IUEA Developing Intelligent Information Management System for COVID-19 and Other Infectious Diseases

IUEA Smart Ventilator (Developed by IUEA Innovators)
IUEA Smart Ventilator (Developed by IUEA Innovators)

As part of its contribution to knowledge and the society, scholars at IUEA are hard at work developing solutions that address the multi-faceted issues – from business to technology that the coronavirus – COVID-19 pandemic has created. Worldwide, the epidemic has infected over 3 million people and has so far killed over 145,000 people. The virus is still spreading, and the government of Uganda and the World Health Organization (WHO) have recommended solutions to slow the spread of the virus. As the pandemic persists, government ministries and universities continue to look for ways to defeat the epidemic. So far, there is no known cure.  IUEA has been working tirelessly to assist the country in battling the pandemic.

It is evident from what has transpired so far that the healthcare system in most parts of the world is not capable of handling infectious diseases that surface suddenly. Even countries with the most advanced healthcare systems and technology – China, the USA, Italy, the UK, Spain, etc. have had their healthcare systems overwhelmed. After living with COVID-19 for six months, some lessons and best practices regarding viral viruses can be gleaned: “diagnose and isolate, maintain basic hygiene, keep physical/social distance and contact trace.

Even more important, have an information-sharing system that will enable policymakers, caregivers and patients to have up-to-the-minute information regarding the virus.

Current research and media reports have identified the major problems that countries are facing in the battle against COVID-19 as 1) there are not enough testing kits; where there are enough testing kits, results take days/weeks to be obtained; there are not enough personal protection equipment (PPE) for healthcare givers and that physical/social distancing, specifically in developing countries where there are many high population density areas, is difficult. Finally, the essential element in fighting a war or managing a company or pandemic is the availability of the right information at the right time to the right people to solve the right problem. So far, it is crystal clear that many countries have difficulty coordinating their efforts in the fight against COVID-19 due to lack of or due to fragmented, inaccurate information. Those who need to know do not have the information they need.

It is irrefutable that useful information is needed to win the fight against COVID-19. It is clear, from interviews and reports, that the collection, storage and dissemination of COVID-19 related information is not digitized and disseminated promptly. If the fight against COVID-19 is to be won conclusively, there is a need to develop an intelligent infectious disease management system for the country. This intelligent system will use machine learning to provide, quick, reliable, up-to-the-minute information for stakeholders throughout Uganda. This intelligent system will incorporate facets of the major problems that have been identified such as the long lag time for test results to be available and the challenge of local infectious disease transmission in high population density areas.

IUEA is proposing an intelligent infectious disease management system that will automate the collection, storage and dissemination of COVID-19 or any other contagious disease data in Uganda. This intelligent system will register users using the national ID, fingerprint or iris scan. Each user will have a profile, including brief bio-data and location data and medical history in the system. The fingerprinting and iris scan components are necessary since most of the participants may not be literate and or, may not have a national ID. The system will incorporate testing device so that users can be tested and the test result instantly recorded – 15-minute lag time – and the user given the green light or required to undergo further tests.

The system will provide policymakers and doctors up-to-the-minute infectious disease information on a patient by patient basis and provide statistics on personal, city, county and regional and national levels.

Key stakeholders will be policymakers, frontline epidemiological staff, doctors, nurses, health ministry and patients. The system will generate accurate reports that can be viewed in real-time by critical stakeholders. Information will be available to stakeholders based on the rights of information that each stakeholder has. Because health information is deemed confidential information, the system will ensure that data partition is done to preserve the confidentiality of users’ data.

The machine learning system will be linked to a national medical records system so that patients’ medical records are available to doctors across the nation. The machine learning system will be modular to enable it handle new infectious diseases as they materialize and to incorporate new test kits as they become available. The system will be cloud-based and can be accessed via a browser, mobile phone, desktop, tablets and other means. Supported mobile device operating systems are Apple’s IOS and Google’s Android Oss.

This system seeks to assist Uganda in the detection, management and control of infectious diseases using the most modern methods. Aims to support Uganda, through the walk-in community-based testing centres, to establish a modern, sustainable approach to identifying and isolating individuals with certain infectious diseases at the community level. The project aims to achieve the following objectives, Equip Uganda, with an intelligent infectious disease management system that will help the country to battle COVID-19 and other infectious diseases. Reduce person-to-person transmission of COVID-19 or other infectious diseases by detecting and isolating infected persons on time, before they transmit the virus to others. Make infectious disease testing readily available to high population density areas by placing the infectious disease management system in existing community centres. Use Machine Learning algorithms to provide up-to-the-minute management of COVID-19 patient information to all stakeholders. Use Machine Learning strategies to deliver reliable infectious disease predictions for specific community groups and individuals based on past medical history. Use walk-in testing centres as a means of reducing the rate of local transmissions for people living in high population density areas in Uganda. Involve communities in managing their healthcare and as a result, increase sensitization to infectious diseases and reduce stigmatization.

If developed, IUEA expects the country to reap the following advantages: A national intelligent infectious disease management system that will allow critical players – decision-makers, frontline epidemiological staff, doctors, managers and patients to have authoritative and reliable infectious disease information in a timely manner, both on a general-need-to-know basis and on patient-specific and virus-specific levels. A national system that will provide intelligent infectious disease data in the areas of surveillance, patient case management, virus management, infectious disease information management and coordination, contact tracking. A system that can be used to help slow down the local transmission of infectious diseases in high population density areas.

Author

Dr. Emeka Akaezuwa, Ph.D

Vice Chancellor, International University of East Africa

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