 Okay, so I know we're already a little bit late and we have great presentations so I am going to fly through this first part. And just give you a little bit of an introduction over the last couple years of where we've been working in DHS to in the space of disease surveillance cross sector data sharing early warning and response. So this is a little bit this is a bread and butter this is where most countries actually starts using DHS to with their indicator based surveillance. Because for them it was just natural it starts mainly at the facility they report on everything else so why not report on my ideas are as well. And this is really really scale so more than 41 countries at this point. About 20 of them prior to coven and since coven we have now seen the adoption for integrated disease surveillance go up substantially. Some of you are familiar with our our WHO toolkit for this. Some of the ways we support this type of surveillance data with the thresholds outbreak alerts, automated dashboards. This core standard metadata from WHO has already been defined for about 15 diseases to support standardization. And of course we have both aggregate and case based reporting modes. So countries typically use a combination of these in order to get what they need. But thinking back to the Afro guidelines for ideas are event based surveillance has always been that pillar, and then we've forgotten about that pillar for quite a while. But coming out of the covert emergency again what we're seeing is that countries that have now really started to strengthen their foundation digitize the indicator based surveillance. They've realized that EBS is a huge part of this early warning. So there are several countries you'll hear from some I think Tanzania today about how they use kind of DJS to for event based surveillance in the country level. But there's also been work with the Africa CDC and partners at his South Africa in establishing a continental wide event based surveillance system. And very much also in line with it is meant to compliments and feed into other systems and tools, including WHOs EIOS so the EIOS being epidemic intelligence from open sources. So we see country regional global level all working together for health emergency preparedness and response we just had a bit of a conversation out in the hallway with many of our colleagues from WHO health emergencies. We talked a little bit with some of these colleagues over the years where there is not such there should not be such a dichotomy between your routine and your emergency, your routine surveillance it is ongoing all the time so that you can actually detect an emergency very quickly. But then what we saw from countries is how much they actually leverage DHS to as a part of that response. So 59 countries were adopting extending DHS to as part of the COVID-19 response strategy. This also included vaccine rollouts for example so the power of an integrated platform to get different sources of disease data and as well as the response. We wanted to have a presentation on Monday sharing with us they have established DHS to as a national EID SR since 2013 gradually slowly building this up. And they actually in the most recent outbreak 2022, they use the system they use this SMS reporting tool that they had that community workers that the public was aware of, in order to actually do a signal management so get those signals to the community of a suspected case, make sure they were being triaged verified moving to the appropriate district officer, and if it met those case definitions it meant sending out an ambulance team, isolating that case and linking them with treatment points of entry this was actually his Sri Lanka and the Sri Lanka before anyone else really did something DHS to for COVID-19. They actually established this at their airports to start monitoring travelers. And this really started to pick up so the combination of DHS to as an extensible system. You can build apps on top of it. We do have support for offline capability. These points of entry were places where you can add new actors who are collecting data, integrating it into this system. This example is also from Uganda where they have more than 60 land borders, and it was really important for them to keep trade open during this emergency, but also being able to to track and monitor the people crossing those borders and make sure that if one of them turns up positive they could also appropriately respond. DHS to for rumor monitoring so this is from Mozambique. Now, I understand that rumor monitoring sometimes it can be very similar to event based surveillance. In this particular case it was a lot about understanding vaccine hesitancy, monitoring rumors to understand what kind of targeted public health communications do I need to have with those people. However, from a functional perspective this concept of rumor monitoring is very, very similar to event based surveillance. And so as a software platform, we spend a lot of time looking across all of these different use cases and saying how can we make the generic structures there, how can we make them possible for you to use and many different ways. We have some new work emerging with us CDC on rapid response team rostering. This also builds on lessons learned already with some basic solutions that countries have done for just trying to understand and manage and roster their community health workers. So again, we are building things based on what's already worked and what's been in the field. Lastly cross sector data sharing we are working with, whoa, with follow with countries to understand how animal health, human health can cross share data with one another. We have new initiatives climate and climate sensitive disease surveillance data so I invite you back to this room at 1pm where you'll actually have a presentation about what we're doing in this space. And then everything for us comes back to triangulation integrated systems, not just for effectiveness but also for efficiency. When you have 100 platforms and you don't have the resources to manage 100 platforms, you have fragmented data everywhere. So we've worked very closely with Afro and others to see how can we bring these different data sources together develop these triangulation dashboards, and these are used as part of response campaigns sometimes target areas of low doses. Sometimes they are reactive because something has happened there is a meningitis case. Now we need to launch a campaign and I can't do that until I have that lab data so everything comes together. Mortality surveillance this is a key part of routine health information systems in COVID-19. A lot of this was used to do these excess mortality calculations. So again we cannot think about this disease surveillance data in a silo. We have to think about how we bring this platform together. And so with that I will hand over to Stefano and the remaining colleagues thank you. Thank you very much Rebecca so we decided to start directly with the presentation with this overview about this huge thematics because I mean we can spend entirely an entire week discussing about surveillance discussing about another week discussing about one else another week so thank you very much Rebecca for this very insightful introduction. I will now ask Will Bowyer from CDC Atlanta is going to provide us a presentation about the creation implementation of a district health information software on the surveillance for viral zoonotic disease. Thank you very much. Can you all hear me. No. Good. I never tell. Yeah, no problem. It's great to be here thanks Stefano for the introduction. My name is Bill Boyer. I'm working at the US Centers for Disease Control and Prevention in their division of global health protection. As Rebecca touched on, just briefly, we are working with them and other agencies on a zoonosis surveillance package within DHS to as part of a toolkit. And I will be discussing that today. Good to go. As a little bit of a background, we have a five year cooperative agreement with the University of Oslo to fund toolkit development and country level his organizations that are involved in this work. The purpose of this toolkit would be to integrate human and animal health surveillance by formalizing and digitizing response communication between those sectors for early warning for improved response and for upward reporting of both sectors. Additional goals of this toolkit would be to provide ministries of agriculture ministries of wildlife and fisheries livestock as well. And all of those in the animal health sector with the same resources and infrastructure that is available to the human health sector in countries. And we also want to build this into current surveillance infrastructures within countries and we don't want to create something completely separate and require duplicate data entry things like that. So this is something meant to integrate these surveillance structures within a country. These are expressed gaps and express needs that have led to the initiation of this project. Some of these gaps, as you may be familiar with with one health surveillance overall is that informal communication across sectors a lot of his paper based a lot of it is phone calls SMS, which may work, you know, one off instances but wouldn't necessarily work in a epidemic scenario. With this project we're hoping to digitize that communication that already exists and make it formal and take out kind of the human error component of that cross sector communication, leading to, you know, early warning response, and hopefully data sharing across sectors with joint investigations. And so I know, you know, this project is right now focused on human and animal health integration. But of course there are other disciplines other sectors that are important, like environmental health. And that is something that we're, you know, considering as a project progresses but really just starting at the intersection of human and animal health sectors right now. And this is what we would want to be included in a toolkit this is an ongoing project is not something that has been completed so the toolkit is not, you know, available yet but it is something we are currently working on and these are the goals here. dashboards and visualizations maps and analyses minimum data elements and reporting requirements within this toolkit. But the big one I'll be talking about today and something that we've been as a as a group, focusing on more recently with our resources is the notification and data sharing across. What's this in the way across sectors. There we go. And lastly, we would include data collection and investigation tools within this toolkit. So this is just a diagram to kind of visualize how this toolkit would fit into current surveillance infrastructures within a country. So on the left you have the animal health surveillance hierarchy. And I'll explain the tools here in a minute in the animal health sector but you may be familiar with EMA I an emphasize of the food and agriculture organization. And on the right we have the human health sector and the public health sector. And as you see in the middle, at national level, we have the DHS to one health is an eye disease module. And this would fit into where DHS to currently fits in countries that use it, and the reporting mechanisms that would be here would would be what is currently in a country so it's not as I was saying, something that's completely and something that would that would cause data duplication and additional reporting. And so the idea would be a zoonotic disease event could occur on either sector could derive from the human health sector or the animal health sector first at the community level. They would go through their normal reporting requirements upwards to in the human health sector DHS to or emphasize the animal health sector. And then those the big goal of this project is to integrate those two surveillance systems at national sub national level to share data for early warning and for joint reporting. So as I mentioned we are collaborating with the food and agriculture organization of the United Nations or FAO, and they have two surveillance infrastructures and systems that we are hoping to integrate with. DHI is a event based surveillance system that is maintained by FAO, you can see their international landing page here. And they do have a similar a similar infrastructure as DHS to which is in a lot of other organizations they have national surveillance systems and national databases that are owned by the country. So you don't see necessarily a lot of of these little dots on on an events on this map, because not necessarily required to be reported up to their international landing page. But they do own their data at the national level and that's where really this intervention would take place. And we're also collaborating with them on the general toolkit and country projects. I'll be talking about in a little bit. And of course they have the technical expertise in the animal health sector. And so that's why, again, is crucial that they're involved in this project. And of course, why I'm here we are collaborating with the University of Oslo and his organizations, utilizing their established global network you can see on this map of course and and their robust and modifiable software that will be needed to, you know, work in this one health space that is complicated. And we are mirroring packages and toolkits that have already been created and published and made available on DHS to his webpage. And we are of course collaborating with their developers to create this software that can be modifiable for countries to use for for their one health surveillance. And we will be implementing these with them, moving forward with with country projects. And so with the country project a few times. We want to create something that is useful that is effective for these countries and with that we need to understand what the needs are at the local level. We don't want to create something just sitting from our desks, you know, thousands of miles away. And so we have been engaging in a couple of country projects one in Tanzania that has gone on for almost a year now, and one in Guinea that is just now starting recently. And the missions of these country projects are to understand their surveillance procedures in country related to one health and related to zoonotic diseases to identify gaps in reporting across sectors, identify best practices and implement those best practices. And then as I mentioned, using those lessons learned to create a global toolkit that will be useful and will be effective in countries. So we visited Tanzania last year in September to learn about their express needs, their use of these two different tools, both FAO tools and DHS tools, and their current one health infrastructure in country. And we're also establishing those relationships with government officials, local FAO partners, their his country office, and the ministries that would be involved in this work. And we learned that primarily that mainland is initiating their own one health surveillance platform. And so that's something that we do not necessarily want to interfere with. We think that that is great. And so we will be supporting them in that. But Zanzibar did express more of a of a need for this data sharing and interoperability between their FAO and DHS two tools. And so in Zanzibar we learned that those FAO tools, and those FAO officers and animal health officers have been trained in those FAO tools, but they aren't necessarily systematically used across the country. However, DHS two is used throughout Zanzibar for both human health IDSR as well as some zoonoses event based surveillance. And there is no formal communication across sectors. So it is really that situation where it's all paper based it's phone calls. And so something that they express the need to digitize those communications. And that is mostly what led to to this project. So our his partners there just last week have continued these next steps with mapping district and local level processes for one health surveillance and to understand the specific workflows across sectors to be able to create a software that is very useful for these folks. And understanding specific user interactions with these different tools, of course, is very important to develop a software that that will be useful for them. And once pilot mechanisms for this data sharing across sectors are created, it will be piloted there for feedback and for integration into the global toolkit. More recently, last month, we had a multi multi agency workshop with a lot of folks in the room here and from from us CDC. And we work together to really conceptualize the use and architecture of this toolkit, what the software should look like what needs need to be met. And we are currently working on piloting mechanisms for information sharing between these two tools. And those can be seen here the goals of these, the goal within this workshop and the outcomes of this workshop, developed two goals related to information sharing and with data sharing. One being goal one being signified by the horizontal lines across the community and subnational levels between the two tools of of FAO tools, and the DHS two tools. And this mechanism that all was already created by our developers, Stefano and Brian with our group and their team is that one directional data sharing event based notification across sectors. 12 minutes now. And the information that is shared within those notifications is really the who what what animals are involved, what humans are involved, what what their contact information is for follow up across sectors. What in terms of if it's a disease if it's a test result. If it's a single event, what the event is. And of course where is important for jurisdictional follow up important, as well as when the event occurred, and goal to signified by upwards reporting into this toolkit into this module is different from goal one and that it is, you know, also data sharing but is unidirectional data sharing, and it is continuous throughout an investigation, leading to a joint investigation between human animal health sectors. And that would be something that we're working towards in the future. In addition to finalizing goal one and that unidirectional data sharing. We're also working to, as I said, develop that by directional data sharing for joint investigations and leading to overall toolkit development. And, and working with country projects to pilot those moving forward. So key takeaways for this, even if the countries that, you know, are in this room and not necessarily working on this on these country projects yet. Key takeaways for them would be to start having those conversations across sectors, understanding what gaps there are in your one health surveillance and what data, do you currently share what data needs to be shared for the other sector to continue their investigations for a proper one health surveillance response. And that would really be something that would help your country, you know, prior to, and when you receive this toolkit in the future to, you know, implement that in country effectively. That is all I have. Thank you. Thank you very much Bill. So the next presenter flowing a bit on the one health topics will be topic from is by Indonesia, going to present their experience on strengthening zoonotic disease surveillance at country level. Maybe just a logistic information I think it was already announced in the primary session so around 12, there will be a testing from the Norway government about the other system so maybe everybody will receive the phone can be very loud with, we don't know if it will be a 12, 1150 or 1215. So in case this will happen a way to avoid all this, this noise will be to put to have their device on a flight mode. Okay, but just in case don't, don't panic. Thank you very much. I leave the floor to traffic. Hi, can you hear me. Yes. My name topic from Indonesia. I want to share something about this is to especially for the surveillance program and genesis. You know, we want to share about the genesis here, especially how we use this is to from nationals implementation and sub national level. Currently, we have the since 2016, we receive many support from donors, especially how to establish the genesis one health condition, especially in Indonesia. Obviously, 2016 we have a tree application from three ministries. We want is from the Ministry of Health Ministry of Agriculture's Ministry of the forestry, for example, this is the big area what we share something. Next, we escalate the features to integrate from three application to be one application we call it like Caesar information system of genesis here. And that is very important to conduct the activities to help some help them how to utilize data from animals information from animals information so human health information and another application for purpose. So, since thousands acting something we receive some support from one from the University of Oslo to implement zoonosis system. We collaborate with the University of Oslo to establish this is to to be main application as national system. And this is the very important you have to know about the this is to in Indonesia is more to get that up from party to level and aggregate to national system. Then we escalate since 2020 is difficult time for us, not only maybe for Indonesia but also for the global we we trans we transform the existing zoonosis to be coffee 19 contact racing. It's very, very difficult to us to implement for the genesis application information system, and we established contact racing is more bigger than than than genesis in terms of the storage in terms of the infrastructure in terms of the application in that area. So, the one thing is what we have now is 2021 we escalate not escalate the scale up for the sub national levels from the existing from the previous genesis we escalate to one sub national level. This is the one city in Bali area, because a number of the rabies is very huge there. So we escalate the zoonosis and existing zoonosis to be main application in Bali area. This is the sample of the of the application. And, yeah, this is the samples and we use zoonosis here, not only for the Ministry of Health, but also sub national level, including facility level if your primary health care primary health care and another facility here. So, 260 active users currently doing some zoonosis applications. What is the item or consists here. So there are eight dashboard cover to eight use case, especially from anthrax until tenesis and Chris this source is sorry I'm not a public health person but is the information. And this is the sample what we use here in separate area. We test and we escalate the number from the West Indonesia in Asia province. So slow easy in one city in Yogyakarta. This is the middle one of area and we continue to to have the local context from the Bali information system. So we have the metadata summary is including more than 1000 data elements 63 indicators and 13 program. And this is the big effort what we say here to align with the UI. Oh, sorry, this is to global packets. This is the important two things we have to consider how the this is to global packets must be utilized for the local context for example languages. This is very important to us because you know the data elements description data elements named or for example we have to convert to local context the local, the local languages this very important to us. And this is the sample you can see from data elements cover the ERS health facility, the point of activities from the health facility and also from the SO to be validated and verification data. This is the data set we have the nine data sets including elisary, rabies, health data center for this CIM L monthly report and we escalate the numbers testing to the Bali area. And you can see it's very huge number. The one things from this is to in Indonesia, especially from Indonesia. The challenges is because we have the limited resource in terms of the public health. So our concern since last year, we utilize the person from the Ministry of Health, local university, for example, and who has been concerned about a zoonosis and public health like environmental health, for example, we engage them to utilize the our indicators, utilize the our information to be important to them, especially for the national level this very important to and you can see here. Especially if you implement the global toolkits like the data set or standardization, we have to translate for Indonesia, we have to utilize this the important to us especially trans translations from metadata is very, very crucial, especially for Indonesia short East Asia context. This is the sample. If you see, since 2019 on 2020, we have a plan to escalate to scale up the zoonosis application especially in Indonesia to be as the main applications from that area. There are a lot of organizations here, 34 provinces, more than 500 districts, 12,000 facilities is mean the primary healthcare instead of another application organization use it. And we test for the villages on the 300 something that I can use the you can imagine this is very big implemented in Indonesia but it's very difficult to have a the good one for the public health. Program rules and we escalate for the denpasar denpasar is the one city in Bali is the big city the capital city of Bali province. We implement denpasar in for responsible is the surveillance information system to be active and it's very, very good for the implementation right now, especially for the one health. We utilize you can see this is the interface already changed from this is to this is to user interface to be the local area as well. And this is the condition. This is the information we took from this is to especially number of rabies, especially in Indonesia. And every information should be utilized or converted to Indonesia number of the bites of the rabies, the animals type for example cases by gender cases are positive from the cases positive in humans is no, but you get the trend of the finding of the rabies very, very good. Enough to collect information and we transfer and we convert to the the map point for example here. And what is the regulations we support, especially in denpasar city. We established some focus area especially in the so we about the preparation and controlling factor infections and genesis. This is 2020 and 2024. There are four groups factor infected and genesis. This is one is about the malaria. DPD zonosis, including the rabies, rodentia, anthrax and episode, sorry, the flu boom is the avian flu. For example, here, let those pyros is hilarious is and warm this the the the regulation the local regulation has been supported by Indonesia team. So, next is about the genesis program in Denpasar. This is the sample from the start until how to utilize the data from this is to and also for the locals. This is the SOR level in here we utilize the information about the type of better specimen check result and checking dog population animal affection administrative and rabies positive animal tracing is the most important what we can see the information and flow chart here. And the second, the big things from Indonesia is about the integration data. The integration data is like many applications has been support many years, a long time ago from many, many donors. For example, the USID, the DEFED, for example, they have a lot of applications. And this is our, our challenging to support how to integrate data between application between system information system in specific area on that area. This context. This is the sample we utilize the information system from rabies. This is to to routine surveillance activity area or unit. Okay, I am, I think this is the enough for Indonesia, you can see the number and, and you know, this is more embedding and buying in in local context. Thanks, everyone, over to Steve. Thank you very much to share your experience for strengthening animal surveillance monitoring integration in Indonesia. And now I would like to have here for the evaluation of the electronic case based surveillance system in Sierra Leone, our colleague. Sorry. Yeah. So, yeah, I will leave the floor to don't go. Thank you very much. Thank you. Like this. Thank you. Good morning, everyone. I'm going to talk on something a little bit different is not an implementation of a system. But this time, an evaluation of assisting. My name is Georgia don't go. I'm a health scientist with centers for disease control and prevention. In the division of global health protection. So, one of the roles that we do is to promote the divisions goal, one of which is to help countries. Data quickly utilize that data analyze it and respond to disease heartbreaks, especially the epidemic prone disease and we do this through working with multiple countries first of all, and then ministries of health in country implementing partners. If center like this one to kind of help them utilize what available tools in the country. Transform it to collect data quickly, improve timeliness and completeness of data to achieve that goal. So I'm going to be brief this is a presentation outline. And let me just give you a context of the country you have seen this map several times if you do DHS to online training Sierra Leone is map is often used. So I just want to give an impression of get give you an impression of what the health units in the country are. They have slightly over 1400 public health units with one national public health reference lab and some for three or four regional referral laboratories and 208 zones. So, why DHS to, as I said earlier we used, we help countries use available tools that they're already familiar with so in when we went to Sierra Leone. They had already started using DHS to was introduced in 2008 as health management information system for entering routine monthly quarterly and yearly aggregated data, they had some challenges, but most importantly after the ball out the West African global outbreak of 2013 2016. We began seeing a lot of changes and the need for her to strengthen the system. So in 2016 to 2019 through a cooperative agreement with M Health, working in collaboration with other partners inside the country as well we customize the national system for reporting weekly aggregated data for about 27 notifiable conditions and that enable transition from pepper based system to electronic reporting. This became kind of foundational for us to begin implementing case based disease surveillance system. A lot of African countries actually have some sort of electronic reporting of aggregate data, either by phone, be smart or even the basic phone, but in Sierra Leone we started using tablets for that. The M Health had developed this custom application where you could send SMS in batches and I think the HS to has adopted that I've seen implementations of that in several other countries. So in 2017 we introduced the first electronic case based disease surveillance system using the HS to trucker. This was based out of the South Africa. This is a trucker template. We, after the ball out break CDC had a cooperative agreement with East South Africa, basically to transform and help the ball affected countries in West Africa to improve on their data systems. So Sierra Leone happened to be one of those countries. 2020. When the COVID-19 outbreak pandemic happened. We already some sort of advantages of implementing the case based disease surveillance system and the country adopted it as a national system for the COVID-19 response. This reporting data management and analytics and, of course, integrating it later with the vaccine management system. So when WHO, sorry when East Centre developed the generic package for COVID-19 Sierra Leone was actually far ahead. We did compare. We didn't need to customize anything. I'm not going to talk about this diagram. Most of you are familiar with implementing trucker program is basically the same concept, the notification stage. Then you go to the program stages and so on. So, maybe the implementation milestones I've already spoken about the adoption in 2017. 2018. There was actually a massive announcements on the trucker system. And our first pilot implementation of trucker was actually in Uganda using the acute fibrill illness. I worked with colleagues from East Centre here and East Uganda. We did that first test and I think kind of helped really improve the functional functionalities in the trucker system. Around 2018, we started piloting, actually we borrowed that concept and improved on the first implementation of the case-based disease surveillance system introduced in Sierra Leone in 2017. Then 2018 we improved it, redesigned it a little bit, taking advantage of the improved functionalities, piloted it in four districts, about eight health facilities. And then start planning rollout in early 2020 but was affected by the COVID-19 pandemic. We kind of delayed the rollout but the system was adopted for COVID-19 response. But eventually we ended up rolling out nationally to hold the public health facilities between August of 2022, January 2021. To date is being used and for many other purposes, not just for notifying events of national public health interest. So, I'm talking about evaluation. These were the objectives. We wanted to assess the extent of the integration of ECBDS in the country's disease surveillance program. Specifically, we wanted to determine systems performance in the following areas, its usefulness attributes, some few attributes. I need to state that this was not a very intensive health information systems evaluation. Neither was it cost analysis evaluation. It wasn't an impact evaluation. It was more of a formative evaluation to help inform our implementation challenges and get ways of improving it. So, we also tried to get the factors that preventing and all facilitating the integration through the investigation of people's processes and infrastructure. And then lastly, we wanted to know the role DHS to place in the disease surveillance and opportunities for improvement, assessing the workflows and so on. I said earlier this map is very familiar but the colors you see here is not for training. It means something. We selected eight districts purposefully based on their reporting rates. Those ones were doing well, those ones were not doing well. And in each of those eight districts we selected five health facilities that have consistently been using ECBDS and also dependent on their reporting rates between January to July of 2022. We're trying to get a mix of high and low volume health facilities. We also reach out to four original referral laboratories and one national health and one national reference lab. And our data collection was two methods we did quantitative data collection using standardized tools at a facility level district and then the labs. We conducted the key informant interviews at national and then districts. So this data collection happened in August of 2022. I'm going to talk about our findings challenges and then importantly lessons learned, we, there are a lot of findings with what a big report but I'm only going to dwell on a few that I feel are very important for this audience. Number one, in terms of human resource capacity which they have been talking about in the plenary data use and infrastructure. We are confronted with a situation early 2022 2020 before rollout. How do you train over 1500 participants. We kind of adopted a three tired approach, building capacity at the national level first, and then we brought districts to the original level and then the people we trained at the regional level cascaded that training to the health facilities. Now, from our own assessment, we went to for the health facilities and indeed majority of all the people we spoke with had benefited from a formal training. Some six said they did not train because the person was trained was either on leave or was transferred or for some reason wasn't at the health facility that day, which isn't a problem. And then, because we've trained the district health management teams a lot to help cascade this training to the health facilities we actually realizing that empowering the district health management teams is a very good thing because it's providing all the basic user support and on site mentorships to health facilities to an extent that the health facilities before they call the teams at the national level to address their concerns they first reach the district health management teams which are nearer to them. And being very supportive so that goes on to minimize cost and time and so on. In terms of that I use all the head districts that we spoke with, we actually got very rich qualitative data through the key informant interviews all the head districts that we spoke with, talked very highly about how the system the data notifications they receive help them as triggers to begin case investigations. Their work has been made very easy using the dashboards that we have built for them for generating reports meetings, not only for health purposes but maybe district wise they call the engagement meetings and so on. The infrastructure. Yes, Sierra Leone was lucky that after the baller there were some significant funds that went to West African countries to strengthen up health systems and Sierra Leone was lucky that every health facility. Got a tablet in that process and made it easier for us to kind of implement do the transformation from both aggregate and then the case based disease surveillance so in the 3039 health facilities that we found somebody to speak with 39 actively using the tablets, seven are not just because the tablet is faulty or is lost something like that. And somehow power isn't what power wasn't a very big issue and isn't a very big issue either those facilities were connected to the national grid. Some use generators as backup and I think through other investments other programs that they managed to install solar systems in most of the health facilities. Internet coverage is not that very good. It is just coincidental that about half of the health facilities went to have really stable and strong internet 18 reported week or no internet and those were reported no internet is a mix between no internet at all and then it's just because they have not received their monthly data for weekly reporting case based reporting. So the government through other collaborations on a monthly basis pushes data for internet in all these tablets. The issues with that some receive some don't receive but at least the mechanism is there for them to receive data for internet. So this is just a snapshot of the attributes majority of the people that we spoke with told us that ECB DS is easy to use for them. They easily to navigate. We are a little bit worried that health care workers not having received a lot of training which are computer based maybe having issues challenges and so on but that proved not to be the case. They form lots easily. We're not having challenges like taking forever to download Lord. They agreed that they learned it easily and confident using the system. Other attributes we evaluated but to contain them in the report I just picked a few. Now, I picked this. For some reason this wasn't a graph. My colors are different anyway. So we wanted to see the timeliness. This is the key element if our goal is to enable countries report timely. How is the system helping the countries to send immediate notification so that the national headquarters aware of what is happening in the remote areas. So we selected 146 notifiable medical conditions analyze them and we compared it with the health facility registers. And since they're using the system, the health facilities of men still maintain a system of logging every event that comes to the health facility. So, about 60% reported those events on the same day, which is good. Another seven 17% reported those events between two to seven days, not bad. Over 6076% of the cases that needed to be reported were actually reported within seven days, majority of which were reported in the first two days, which is fantastic. And of course, not everything was reported some for four cases, which is 30% were not yet reported at the time. When we visited some few cases were reported after one month those challenges happen. Then, in terms of completeness of report, completeness here is the records are the records in the system in the register are they reported using ECBDS. So our completeness rate was at 77%. However, if you remove January, you know issues people are coming back from Christmas and so on. The completeness rate actually increases to over 80%. So generally is consistent reporting using ECBDS. I want to rush through. I'm not going to go through this key challenges. This is very common internet power staff attrition. We still see disparities between health logs and so on about 20% of that. Now, what lessons did we learn. Now, ECBDS is playing a very important role as an integral part in the case business surveillance system. There's instant or timely alert notification, it has streamlined the workflows. The districts, everybody in the Iraqi of surveillance know what to do and is a medium for data sharing. The staff are very okay. They value they understand the use of electronic tools. That wasn't a problem. And the capacities that we have built at the districts are really empowered disease surveillance. And, importantly, empowering the districts to provide user support technical support at the much more sub national level is a very important thing it has elevated a lot of reliance on the national team and turn, turn around time. Other factors that affect the use of digital tools in disease surveillance may not actually be at the health facility neither individual is much more infrastructure or government policies. We have seen issues where they don't have a plan to maintain tablets or regularly supplying data for internet. And then another thing, as much as we build the information systems, they don't work in a vacuum. We realize that we need auxiliary systems in order to enhance ECBDS performance, we need a system for tracking tablets, for example, for tracking healthcare workers so that it informs government when they are transferring are you transferring a train one or an untrained one you need to replace with a train, but also if you have transferred a trained one, then you need to go to back to that health facility and train one. And lastly, the ticketing system. This may sound a little bit complicated, but it's very important to kind of keep track of the common issues that are coming from the health facilities. This way it enables you tailor your support to health facilities and lastly leveraging on other technological platforms like WhatsApp is playing a very big role. Health facilities staff are able to share their experiences seek for support from peer support from one another at times even the district people told us they take a snapshot of their issue send it through WhatsApp so they're able to understand what the issue is and respond appropriately. And I think that's it so we worked with the Minister of Health that great people. Minister of Health Sierra Leone. Our on the ground capacity building IP of net doing a great job there and then if is South Africa is providing some kind of high level technical assistance to the in country team and my colleagues at CDC both in the country office and then at at what does so thank you so much. Thank you very much George. So continuing line with the event based surveillance system I would like to call here. For presenting, representation on a flexible and robust electronic even based variance assistant for reporting monitoring events in Tanzania. Thank you very much. Okay. Okay. Hi, my name is a Jeb. I'm system developer. So, unfortunately, I need to apologize I may not be able to be a little bit of surveillance, but I'm on behalf of my colleague I'm presenting the work that we have been doing on improving electronic ideas are in Tanzania mainland, and that is event based surveillance. So, in summary. Oh, yeah. So, basically from the Tanzania mainland, we already had started or had developed the electronic based surveillance that by at the time was based on a indicator based surveillance collecting immediate and weekly data, at least to support a response. But lately, we started into now moving to event based surveillance. So as a, I just a component, the event based surveillance was aimed at, oh, at ensuring reporting of unusual alerts or rumors that are happening in the community, and that to contribute towards early warning and response. And in mainland Tanzania, most of the alert have been noticed into coming from community health facility, for example, unusual symptoms or unusual results also points of entry, but also from other sources around media scanning call centers around so Tanzania mainland has one one nine nine call center where public sense different messages around. So as just in a little bit of a background which I say earlier is that until recently we had no any of the event based surveillance component, we have a system but we didn't have that and most of the rumors were manually collected, and hence was really not effective for our but in now 2021 moh Tanzania of course in collaboration with the DHS to team and MDH with the funding support from CDC Tanzania we have to acknowledge them also one of the representative is here, we started to implement the event based surveillance. So also to comply with the third edition guideline that we we actually started to use by that 2021 so basically in summary. In mainland, this is how the, the component, this is just a component to within a desert works so as I said, a lot can come from the community we use community health care workers to report different alerts, and if they are reporting to the facility nearby facility within the catchment and the facility are the ones that perform sort of triaging and verify whether those are lots are okay and of course they notify the higher level, but also the community the alerts also can come within the district itself, or the region, or the national or as I said earlier, also from border health, but also from the call center. Now from the call center there is another system in mainland that collects different messages and calls from public. So we have been in, we have integrated the event based surveillance component to with the call center. But again, the verified alerts are then been linked to all compliments in the database surveillance, and then the idea Sarah also handles the entire outbreak management that also includes contact tracing, etc. Yes, moving on what we have done for EBS is actually, we have integrated it with the call center so there's that message that the public can send if there's an issue through SMS and that message is sent to EBS component, but also for community health care worker or health facility workers we use the Android application that is a comprised of indicator based surveillance event based surveillance but also some of malaria case based surveillance in one application, and then they can also use that to report, or within the district or region or national. There's also a DHS to custom app that is a web based that can be used to report and handle all that verification and investigation aspect for for EBS. As just quickly, I think this is known to most of you, probably new to me but these are key aspect for EBS that we are doing in the mainland so there's a detection that comes from all those area, the striaging actually ensuring we are filtering all duplicate or hoax a lot in order to remain with the ones that matters. And also there's verification now to verify whether the alerts that have been filtered are really valid this involve the district team to communicate with the facility or whoever that has reported to ensure if the alerts are valid and also they now performing investigation which actually now that is where it provides linkage linkage to indicator based surveillance cases. So for achievement at the moment. This has already been rolled out in six region and the first pilot was conducted in Gorongoro. I guess we wanted to see some, some lions. So, okay, okay in the crater we also welcome you guys in the crater. So we made the first pilot in Gorongoro, where most of the alert were around and most, most of them were really related to animal. So that's why we started there and more like is more than 300 users were trained and at least some more like 5000 alerts have been reported during this initial roll out so you can see our one of our CHW from Gorongoro if you see this close the you know exactly where this come from being taught how to use the Android application. My presentation is very short so in conclusion, we see that EBS as a potential for for ensuring the timeliness in the outbreak detection and the dissemination. Also, we are seeing that it has potential to support cross sector data sharing as you know, we are collecting the alerts the alerts can be of animal relation or environmental relation so there is a potential for using this EBS to more likely send notification or receive notification from other One Health initiatives that are around. As I said, most of the alerts in Gorongoro are based on animal related so that this probably could be the case. So as for future work I think it's the same as I was saying as a potential. Also this EBS or the entire IDESARA can sort of be integrated with the One Health initiatives around. Also, we are also looking into performing a national wide roll out because we rolled it out in only six regions, but also we saw a little bit of a gap in the data use so also one of the future work is now to strengthen the capacity on reporting and using the data. Just to highlight in general, the EBS is just as a component as I said earlier within the entire robust and flexible IDESARA ecosystem that now covers the indicator based surveillance report the cases that have been reported from the facility together with the event based surveillance and now we are now working finalizing the entire outbreak management component within the IDESARA so from the cases to now the potential outbreaks to handling of events, contact tracing, etc all in one single ecosystem that uses DHS to. I have to acknowledge and my colleagues from DHS to Dism Team also from the Minister of Health MDH but also from CDC Tanzania one of our colleagues is here Mr. Zaharani so thank you very much so unlikely we have some technical issue with the last presenters will not be able to join so let's see the bright part that we have more time for any Q&A so if there is any questions maybe I will invite the presenters to be here on stage with me so they can answer to the different questions as well online and we can check if there are any questions. Don't be shy. Okay, we already have two questions that's fantastic. Okay, so any questions. So thanks for the presentation my question is on the last presentation on event based surveillance because it's my area with WHO so so you mentioned most of the rumors that you receive at least for the time being is animal related. So once you collect that data from the Android phone is there a way currently where you can relay it to the to the next level, because you said the triaging and verification is done by the community health worker. So most of our community health workers don't have training specifically for animal health related adults. So I just want to know how you relay the the alerts, which are considered related to animal health goes to the next level. Okay, thank you. I'll try to answer that because I'm developer. Okay, so basically from, from the Ngorongoro pilot, most of the human related alerts but mostly come from animal diseases. So at the moment we, we do not have expertise really on animal surveillance. This is also only health surveillance. What I put in there is actually this has a potential for those alert to now be to now be transferred to animal surveillance aspects so they can actually fall upon that battle on the triaging verification and etc. In my presentation, the triaging is not done by the community health care workers. The community health care workers their purpose is only reporting the triaging are being done within the health facility that whose the catchment for those health care workers. So how it is done now is actually the alert is being reported health facility are trying to try to verify and investigate and then they are notified at higher levels. But I think there are some initiatives to now link that to animal surveillance. So the other aspect of responding to animal can come come up. I hope I answer your question. All right. So maybe to add to that last because we had a presentation on mind about emergency in which Uganda show the alert system in which the triage was done not a health facility level for example at district level. So yeah, with protocols and algorithm. So yeah, just to add on this in case you are interested are all the presentation will be will be available. Thank you. So the next question. Okay. Thank you very much. My question goes to judge the evaluation that you did in Sierra Leone for CBS. If a country wanted to do a similar evaluation, are these tools available. Can they have access to the tools and how would we go about that. The reason I'm asking is because Uganda has done a pilot of CBS, but we're at a stage where they want to scale up but everybody's advising that we need to do an evaluation of the pilot before we scale up. Thank you. So. Yeah, we can take a second question. Thank you very much for the presentations. My question goes to Sarah Rewan on the timeliness of reporting. I saw that it's still low. The proportions are very low on timely reporting. And I was like what was the reason behind the low reporting rate, a timely reporting rate, and what is it that you have recommended to improve your work so that we have the people to report timely. Thank you. Thank you so much for the questions. The first one was about the availability of tools. I know about the ICBDS implementation in Uganda was part of it. I have a very good history of that. And the tools that we use the concept was developed out of CDC frameworks one framework for evaluating program evaluation, and then the other one for evaluating information systems for disease response. So we developed our tools from scratch, but based on those frameworks and borrowed ideas from other subject matter expertise and other countries as well. So we actually shared this with one of the countries in Eastern Asia. And I think we are in the process of developing a much more standardized data collection tool for disease. And on top of that, there are also lessons that we have learned during the, the evaluation itself, which will make us also improve on the tools. So I think me working with Uganda as well. I think it should be easily shareable with you. And there's no problem with that so we have something to share. Thank you. The second question was the reasons for law completeness. Did you use local. Okay, okay, let me explain that. So that was on timeliness. How quickly were they reporting the medical conditions. About 60% on the same day are 17% within one week. Those are two to seven days on the second day to seven, which is still not so bad. And then only 3% were not yet reported at the time it conducted this evaluation. And some part the balance were reported within a month it varied. So the reasons as it as you saw even answering the law or completeness rate. There was a factor in January people on leave that trying to regain the momentum the rhythm after Christmas. If you remove January which was kind of an outlier, all these rates go up. Yeah, as I demonstrated on the completeness, it's about 77%. But if you remove January that you have a completeness rate of over 80%, which is kind of average African wide average review some manuscripts and so on. Every country is grappling with completeness rate of between 80 to a good case canary about 95%. So it's not really law. It's within normal. And on the notification, you know, of medical conditions for us we we we wanted them to be reporting within 24 hours. Yes. Yeah, it depends on what is the problem of where. Yes. So now if they take seven days for me, I think it's it's on the lower side. And if they go beyond seven days, it's a, I feel like it's not good enough. So we expected the best. Thank you. I do think as I explained to you about the January factor. I do think because probably our disaggregation was two to seven days if we split it up to within 24 hours. I think I will be able to present it better that way. So I think, yes, it's still not 100%. But it's also not bad. Thank you for all the presentations and it's great that we have multiple sessions for like surveillance and, you know, public health emergencies and everything. So my question would be to bill talking about the one health aspect. You know, we've talked about sharing data across sectors. So you presented sounds great. I'm just wondering like what does that look like within a country. You know, on the ground in the level where these actions are going to happen. Does that mean it happens at the national level and data. The systems are integrated. Does that mean there's information sharing. Does the information go to like a data warehouse or health information exchange and then people are given access. Does that mean animal sector has access to the human sector. And then the HIs to instance where the data are and they can look at or, you know, I'm kind of and then what like how is the information shared in reality. How does it happen. And then at what levels does that happen. Does it only national level and then stuff has to trickle down, or can it happen at district level or so can you describe kind of like what it would look like in in reality or on the ground. Thanks. That we've been grappling with recently, especially when this last workshop with all agencies involved in this, but the mechanism that we have currently developed at that workshop and that we're working on now that unidirectional professional mechanism would be within either a, a initial user of a community level user of DHS to or EMA I which is the event based reporting tool that reports up to emphasize animal sector. It would just be a checkbox in their current reporting documents. With that checkbox it would be something along the lines of, is this a zoonotic disease that needs to be reported to animal health sector or human health sector whichever is the opposing sector in that. And it would be instantaneous so it would be a notification, a one time notification to that sector with the information that is in that document, or whatever information is requested and that's something that's modifiable by countries with that mechanism. But if that makes sense. And the bidirectional notification would be different in that it would be something that would be a live kind of module for at the country level for both sectors to access. That's a lot more complicated, especially with data use restrictions sharing restrictions things like that within a country it's going to be different from country to country but the goal of that would be to have something where if there is a suspected one notifications out, and then to that one module and then if there's a test result of that same suspected case that confirms or denies right that wouldn't wouldn't necessarily be multiple notifications across the sector and different times but it would be one platform that can be continuously accessed by by the opposing sector and both animal health and human health officers at the community level would be able to access that that would be ideal. That's a lot more complicated and that's something that we're working towards but right now that unidirectional one time event based notification across sectors is something that is the lowest hanging fruit in this instance, so to speak. And something that that is a mechanism that has been created and will be piloted for for feedback and hopefully using that to to work towards that that second goal. Thanks for your question. Yeah. I think it's a really good question and also why CDC is helping us to support some pilots but we also did some landscaping. I think it's a bit around the the DHS two side that even if you saw in these other event based scenarios. It has to fit into that country structure so who is trained and who should receive because there's a very real risk that you are inundated you're just inundated with information and then you can't act on it. So within DHIS to the idea is that then that needs to go to the designated focal point but first there also needs to be that process of defining what actually constitutes an alert that it should actually go to the other sector. And I think, you know where a lot of countries are they have stronger DHIS to our electronic indicator based surveillance systems. So I think the event based surveillance systems as as presented in Tanzania are just now starting to really get up off the grounds in a digital way. So I think at least from the DHIS to platform perspective we are seeing this work in a way that it can be just sharing and it can actually send data to different systems and we have also seen in some architectures such as and Burkina Faso. So there's flagship initiative of USAID so a lot of like funds went into that system where they actually had three DHIS to actually do that for. So they have Ministry of Agriculture Ministry of Animal and Livestock Ministry of Environment Ministry of Health, and then they all kind of shared their data to an overarching one. But that was at an aggregated level so I think there's many architectures that we want to continue looking at to see, at least on my DHIS to hat on how can we support them in multiple ways. I'm not heading on to that question, but to my sister who asked that question. One of the reasons that I thought I should tell you and forgot was for cases that were reported late. Apart from the January being an outlier where that at that time when the case came to the health facility they were lacking data for internet. But that doesn't mean the case never found its way to be reported. In that situation they were using make a phone call to the district health official to come and investigate the case. But this timeliness of reporting are best of when they reported on the system, but if they didn't have data for internet at that particular moment, they would call the district officials health officials to come and investigate the case. And we still have one minutes for one last question. It's really short, short question. Yeah. Thank you. Thank you very much. I am to make up from West African health organization. And my question are going to the presenter of from CDC because I was happy to see the tools, the proposition of that one health surveillance tool you are proposing to do. Since 2017 after Ebola crisis in West Africa, we have been trying to put develop some kind of the integrated epidemiological surveillance between human and animal health, but we have been using DHS to under the human surveillance to incorporate if I can say that the animal health trying to respect also what they have been doing with the animal health organization organization, not to avoid the work, but seeing this integrated work we are trying to do. I think it's very good. I'm sorry to confirm me. If the workshop coming on next last week in West Africa will be based on these tools or not, because I know so the CDC are organizing with the echo was on last week of June, one workshop on the one health tools for the for the surveillance. I just want to confirm if it is the same tools or if other initiative also are going parallel in in CDC. I think I got that. Parallel initiatives would be the short answer to that. Parallel initiatives would be the short answer to that. Parallel initiatives like so so that isn't necessarily like no one from our team, I don't believe is is going there with these same tools at that workshop that you're talking about later in June. I think these are parallel initiatives that are taking place. Does that answer your question. Yeah, yeah. Thank you very much for for the participation. Thank you very much for our speakers. And yeah, in case there are any other questions you can tackle them. Thank you very much.