🌍 Project Objective
🔎 Vision
The overarching goal of this project is to develop and deploy AI, data science, and mathematical methodologies and technologies for disease detection, data management and processing, and real-time model validation and calibration using advanced computational methods.
📊 Program Focus
Our NSERC-funded program centers on modeling ecological dynamics in changing environments by integrating diverse data sources. We have curated a large volume of conventional and unconventional data, including public datasets (e.g., social media, news) and private platforms like African infectious disease portals, COVID-19 dashboards, and Monkeypox stigmatization studies.
🛠️ Tools & Partnerships
We’ve created AI-powered interactive data visualization frameworks to track outbreaks and health trends. With collaborations across 10 African governments, we access District Health Information System 2 (DHIS2) portals. In Canada, our partnerships with government agencies, hospitals, and research institutions enable access to Acute Care Enhanced Surveillance (ACES), wastewater-based surveillance, and more.
📁 Data Scope & Ethics
Our datasets span animal and human health, environmental, demographic, and financial domains to support wide-ranging applications. All data are curated following FAIR principles. For Indigenous communities, we adhere to OCAP® standards. We continue to improve methods for extracting valuable signals from unconventional sources while strengthening multi-source data integration.
📚 Selected Refereed Journal Publications
Sharma, Y., Laison, E. K., Philippsen, T., Ma, J., Kong, J., Ghaemi, S., ... & Nasri, B. (2024). Models and data used to predict the abundance and distribution of Ixodes scapularis (blacklegged tick) in North America: a scoping review. The Lancet Regional Health–Americas, 32.
Yuh, M. N., Ndum Okwen, G. A., Miong, R. H. P., Bragazzi, N. L., Kong JD., Movahedi Nia, Z., ... Patrick Mbah, O. (2024). Using an innovative family-centered evidence toolkit to improve the livelihood of people with disabilities in Bamenda (Cameroon): a mixed-method study. Frontiers in Public Health, 11, 1190722.
Nunes, M. C., Thommes, E., Fröhlich, H., Flahault, A., Arino, J., Baguelin, M., Kong JD ... Coudeville, L. (2024). Redefining pandemic preparedness: Multidisciplinary insights from the CERP modelling workshop in infectious diseases, workshop report. Infectious Disease Modelling.
Kaur, M., Cargill, T., Hui, K., Vu, M., Bragazzi, N. L., Kong JD (2024). A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets. JMIR Formative Research, 8, e46087.
Bain, L. E., Yankam, B. M., Kong, J. D., Nkfusai, N. C., Badru, O. A., Ebuenyi, I. D., ... & Adeagbo, O. (2023). Global Health Mentorship: Challenges and Opportunities for Equitable Partnership. BMJ Global Health, 8(11), e013751.
Kaur, M., Bragazzi, N. L., Heffernan, J., Tsasis, P., Kong JD (2023). COVID-19 in Ontario Long-term Care Facilities Project, a manually curated and validated database. Frontiers in Public Health, 11, 1133419.
Nia ZM, Ahmadi A, Mellado B, Wu J, Orbinski J, Asgary A, Kong JD. Twitter-based gender recognition using transformers. Math Biosci Eng. 2023 Aug 3;20(9):15962-15981. doi: 10.3934/mbe.2023711.
Movahedi Nia, Z., Bragazzi, N., Asgary, A., Orbinski, J., Wu, J., Kong JD (2023). Mpox Panic, Infodemic, and Stigmatization of the 2SLGBTQIA+ Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis. Journal of Medical Internet Research, 25, e45108.
Fevrier, K., Effoduh, J. O., Kong JD, Bragazzi, N. L. (2023). Artificial Intelligence, Law, and Vulnerabilities. In AI and Society. : 179-196.
Ji J, Wang H, Wang L, Ramazi P, Kong JD, Watmough J. Climate-dependent effectiveness of nonpharmaceutical interventions on COVID-19 mitigation. Mathematical Biosciences. 2023 Dec 1;366:109087.