Social Media Chatbots (SMC)

In order to effectively respond to disease outbreaks and contain epidemics, timely detection and containment of cases are crucial, yet routine disease surveillance systems often lack efficient and scalable reporting tools. The ongoing COVID-19 pandemic has laid bare obvious gaps in disease surveillance, particularly in the private sector, which is the often the first point of care for people seeking fever treatment. For example, an estimated 75% of people in Uganda and 90% in Uganda’s capital of Kampala first seek care for fever in private facilities, confirming the need to further invest in surveillance within this sector. This is particularly the case in malaria, Rubella elimination settings, where standard protocols require every case to be reported within 24 hours to the local response teams and national health authorities.

Our Solution is social media Chatbots (SMC) that we have developed and successfully tested a novel approach to reporting malaria, Covid-19, Rubella cases and other disease surveillance data: chatbots built on popular social media platforms such as Facebook Messenger and WhatsApp. A chatbot is a service, powered by automated dialogue rules and sometimes artificial intelligence, that you interact with via a messaging interface.  This simple yet highly innovative approach allows front-line health workers, such as pharmacists and doctors, to use the communication platform that they already use on a daily basis, on their own device, in their own language, and without needing any separate accounts, passwords, or applications. Once connected to the social media account dedicated to the chatbot, the provider starts a conversation through the platform’s messaging app, such as Facebook Messenger and/or WhatsApp, and is prompted to answer a series of questions with automated response options, built-in skip patterns, and quality checks.

In order to effectively respond to disease outbreaks and contain epidemics, timely detection and containment of cases are crucial, yet routine disease surveillance systems often lack efficient and scalable reporting tools. The ongoing COVID-19 pandemic has laid bare obvious gaps in disease surveillance, particularly in the private sector, which is the often the first point of care for people seeking fever treatment. For example, an estimated 75% of people in Uganda and 90% in Uganda’s capital of Kampala first seek care for fever in private facilities, confirming the need to further invest in surveillance within this sector. This is particularly the case in malaria, Rubella elimination settings, where standard protocols require every case to be reported within 24 hours to the local response teams and national health authorities.

Digital reporting solutions aimed at replacing traditional paper-based reporting mechanisms have been introduced in Uganda just like in many countries across Africa and globally, but these are generally dependent on substantial investments in training of end-users and in equipment procurement. Even when financial and human resources are available, many mobile data collection solutions present challenges with software maintenance, device compatibility, and user management, and are thus often difficult to deploy at scale in a sustainable manner.  

To overcome the limitations stated in the Problem section above, we have developed and successfully tested a novel approach to reporting malaria, Covid-19, Rubella cases and other disease surveillance data: chatbots built on popular social media platforms such as Facebook and WhatsApp.  

A chatbot is a service, powered by automated dialogue rules and sometimes artificial intelligence, that you interact with via a messaging interface.  

This simple yet highly innovative approach allows front-line health workers, such as pharmacists and doctors, to use the communication platform that they already use on a daily basis, on their own device, in their own language, and without needing any separate accounts, passwords, or applications. Once connected to the social media account dedicated to the chatbot, the provider starts a conversation through the platform’s messaging app, such as Facebook Messenger and/or WhatsApp, and is prompted to answer a series of questions with automated response options, built-in skip patterns, and quality checks.

Reporting a positive malaria and Rubella case or a suspected COVID-19 case instantly becomes easy, fast, and secure, with minimal training and no extra cost. Just open up Facebook/WhatsApp on your phone, type a keyword in the Messenger/WhatsApp, and go with the flow: the chatbot will guide you through a series of questions such as the RDT test results, the age and gender of the patient, the village of residence, treatment provided, and any other relevant data points.

How Do We Use the Bots?

We currently use two platforms for malaria, Rubella, and Covid-19 reporting: Facebook Messenger & WhatsApp Messenger.

In Uganda-Kampala, we are now refining our chatbot which will be using Facebook Messenger and WhatsApp Messenger to report RDT-confirmed malaria, Rubella and Covid-19 cases. Our target is that as of September 2021, we anticipate to register private sector providers (pharmacies, clinics, government health centers) to use the chatbot for malaria, Rubella and Covid-19 case reporting, including essential data points such as treatment provided, referral issued, village of residence, and there will be basic patient information. Case reports are automatically uploaded in our DHIS2 database, where previously all data were reported on paper and entered centrally by the M&E team. Our disease surveillance data are sent every day/week to the Health Management Information System, which also runs on the DHIS2 software, via a custom app that automatically pushes data to the national Health Management Information Systems (HMIS). This ensures that the national malaria program at the Ministry of Health has access to all private sector malaria, Rubella, and Covid-19 case reports.

How Does It Work?

The client-side messaging platform is connected to DHIS2 in a way that data reported to the bot are automatically pushed as events to a cloud-hosted DHIS2 instance. The chatbot flow is defined using a configuration file and each of the questions is mapped to the corresponding data element in a DHIS2 program or dataset, using a. json dictionary. The bot itself is a web service in node.js runtime environment, which can be hosted either on-premise within the instance or in a cloud computing environment such as Microsoft Azure or Amazon Web Services. The chatbot uses the bot framework SDK that can publish the same workflow in other messaging platforms. A library that defines the chatbot’s workflow logic enables the extraction and transformation to structured data pushed to DHIS2 through API calls. Incoming data are instantly sent to DHIS2 but are also stored in a file system with logs hosted in a separate cloud middleware which can be accessed by local system administrators. The .json files include error messages and submitted payloads according to status (successful submissions and failures). This prevents data loss in the event of connectivity issues or conflicts coming from the DHIS2 instance, making it possible for local system administrators to navigate all issues and re-submit relevant data to the bot.  

The connection between the messaging platform and DHIS2 is enabled by mapping the provider’s social media account with the corresponding DHIS2 organization unit, i.e. the pharmacy or clinic. Data collected through the chatbot can be sent to multiple programs and even simultaneously to different DHIS2 instances, making it easy to share the same records with the Ministry of Health and implementing partners.

The chatbot engine that is used to define the workflow with response options, skip patterns, and data validation strategies can be expanded for more advanced functionality, such as fuzzy matching based on extensive lookup tables. This may be useful, for example, when needing to report the village of residence in a structured manner: users can enter the village name as free text and will be asked to validate their choice against a number of possible matches based on a predefined match score. Email or SMS notifications may be sent to supervisors or other field staff when data submissions trigger a specific alert threshold, e.g. when a positive malaria, Rubella or Covid-19 case is reported.  

Disease surveillance systems in African countries and globally often lack efficient and scalable digital reporting tools to effectively respond to disease outbreaks and contain epidemics. The COVID-19 pandemic has revealed gaps in disease surveillance particularly in the private sector, which is often the first point of care for people seeking fever treatment.

Test. Treat. Track. These three words guide efforts towards disease elimination—as well as combating other deadly diseases. In many countries, that last step, tracking, is still facilitated using traditional paper-based reporting methods or complicated digital reporting tools that makes it impossible to capture and share critical data rapidly, identify where the disease is occurring, and ultimately curb its spread. Even individuals in any given community lack a reliable platform for accurate health information given the many sources of false information platforms.

Chatbots, Faster & Easier 

In collaboration with partners such as the LivingStone International University, we have tested and currently refining our chatbots built on popular social media platforms, such as Facebook and WhatsApp, to support reporting malaria, Rubella, and Covid-19 cases and other disease surveillance data. This tackles the issue of delays from paper–based reporting and decreases the barriers to entry presented by complicated mobile reporting tools. The chatbots allow front-line health workers from pharmacists to doctors to leverage a social media platform they already use on their own mobile devices, in their local language.  

Our Elimination of Disease Outbreaks through Surveillance project works with private sector providers to increase access to quality disease case management. The project facilitates the reporting of disease case data from the private sector into national surveillance systems.

This easy-to-use messaging service also has the potential to reach 2+ billion people and enables government Ministries of Health and their health partners to get information directly into the hands of the people that need it.

From government leaders to health workers and family and friends, this messaging service has capacity to provide the latest news and information on disease outbreaks such as Malaria, Rubella, Coronavirus including details on symptoms and how people can protect themselves and others. It also provides the latest situation reports and numbers in real-time to help government decision-makers protect the health of their populations.

The service can be accessed by a link that opens a conversation in Facebook Messenger and WhatsApp. Users can simply type “hi”, hello, to activate the conversation, prompting a menu of options that can help answer their questions about Malaria, Rubella, and/or COVID-19.  

Test. Treat. Track. These three words guide efforts towards disease elimination—as well as combatting other deadly diseases. In many countries, that last step, tracking, is still facilitated using traditional paper-based reporting methods or complicated digital reporting tools that makes it impossible to capture and share critical data rapidly, identify where the disease is occurring, and ultimately curb its spread. Even individuals in any given community lack a reliable platform for accurate health information given the many sources of false information platforms. In collaboration with partners such as the LivingStone International University, we have tested and currently refining our chatbots built on popular social media platforms, such as Facebook and WhatsApp, to support reporting malaria, Rubella, and Covid-19 cases and other disease surveillance data. This tackles the issue of delays from paper–based reporting and decreases the barriers to entry presented by complicated mobile reporting tools. The chatbots allow front-line health workers from pharmacists to doctors to leverage a social media platform they already use on their own mobile devices, in their local language.    

Our Elimination of Disease Outbreaks through Surveillance project works with private sector providers to increase access to quality disease case management. The project facilitates the reporting of disease case data from the private sector into national surveillance systems.

This easy-to-use messaging service also has the potential to reach 2+ billion people and enables government Ministries of Health and their health partners to get information directly into the hands of the people that need it and data collected through all of these chatbots can be sent to multiple DHIS2 instances, making it easy to share the same records with Ministries of Health and implementing partners. 

From government leaders to health workers and family and friends, this messaging service has capacity to provide the latest news and information on disease outbreaks such as Malaria, Rubella, Coronavirus including details on symptoms and how people can protect themselves and others. It also provides the latest situation reports and numbers in real-time to help government decision-makers protect the health of their populations.  

As of November 2020, 100 private sector providers (60 pharmacies and 40 clinics) had been trained on using the reporting mechanism. Since the launch of our prototype in early September 2020, 100 outlets reported 500 customers seeking treatment for fever and/or respiratory illness.

Data collected through all of these chatbots can be sent to multiple DHIS2 instances, making it easy to share the same records with Ministries of Health and implementing partners.  While still early in the process, initial feedback from end-users indicates that the use of social media chatbots for digital reporting is feasible and offers several advantages.   

This year, through consultation with our partners we have decided to build upon our proof-of-concept to ensure that the platform is officially launched by July 2021. 

KEY LESSONS

Some early lessons learned while building and deploying the chatbot include: 

• Users like a familiar interface, local language and automated flow, which all make it easier to report data. This is particularly relevant when providers only need to report cases only occasionally. 
• The bots did not yet remove the need for in-person case notification to local health authorities but can improve the timeliness and accuracy of case surveillance overall. 
• End-users want options. There’s no “one size fits all” solution, which makes it necessary to provide them with a range of reporting tools, both digital and paper, to accommodate for all preferences. 
• While digital reporting makes disease surveillance more timely and easier, there are still complexities inherent in supporting a surveillance system. For example, large networks of providers still require active user management by central monitoring and evaluation (M&E) teams. 
• Training on the use of the chatbots is easy and can be done over the phone (e.g. using WhatsApp), in person by field staff or during meetings with providers. 

SUCCESS METIRCS

• -Number of subscribers, and cases reported on the platform
• The ability of the platform to ease the work of healthcare providers in being able to easily detect, monitor and respond to any disease outbreaks.
• Ability of the platform to inform and educate the general public with the right information that may lead to behavior change and help them stay vigilant and safe against diseases.
• The number of partners, grants, awards and sponsorships generated through this project could also be a critical metric for impact measurement.

On balance, our experience shows that these social media chatbots connected to powerful information management systems such as DHIS2 have the potential to change the way that we collect data. They provide health service providers with additional options to rapidly report disease surveillance data to the government, in a user-friendly and low-cost manner.

The chatbots connected to DHIS2 are highly flexible and customizable for each country context and have the potential to be applied to other simple mobile data collection needs. Besides case reporting, this also includes aggregate reporting of activity reports and stock levels:

Chatbots, in contrast to newspapers and online information sources, can often hear and respond in natural language, improving access for people who cannot read or have difficulty using the internet. They can be available any time of the day to answer questions with up-to-date information, and unlike human experts, can concurrently speak with millions of people at the same time in local languages and dialects.

The primary objective behind these chatbots is to leverage messaging platforms being used to spread most of the misinformation on the disease and increase the share of dependable information, which is available quickly and easily. Facebook and WhatsApp each has over 2 billion users globally, making it the perfect information delivery mechanism in this case.

We always leverage opportunities to use technological solutions to enhance the delivery of healthcare services by healthcare actors and governments. Technology has been critical for strengthening our public health response to diverse disease outbreaks before. This interactive chatbot is a welcome initiative that will be integrated into existing technology deployed for communication at the National Health Management Systems. The solution also uses a probabilistic reasoning engine, combined with a deep medical knowledge base covering thousands of conditions, symptoms and findings. It takes all of the patient’s information into consideration. In the near future, we will create a specialized version of our solution for CHWs, by setting up a toolbox, which includes lab tests to expand diagnostic capabilities, and to integrate the respective treatment recommendation to enable prompt and quality care.

The new service, which is free to use, is being designed to answer questions from the public about any disease outbreaks such as Coronavirus, and to give prompt, reliable and official information 24 hours a day. It will help us to combat rumors and provide the public with reliable and credible information and practical advice to protect them from the virus.

This chatbot offers a wealth of information to users - including practical advice on how to protect yourself from coronavirus, answers to frequently asked questions, directions for verifying the facts and stopping rumors, practical advice for travelers, as well as any other queries that users want to raise. Several doctors and communicators have been made available to respond directly to any queries.

Chatbots provide instant conversational responses and make connecting simple for patients. And when implemented properly, they can help care providers to surpass patient expectations and improve patient outcomes.

Our chatbot solution, which is powered by an AI engine and driven by natural-language processing, enables real-time, patient-centered collaboration through text messaging. The tool helps patients with everything from finding a doctor and scheduling appointments to outpatient monitoring and much more.

By taking an all-in-one communication approach, our solution encourages patients to proactively share their health information, which, in turn, enables care providers to cut costs, improve care quality and boost patient satisfaction.  

Current number = 0

In one year = 100,000 people

In five years = 20+ million people

Our impact measurements are based on our ability to meet and effectively to the user needs and feedback we got during the first user-testing of the product as seen below.

• Users reported a strong preference for the new reporting mechanism compared to “traditional” mobile reporting tools such as DHIS2-connected data collection apps, especially as the chatbot works through a familiar messaging channel on their own devices.

• The automated prompts in local language make it easy to report data.

• This is particularly relevant in settings where reporting frequency is low, as users don’t need to re-member how to navigate a complex digital form

• Training can be done over the phone (e.g., using WhatsApp) or in person by field staff or during meetings with providers.

• Digital reporting mechanisms should include a range of options that are context-appropriate and that allow for providers to use a platform that most easily facilitates timely and complete reporting. While the Facebook and WhatsApp bots are accepted, it is important to note that there is no “one size fits all” solution and that options should be tailored to accommodate other preferences, which may include mobile data collection apps, SMS, or even sending pictures of manually completed paper forms – something that is often forgotten when designing digital solutions.

• The bots do not yet remove the need for in-person case notification to the local health authorities who are responsible for case investigations, but they enable easy and fast reporting. Data are thus more rapidly available and open up the potential to improving the detection and containment of epidemics by central and local surveillance and response teams.

• Large networks of providers still require active user account management by central teams and DHIS2 system administrators, who need to ensure that new users get swiftly enrolled and that the social media user IDs are mapped against the DHIS2 organization units.

Once we are able to fully meet the above bullet points/concerns as raised by our users, then we shall effectively measure our success.

Finally, impact is and shall also be measured based on number of subscribers, engagements, awards, grants, partners both from the private and public sectors, feedback from users etc.  

The team is composed of 5 members on full-time support and 2 part-time.

Joseph Mulabbi is the team lead with expertise in Communication and Media Technology, a degree he attained at LivingStone International University.

George Maina is the CSO with a masters from Kumi University as well as experience in software engineering, design and development, and is also an entrepreneur.

Emmanuel Wegoye has over 10 years experience in healthcare, with masters in medicine, and masters in Neuroscience and a Diploma in Physiology. A medical researcher turned serial entrepreneur.

Other members include Derick with a bachelors in ICT-an expert in web design, software mobile applications, AI and ML.

Mukibi Robert has a master’s in medicine from Makerere University, 10 years in the pharmaceuticals and medical field expert.  

Joseph Mulabbi, Managing Director, ArqLite Green. Experienced Social Entrepreneur with a proven track record of leading an international, award-winning social enterprise, building strong partnerships with NGOs, foundations and government.

George Maina, CTO. George is an experienced ICT consultant in Uganda. With a masters in computer science, he has worked previously with some of the leading healthcare NGOs in Uganda managing their IT platforms. He designed an app for Ministry of Health and is currently working on information center data based for the Ministry of Agriculture.

Emmanuel Wegoye is a Neural Surgeon and is among Uganda's 5 neural surgeons in the entire country. He brings his medical expertise and healthcare expertise to cowork with the team to develop a robust platform that is meant to effectively aid the healthcare services in Uganda.

Other members include Derick with a bachelors in ICT-an expert in web design, software mobile applications, AI and ML.

Mukibi Robert has a master’s in medicine from Makerere University, 10 years in the pharmaceuticals and medical field expert.

Evelyn Nengoni has a bachelors in degree in nursing and midwifery from Makerere University, she has over 10 years experience in the healthcare sector and is also a healthcare consultant.

Mary Amuge is a business development fanatic with a masters degree in international business from Amit/Makerere University. She has experience in sales and marketing, research and social work. 

We have zero tolerance for racism and any form of disrespect and/or discrimination against gender, sex orientation, race, ethnic background etc. We provide a mutual and an equal platform for all and we provide equal opportunities for all who qualify to compete for job openings at our organization and we show no partiality whatsoever. This is partly exhibited in the gender balance in our employees both from the board to management and downwards. We embrace all our differences and work together to achieve a common goal and we celebrate every achievement regardless of who, where, what, and how.

We believe in the power of our technology to create long-lasting impact. Establishing partnerships and developing a network of strong supporters is crucial to achieving our mission. Becoming an MIT Solver would tremendously advance our work, allowing us to connect with relevant organizations in global health. In addition, mentoring and guidance by the respective experts within the MIT Solve network, would be also of great support, since we are newly taking up our operations with the ArqLite Green. Through MIT Solve we could increase our visibility and raise more awareness for our work within a broader audience. We are also applying to this challenge for the chance to win equity-free funding which, if gotten, will accelerate our expansion timeline. We are also applying for the opportunity to be part of MIT Solver’s brilliant community committed to social impact. We believe that MIT Solver can give us tactics on how best to hold on to our social impact goals while pursuing our business goals. Being a winner will also give us access to some of the most intelligent minds in the world who can provide feedback on our technology solutions and connect us to partnerships which can help scale our business.  We also welcome the opportunity to exchange ideas and lessons learned with colleagues and peers who have been experimenting with new technology in low resource environments. We value working in partnership and the mutual growing and learning that comes with collaboration

We seek partners to help us in crafting our business model as well as advise and mentorship on the right technology, software and how best we can be able to market and scale our solution in both local and international markets.

• Private and public companies and NGO partnerships to help us develop prototypes of the platform tool adapted for use among different locations and types of semi-skilled health workers
• Partnerships that can help us introduce an effective referral system across stakeholders within primary healthcare
• Form partnerships with relevant stakeholders, such as local governments and the private sector, to implement our tools on the ground in sub-Saharan Africa.

• Strategic Development: We are actively seeking support to improvise the business development strategies.
• Technological Support: We are looking for synergies that help us go well with the use of machine learning and AI to develop our tool while improving our interface for better user experience and engagement. 
• Human Resource management – We are looking for a network of healthcare researchers, doctors and specialists across the globe that will be interested to utilize our solution to continue their medical practice but also as consultants and mentors.
• Scale Up – We aspire to build consortium at National and international level to build synergies for sustainable development. We are looking for partners who can match their resources with ours to eventually scale our solution, gain new active users and maximize utilization of our services to a greater number of beneficiaries that may be beyond our reach at the moment.

We aim to develop partnerships with MIT to connect with mentors, experts and advisors to build and expand our AI tool thereby gaining consumer insights, integrating predictive algorithms and supporting our research processes.

We also aspire to expand our partnerships with mobile operators across Africa such as MTN, Airter and Mobilink to broaden our reach by gaining low-cost customer acquisition and market insights, access to mass communication channels including API access for SMS and IVR, access to mass payment channels for easy payment collection processes, access to retail customer touchpoints, access to technical and commercial support and gain visibility and credibility 

In addition, we aspire to build partnerships with tech giants such as Google, Apple, Microsoft, Amazon and Facebook to access cloud computing, Telemonitoring through wearables, customer data acquisition and artificial intelligence resources,

We are also actively seeking large organizations and corporations such as Philip, GE healthcare, Nestle and Samsung to adapt our solution either for their employees directly or utilize it for their clients as a white label solution. This will enable us to expand our reach and customer base.

Other partnership goals include;

• Peer-to-Peer Networking
• Organizational Mentorship
• Impact Measurement Validation and Support
• Media Visibility and Exposure
• Grant Funding
• Develop prototypes of the chatbot tool adapted for use among different types of semi-skilled health workers
• Introduce an effective referral system across stakeholders within primary healthcare
• Form partnerships with relevant stakeholders, such as local governments and the private sector, to implement chatbot tools on the ground in sub-Saharan Africa and South Asia

Globally, more than 4 billion people lack access to basic healthcare services. This urgent situation is primarily due to financial and geographical barriers, as well as a global shortage of healthcare workers – particularly in rural areas. This alarming situation is mainly attributed to major financial and geographical barriers. In both developed and developing countries, healthcare resources are mostly concentrated in urban areas, resulting in limited access to appropriate care. The demand for affordable, effective and quality health services is high, but cannot be met by the traditional, costly model of delivering healthcare solely through doctors and nurses, which are most often not accessible in rural settings. The massive shortage of more than 7 million health workers, urges us to think about new solutions that can be deployed quicker. Rising smartphone penetration in both developed and LMIC, provides the unique opportunity for mobile AI health applications to facilitate new access to healthcare for vulnerable communities and fundamentally transform health care delivery.

Robert Wood Johnson Foundation Prize, we will be able to advance our effective solution that will help save lives globally because it is our mission to overcome these challenges and bring life-saving, high quality care and decision support to millions. We can achieve this by empowering community health workers and local drug shop dispensaries with Artificial Intelligence e (AI) via mobile technology as well as help individuals to understand and manage their health through a personalized health assessment, while providing earlier health information and decision support to doctors. With an approachable, user-friendly interface, anyone can enter their presenting complaints. With the warm, friendly tone of a doctor, by guiding users through a series of questions related to their symptoms and provides them with a list of conditions that they are most likely to have.

By partnering with relevant health worker organizations in LMIC, we strive to create an adapted version of our platform for community health workers and drug shop dispensaries to improve decision-making, as well as introduce an effective referral system across stakeholders within primary healthcare, benefitting millions of people. 

According to the mHealth App Economics 2017 study, 61% of decision makers and experts of digital health see Artificial Intelligence as the most disruptive technology shaping the digital health sector. And although AI is still in infancy its capability to offer significant digital health personalized value with the right actionable insights by empowering a new generation of personal health companions and medical chatbots, telemedicine and the prominent IBM Watson for Oncology notably improves the quality of people’s lives and transforms the healthcare sphere.

Digital solutions powered by Artificial Intelligence’s data driven nature and its ability to process unthinkable amount of data, identify the relevant insights to be matched with specific patient case and records, leads to unique user experience. Taking prompt actions to feel better and manage more effectively one’s everyday condition gives a sense of responsibility for one’s own health. In some rural areas around the world with no easy physical access to a doctor, AI based mHealth solutions could be a game changer for people with health conditions that are not-life threatening. AI and machine learning, chatbots, predictive diagnostics and telemedicine provide the support doctors need in the patient-centric journey.

At present, some medical chatbots that utilize advanced Artificial intelligence algorithm / self-learning AI technology can be used as a personal health assistant to: check symptoms and get a diagnosis, advise how to treat the sickness and whether one should see personally a doctor, book a consultation with a medical specialist, and allow for remote monitoring of a health status. The quality of the medical and scientific data that is behind the AI technology used, the ability to process more cases and insights, as well as the propensity to learn from real time smart conversations with the user and to build a personalized profile with every interaction make one chatbot a trustworthy partner in managing one’s health.

Globally, healthcare is complicated, inaccessible and focuses on reactive versus proactive care, and Ada is shifting the healthcare model to put the patient first.

By complementing the strengths of human doctors with machine intelligence, we are building a comprehensive medical knowledge base covering hundreds and thousands of conditions and symptoms and cases. With our platform’s intelligence supported by a deep, curated medical knowledge base and proprietary artificial intelligence technology, the platform is able to consider the patient’s full medical history, along with data from a broader range of sensors, devices and other sources, when making a health assessment.

In terms of usability, the platform is approachable and with a conversational interface that encourages users to engage. The platform’s assessment is developed to work much like a good doctor would, determining the most relevant, helpful questions to ask, with intelligent algorithms enabling Ada to ‘get to know’ each individual better over time, providing a more comprehensive health picture and increasingly tailored guidance.

Our platform in a nutshell is an AI-powered health management platform that supports both patients and clinicians. From day one, our team has been focused on providing very detailed, high quality medical insights and decision support.

Therefore, we highly quality for The AI for Humanity Prize and it would enable us acquire the much needed technical capability as well as to help us develop prototypes of the platform tool adapted for use among different locations and types of semi-skilled health workers and also help us secure a network of healthcare researchers, doctors and specialists across the globe that will be interested to utilize our solution to continue their medical practice but also as consultants and mentors.

Covid-19 has shone a harsh light on weak health security and resilience planning worldwide. Governments and donors are the primary funders of the healthcare systems in Africa, serving over 70 percent of the 1.3 billion population. With these actors barely covering crucial budgets, their ability to efficiently anticipate, adequately prepare, and correctly deploy resources to respond to health threats is severely stifled.

Since we are experts in the healthcare field and currently building a healthcare disease surveillance platform, through The Global Fund Prize and using our artificial intelligence-driven platform we can be able to incorporate a healthcare medical equipment service that provides powerful visualizations in tracking disease burdens and forecasting the demand of essential healthcare products. Using action triggers and recommendations, the platform is able to provide a robust collaboration framework that ensures seamless just-in-time sourcing with tools to support resource mobilization needed for procurement and on time delivery of orders by suppliers. Depending on the required outputs, the platform ranges from simple business intelligence models to complex artificial intelligence models that can predict and prescribe outcomes. Its aim is to incorporate data science attributes in the day-to-day planning of healthcare supply chains. By synthesizing historic data from key actors and on-going processes in the healthcare value chains, the solution provides; powerful customizable dashboards for disease and commodity trends, potential stock-out alert triggers, scientific performance measurement and capacity building tools for suppliers. The solution can run as a standalone system or can be integrated with other systems to provide holistic insights and visualizations. The integrations are with systems that manage disease surveillance, procurement, warehouses, logistics or supplier management. This gives a unique opportunity for key actors to effectively collaborate and make decisions based on real time insights and projections made by AI and machine learning models at the core of it all. 

The solution is developed to support the operations of actors working to ensure health security and resilience. These include government agencies, donor organizations, medical institutions and supply chain actors (manufacturers, buyers, suppliers, financiers) - critical to the availability of essential healthcare products in the country. Lack of supplies due to inefficiencies in the supply chain processes ultimately negates the health of the population that depend on government and institutional bodies to provide subsidized medicines such as ARV’s. We approximate 80% of the population in Africa to be beneficiaries of the platform.

Through this we can be able to provide a scalable end-to-end holistic approach, with the potential to unlock trade and investment opportunities and transform how essential health products are sourced.