includes the key content in a modular way. So you can sort of pick and choose. We take the immunization toolkit as an example. It includes the immunization registry for doing case-based follow-up of children. It also includes the monthly reporting forms. Includes a stock component, for example, for doing the facility level logistics. And then countries can pick and choose what is relevant for them. So just a few example, malaria toolkit. We have two modules depending on the situation in the country. Some countries are in what they call burden reduction, so they have a very high malaria burden. The focus is on reducing the cases. Other countries are in the elimination phase. They're trying to completely get rid of malaria. So there are different modules depending on the situation in the country. And in addition, we have the case-based modules for malaria elimination. Then we have the configuration in DHS2 and the training material. I think we mentioned many of these, especially on Monday, Tuesday, we talked about the different health areas. We have the same for tuberculosis. For data quality, we have the session. We have the toolkits for data quality with the standard metrics, dashboards, et cetera. So that's something you find on the DHS2 web page. You can have a look at what is available and how they can be used. So the last thing I wanted to say is sort of a clarification. I think it's very easy to get these toolkits, very useful. I don't have to do all the configuration. But you shouldn't just assume that because you're using DHS2 for a health area where there is a toolkit that you should use the metadata that comes in the package. You can also build very nice things, even though they sometimes look a bit funny, like this panda bear here. You can build things from scratch for the same sort of use cases that we have in the toolkits. And it might be a better solution for you. So you really need to consider, is it actually useful for me to take the JSON file with everything pre-configured compared to just using the guidance and looking at sort of the design advice that is in that and rather building from scratch yourself. So summarize these toolkits meant to help countries improve data quality analysis use developed together with some of the global partners, WHO, UNICEF, available for a lot of programs meant to be used together in an integrated way. But you really need to think of for each implementation, what is the best way to use this? Is it just to look at the guidance, the examples, or is it to actually use the content that comes with the toolkits?