Project Objective: Human Behavior & Social Impact

This project explores how human behavior, communication platforms, and public perception influence health outcomes during epidemics and public health crises. By combining behavioral science, social data analysis, and artificial intelligence, we aim to improve public health response, policy design, and societal resilience in the face of misinformation, stigma, and behavioral complexity.

Key Focus Areas

  • Human behavioral dynamics during epidemics, including adoption of preventative behaviors, vaccine hesitancy, and compliance with guidelines.
  • Public health misinformation on social media and its impact on health behaviors, trust, and risk perception.
  • Sentiment analysis and emotional trends using real-time social media data to track public opinion and detect early warning signals.
  • Computational advertising and influence tracking in online networks to study how information spreads during crises.
  • Media influence during health emergencies and its role in shaping community responses.
  • Self-medication behavior and healthcare stigmatization trends across diverse cultural and digital contexts.
  • Leveraging AI for large-scale social media monitoring and actionable insights into public health messaging and misinformation control.

Outcomes

  • Improved understanding of public behavior and attitudes during pandemics and epidemics.
  • Early detection of misinformation outbreaks and public sentiment shifts.
  • Development of socially-informed models for guiding public health campaigns.
  • Evidence-based recommendations to policymakers and communicators for combatting stigma and disinformation.

đź“š 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.