Explore our scholarly contributions across peer-reviewed journal articles, manuscripts under review, book chapters, conference publications, and other research outputs.

Selected Peer-Reviewed Journal Articles (Published)
  1. Kong, J.D, & Bragazzi, N. L. (2026). Mapping the Digital One Health/One Digital Health paradigm: A bibliometric and foresight-based analysis of emerging trends and future directions. Digital health, 12, 20552076261433841. [PA]
  2. Xu, Y., Wang, H., & Kong, J.D. (2026). Environmental semantic clustering-guided multimodal fusion for enhanced interpretability in methane concentration prediction. Journal of Environmental Management, 401, 128845. [SRA]
  3. Gemechu, H., Biru, G., Gebremeskel, E., Teshome, F., Nemomssa, H. D., Dese, K., ... & Kong, J.D. (2026). Machine learning framework for early detection of polio outbreaks from acute flaccid paralysis surveillance data. Virology, 110863. [SRA]
  4. Omame, A., Iyaniwura, S. A., Ebenezer, A., Han, Q., Wang, X., Bragazzi, N. L., Kong, J.D., & Woldegerima, W. A. (2026). Pre-exposure vaccination in the high-risk population is crucial in controlling mpox resurgence in Canada. BMC Infectious Diseases, 26}(1), 14. [CA]
  5. Yazdinejad, A., & Kong, J.D. (2026). Breaking interprovincial data silos: how federated learning can unlock Canada's public health potential. Royal Society Open Science, 13(3). [SRA]
  6. Kong, J.D., Gillies, M., Gardner, E., & Bragazzi, N. L. (2026). Multi-model large-scale AI framework for avian influenza surveillance and preparedness: Harnessing large language models to enhance risk communication, real-time decision support, and public health response strategies. One Health, 22, 101357. [PA]
  7. Kong, J.D., & Bragazzi, N. L. (2026). Framing the Convergence of One Health and Digital Health in the Global South With a Gender-Sensitive Foresight Perspective: Delphi Study Using Latent Semantic Analysis. Journal of Medical Internet Research, 28, e78702. [PA]
  8. Badran, E. F., Rayyan, A., Al Jaberi, M., Azzam, M., Ramadan, R., Khader, Y., ... & Kong, J.D. (2026). Infectious disease burden and surveillance challenges in Jordan and Palestine: a systematic review and meta-analysis. Frontiers in Digital Health, 7, 1713089. [SRA]
  9. Omame, A., Bragazzi, N. L., Asgary, A., Ugwu, C. L. J., Kong, J.D., Wu, J., & Woldegerima, W. A. (2026). Assessing the impact of vaccination and behavioral change on Mpox transmission in high-risk groups in the Democratic Republic of Congo using an age-structured mathematical model. One Health, 101324. [CA]
  10. Chabalala, V., Rudolph, C., Mosala, K., Nkadimeng, E. K., Mosomane, C., Mathaha, T., ... & Kong, J.D, Mellado, B. (2026). Spatiotemporal Graph Neural Networks for PM 2.5 Concentration Forecasting. Air, 4(1), 2. [CA]
  11. Movahedi Nia, Z., Bragazzi, N., Gizo, I., Gillies, M., Gardner, E., Leung, D., & Kong, J.D. (2026). Integrating deep-learning methods and web-based data sources for surveillance, forecasting and early warning of avian influenza. Journal of The Royal Society Interface, 23(234). [SRA]
Peer-Reviewed Journal Articles (Under Review)
  1. Yazdinejad, A., & Kong, J.D. (2025). Responsible Use of Large Language Models in Digital Health: An Equity First Governance Framework. Available at SSRN 5962741. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5962741 [SRA]
  2. Nia, Z., Bragazzi, N. L., Gillies, M., Gardner, E., Leung, D., & Kong, J.D. (2025). Highly Pathogenic Avian Influenza in Canada: Spatial Analysis of Ecological Hot and Cold Spots and Environmental Drivers. Available at SSRN 5943836. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5943836 [SRA]
  3. Shuaib, S.E., Nia, Z.M., & Kong, J.D. (2025). Analyzing Reddit and Facebook social media content on Canadian fishers’ and fishing communities’ attitudes toward species range shifts: A sentiment and topic modeling study. https://track.authorhub.elsevier.com/?uuid=da3b3072-6b95-4c94-b3d5-35c1ab18bc61 [SRA]
  4. Ayana, G., Yohannes, D., Dese, K., Daba, H., Tefera, M., Alayu, M., ... & Kong, J. D. (2025). Development of a Centralized Data Repository System to Overcome Fragmented Polio Data Collection and Strengthen Acute Flaccid Paralysis Detection, Surveillance, and Response in Ethiopia. Surveillance and Response in Ethiopia. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5849682 [SRA]
  5. Biru, G., Gemechu, H., Teshome, F., Gebremeskel, E., Nemomssa, H. D., Dese, K., ... & Kong, J.D. (2025). AFP Assistant: A Retrieval-Augmented Generation and Large Language Model-powered Multilingual Polio Chatbot for Low-Resource Language Communities. Available at SSRN 5797544. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5797544 [SRA]
  6. Gebremeskel, E., Teshome, F., Biru, G., Gemechu, H., Ayana, G., & Kong, J.D. (2025). Scan Psoriasis: A Vision Transformer-Based Psoriasis Detection and Clinical Classification. Available at SSRN 5797402. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5797402 [SRA]
  7. Gemechu, H., Biru, G., Gebremeskel, E., Teshome, F., Nemomssa, H. D., Dese, K., ... & Kong, J.D. (2025). Machine Learning Framework for Early Detection of Polio Outbreaks From Acute Flaccid Paralysis Surveillance Data. Available at SSRN 5797346. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5797346 [SRA]
  8. Ayana, G., Gulilat, H., Nemomssa, H. D., Malik, T., Zeynudin, A., Berhanu, B., ... & Kong, J.D. (2025). Mpox Cases Surveillance in Ethiopia: A Review on Surveillance Infrastructure and Early Response Capacity. Available at SSRN 5459856. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5459856 [SRA]
  9. Ayana, G., Gulilat, H., Lemma, K., Teshome, F., Daba, H., Malik, T., Eshete, M.T., Woldie, M., Zeynudin, A., Gidi, N.W. and & Kong, J.D. (2025). A Rapid Evaluation of the Preparedness of Ethiopia's Disease Surveillance System for Mpox Outbreak: A Cross-Sectional Study of Perspectives from Professionals Across Various Levels. https://ssrn.com/abstract=5387168 [SRA]
  10. Zhou, X., Nia, Z., Bragazzi, N.L., Gizo, I., Gillies, M., Gardner, E., Leung, D., & Kong, J.D. (2025). Predicting Avian Influenza Hotspots in the U.S. Using Logistic Regression and Random Forest with Augmented Data via Empirical Distribution Method and Stochastic Variational Inference. One Health. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5211568 [SRA]
  11. Feng, R., Han, Q., Iyaniwura, S., & Kong, J.D. (2025). Leveraging Mathematical Modelling to Evaluate Malaria Vaccination Roll-Out Strategies in Cameroon. Royal Society Interface. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5250090 [SRA]
  12. Ayana, G., Kong, J.D. (2025). Critical Analysis of Canada's Africa Strategy: A Partnership for Shared Prosperity and Security. The African Review. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5171987 [SRA]
  13. Xu, Y., Yazdinejad, A., Wang, H., & Kong, J.D. (2025). Methane Monitoring: A Systematic Review of Multi-Source Data Integration Challenges and Solutions. Science of the Total Environment. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5218738 [SRA]
  14. Kong, J.D., & Bragazzi, N.L. (2025). Mapping the Digital One Health/One Digital Health Paradigm: A Bibliometric and Foresight-Based Analysis of Emerging Trends and Future Directions. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5341135 [PA]
  15. Kong, J.D., Bragazzi, N.L. (2025). Framing the Convergence of One Health and Digital Health in the Global South: A Gender-Sensitive Foresight Perspective Using Latent Semantic Analysis. JMIR. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5285073 [PA]
  16. Nia, Z., Bragazzi, N.L., Gizo, I., Gillies, M., Gardner, E., Leung, D., Kong, J.D. (2025). Integrating Deep Learning Methods and Web-Based Data Sources for Surveillance, Forecasting, and Early Warning of Avian Influenza. Royal Society Interface. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253151 [SRA]
  17. Fredston, A., Ovando, D., da Cunha Godoy, L., Kong, J.D., Muffley, B., Thorson, J.T., Pinsky, M. (2025). Dynamic range models improve the near-term forecast for a marine species on the move. EcoEvoRxiv. https://ecoevorxiv.org/repository/view/8863/ [CA]
  18. Yazdinejad, A., Kong, J.D. (2025). Breaking Interprovincial Data Silos: How Federated Learning Can Unlock Canada's Public Health Potential. Royal Society Open Science. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5248862 [SRA]
  19. Ayana, G., Trigui, H., de Castro, R., de Carvalho, A., Nsagha, D., Badu, K., Faye, S.L., Mellado, B., Lazo, L., Lee, A., Colome, M., Espinoza-Lopez, P., Marcelo, A., Koulali, M.-A., Qasrawi, R., Sinha, C., Chirgwin, H., Musa, E., Kong, J.D. (2025). Shifting from Margins to Momentum of the Global South Leadership in Responsible Artificial Intelligence Solutions for Health: Lessons from the UNGA79 Science Summit. Lancet Global Health. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5222262 [SRA]
  20. Xu, Y., Yazdinejad, A., Wang, H., & Kong, J.D. (2025). From Detection to Decision: A Systematic Literature Review of AI and Machine Learning Evolution in Methane Modelling. Atmospheric Environment. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5218753 [SRA]
Book Chapters
  1. Zewdie, G. A., Yazdinejad, A., & Kong, J.D. (2026). Bridging the AI Divide: Approaches to Ensure Equitable Access to Computing and Data. In Foundational Principles of AI Governance and Policy (pp. 71-90). Cham: Springer Nature Switzerland. [CA]
  2. Kong, J.D., Fevrier, K., Effoduh, J. O., & Bragazzi, N. L. (2022). Artificial Intelligence, Law, and Vulnerabilities. In AI and Society (pp. 179-196). Chapman and Hall/CRC. [PA]
Conference Publications
  1. Chiraira, I., Cheng, L., Karmoude, M., Mckenzie, R., Munhungewarwa, B., Chandna, R., Kong J.D., ... & Mellado, B. (2025, August). A Scalable Reinforcement Learning Framework for Wireless Sensor Networks: Spatiotemporal Cluster-Based Multi-Agent Reinforcement Learning. In 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) (pp. 1-10). IEEE. [CA]
  2. Tornimbene, B., Rioja, Z. B. L., Brownstein, J., Dunn, A., Faye, S., Kong, J.D., ... & Morgan, O. (2025, March). Harnessing the power of artificial intelligence for disease-surveillance purposes. In BMC proceedings (Vol. 19, No. Suppl 4, p. 7). [CA]
  3. Mckenzie, R., Cervello, A., Chabalala, V., Chiraira, I., Mathaha, T., Mayana, L., Kong, J.D., ... & Mellado, B. (2024, November). A Cost-Effective Air Quality Monitoring System for the Global South. In 2024 IEEE International Humanitarian Technologies Conference (IHTC) (pp. 1-7). IEEE. [CA]
  4. Ogbuokiri, B., Ahmadi, A., Mellado, B., Wu, J., Orbinski, J., Asgary, A., Kong, J.D. (2022, December). Can post-vaccination sentiment affect the acceptance of booster jab?. In International Conference on Intelligent Systems Design and Applications (pp. 200-211). Cham: Springer Nature Switzerland. [SRA]
  5. Kong J.D., Kumar, S. S., & Palumbo, P. (2014). DDE models of the glucose-insulin system: a useful tool for the artificial pancreas. In Managing Complexity, Reducing Perplexity: Modeling Biological Systems (pp. 109-117). Cham: Springer International Publishing. [PA]
  6. Palumbo P., Pepe P., Kong J.D., Kumar S.S., Panunzi S., De Gaetano A. (2013). Regulation of the human plasma glycemia by means of glucose measurements and subcutaneous insulin administration. IFAC Proceedings Volumes. Jan 1;46(20):524-9. [CA]
Policy Perspectives
  1. Canada’s Africa Strategy: What You Need to Know and Why It Matters for Health, AI, and Innovation
  2. Critical Analysis of Canada’s Africa Strategy: A Partnership for Shared Prosperity and Security

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