There you go. Thank you so much everyone for coming and hopefully more people will come but nonetheless the the session will be recorded so you can watch it also later on. And I think there is also the translation in French so that's actually handy. Today what we're going to talk about a little bit is actually the use of DHS to for campaigns. I don't know if you have already seen it we have done recently also a webinar about that, and we started mostly like at the beginning with supplementary immunization activities. That came out of the need because after COVID after many years and more than 50 countries that have adopted DHS to for API, and there were like new use cases and of course like the COVID pandemic has brought a lot of like different type of implementations. And that bringing in together all the type of of experiences and use cases that we have found out there was very much needed as the use, the need like was more expressed by different countries. We started, as I said with immunization campaigns but there are many more campaigns out there. So, but not distribution mass drug distribution, of course, campaigns for residual spraying. And today we're going to see a little bit of different use cases not just necessarily immunization. And just to give you a little bit of an idea what we put out already. It's what you see here at the bottom right of the screen. We have a short documentation on the use the design and implementation of the highest to so like different type of considerations that you have to keep in mind in order to put in place the highest to for a campaign. And of course, when we are talking about a campaign is not just about entering the data but like it's about planning the pre campaign phases so we're talking about micro planning try to understand what is your structure and such. And use the highest during the campaign. So, of course, you might track your coverage is in my track like your teams you might track your, your progress. The most importantly also how to use the, the highest for the post campaign. We all know that probably the highest to is not the tool that you might want to use for your coverage surveys, but nonetheless you can still integrate this information and maintain it in order to triangulate this information later on in your HMIS. So we will try to like cover a little bit like how these different use cases have approached the different type of campaigns. And of course, as I was mentioning and of course we saw it at the other day as well from Scott the presentation, how much potential there is the highest especially for micro planning and mapping at the moment. I've seen different type of use like from the org unit profile where you can put so much information linked to your organization unit be it yours, your, for example, target population divided by use by age groups so it could be for example, either whether it's a vitamin a distribution whether it's an immunization distribution, or for example try to map your structures or in general, trying to catch like the catchment layers so you can actually understand where your population needs and like how it concentrates in the different areas that you're trying to target. Of course, it's really important, especially when it comes to campaign to remember that micro planning the micro planning that you've done can be carried with you because right now with the Android app you can have your, your micro planning and your dashboard offline so you can actually follow your progress as it goes. And of course that he was also mentioning the other day some upcoming features, like for example, the printing that is very important, but also what's very handy, especially for, for campaigns, it's the, is the travel time so you can actually plan how much, how much time we will need you to reach the different communities, and also to better plan the kind of the resources that you need to put in place in order to reach them. And as we were saying this, it's about considering the different phases of the, of the implementation. So like for example, whether you're doing off data collect offline data collection, if you want to do any kind of like checks for quality for your data, if you're doing real time monitoring of your data whether you're doing retrospective analysis and such, and then there are can be also integrations that you might want to consider, like for example rapid pro integration we have seen many already and we are working in that way to, to build it even further. And of course as I said the evaluation might not be your, your main tool but you can still triangulate this information and bring them in your national HMIS. Also if you want to do a rapid convenience monitoring, and of course, trying to like use other apps that are already available within the HIS for enhanced analysis here we're talking about bottleneck analysis, the action tracker to try to like make sure that you are on track when you are planning your follow up activities to maintain the goals that you have set. And, and with these like I don't want to steal any more time because I think that we have a really good use cases today. We have three presentations, all covering campaigns but in different forms here. The first one is going to be Babacangom, who is going to show us how they use the HIS too for mass administration of medicines. And then we will have Pramil, who will show us how the system has been used for supplementary immunization activities in Timor-Leste. And, and finally, Coffey, I hope everyone knows him. He works for West, for his West Africa, and he will show us a little bit like a different use cases across Western Central Africa, both for immunization but also other type of campaigns that they have done for example for mosquito nets and such. And with this, I do not wish to like actually steal any more time. And I would actually invite our first speaker to come over and he's going to be Babacar. Yep. It works. I'm my audible. Yeah. Thank you Victoria. Good afternoon, everybody. My name is Babacar Angom. I'm the digital data system leader at Sightsevers, and I'm based in Senegal Dakar. So today's presentation will cover the use of the DHIS too for mass drug administration and real-time reporting and monitoring in Nigeria. So I have two co-authors, Laura Sanjian-Gio from UK and Christian Edmusu from Nigeria. Often what we've seen so far is MDA records are compiled at the end of the MDA campaign. And it's only at that moment that the programs are aware of any issues regarding the coverage. So at this stage, it's often too late or more challenging, if I can say it like that, to have an adequate mop up of the campaigns. Now this presentation will cover the efforts that we've done so far to support the digitization of the mass drug administration from the community level to the up to the national level using the DHIS too. Yep. Well, so here is the outline. So we'll be, we'll put focus on the planning, the design, the implementation and the evaluation, basically as Vitoria presented and we also present some recommendation in the scale of plan. So you need to know that we are talking about negative tropical disease and it's a set of 20 disease or disease group with common, I mean, with a single commonality and they have an impact on Improvish communities. So MDA is a kind of a strategy that is implemented to administer drug to at-risk populations in given areas and regardless of their disease status. And it is implemented in NTD endemic areas, as I said, such as Nigeria. So since 2019, we worked with the Ministry of Health, with the Federal Ministry of Health through the Accelerate Trauma Elimination Program, which aims to eliminate, I mean, to support approximately eight countries to eliminate Trauma as a public health, as a public health risk. And during the implement, I mean, the assessment that we've done so far, there was some bottlenecks when we were presented, when we were, when we wanted to, to try to call to implement the tool. They were delayed in terms of the quality of the data and also poor documentation of the treatment numbers and the reporting rates. And also Nigeria Federal Ministry of Health uses the DHIS tool as the HMIS for routine health programs. So, in terms of planning, the first step was to be, we worked with the M&E unit of the NTD program to identify use cases with the, with the manual process of reporting data from distribution campaign. And right after we've examined the existing data collection tool, the data flow and the indicators, but taking into consideration also the real time approach. The other thing also was to define the user profiles and the roles and the, I mean, the users that will, that will use the platform and we also put in place a kind of long-term training plan strategy in order to, to make sure that, you know, the end users such as the LGA is the local government and the various teams and also the state team will be able to use the platform accordingly. And initially right after those phases, we piloted the tool into two states and we've done an evaluation to understand how the tool can strengthen the quality, the accessibility and the usage of data for programmatic action and ownership. This is actually a diagram that shows the flows and the roles during the mass drug administration, the campaign. Initially, prior to the MDA, information regarding the targets and also the drug allocation are entered into the platform. So it's done at the LGA level, those targets. And as the MDA progresses, they enter the information regarding the treatment data and also the drug allocation and the drug usage. And right after they, we have a kind of a common center that is set up at the, at the state level, that is set up at the state level where the state teams and also the, how do you call the LGA teams, we will reside approximately 10 days in order to provide technical support regarding the data entries and also the low coverage and the numbers and at that stage any issues that may arise should be reported through the common center so that they can, they can support the teams accordingly. In terms of design, we have different component that we've took into account. The first one is regarding the hierarchy. In terms of hierarchies. We set up the organization unit hierarchies, taking into account the standardization of the community of the standardization of the list of the communities. So information are collected at the communities level. And at that stage, we worked also with the federal ministry of health in order to harmonize the process because that process was not harmonized initially. So basically, what we've, we propose a kind of mechanism in order to have a two level verification at the national at the state level and also at the, at the LGA level before we upload the list of the communities into the system. In terms of frequency, we enter, they enter the information at the information regarding the population target at LGA level where and where those information is entered annually and regard and for the treatment data, it's a daily, it's a daily reporting for the population itself. It's provided by the state entity data manager and he used the projection from the previous census based on the information regarding those, those, I mean those demographic information. And from for metadata. So we configured the organization unit, the program indicators and also the data elements based on the forms that are validated or that were validated by the program. System wise or platform wise, we use the, how do you call the single event without registration and I mean also the capture module in order to enter information regarding the treatment and what in in terms of the population information, they enter those, those, those data, using the aggregate platform which is the data entry and right after days that are visualization aspect where we designed the dashboard using the scorecard to track and visualize the information, some legends to at least highlight the special coverage using the conditional formatting and for the drug ratio allocation. So we also monitor the comments and submission in order to take into account information that will be provided for the comment center that needs to be taken into account. So here is a snapshot of how the forms look like. So, on, on the, on the left here, we have an online forms to enter the, to enter distribution team activities which is the treatment data, and it includes the sensors the treatment information the drug usage the drug location and also some information regarding the disability and the SAE which are the server adverse events. The scorecard is also put in place in order to drill down or roll up information from the community level up to the national level and those information can be aggregated to, to highlight or to display the coverage. There is also here a coach that display the overall coverage based on the districts which are the local government areas where the master admin the master campaign took place. In terms of implementation, several benefits were how do you call highlighted. So the first one is regarding the improvement of data quality and completeness, which will allow us to at least, you know, know, for instance, the see to crack down the visibility if there is any, any issues regarding the quality of the data that will be that that was submitted. We also the platform, the platform also allows visibility for I mean on the progress of the campaign and to easily identify issues with reporting and following for for course corrective action. And the last point that I wanted to mention is, when we put in place the this platform, it allows also to know, for instance, if there is any data manipulation, which can help us also to flag the issues and put more mitigation regarding those data manipulation. Among the challenges, there were some this, this currency between treatment reports on the DHS to in the state Excel treatment as I said in the beginning. So the government or the program itself they were using an Excel spreadsheet in order to aggregate or to evaluate the reports, and when we were doing the comparison or the evaluation we saw that those information that they reported on the Excel sheet were different from the one that they reported on the DHS to and that was one that we are trying to solve. And in terms of the reporting also there was some delay on the platform due to internal review process and also some poor internet services such as the connectivity. And lastly, as I said, since before each had to call mass work administration campaign we need to have the list of the communities information are collected at the community level. Sometimes they might have some delays in the submission of that list to be uploaded into the system. Thanks to the task force for global health we were able to evaluate the tool so a study was conducted in order to see the usefulness of the tool in terms of the hardical during the mass work administration campaign. We were we were focused on two aspects. The first one was the coverage evaluation survey, which is a kind of survey that helps to validate the reported coverage estimate and what we've found what what we've seen so far was that there were a coverage reported and the coverage survey one when we've done the coverage evaluation survey and unlikely they, they might have some issues with the denominator population that's why it was one of the one of the findings that we've seen so far when we've done the coverage evaluation survey. The other one is regarding the government ownership and in terms of government ownership we took in place two to three dimension that are used. That are used that are quality and and based on those information we found that this the platform helps the team and also the country to improve those aspects regarding the government, the government ownership. Now, in terms of recommendation there are several of them. The first one is regarding the LGA workload, as I said, it's a kind of duplicate entry because in some LGS. They are using the excel sheet and there is also the DHS to so the program. I mean we are working with the program and the country itself in order to replace that spreadsheet use at the LGA level, so that the system can be used properly. The other thing also that I wanted to mention is regarding the community listing the context in Nigeria is quite sometimes challenging because of the number of communities that we have within the, within the country. So it will be good to engage early as soon as possible with the, with the LGS and also the states in order to have the community list that that need to be uploaded before the MDA campaign. And the other one that I wanted to mention is regarding the connectivity definitely since the tool. I mean, if you want to use the DHS to you need to have internet connection and the infrastructures that needed to be to be hard to call to be taken into account prior to prior to roll out. In terms of system wise so since we are also collecting information regarding the drug usage. So separate drug tracking system need to be put in place so that we can track down the drug availability at each level. And then also the logistic team can, can, can, can give more insight can have more insight on the system. And the last one is enhancement into this. I mean, regarding the system by, by, you know, adding some, some kind of validation criteria or validation rule based on the maximum and the minimum range for certain indicators. And the scale of plan. So you will have, you have here on your, on your right a map that shows where the, how do you call them, the DHS tool was, was roll out and so far we implemented in certain states with the exception to scale up to scale it up to all the 36 states and federal capital territory of Nigeria. So we integrated the mobility information such as, for instance, if you take lymphatic fluorescence, those hydro cell and lymphedema management cases mobility cases. So we want to integrate those information into the system. The other one is regarding the historical data so that we can at least have an overview of the past treatment that took place within the country and that will help also the ministry to improve the, to improve the quality of the service and lastly, increasing also the coordination with entity program and also the process that manage the national system by doing, by having kind of interoperability where those data that we collected during the MDA campaign will be integrated into the HMIS. That was it for me. Thank you so much. Thanks for attending. Thank you so much for the car. It was fantastic. And it's always nice to see new use cases actually. So we are having now from mail. Unfortunately, couldn't couldn't join us in person. It's a pity couldn't get the visa on time, but nonetheless, he has a super interesting implementation presentation for immunization activities and other stuff. And I see him that he's online. So hold on a second. Can you share your screen premier please. Super. This one right. There's a multi step approach here. Okay, can you give it a try to talk to see if everyone can hear you. Fantastic. Okay, then I leave you the floor. Thank you so much. And see the screen right. Yes, we can see. Thank you. Okay. Good morning. Good afternoon. Good evening, everyone. So, I'm from million again. So apologies for not being able to be there physically, but I'll be sharing the experience of Timor-Leste on using the HIS to for this supplementary immunization campaign which happened this year. So this is an outline of my presentation so I'll be briefly showing what Timor-Leste health information system is which is the LHS then what is happening in the immunization related to the LHS and with what is the outline of pre campaign during campaign and post campaign how we did use the DHS to to manage this campaign and what is our follow up plan. So just a little bit about Timor-Leste for those who are not very familiar with the country so it's a very young country so it's suppose it's the first new sovereign state of the 21st century where it was declared a sovereign in 2002 and so the country is still 20 years old and it's about 14,000 square kilometers in size and population is just over 1.3 million according to the recent census. And in the structure of administration, there's 14 municipalities, one national hospital which is called the HNGV, the entire referral hospitals, 72 committed senators and 350 health boards. The LHS visit which is Timor-Leste health information system, which is the LHS through based, was implemented and initiated in 2014 so that this is the snapshot of the journey of the LHS so as I mentioned it was initiated in 2014 then initially in five districts then three districts added then five districts more added so likewise it expanded till 2020 and then after 2020 it had a major leap because there was so many developments especially related to COVID-19 immunization tracking and also immunization other immunizations then portion upgrading and adding of indicators. So what is happening in the immunization in Timor-Leste, in this Timor-Leste health information system so we have monthly aggregate data for EPI reporting from health facilities so each health facility will send a monthly aggregate into the system and also in addition to that we have COVID-19 daily reporting the number of doses given for COVID-19 vaccinations from each COVID-19 vaccination post so this has been happening for the past two or three years and still continuing so daily we have the COVID-19 vaccination data. And this data entry is done at community health center levels for all the health facilities mainly because due to this communication challenges this we have some internet issues in the small health posts and other health facilities so CHCs the community health centers are the main point of data capturing into Timor-Leste into the system. So apart from that this year we have done this supplementary immunization campaign which I'm going to talk now and it was for five drugs like three vaccines and two other drugs. It was for PV, PCV, measles and also vitamin A and Albinazole and then we followed it up with this immunization coverage survey in 2023 March to April for EPI in Odessa. So this is an outline of how we use the system for this supplementary immunization campaign so we had pre-campaign planning where we did the operation plan designing testing and training and then during the campaign how is the data, we used the data DHIs too for data capturing then validation and improving data quality then daily how we send daily updates and conduct a real time monitoring and post campaign also used to not using the TLHIS one is the rapid convenience assessment then the data audit and coverage survey and which made this data triangulation possible. So moving on to pre-campaign planning. So in the operational plan we used TLHIS to get this routine EPI coverage for this to do the initial needs identification and resource allocation so from this chart you can see the red lines where we needed to protect these children especially from one to five years with these four measles and rubella and then also then enumeration was done also using these family registers and house to house visits. This family register also came from an electronic version from another software and then for setting targets for each municipality how many children should be vaccinated how many children should be administered the drug because we had a 95% minimum target and using the enumeration and the population estimates from the TLHIS we were able to perhaps we were able to set separate targets for each and every municipality and then also to plan where the vaccination posts are conducted using the facility mapping we had all the post mapped in the system so it was easy to plan the vaccine post and also we had integration with the COVID-19 vaccination so the SIA was integrated with the COVID-19 so here in vaccine post both the SIA components and the COVID-19 vaccine was given and also for planning of this infrastructure the equipment and the connectivity. This is the design how we plan the design, especially the data flow of the data was fed into the system and how it was aggregated and analyzed. For example, the vaccination post we had a daily data coming from the vaccination post and it was sent to the community health centers or the closest health post or sometimes the private clinics the hospitals and H&GV the national hospital they also conducted vaccination posts. And these were aggregated that these places and sent to the CHCs for capturing so capturing into the system so from above the CHCs it was totally paperless and it was managed through the DHIS too. So how to place the vaccination post and the metadata for data collection that is the data sets then outputs for analytics and user management so everything was done during this design phase. And then we also did the testing we have a test server so tested with data entry and analytic performances and also how the users accepted the system for this campaign. And then further on pre-campaign we had this training and readiness so we have we did the national DOT and also then the sub national level training and also then we prepared this guide one for campaign guide and one for the system guide so we had one pages for data entry and also one page for data validation both in English and data version which is the local language and also conducted a DNS assessment checklist. So during the campaign so this is what we did during the campaign. As I mentioned it was a hybrid system we had paper based at the vaccination post and then aggregated then entered into the system daily so paper based and electronic hybrid reporting was used and daily aggregate data entry was entered at the CACs and these contained doses administered for each product or five products with the sex disaggregation and then also the AFI and the reactions for the vaccines and the drugs then stock information how many received how many given how many discarded and how many returned those types of information for all the drugs. This went a daily and it was advised to enter it before 10am next day to have the completeness so timeliness so timeliness was set one day and completeness we allowed five days if sometimes it was the weekend so that was how we conduct the campaign and also how we ensured data quality so we ensured the validity consistency and accuracy using this inbuilt validation rules for example. If you think of oral polio vaccine which is given to all children and other vaccines were given to only certain age groups so there had to be the oral polio had to be more than other vaccines so those kinds of validations we included in the system that was well dated during the data entry so that warnings were given and errors were minimized then we used the outline detection and trend analysis also for improving data quality and then we generated daily updates so all these infographics were sent daily. So next day after 10am with the data in the system we send daily updates with coverage reporting rates and cumulative numbers with targets and the data tables all these were sent to all the healthcare workers using WhatsApp and email and it was monitored daily using these and apart from that the administrator also uses these dashboards special dashboards for SAE campaign where we had all the charts, graphs and maps and apart from that they also had using the data visualizer and the maps app they created table charts maps as they wanted and used it for analysis. Then on moving on to post campaign so we conducted this rapid convenience assessments so this was also like a hybrid one some had filled it in paper in the fields and some added it in the system so all those who added it in paper then came to the centers and entered it into the system using the DHIS2 events app we were planning to use the mobile data capturing but due to devices issues then we couldn't complete that but it was totally then entered into the system finally then for this post campaign evaluation. Then we also had the separate data analysis component on RCA how many people how many children were vaccinated what is the coverage in this assessment so that kind of snapshot we was able through the system. Then we also the HMIS Department of Ministry of Health they also conducted an evaluation data audit to check the data completeness and the accuracy of both SAE and also the EPI. So we checked for this transfer errors from paper to other paper and then aggregation errors in the papers and then data entry errors validation errors so all these errors were checked by the team visiting each and every municipality and then data audit both for SAE and EPI and following the completion of campaign we had this EPI coverage survey so that was the first time we had total digital technology based survey for Ministry of Health coverage in the molestase so there we used individual event module in DHIS2 and we had tablets. And using the mobile have DHIS2 mobile app we conducted the survey and we were supported by the Department of Statistics who also had some experience doing the census so they also supported us and in this survey we captured all the locations and then EPI and SAE coverage both. And there were separate dashboards for the supervisors and also for the managers to check daily how many areas were covered, how many clusters were covered so that was daily monitored by the supervisors. So in follow up we were able to get 100% reporting into the system so all about 6 weeks we conducted the campaign so everyday reports were completed by the end of the campaign and almost all districts had good timely reporting also and then using this monitoring system we were able to achieve the national targets which was 95% coverage for all the products. So now in we are awaiting the final results of this immunization survey and then we have three data sources for this immunization and we can do a good triangulation of data to check the coverages and where the assess further interventions and plan for the first for the interventions. So these are some pictures from the users who from the peripheries the CHC is supported by the supervisors we had immunization consultants also supporting them and they were quite happy to put this with the system and what they have achieved through the system. So, thank you very much, thank you very much for listening about the success story for SAE campaigns. And thank you so much. They looked indeed pretty happy where they were entering data I don't know if they were posing but they looked happy enough. Thank you so much for the use case it was fantastic to hear also especially for the, the, the evaluation actually that's pretty interesting not. I haven't seen a lot of use cases for the evaluation so I think that's pretty useful so for other users out there to see that it's possible to do also directly in the HIS. So thank you so much for mail. We have our last presenters. And it's coffee, who is going to show us a little bit about the. Hold on a second. He's going to show us about there were the work that was central his was central Africa has done across the region and he is going to give us a little bit more information about the campaigns they they have supported. So, to you coffee. Thank you Victor. And this is a presentation that was put together with the team from his forces on to Africa. I hope you can hear me. Okay, so you have the team members there. And we're going to share with you some experiences regarding immunization campaign in Congo but also some highlight from the benefit campaign that we did in Guinea and then. That's coming. Okay. Is it moving. Okay, so they are the high and outlines. In terms of background regarding the campaign immunization that we had in the Congo, Brazil, not DRC. So, in 2020, the country was facing a large scale missile immunization epidemic. And it was hitting knife and department out of 12. And we've had deadly toll for our children. And you should know that in Congo, measles is rampant in the country in the epidemic and endemic mode, but other than the previous years, we have seen an increase in outbreaks across the country. At the same time, the country was facing the resurgence in yellow fever, especially in the point in our department. So it was decided to have an immunization response. And that was decided to be done in the DHS to which was the first time they use DHS to for this kind of intervention and that was under recommendation from Gavi. So, this is a snapshot of the, the form that to use. And we, we have configured in the DHS to two firms, one for the synthesis, daily synthesis on not mom, but measles, and one of another one for the yellow fever. In terms of planning, we had use an aggregate approach, and we have matched that with the national deployment of DHS to at that moment because DHS to was not deployed at the facility level that time. So, data tip in was happening at the district level, but they were typing data by health areas, which is a new data layer using laptop, we have done testing training and micro planning as well. So regarding the design, we have a metadata dictionary. We have configured a set of data element indicators and imported the users from EPS spreadsheet. In terms of Iraqi, I was saying that we have to create a new layer, which is health area, a set of health facility, which was not there in the system before the intervention. We were not collecting data per sex. This is something that was very interesting because it has been now correctly documented that there is no discrimination in terms of sex, and this was a very important decision that was taken. Don't collect data you don't need and then you don't you don't know what to do with and we were collecting data on the stocks and if I as well. We designed the dashboard and we have for data validation purposes configured some mailbox so that they, the monitoring team can monitor in real time, the validation rule violations. The usual training training materials like user gate and also what you call the testing in the field and so on. So here, here is a snapshot of what we designed in terms of the calculation for the missile and then something like this as well for the yellow fever. This is a snap on the validation rule violation messages that the team was receiving whenever the rules were violated. So, in terms of running the system we have some challenges the same as the one that colleagues has presented some minutes ago is about the internet is about the agenda of the Ministry of Health. We have a very heavy agenda we have to adjust with it. And also, there was a competition between data routine data typing and immunization data typing because it was the same people that was in charge for these these tasks. In real time monitoring was a success because the, the team was sitting at the API program was able to have the data dashboard for both performance and also for data quality. And this is a snapshot of what was ongoing during the you can have the map the figures, and so on, the same for missiles and rebella dashboard. This one, we achieved 93% of coverage for yellow fever but you can see that we have achieved over 100% of for the rebella they the API program claim that it was not under estimation, but currently they are under an evaluation to check the denominator. And this was because of these DHS to that had triggered another question that they are trying to to answer for their data quality. We have not included the rapid convenience assessment and integration was done with the HMIS since the beginning. This is was the impact of this campaign we did. Data was available. The report was available in two weeks, which was not the usual because they used to have several months before data can be available. I got a call from the API director saying that I'm more than satisfied with the way that I was managed through DHS to for this campaign. I want all routine API to digitize in DHS to what we did, because the configuration workers was done to carry it and then we have ended parallel reporting in Congo Brazil now. The second tour for yellow fever has also been conducted in DHS to and then OP view was configured in May for an upcoming campaign in June. And the one of the API data manager was saying that he was very impressed. And he even went more when father saying that he's feeling certain seniority after he has used DHS to for this campaign. And he's confident that they'll do more later on. Let me bring you to Niger for a quick snapshot on what we did there. That was some, some screens. There we have a bed net campaign that we conducted on the pilot mode in six district over 72. And that was an increase because in the previous campaign we did for district. So we use one tracker and three aggregates. We have a usual hierarchy and put some dashboard there. The challenge we faced was almost the same. We are having some difficulties in terms of Android use, despite the fact that we have a smartphone that were used. This one was a very simple one. And the one that we, we were challenged with was the one we did in this awesome snapshot of what we did in Niger. But in Guinea we have a different type of challenges. We conducted this benefit campaign country wise, and they want a very huge pilot. We need to run a three day preparatory, preparatory workshop for that pilot hosting was a challenge. I will come back to that later. They want a full system with one tracker, three aggregates, and they have segmented the country into two zone. And after we have created the normal hierarchy, they wanted us to create two new layers, one for the sites. So we have to create 2.5,000 sites for distribution but they want an emulation to be conducted on a village basis. So we have to design over, I can say 20,000 villages to conduct that enumeration. Android capture was also a problem because we used the Android capture for the demo. But after the demo they say that they don't want it anymore. They want a custom app. So we have to design it, but the resources were limited the time was limited. We don't have the time to properly train the people. We generate three main dashboard but during the running they want more dashboard. So we have to create a lot of dashboard again. And the user interface, we need to unroll the house road and they want us to count every single person in the household up to 15 person. So this creates a lot of challenges, including the fact that we have to capture stock data using batch numbers including the system. This is a snap of what we used in Guinea. You have some data entry form. You cannot see the six system that we deployed for that campaign and some idea of what we were capturing as data. This is the Android version. And during the running we have some challenges in the server. They insisted to have a physical server that was virtualized but that server was saturated quickly we have to purchase another server by the way they haven't paid us yet. And then that one crashed again. And then, by the end of the campaign they want us to move all the database to the country national data center because of some sovereignty policy. And we have to run a several several versions of the app during the campaign the MDM that was purchased. They called it and watch that was used by serious doesn't work well when you change the version it doesn't update it across all the, the, the, the, the, what you call the devices and then you have to manually update it and then take the data and put it in. It was very challenging. But what was something was very instrumental in this campaign is the, the real time monitoring team made of it and statisticians and many from all the ministry sitting at the national and original level. They were very reactive and that helped us overcome the challenges that we're having. That's why all those these campaign were so successful in Niger they want to continue with DHS to, and they want more they want to use stock management and they want to use DHS do for the supervision during the campaign. A statement from the national malaria program coordinator you're saying that DHS use for LN campaign was successful and due to his consistent support challenges were overcome, despite some data discrepancies, we want DHS to for the next campaign. We want a resident his aspect for three months and they have budgeted that in their current budget so that we can go and enjoy some time there. And then we will score even better for the next campaign. In Congo, we have a huge success because data completeness and time is over there. And it paved the way for the other campaign as I was saying, that will, that have some enablers. The new EPA director which is very high demanding. We need those kind of people at the sitting on the top of the programs, and a good recommendation from Gary. I don't know what kind of donors are there but I would like to play for you to help us so that we can give some very nice recommendations at this one that we had. It worked also as an attractor for other countries to come in because in DSE we were able to conduct recently Ebola campaign using DHS too. We have secured funding for to conduct WHO funded campaign in Togo, and then we just have a request from Sierra Leone for routine immunization isolation campaign. So we think that these experiences has been very successful despite the challenges and we are looking to do more. That's all from me and thank you for your attention.