Research results (AI4COVID) / Résultats de recherche (IA en réponse à la COVID-19)
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Item Global South AI4COVID program : final technical report template(2023) Ruranga, Charles; Akili, Viviane; University of RwandaThe general objective of the LAISDAR project was Leveraging Artificial Intelligence and Data Science Techniques in Harmonizing, Accessing and Analysing SARS-COV-2/COVID-19 Data in Rwanda. The research approach, methodology and key activities have been implemented as planned. Collected data has been analysed and findings disseminated through conferences, workshops, and publications. Many studies have been conducted in this project and this report also present key research findings.Item AI4COVID gender action learning : final peer-learning workshop(2023-02) Hailemariam, Mahlet; Mbuthia, Michelle; Todd, Jim; Taylor, Amelia; Muyingo, SylviaThis webpage offers a short summary of the aims and topics of the AI4COVID Gender Action Learning (GAL) Final Peer-Learning Workshop.Item INSPIRE PEACH courses(2022) Kanjala, Chifundo; Muyingo, Sylvia; Wamukoya, Marylene; Taylor, Amelia; Bhattacharjee, TathagataThe website offers information on the training program and courses created by INSPIRE PEACH. The courses are designed to help uncover and address the skills and knowledge gaps of health data professionals with several pathways of training in mind such as data trackers, data managers, and analysts. The courses were developed with the aim to support scientists working on health data mapping and transformation tasks and data discovery, access, and reuse.Item Platform for evaluation and analysis of COVID-19 harmonised data(2023) INSPIRE PEACHThe emergence of coronavirus disease 2019 (COVID-19) as a global pandemic presents a serious health threat to many low-and-middle-income countries (LMICs) and the livelihoods of its people. The need for accurate, real-time data is urgent, so that health policy and planning can be updated to combat the threat. Obtaining those data requires innovation in data collection and aggregation, especially under lockdown restrictions. Artificial Intelligence (AI) and Data Science (DS) innovations are needed to get accurate, real-time data, using multiple data sources. In many LMICs, there are methodological gaps in data integration and a lack of information and research capacity to make informed decisions and guide public health policy. The absence of data makes it difficult to identify vulnerable populations and to give them appropriate information for their health. This project proposes to develop the key elements of a coordinated Pan-African COVID-19 data ecosystem. We will build a robust suite of data standards and technologies, diverse data integration methodologies, using the power of AI and DS for analysis and oversight through a trusted governance and policy environment.Item INSPIRE data hub : technical results of phase 1(2023) Kanjala, Chifundo; Greenfield, Jay; Gregory, Arofan; Todd, Jim; Bhattacharjee, TathagataThe INSPIRE Data Hub is a FAIR data resource containing longitudinal population health data from Health and Demographic Surveillance System (HDSS) sites in southern and eastern Africa. It is designed with the idea that population health data can be usefully combined with data from other sources, notably routine healthcare data from clinics. It is designed to be both scalable and extensible, based on international standards, allowing for additional data in new areas to be introduced without requiring a new hub infrastructure.Item Banking on artificial intelligence and emerging technologies(The Standard, 2023) Muyingo, Sylvia; APHRCThe African continent is experiencing a remarkable transformation in various sectors, with healthcare being a critical area of focus. The COVID-19 pandemic was a watershed moment, compelling governments across the world to rethink public service provision, especially healthcare. In particular, the incorporation of Artificial Intelligence (AI) and other emerging technologies in healthcare access is ushering in a new era of innovation, efficiency, and accessibility, revolutionizing healthcare services for the people of Africa and beyond.Item Inspire Peach : AI-powered COVID-19 data project(The AfricaBrief, 2023-06-20) Issa, SumeyaThe Inspire PEACH project has emerged as a transformative initiative to address the critical data challenges faced by African countries like Malawi during the COVID-19 pandemic. By utilising modern technology and data science, this project seeks to enhance data collection models and provide reliable information. During a two-day international dissemination workshop [26–27 June] in Blantyre, health sector experts emphasised the significance of the Inspire PEACH project for vulnerable economies and its potential as a solution for African countries.Item Groundbreaking project to unveil COVID-19 insights during Malawi workshop : AI and data science workshop in Blantyre kicks off, June 26-27(The AfricaBrief, 2023-06-20) Mwale, WinstonThe two-day workshop, organised by the Platform for Evaluation and Analysis of COVID-19 Harmonised Data (PEACH) project, gathered a diverse range of stakeholders, including experts, researchers, and policymakers. The workshop aimed to leverage data-driven insights in the fight against the pandemic.Item Inspire Peach project to revolutionize COVID-19 data management in Africa - expert(The AfricaBrief, 2023-06-23) Issa, Sumeya; Mwale, WinstonIn an exclusive interview with AfricaBrief Dr. Muyingo, the Principal Investigator during the project, highlighted the project's comprehensive approach to addressing critical areas in data management and healthcare.Item Malawi, Kenya use AI to close COVID-19 data gaps : AI and data science being used in Malawi and Kenya to tackle COVID-19 data gaps(The AfricaBrief, 2023-06-26) Issa, SumeyaIn the quest for more reliable solutions to pandemic preparedness and the need to address existing information gaps caused by outbreaks like COVID-19, Malawi and Kenya are among the countries and partners embracing the use of Artificial Intelligence (AI) and Data Science to tackle issues related to COVID-19 data in Africa. Under the Inspire PEACH (A Platform for Evaluation and Analysis of COVID-19 Harmonised Data) platform, Malawi, represented by the Malawi University of Business and Applied Sciences (MUBAS), and Kenya have joined forces as partners.Item Malawi MUBAS leads AI applications in Inspire Peach project : AfricaBrief interview - Dr. Amelia Taylor on Malawi's role in the Inspire Peach project(The AfricaBrief, 2023-06-26) Issa, SumeyaThis AfricaBrief Interview features Dr. Amelia Taylor speaking on Malawi's Role in the INSPIRE PEACH Project.Item AI for Health : APHRC partners establish COVID-19 data hub(2023-06-23) APHRCThis video discusses how APHRC and its partners created a data hub to collect Covid-19 related data.Item Enabling data sharing and utilization for African population health data using OHDSI tools with an OMOP-common data model(Frontiers, 2023-06-09) Kiwuwa-Muyingo, Sylvia; Todd, Jim; Bhattacharjee,Tathagata; Greenfield, Jay; Taylor, Amelia; Yap, PeilingThe COVID-19 pandemic has spurred the use of AI and DS innovations in data collection and aggregation. Extensive data on many aspects of the COVID-19 has been collected and used to optimize public health response to the pandemic and to manage the recovery of patients in Sub-Saharan Africa. However, there is no standard mechanism for collecting, documenting, and disseminating COVID19 related data or metadata, which makes the use and reuse a challenge. INSPIRE utilizes the Observational Medical Outcomes Partnership (OMOP) as the Common Data Model (CDM) implemented in the cloud as a Platform as a Service (PaaS) for COVID-19 data. The INSPIRE PaaS for COVID-19 data leverages the cloud gateway for both individual research organizations and for data networks. Individual research institutions may choose to use the PaaS to access the FAIR data management, data analysis and data sharing capabilities which come with the OMOP CDM. Network data hubs may be interested in harmonizing data across localities using the CDM conditioned by the data ownership and data sharing agreements available under OMOP’s federated model. The INSPIRE platform for evaluation of COVID-19 Harmonized data (PEACH) harmonizes data from Kenya and Malawi. Data sharing platforms must remain trusted digital spaces that protect human rights and foster citizens’ participation is vital in an era where information overload from the internet exists. The channel for sharing data between localities is included in the PaaS and is based on data sharing agreements provided by the data producer. This allows the data producers to retain control over how their data are used, which can be further protected through the use of the federated CDM. Federated regional OMOP-CDM are based on the PaaS instances and analysis workbenches in INSPIRE-PEACH with harmonized analysis powered by the AI technologies in OMOP. These AI technologies can be used to discover and evaluate pathways that COVID-19 cohorts take through public health interventions and treatments. By using both the data mapping and terminology mapping, we construct ETLs that populate the data and/or metadata elements of the CDM, making the hub both a central model and a distributed model.Item Vulnérabilités des femmes en contexte de réponse à la COVID-19 au Sénégal(2023) Ndoye, Tidiane; Diène, Hélène Agnès; Bousso, Mariata Delphine; Faye, Sylvain L. B.; Diouf, Souleymane; Kelly, Ibrahima; Ndao, Iba