 So, to pay tribute to all of you that actually came here on time, we will start. And this plenary will actually, this kind of the first of the two plenaries, well, the row of plenaries, will actually be about the topic of the conference this year. Sharing innovation across sectors. And we will have many, many, many sectors presented today, up to 22, isn't it? 22 sectors will be presented and six countries. So, so stay awake and we will have a first presentations and then all the Q&A and the discussion will be saved for the panel in the end. So let us start with the prosper. Talking about the cross sector use cases. Key responses to assess to measure this sdgs. And then we will continue with Malawi with the Ministry of Agriculture. Then we will continue with the year and talking about synosis in DRC. Then we will end up with John or answer on honor or we'll see talking about climate health and also civil registry from law. Okay. Okay. Good morning. Okay. There's still more coffee out there so we could, we could pick some coffee and come with it. Yeah, so good morning and welcome to the final day. A great opportunity for us to be sharing with you. The shareings and the cross sectors that we're talking about. So I'm here. I'm just putting on big shoes for three countries. Again, this already shows the sharing we already have that I'm able to present all the three use cases in the three countries. The sharing has already started happening so I will be sharing the, the different cross sector implementations in the different countries. So when we talk about cross sector, we're talking about more than one government more than one ministry more than one institution in a country. So most of us have been talking about health, health, health, health, education came in last year, but now we're talking about, you know, all these so many that I'm going to share. So there's a compilation of a summaries from the two powerful implementations that have really driven DHS to crazy as we shall share, but also produce some good insight to what we can be able to do in terms of improving the DHS to to monitor and have it as a digital public good. So when we talk about cross sector, this is the mess that we are in. You know, you talk about health, you talk about environment, you talk about climate health, you talk about education, you talk about finance, you talk about sports. All these so many sectors is what we're looking at so a little piece of this has been picked in Uganda in Uganda and in Rwanda and in Ethiopia. And we're going to share with you to see how they are the DHS to is really helping in terms of bringing the data together for translation and being able to monitor the government programs. The DHS is in the center of this, getting all this data, exchanging the data, managing the data, visualizing the data in these different sectors. So, these are the different three use cases and again they could be more, we didn't go out to look for many, but these are the three use cases that we already know right now that have been shared in the different sessions. We look at Ethiopia at a level of a district cross sector implementation and really using the basis of DHS to drive this implementation. They are looking to see and they are being able to use the DHS to for health and build on other sectors like agriculture and the rest as we shall see to be able to monitor the keep performing indicators for what they have as a transformation agenda, trying to be able to improve the social welfare of the different districts. And so they are bringing all these two sectors, these three or four sectors to be able to look at data, try and use it together. And then we move to Rwanda, where it's looking at more on the local government that could also be below the district and really looking at how you can be able to monitor accountability across the different local governments. Even to the grassroots of where they have the lowest, they are operating at the lowest political entity to be able to monitor innovation. So here you have targets being set by the different governments with funds allocated, and then moving from village to village to be able to monitor these indicators. And then the mix of implementations where villages or local government have different targets and set of indicators that you are monitoring and will also be able to see how this is is is is implemented, especially how DHS to is really supporting this kind of implementation, moving from the paper based kind of monitoring to now an electronic monitoring for a local government. Then we come to Uganda, which has all the mixes from the national level also up to the also the grassroots, where we are monitoring the national development plan so governments also have their national development plans. So for us we have plan plan three, which is towards the vision 2040. And here we are looking at all the sectors actually in the country. As I shared in the previous slide, and also a new initiative which is also looking at the Polish development model, where the different policies are given grants and they're supposed to use them and then we're able to monitor what happens. So, this is how the DHS now comes into the mix of all the things. And as we talk, there are quite a number of systems that we all know in the different governments so we have to exchange data between them, like if we miss the fund the finance system so that has to be, you know, exchanged from those systems. So what motivated us to really use DHS to in these in these three countries, and again even more that are coming. So, for most of these implementation, I may not want to talk about how much it has costed them to be able to decide whether to go for DHS to, but a lot of our local governments and our governments have been depending on when on vendor systems, which have been quite expensive in one of the countries. The last vendor before DHS to, I don't use all the funds to do requirements gathering and they stopped there. So the DHS took up the requirements gathering and the requirements gathered and they were able to use it. So, we find a lot of challenges in terms of how much it has been costing the governments to be able to develop these systems, maintain them with expatriates, most of them are expatriate to the driven. We have upgrades. We've seen somewhere where people have to be thrown into the country to just adjust one data element. And also sometimes functionality, especially around the visualization that has also been one of the biggest motivator of the DHS to then of course the local expertise that are in the country that have been able to demonstrate the functionality, the capabilities, the sustainability model of DHS to, we have of course our his groups that have been in the three countries, but also most importantly, the teams that we have been able to train over time. I think when you look at our academy training database, we are almost now over 10,000 or something like that. And these people have all been trained in the use of DHS to and they're all, you know, out in the countries there. Then of course, thanks to the Ministry of Health in these countries that have really implemented the DHS to phone over 10 years. So a government looking at an implementation which has been stable for 10 years really gives them the confidence to go for this solution. Then of course the flexibility around the DHS to that you can be able to even add on top scripts, up plugins, support extra functionality, because when you get to these sectors we find quite different requirements that are not supported by the core. Then of course also the track record in health as I've shared, but most importantly around COVID, the COVID implementations in these countries really drove the cross sector implementation. So in this, in the instance that we are running, in the provision that we're running for COVID, we just realized that we were able to bring the different sectors for Uganda. We talk about education and health, we for one that we talk about, you know, the immigration and all these other sectors. These have also been one of the key and also having also these other extension that we had already started the education as we've talked about the judiciary in Uganda, monitoring how many cases have been or been addressed. The social protection and agriculture in Malawi as you've shared and environmental environment and minerals in Rwanda. So this has also been able to give the confidence of the governments that these systems can be able to work in the government. So in terms of progress, I just give a snapshot. The implementations are up and running. For Ethiopia, they have been able to customize this on top of the DHS to for education added those different sectors, and they're able to generate the data, being able to pilot and now moving to more of the districts what they call there where it does. For Rwanda, they never pilot, but this one they did some pilots, but the pilot here is really to inform the next implementation. So, much as they talk about a pilot, it is just a whole administrative unit with all the different levels, and this is just being used to be able to implement in the next. As I shared for Rwanda, they have different indicators almost for a different sub unit as they move from one province to another province. For Uganda, the configuration has also been completed for all the NDP target indicators, over 5000 indicators into the system because we're looking at all the sectors. And the targets because they have been able to set the targets for each year until 2040, all the targets have been put in the system, and then for the previous two financial years that has been uploaded, and now the rollout and the training is ongoing in all these different sectors. And then for Uganda, because they want this to be, you'll see we're going up 2040, so for us to be able to sustain it, there is an initiation of an MOU between his and the office of the Prime Minister to be able to support this as we keep monitoring the progress. And of course there's challenges, not so many though, just for them for now. The challenge we will first a little bit as a standardization of indicators. As we know from health you have had this one HMI stool, it's the same everywhere you go, but here you find that the indicators probably could even be the same defined different from one, from one sector from one implementation site to another implementation site. So you'll find that we have quite a lot of multiple data elements, data sets indicators, that's why they become so many, because sometimes they slightly change as you move, but again the HMI stool with its robustness, we are able to cater for that, that the mitigations are what is in blue. And then there are some of the unique functionalities and features that the governments may want in terms of security in terms of visualization in terms of data capture. But we've been able to sort of this by just adding a few apps on on top of the HMI stool that would be, you know, soon implemented in the core. Then is efficient funds for, for implementation. Again, as you see this is talking about more than one sector we've been struggling with health alone, but now if you're going to train the whole country, all the ministries and so on it becomes quite challenging and it requires a lot of budget. So we've been trying to do a lot of online training. Thanks to COVID for teaching us that. And we've also been developing user guides which are very simple to use, and then also the e-learning platforms. Mudo has also been very keen in this. We've really been able to do this and then also the YouTube videos that have been shared with these ministries for them to be able to get the training. Then interprobability with other with multiple systems, some of which are very sensitive in terms of data sharing. You talk about, you know, this, this ministry sharing their budget with the other one, they may not be able to want to look at that. So some of the things we've been able to do is just, you know, sometimes we export and import with Excel. And lastly, this is a quote from last, I think that was in 2011, where I said everything is possible in the HIS2 and I took that, you know, as a quote in the Bible and we've been using it and that's why we've been able to really push the HIS2 beyond. So with the HIS2, everything is possible. I think the great platform that we have here in terms of what you can be able to add and how you can be able to switch to turn it around has been one of the, you know, lessons learned. You can have apps on top of it. We can have scripts. We can have plugins. Very key, you know, imagine when you're sitting and you're able to look at all the different sectors, like when it comes to health, you want to look at agriculture, how it contributes to your nutrition programs and education, how it contributes to your immunization programs. Then again, this has also, you know, sparked up a lot of interest. We already have Gambia and Marui knocking on the door. Before even we finish these implementations, Gambia is already now up in the, actually the demo was already up yesterday, prototype to be shared with the government to be able to look at that. Installation is also very key. We really need to build the capacity within the institute, like for now for the government, this is a big undertaking. So MOUs are important and then establishing for working environments within the MOUs that we're about. Just a quick snapshot of what you can be able to realize this could be all the different indicators that you can bring on the dashboard. Here you can have a scorecard looking at your different ministries and quickly look for out for the reds. This is one of the beautiful dashboard that you will find in the president's office, looking at, you know, what, how the sector is performing in the different the directives for the manifesto they are running. And then lastly, in terms of appreciation, we really want to thank the governments that have been able to participate with us in this, the government of Ethiopia, Rwanda and Uganda for taking this bold step. And I think they are not regretting, as we talked to them, we had a nice presentation from Uganda and Rwanda and Ethiopia the other day. The national and the regional implementation needs that we have in these countries, the districts, ministries and all that. The development partners that have funded this European Union has been funding Uganda and is now funding the implementation in Gambia. Then his groups that have taken this work and Rwanda, Ethiopia and Uganda and also the UIO teams that we've been all, you know, disturbing and telling them, you know, we need this and when they say that we can't do it, we say, okay, the HHS can do everything so we shall be able to fix it. Thank you very much. Thank you so much, Prosper, I forgot to say that Prosper is representing his Uganda, but you all know that, I think. So, let us welcome Jennifer and Kossi from Ministry of Agriculture and Malawi, talking about the NAMI project. We heard a bit about the NAMI project last year as well. We even have a PhD student that will start up working on this project from Malawi from the same team coming to Oslo in August. And also have to mention that these projects that Prosper was presented also have PhD students that are studying, because we really think this is kind of super interesting and I think it's spot on for the sharing on innovation cross sector. It's a good example. So over to you Jennifer. Thank you very much, Kristen. Hello everyone. Hello. Yes. Thank you very much for having me and to share what we are doing, how we are using the data used to in the agriculture sector in the Ministry of Agriculture in Malawi. So my name is Jennifer Kossi. I'm an economist and also I'm the one who is conducting the NAMI system in the ministry. So, let me begin with by saying that I have a friend, a colleague who usually comes to my office and say, Jennifer, I love NAMI system. I love the functionalities of the DHS2 platform. So, I'm able to utilize that address the level. So, that's why I'm here to share with you why we love NAMI and why we think the DHS2. It's a good platform to tries in different sectors, including agriculture. NAMI, our vision is that it's a one stop system where you will find different data sources, different data sites to do with crime rates, data to do with marketing, production, and the system we are collecting data at lower level by the extension workers, including the ones who are collecting data, and the data is either collected aggregate data or it's individual level data. In this system, we are making sure that under the day it's being utilized by different stakeholders in the ministry, including the farmers as well, including the academia, the research institution. So, at the end of this, we also are developing a public portal where we want to share some of the analytics and reports that will be generating through the system. So, just a quick update of what we have achieved in terms of the implementation. So, we have rolled out 12 modules out of the 18, and I know that as we be going in the future, the 18 modules is going to increase based on the needs of different users and stakeholders. So, we had 12 modules, and one of the modules that has gained momentum in our ministry, it's the House of Registration, and as of now, we have registered over 807,000 households, and this system we're implementing in 12 out of 28 districts. And 1,622 devices translating to the number of staff that were trained and that are collecting their crash data in the system. So, this is just a snapshot of the House of Registration as I indicated. It's one of the modules that the ministry and even the donors in our sector are interested. Because we are able to collect detailed information to do with the House of Demographics, the enterprises, the households are involved, even the support that they are able to receive from NGOs and support from also from government projects. And this is assisting us in terms of targeting and programming different projects based on the information that we are collecting at household level. And also from this House of Registration, we have learned more in terms of the capability of the DHIS2 platform, because we have been able to develop customized application on top of the DHIS2 to facilitate in terms of sampling of the households and those sampled households, allowing them to different programs. For example, food situation assessment that we do bi-weekly and also production estimates that we collect every quarter and that is an annual exercise. So, my presentation today will focus on the key modules, what we are doing and what we want to do moving forward. We have three modules. We have the Majority, looking at weather and climate data. We have the Farm Organization, House of Registration. It's one of that. It's one of the modules. It's one of it. We have lead farmer. These are the farmers that work with extension workers in delivery of extension messages and also a module to do with animal health and livestock. Here we are looking at disease outbreak and livestock production estimates and other data information that we are collecting in the three modules. So, to start with the weather and climate efforts that we have started and NAMES, we want to have a beta weather data collection at community level. That's our vision. According to we are just collecting our info data, but we want to go more and be able to collect other weather parameters including a temperature and humidity. Our vision is that based on the information that we are collecting on weather and climate should guide us on farming practices and pest disease management and other resource allocations from national level to household level. And also we are looking at combined analytics, how we can link weather with crop and more nutrition data sets because I know that weather has a diary effect on crop animal and nutritional aspects. Then also we are looking at linking the climate efforts that we have through extension services and the model of farmers that we are registering the lead farmers and the farmer food schools. So what we want is that we collect this climate data. We analyze it. We develop extension services, extension messages based on the products and that we have developed and for that we will be share to the farmers. So that will help us in documentation of the best practices based on the information that we are collecting on the weather and climate data and also support mentorship efforts. So the tools and the work that we have done in the numbers so on weather and climate data we have configured 379 weather stations as part of the reporting hierarchy and this is being collected at community level. So we have data at lowest point as possible and climate efforts through extension services. We have currently registered 6603 lead farmers and 85 farmer food schools. And since the activity of the registration is ongoing, we expect that the number of these lead farmers and the farmer food schools, it's going to increase. So as I said earlier, these the lead farmers and the farmer food schools were using them as a model. They're used in dissemination of acacia technologies and messages and also we are able to monitor and map the interventions that are being implemented by the lead farmers. And the farmer food school. So this is just a snapshot of some of the analytics of visualizations that we are generating using dynamic system, the rainfall that we collected last season and this season. And also this is also a visualization showing the number of lead farmers that we have registered per district and the analysis can even go to the lowest point of data collection so we can be able to know that in this specific area we have this number of lead farmers. So that will help us in terms for better programming and targeting. And the other modules that also we have in dynamic system it's the livestock and animal health. So as I said, they on in this module we are looking at the production aspect. And also we are looking at the animal health aspect in terms of the disease outbreak. And in terms of the we have currently started with the production. Production collecting of production of different life talk. And under this. We're also able to collect some different dynamics of different life talks that we that we keep in our communities. So we are able also to know in terms of how many dogs have died due to rabies. How many people have been bitten by dogs. So it's one of the parameters that we are able to track under the production questionnaire, but we have a set of data sets that go into details in terms of animal disease outbreak. So that's where we are going in terms of in terms of further configuration of the animal disease and more health in terms of monitoring and survey surveillance of the animal race. Yeah. So we also work with the Ministry of Health in different portfolios, whether to do with nutrition, whether to do with disease outbreak in terms of as a noted diseases. So we also have identified opportunities for community level one health efforts. So we are looking at us as a ministry, being able to provide climatic data to the Minister of Health, and for them to be able to utilize that information that we collect by the extension makers for their own systems. So we are looking at guiding efforts on how we can link between climate change, food production that affects human nutrition and health. And also we have the one healthy surveillance that as a ministry we are part of the team that we do work together in terms of surveillance of as noted diseases. So we are looking at cross sector analysis of disease patterns using the system. And also on the human health and labor availability. So we are also looking at cross sector analysis of disease burden impact on agricultural labor availability that if a person is my nutrition, that will also affect in terms of productivity in the architecture sector because of labor availability. So we want to create a synergy where we can work together to have a one platform where we can be collecting different informations and be able to utilize in our own respective sectors. So what are the new and future efforts that we have started and also we envisioned moving forward. So we want to start importing a 10 year info data. We have managed to gather historical data for 10 years on info data, but also that's one of the challenges that we are currently facing, because we are migrating from paper based to electronic. So to gather the, the paper based historical data has been a challenge. And also we are in partnership with the University of Malawi's Center for Zerians at the food system. Here we are looking at the center providing capacity development for our staff in the ministry in terms of how we can further develop the system and also utilization of the system. And also we are looking at development of automated instruments for additional parameters as we already indicated, we are just focusing on the rainfall data currently. In collaboration with the investor Voslo as already indicated by Kristen, they have identified a PhD student that would do research on the enormous system, and also collaboration with the minister of health on common areas of efforts at community level, using the one healthy platform together with the NAMI system. Lastly, we cannot forget the ones that they are mandated to generate climate information. We work together. So we want to have want the department to be able to disseminate more personalized and actionable climate products to the farmers because currently the climate products that they are producing it's at high level at national level, but we want to find a way of how we can, the analysis should go as well as to the community level when they are developing their products. And lastly, we want NAMI not to be a system only that generates data, but we want also this system to benefit the farmers who are getting the information. So we want this system where but when you collect that information, we should be able to send back the feedback in terms of keep giving them the update generating extension messages coming up with extension technologies on how they can benefit in their livelihood in terms of production and productivity so it want to be a one way, but it has to be a two way whereby they give us the information, we utilize it and we give them back, and they benefit from the system. Thank you very much. Super Jennifer very very interesting and on the spot presentation for this session and this is a good transition over to your own that will talk more about animal health. It was introduced here and we will go more into depth of the synosis for the DRC. So then we have seven countries, more countries, and we will have so so write down your questions if you know we save it for for the time of the panel to discuss and to ask questions and I have many of them to Jennifer but we can also use the next one here. Yeah, good morning everybody. I'm about to talk about one health and the one health approach but we do focus on animal health in fact because if you want to achieve something on the one health side we need to also maybe put more emphasis on the animal health because that's kind of a little broader in terms of health information system. So we start by comparing the domains of animal health with the human health surveillance. So to see what are the differences because if you just take the approach from human health and try to implement it in animal health it doesn't necessarily pay off very well. So we are looking into lessons from Kenya and we have a pilot project working in the DRC which we then try to to to to apply the learnings to. So first and why this animal health surveillance is important. And, well, yes. Even though there are some some questions around covid we can say that anyway that it's kind of the transmission between animals and humans that that is the focus we have more obvious things like. Antrax rift valley fever monkey pox and talking about the DRC Ebola of course is an important reason for looking at early warning and this health security. So the general approach is then to integrate animal and human health surveillance into a one health approach. And the reason why we want to focus a bit on animal health because that is the poorest developed partner in this partnership. Lesson from Kenya. They have a system with paper and electronic reporting surveillance data. And surveillance is very much about a little interesting for us to try to fight against all the zeros in in the general. HHS, HMIS, because here is a kind of a compulsory server reporting they want to see whether a disease is not present that's kind of a very important part of the disease surveillance in this system. And the end users of the system that's veterinarian officers and uses their farms slaughterhouses and they're using a mobile data for for data entry so. The digital system has the potential to give real time real time data. The problem is that it's not well implemented but it's not well functioning. And we will look into why because this is leading to serious and the reporting and gaps in reporting. So, discussing with the people involved in this system and possible causes for this. So, who are performing sub optimal performance is of course that maybe particularly in the in Kenya then you have complexities between the wild animals wildlife and domestic animals. And the reporting across and within is not causing problems. And then we also see what we have also learned to to observe a lot in the more well known HMIS reporting that is the poor reporting structures. If no data reported and we get no complaints as people are saying and you can stop reporting and you hear nothing that from from the level above you. Passive reporting is is a is a general problem. And maybe because it's about animals and it's maybe so not so focused on on say the economic aspects of the farms and cattle farming for example there's no urgent around reporting so it's not what they say not so very compulsory to report. And that is then of course resulting in the reporting. And it's also poor connection with the human health. And see that human health is more concerned with with sonotic diseases than the veterinarian animal health are. Maybe that is that is an important thing to address because of course farmers animal health they are more interested in the economy of things than necessarily to focus on. The few diseases that can can transmit a little bit to humans. And also what they complain a bit is that one health is very often understood that human health people trying to educate the kind of the animal health people so that's some kind of disagreement between the between the between the the camps. So these are then lessons from from Kenya and then we move to to DRC and see how we can apply these lessons to strengthen. In particular the animal side of things in in in in DRC. So of course, DRC is known as a hotspot for for sonotic diseases and a great concern when it comes to kind of disease surveillance and health security. So we have Ebola and just now we have mom monkey box from from DRC and DRC has used this global system for some time. I'm impressed is one and this is about reporting to FO at the at the headquarter but based on on rabies projects in one province Congo central in DRC. And then they used DHS but at a global instance and then they wanted to to to make it local. And we started to work with them and to expand from rabies to more general animal health surveillance. And when it comes to the other part and in one health approach the minister of health in DRC I've used DHS to since 2015. We started then last year, late in the year with the ministry of livestock and fisheries in in in in this this Congo central and a university in kinshasa the pedagogic University of kinshasa. And then we worked on putting up local instance in for for these province on animal health and to having as an object objective to to work on an integrated dashboard on sonotic diseases with the human health and animal health. And so the project and customize the tries for for for the animal health surveillance, the pilot. And to make it interoperable with the with the. What is the guard that was the rabies system. And so that you don't have to enter the data twice. And to make make the system interoperable with the FIO system. And of course also to work on this integrated dashboard with with the general HMS in DRC. Or challenges in DRC when it comes to this animal health part. Of course, also in particular maybe in the DRC the information system in animal health sector is much less structured than the human health. Because the human health or the general HMS and then it's just established with a basis in the health facilities. And more or less dedicated, it's just officers who are responsible for data reporting, etc. But you don't have anything like that in the human health. If you look beyond the last administrative structure you have, you have farms you have people. And that is, of course, source for for for some some challenges. And of course you do in the DRC you don't have many veterinarians you have trained animal health surveillance officers that are responsible for so called sectors come back to that. And the problem is of course that that the structure of reporting the hierarchy as we call it in the DHS to lingo is different between the two sectors. So it's difficult to correlate data. So we need to manage multiple hierarchies to continue in the DHS to lingo. So that is a challenge and the paper based system and the computer based system are not well developed. And also there's less stakeholders, including donors etc. that are interested in in the animal health as compared with the human health. So if you look at the structure between human health you have the human health hierarchy as the reporting structure and and hierarchy you have the the provincial central. So you have something they call it Sunday Sunday, which is a bit like district and you have a Sunday. And at the base, you have a formation on Sunday Sunday and that's the facility you have the facilities and then up to the air and to the Sunday Sunday to the province. So if you compare with with the animal health hierarchy you have. Territory, which is either many territories in one Sunday Sunday or one to one or or even the opposite. And that makes things things complicated and the same between the sector and the edit something so that is the complexity. So implementation. Actually it's been working since, since last year and they have supervision, starting with training and supervision every, every, every quarter that is still working. Of course, depending on funding, how this is continuing. We have a screenshot of one health notification dashboard where you have one monkeypox rabies Africans find fever. Among others. So the system is working and collecting data. If you look at the way forward. Important. Test out. Generally, this aggregate health reporting. The first thing we have found out is very important is to make the system more generally useful for the agriculture sector for the, for the animal health sector, and to include also other many indicators that might be important and increase the usability for for those who are interested in the animal health so that you get a stronger animal health system in order to integrate it well with the human health. And more and more make information output for multiple stakeholders, farmers, local government, traditional structures, etc. is important. And to collaborate with the human health on the sonotic dashboards that's obvious and work on including integrating climate data, environmental data, and thereby to expand the one health approach and make it more vibrant to put it that way because animal health is maybe more, more, I mean the climate and environment, etc. and maybe more directly have more direct impact on animal health than than than most other areas so that is important to to work on expanding the one health approach. Thank you. Super interesting and I hope we will have time in the panel, depending on on john's time consuming, but very, very interesting to expand our area of health that also the importance of animal health in in the whole one health concept. So that's very interesting. So now john will go from Africa to Asia and talk about two initiatives in in law, both the climate health initiative as well as civil registry. Thanks. Thanks Christine. So I will not take a long time. I will just try to finish as much as soon as possible so that like we can have more discussion. Too fast. Too fast. Okay, 10 minutes. So, I just want to, my name is john Lewis from his Vietnam, a part of his patient hub and part of units to possibly been working with the HRs to for quite some time, I just want to give a bit of background about law. So now we first started in 2013, and now it's been 10 years we just recently celebrated our 10 years implementation of the HRs to in law. We started with on and with all the people on establishing the HRs to core team. Like all the people are there integrated with the different programs started slowly building the, the digital health strategy, HR strategy and heal strategy in 2014 and 15. And then in 2016 was building the provincial core team district core teams and other things and also try to include different programs like EPI NCLE and other things. And then like in 2020 onwards it was more about how do we integrate with other different ministries and other include all the other data, which is essential for health information system. This is just a few slide like what is there inside the HRs to and what is there in outside in the country and how the data can be linked or work together in using a public dashboard or using internal mechanism or things. To give all the description about what we're trying to do, but focusing on enhancing the health system resilient on building them the early warning system for climate sensitive data. So this is something which double HR allow along with this is surveillance team and with the Ministry of Health and with the climate data we've been trying to work together. So this is just to impact on the climate change. The climate change of our expertise to like have the climate sensitive diseases. Now, actually it's a landlocked country next to Vietnam, and it has a long river and all things and it's, it's a border between Vietnam, Cambodia, Myanmar, and Thailand. So now what's happening, like we are just seeing also the climate change in Oslo. We never had so good weather. Usually when we just say summer we have like okay 48 hours of summer. So now we have like four, at least like four weeks of really hot weather. Again, it's happening in in love. It's a rainy season are getting shorter and more intense so that's related to the floods, and more frequently the large dango outbreak so we're just like giving what's happening based on the climate, and also the it's getting longer or more warmer. It was 42 degrees which was reported just a few weeks back in love. So it is affecting the agriculture, the food security, the rural population. And it also has very close correlations between the the waterborne diseases in the dry season which accounts for 11% of death among children under five. So the health worker already know that there is a direct correlation between climate change and the health, but like what we can try to do. How do we build that one in a routine health reform system or how we can try to help them up. So the first thing like we worked with NCLE program to strengthen the disease surveillance data in DHRs too they've been using quite well so they started with their with their Excel sheet and then they saw the potential of DHRs too they've been using it. They're also now been using the not only the event based surveillance but also indicate based surveillance. And then like what we did is to host, we went to the Ministry of Natural Resources and Environment got all the climate data put into DHRs too. Both the Minnan Max and also the average rainfall in DHRs to itself. And then we worked with the University of Gothenburg on early warning system, which combines the data from the climate and the rainfall and predicts when can it predicts the outbreak in both in diarrhea and then good. So that's the model we've been trying to work on. And our colleague around here Jason Pickering is working very closely how this tool can be useful, not only for the law but as a generic tool which can be used in any DHRs instance. So this is what has been happening right now and we've been trying to working on this automatic data exchange between DHRs too and you want, and also have a very strong linkages between Ministry of Health resources and environment. So that's just a few things like how it works. Here like we DHRs too is collecting daily in the event based the this is surveillance data. And we also combined to weekly. The rainfall and the things are the daily data which we are also putting that putting it down, but we are analyzing only by weekly basis. So there are not so many weather stations we have weather station but like in four of six different places in the whole country, the country is of 18 provinces. And then we are making the combining the data and all just see and then based on that one we get trying to get the response out. So this is the what we are planning right now we have just like integrated between DHRs too and the evo in a semi automatic way, where we push the data to evo system and evo system use the output, and then we put the evo data back into DHRs too. But we want to try to make this one automatic so that like it can be used, not only by the higher level but at least at the province level people and district level people. So this is just an example of combining the diarrhea data in one of the place in Odum Sai with the rainfall and temperature so or the last few years. Same thing with the rainfall and things are with the with the dengue. So like one of the things like this is not the district but like the evo system causes a district but like these are all the provinces in law we have 18 provinces. So all the different things and then these are the all the different accuracy and based on the things what they've been trying to predict the positive predict value and negative predict the value and based on that one they've been trying to use. Same thing for for evo for the all the things you just see like we didn't have some of the data we are missing for some of the provinces. So again, so these are the few of the things output what we've been trying to produce. So how this will help. If you know the outbreak based on the climate we can try to prepare a bit more better, or as I say much more better. And with the like the diarrhea outbreak and all the things so we can have the or stocks and all the things in the in a particular area prepared the health worker, which they already know that there, there will be because it's they know that okay the climate changes happening but like we know there will be diarrhea things but we don't have sufficient drugs or the equipment or the things so they can try to deal with that one, and also educate people when they go out like okay you have to drink more water and all the things and so that can be the few of the other place. The second topic, which, which I'm going to talk very quickly is about how what all the different things what we did to integrate between civil registration system and DHR state. So I guess it started a long time civil registration system, which is, or we call he CRBS, they use their software called Hera, which they just started last year, end of last year and this year to do the all the registration and everything, but the ministry of health and all the data. Ministry of Health did a survey, how to do whole survey by the all the health worker, which is called the family health system where we collected all the family members details family details also details like water and sanitation and we try to compare all the different things, and we also just see these are all calculated in DHR state by the way. So we had 6.3 million population data in DHR state, the total population of law is 6.8. So we had 92 percentage of the coverage in in family health system itself. This is the survey is usually was done every year, but during during the COVID. We, the minister of health didn't do that one because like we have to be locked down, but COVID also helped us because like DHS to system was used for building the COVID certificate. That also helped to collect 6.2 million record and 30% of the record has been verified by the public itself and rest all the things because of the COVID certificate and COVID vaccination ID. So 6.2 million people have the unique COVID certificate ID which can be used across different places. So we have all this data now, and then civil registration just started and they had 100,000 data and I say how best we can try to collaborate. So what we just say okay look we have all the data we can give it to you you can verify with your own stream and other things, and then you can provide national law ID, which then we will be imported into DHR state and once we import, people cannot change the ID the name the first name last name date of birth and the sex and other few details. So those are part of civil registration system. What we will try to do on the birth notification is whenever the births happening in DHR state it's been recorded we just send these are all the information what will send it to them, and they will verify and all the things and they will send back the things. This is something which is very essential. So Ministry of Health and Ministry of Home Affairs, who's a part who's dealing the initiative of ECRBS, they have an agreement on like how do we share the data. First thing is the general things and then in the middle section, there are some sorry everything is in law, even I don't understand law. But like I can understand there is something called API API API in few places. So what they've been like trying to just say like okay, these are all the information which we will be sending to DHR state. And these are all the information where DHR state can send using this API. So it is also at that particular minute level details is how the data exchange is happening. And it is being stamped and signed by the both ministry. So this will allow the technical people of Ministry of Health and Ministry of Home Affairs to work together. So they have a broad agreement and at the level down so then they don't have to go and ask every time or can we share this data can we share this one how do we share. So those are all different things has been chatted down and we put on things similar kind of things we won't try to do that one in the climate things but we still don't know how best we can try to use it. Because the climate stations are in different places with the WHO initiative what we've been trying to do is to have few other weather station installed in the health center so that like data exchange can happen. And like we've been working with them, the University of Oslo, the, the core team on how data can be stored and communicated across and predict things. So that's basically I want to have. So we have more time for the discussion. Very well done, John, and everyone can I call all the presenters up to the to the stage here you're Jennifer. Prosper. John, you have to go and sit. And you can prepare yourself for some questions, but I will just while you are. Maybe starting with, with Jennifer, because we are following up on John's, John's topic of exchanging data between ministries that's a challenge, I assume. So could you share some of your I mean you have the Ministry of Agriculture Health. How is that has that been a challenge in Malawi. Thank you very much for the question. Yes, for us is also a challenge in terms of data sharing when it comes to low data. It has been a challenge. But what we do is that when maybe we are developing reports, we do invite the stakeholders that we have to work with informing them what is required. So maybe that can act like an MOU between the two ministries. So once the authorizing authority from that ministry authorizes that they can be able to provide that information. We're able to get that information. Yeah, and but most of the times we do work together in different forums, for example, to do with the nutrition aspect. Our ministry we have a department, the Department of Extension. We have a section that deals with nutrition intervention in the culture sector, but they do work in hand in hand with the Department of Nutrition in the Ministry of Health. So in terms of collaboration and maybe access of information when we are working in that environment or forum, it doesn't create that kind of challenge, but maybe if there is that not collaboration that's when there is more challenge. Yeah, thank you. Thank you. And we have here, here now, you know, going from the whole national development plan, all the way down to the community and to the extension workers, it's kind of a big span of scope. So, you know, do you want to comment? It's not so much tested out on the sharing between animal health and human health in DRC, but nobody has so far opposed to the idea of a shared dashboard where people are sending data from from the one system, HMIs and new system into the same dashboard. So, it's not so far an issue, as far as, as far as, of course, add to that, but, but more important is to, in that case, with the, with the, say, the agriculture, the Ministry of Agriculture, Fishery and all that. And, and the Ministry of Health is to start working together and to work together on on the data. That's not the, there. And in order for a kind of integrated sonotic system to surveillance system to be realized, that is, of course, important. But also it's important that the animal health side and learn a bit from from what has been achieved in human health in order to develop the systems at these periphery levels in the, out in the, in the districts and in the province. You guys can also ask questions so prepare yourself there is one there but I just want to say one question I have the incentives for the farmers to do animal health. It's not really there because they are you know they want to, you know, bring the livestock up but of course if if an animal dies is you know it's an economy. The institutional practices are super different from the, the animal side than the, the human health side so that I guess will be a huge challenge even though it's impacting a lot and more. I saw a hand. Thank you. Thank you for the presentations. So, from allowing the, it was really impressive to see that you have 379 weather stations. And I, I was curious as far as, I guess just lessons learns experienced experiences and how you found how you find I guess maintenance and the quality coming from those other stations, and also maybe from allow with you know you recognize this as a, as a different you know you have six and you have 18 provinces. If you're looking also peaked by this number or if you're looking at Google Earth Engine or, I guess, what you feel like next steps might be for you. Thank you. Okay, thank you so in terms of maintenance and data quality. So for us, the system in terms of data quality checks is that once the extension workers collect the any data at community level. The one who is heading them or the coordinator, and we're calling it at EPA level, that's extension planning area, the ones who could net a cash activity. Yeah, is the one who is responsible in terms of data validation so we go through stages of automation before it's utilized by the ministry, or even accessed by the Department of Meteorological Services. So, in terms of the weather stations, the way they are is that some of the weather stations that automated so the department of mates, the other ones that are active directory, the weather information directly from the automated stations, but some of the stations that are not automated so they have to wait for the extension workers to collect that information and be able to share with the Department of Meteorological Services. Yeah, thank you. So based on the on the law side like it's, yeah we looked at the Google Earth engine and try to get the weather data, but now does not really have so much there. So like we even looked at the because it takes the average things right, and it takes from the different points of the weather data and then it's not so accurate. It's been one of the challenge. So what the, the, the miniature and the ministry of health with trying to are trying to do is to buy a few weather station data and install it in different places. And we looked at a few of the devices it's not so expensive, and it can directly send the data to the server and we can get them, both the rainfall data and the, the climate data into the system and then like we can just see how best we can try to use it utilize it. So that's what we've been trying to focus on. So average is not a good thing when it's come to climate data actually temperature is the peaks. Thank you for the presentation. I think it's for the for Malawi in Kenya. And, yes, see, I think it's, it will be very good to learn more about you know how the use of the data at the community and the community, the community level, but then my also particular interest is for the lab presentations on the CRBS. So we are pushing the data into the CRBS, but what will be the use of the CRBS data back into into the, the, the, the health data as part of the analytic and the products of the system. And just to address on the law first and then I can give the mic to you on to answer on the result or take one with the CRBS what we just told that like from the Ministry of Health side, all the parts, and all the deaths, whatever it is collected in DHS to, we will send the notification to the we are just sending only the notification with given the ID numbers and all different things and what the Ministry of Home Affairs with the Hera system will give is all the deaths happen in the villages. So that will be pushed into the DHS team. So we are giving the notification that it confirm it and then give the national ID on the death side. So whatever that's happened in the hospital, we are going to share with them and whatever the village that happened, we will share it back. But the challenge is in DHS to our organ is the facility, the hospital and all things in the CRBS it's only districts and villages. So when they, these are the different things the challenge between you to try to to take care, but in law instance, villages is also part of law DHS to organ so it was easier to transfer the data between the CRBS and DHS to the DHS. Lessons from the human part of the information system is of course that you need to feed the information back and get interest around the information at a local level as possible in order to move forward. I think that is one of the lessons from the general human information system that we need to give to the animal health side that even though it's not necessarily achieved everywhere in the nation, etc. But if you're not being able to give data that are interesting, I mean for farmers for example when it comes to animal health, then it will be no progress anywhere. And that is also the reason why we are saying that we need to include other indicators, not only the sonotic diseases because the farmers may be more interested in diseases that are affecting their economy and livestock. And that kind of things and necessarily that kind of speciality of transmission between animals and humans. So, so to strengthen them more generally the information system in animals is probably the best way forward to also get the early warning and health security surveillance that we are interested in from the other side. So, give data back to the people is important and the data that they want or need. We have a quite big spam from animal health to monitoring the SDGs across sector, I would say, but however cross sector. And so prosper you are presenting both from the National Development Plan, but also down to the Rhonda even though that's Andrews topic and adult and team. Have you seen any of the incentives to actually utilizing the data on a different level than the national, you know, at the national, how low can you go with those data. Yeah, thank you very much. Yeah, I think in all the implementations we we've seen the most incentive that most of these use, I mean, most of these implementations go with funding so they are the sources attached to, you know, the innovation, I mean the presentation that you had happening at both national level, district level and then village level. So you will find a lot of need to report. I think the reporting. We had one question which was about, you know, how, how do we get these sectors or report. So one of the incentives that as you report your data, you are getting more funding so it's like results almost best financing. And also, there is also a competition that is among this because there's a lot of comparison between one village to another village as you're doing your reporting so this data is available at different levels we've seen in Rwanda it used to be on, you know, boards where people go and read but now you have it to the dashboard and you can have it on the phone. So the more incentive is the team being able to see that they are, you know, being counted and also the reporting covers with more funding as you as as you are as you are implementing. Thank you. Any question from the audience to this distinguished panel. Kristen almost asked my question, but this is to prosper on Uganda specifically. I can imagine that to the level of integration you've achieved in Uganda is actually quite impressive and very expensive. Do you think Uganda is at a place where this is now institutionalized, where if the European Union doesn't fund it. There is enough value that's been seen. I mean the president has a dashboard that the government will continue to fund this because they see the importance and how critical this data is for the economy. Yeah, thank you very much. And that's one of the, you know, the big thing that we look out into implementation especially in the government's really looking at sustainability not only just having a good use case that can be able to you know showcase in a conference or whatever, but the people really using the system so the beauty around Uganda implementation is that the system has been in place. Whether it has been, you know, it's been more of Excel spreadsheet so people have been reporting with a, you know, Excel and the Office of the Prime Minister go through all these Excel to look at the different sectors and the generated report. But the biggest incentives is for them being able to, you know, as fast from the Office of the Prime Minister which is managing this being able to manage the data very well, you know, having a robust system that can be able to give them. But, but also for the other sectors also being able to have a place where they can be able to go online and look at their data. So that's one of the biggest incentive that is really pulling this. Then they have been also structures of this reporting in those ministries, different ministries, they have, they have structures of who is reporting when to report and the data and so on. So that's that structure is already there. So this platform is already is already finding some comfort in the implementation. Yeah, so the European of course Union has the contract they had with us to support this is ending this month. And that's why we have asked us to have an MOU where we can be able to keep, you know, supporting them as we keep moving. But we really see that they're also thinking of, you know, in the next financial year, which is the beginning this year to put a budget that will cater for, you know, the maintenance of the system is being hosted by the by the national data warehouse. So that's where it's hosted so there's no cost to the hosting, but also the budget that they are planning in and they've actually asked us, you know, like what kind of implementation needs we need like trainings, regular trainings and system data and so on. So there is a really good great willingness to be able to support it moving forward. Thank you. Thank you. Any other question from the audience. If not, I have one I can take it more generally but the hinting at agriculture in January. We have seen in education that the appetite for having better data system for analytics are coming from industries when they look to health that have better have you seen any of the same has that what has been driving for us from agriculture to use the data leading question, you know, but I'm wondering whether this kind of appetite for for data has kind of spread or diffused through, through the, you know, pandemic or the quality or the more data, as we have seen in education, not jealousy but you know a bit of enemy and competition between health and education. Jennifer. So for us in the ministry, I think before they influence the start of the dynamic system and there is always has been interest in agricultural data by different stakeholders that work with, but I think the challenges that we're having then was that in terms of having timely data, having a database where the information is concentrated. So with the introduction of the system in the sector, it has gain interest with the donors and gain interest with academia there is such institutions, the that use information for different reports and also generating different policies. And also there's an interest where by now we want to be using further the household registration for different innovations, maybe also including the subsidy program that we implement in the ministry so yeah for this system I think it will provide whereby accessibility is the accessibility of information before, rather than that before when we, it was a challenge for one to have access to our precious data, yeah, thank you. Yeah we have one question online so the question is for all of you. In any of the countries we are using DHS for cross sector, do you have any data sharing policy. That's the question. Like it's on the law side like we have within within the ministry, the minister of home affairs. Hello, can you hear me. So in law like we have the things with the minister of home affairs and ministry of health. So they're like we have a clear cut data sharing agreement what data can be pushed and also what are the different fields that the minister of home affair is collecting for the birth and the death, and what are the different fields with DHS is collecting. So they are also including few of the data which they want minister of health to collect, so that they can try to do so this is not only agreement on the data sharing but also on the metadata side and all. So that is been there between two ministry with the ministry of natural resources and the environment. We are just starting. So where we are pulling the data from there, but I'm not quite sure what data will give back to them. So right now we are just like only pulling the data of the climate and the things from from these weather stations but not not much what what we can are giving back to them. That's from from law side in Kenya there is an agreement between ministry of health and and the climate meteorological agency, whatever that is called on sharing of climate data and health data. That is something when you have a meeting in the ministry of health in Kenya informed about and they are actually launching initiates around climate and health and we'll have a big conference later in the year. So, they focus on that sharing. Talking we're just commenting well before you Jennifer so so world meteorological organization are advocating for open data. So that's kind of in the era of sharing, but in practice of course different Jennifer. So for us, we also have a data sharing policy that is being managed by the Department of a government under the Minister of Information. So as the government entities were able to utilize that policy. And also we have the national statistical phase. That's the other ones also who coordinates and oversee all the data statistics that are collected in the government sectors. Yeah, so we have that person thank you. I will put my commissioner from Minister of Education for heresy from Uganda on a sport to help me with this but I for in terms of data sharing but I know Uganda has had an initiative. So maybe I'll ask you to comment a little bit on data sharing across sectors. Thank you very much. I think data sharing across sectors in Uganda is something that is being promoted especially under the current national development plan framework that prosper presented. And this is to align all sectors towards ensuring that we achieve the vision 2040 or the development plan goals. And we are using the program based approach to planning and also to performance monitoring. So we all have indicators and this is to enable sectors to move from being implementing silos, but like for example, the health, the human capital development program is comprised of three sectors health education and gender and social development. So on a quarterly basis, we actually have to show cause on how the human capital development program has contributed to the achievement of the national development cause so we have an M and E framework, where we have to look at all these indicators and see the performance. So we must know how education is performing gender and social development and health, and we are assessed as a program towards this achievement and this is done through the office of the prime minister as the officer of government. So I think that is the sharing than instead of having one sector information system, we are now opening up to see how we all contribute to the goals. Thank you. Thank you very much. Thank you very much. Just a short question to Lavi. I'm from Pakistan. Do you have any plan to actually study the impact of the weather on the incidence of the disease. In future, the impact of the weather on incidence of different diseases in your areas. Sorry. Okay, yes. Yeah, we have plans on how we can assess the impact of climates on different diseases, including the animal diseases. That's why we are saying that we have started with the climate information. And also we are also looking, we also have a module on the animal health. And in the future what we want to do is to link these two modules and be able to assess on how one module one data contributes to the other data set. So that is where the impact of climate is affecting or impacting disease outbreak on livestock. Yeah, so that's where we are going. Yeah. Thank you. That is the last word from this distinguished panel. Thank you so much a big hand. We have a coffee break, but please come back sharp because we have then a very, very exciting plenary again with looking back looking forward for DHS2 to become an innovative platform and we will have presentation by Lars, Austin, and again a distinguished panel. Okay. See you all.