Makerere University (Uganda)

Academic Institute

1196

The insufficiency of COVID-19 testing infrastructure is a global phenomenon, but it is more prevalent in developing countries such as Uganda, where there is a dearth of requisite resources (equipment, test kits, testing centers/facilities, and personnel). Currently, testing resources have been focused on high-risk demographics (cross-border truck drivers, air travelers/returnees) and their contacts. As of August 20, 2020, only 333,667 samples have been tested, of which some are repeat/follow-up tests for the same subjects. This is a drop in the ocean for a country of over 40 million people. Recently, there has been a surge in community transmission and COVID-19 deaths. To contain community transmission, there is an Independent Peer Review Being Sought PLEASE STATE THE NAME OF THE PEER REVIEWING ORGANISATION THAT IS BEING APPLIED TO/HAS GIVEN APPROVAL, AS APPLICABLE We are applying to an Institutional Review Board (IRB) at Makerere University. The application is catering for both data we seek to access from SAIL plus access to patient data from Uganda Research Ethics Not required THE PROJECT USES WILL USE ONLY ANONYMISED DATA, AND THEREFORE RESEARCH ETHICS REVIEW IS NOT REQUIRED Yes 2 of 6 urgent need for an efficient, rapid, and widely available method to screen for COVID-19. The major goal of our work is to develop a robust mobile application for pre-emptive screening for COVID-19, that utilizes machine learning models trained on anonymized clinical data from confirmed COVID-19 patients. This will be followed by evaluation studies among COVID19 patients in a prospective clinical study. The application will be used by health workers, in homes, on office premises, within education institutions, and access-controlled public spaces and will facilitate early diagnosis and isolation of COVID-19 patients, thus stemming community spread of COVID-19 in low-income settings.

The proposed system, when made widely available, will facilitate the accurate screening of COVID-19 in Uganda and other low-income settings and could potentially have a global impact. In developing countries, efficient screening will ensure that the limited testing infrastructure is put to the best use. Moreover, when deployed in homes and public spaces such as schools and shopping centers, our solution will facilitate the early isolation of potentially infected persons, thus controlling community spread. The integration of machine learning for automatic screening will ensure ease of use (the device will not require a trained health worker to operate). We shall also integrate a networking module in the hardware, such that the National COVID-19 response team is efficiently notified of potentially positive subjects, hence facilitating efficient follow-up. While Uganda has lifted some of the COVID-19 lockdown restrictions, there is still a lot of uncertainty on when some sectors such as education will resume. As such, our technology will bridge a pressing need for rapid and efficient screening for COVID-19 across several sectors and industries.

11/03/2021

Anonymous

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