Objective:

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.

Our NSERC-funded program focuses on modeling ecological dynamics in changing environments by integrating diverse data sources. We have collected a vast array of locally relevant, conventional, and unconventional data from public (e.g., social media, news) and private sources, including African infectious disease portals, COVID-19 dashboards, and Monkeypox stigmatization studies.

We have also developed AI-powered interactive data visualization frameworks to track disease outbreaks and health trends. Through government collaborations in 10 African countries, we have access to District Health Information System 2 (DHIS2) data portals. Additionally, partnerships with Canadian government agencies, hospitals, and research institutes provide access to Acute Care Enhanced Surveillance (ACES), wastewater-based surveillance data, and more.

Our dataset spans animal and human health, environmental, demographic, and financial domains, ensuring broad applicability. Data curation follows FAIR principles, while Indigenous community data adheres to OCAP® standards. We continue refining techniques to detect potential signals from unconventional sources and enhance data integration across diverse systems

On going subprojects
  1. Integrative Infectious Disease Modeling: Develops models incorporating human behavioral dynamics to enhance infectious disease control strategies.
  2. Long-COVID-19 Research: Utilizes machine learning, geospatial analysis, and mathematical modeling to advance understanding and intervention strategies.
  3. Integrative Modeling: Assesses the societal and economic impact of public health interventions by integrating multiple models into a comprehensive framework.
  4. Early Warning System (EWS): Uses AI and deep learning to develop an automated system that collects, processes, and visualizes data from online sources (e.g., Google Trends, social media, satellite data) to predict infectious disease outbreaks.
  5. Mpox & Zoonotic Threats Modeling: Applies mathematical, geospatial, and AI-based models to study the epidemiology, transmission, and intervention strategies for mpox and other zoonotic diseases, aiding public health decision-making.

6. Hybrid AI & Mathematical Models: Develops a framework integrating AI and traditional epidemic models to identify relationships in time series data.

7. Forecasting & Intervention Optimization: Builds transmission dynamics models incorporating population demographics, infection characteristics, and pharmaceutical/non-pharmaceutical interventions.

8. Climate-Sensitive Infectious Disease Modeling: Uses epidemiological, geospatial, AI, and mathematical models to assess risks, predict control strategy effectiveness, and support public health decision-making globally.

9. AI-Powered Disease Outbreak Detection Tool: Designs an AI-driven, real-time platform integrating conventional (e.g., historical, genomic) and unconventional (e.g., Google Trends, social media) data for respiratory disease prediction and intervention.

10. COVID-19 & Antimicrobial Resistance (AR): Applies mathematical modeling and wastewater surveillance to evaluate the pandemic’s long-term impact on AR dynamics and critical intervention thresholds.

11. Agent-Based & Network Models: Expands and refines agent-based modeling for infectious disease spread.

12. Immune Response & Cross-Immunity: Develops models analyzing immune memory and pre-existing immunity from prior infections.

13. Infectious Disease Data Curation & Forecasting: Collects, curates, and integrates animal, human health, environmental, socio-economic, and financial data to forecast infectious disease trends via dashboards.

14. Malaria Dynamics Modeling: Uses mathematical modeling to study the impact of human behavior, vaccination, climate velocity, and seasonal variations on malaria transmission.

15. Sentiment & Emotion Analysis with AI: Compares ChatGPT, Gemini, and Transformers in conducting sentiment and emotional analysis.

16. Resilience of Vulnerable Communities: Investigates pandemic lessons, post-pandemic recovery, and data gaps affecting community health, livelihoods, and income.

17. Mental Health & Substance Treatment Disruptions: Examines service disruptions during COVID-19 in the Jane and Finch community.

18. Community & Street-Level Care During COVID-19: Conducts a comparative study of community, neighborhood, and street-level care responses to the pandemic.

19. Sustainability, Governance & Equity in Post-Pandemic Recovery: Explores climate resilience, governance, and equity-focused strategies for sustainable recovery.

Some of our Refereed Journal Publications so far under this Theme

  1. 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.
  2. 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.
  3. Nunes, M. C., Thommes, E., Fr ̈ohlich, 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.
  4. 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.
  5. 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.

 

  1. 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.
  2. 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. PMID: 37919997.
  3. Movahedi Nia, Z., Bragazzi, N., Asgary, A., Orbinski, J., Wu, J., Kong JD (2023). Mpox Panic,Infodemic, and Stigmatization of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis of a Large, Multilingual Social Media Data. Journal of Medical Inter- net Research. 25, e45108.
  4. Fevrier, K., Effoduh, J. O., Kong JD, Bragazzi, N. L. (2023). Artificial Intelligence, Law, and Vulnerabilities. In AI and Society. : 179-196.
  5. 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.
  6. Zahra Movahedi Nia, Ali Ahmadi, Bruce Mellado, Jianhong Wu, James Orbinski, Ali As- gary, Jude D. Kong. Twitter-based gender recognition using transformers[J]. Mathematical Biosciences and Engineering, 2023, 20(9): 15962-15981. doi: 10.3934/mbe.2023711
  7. Avusuglo WS, Bragazzi N, Asgary A, Orbinski J, Wu J, Kong JD. Leveraging an epi- demic–economic mathematical model to assess human responses to COVID-19 policies and disease progression. Scientific Reports. 2023 Aug 8;13(1):12842.
  8. Movahedi Nia Z, Bragazzi NL, Ahamadi A, Asgary A, Mellado B, Orbinski J, Seyyed-Kalantari L, Woldegerima WA, Wu J, Kong JD. Off-label drug use during the COVID-19 pandemic in Africa: topic modelling and sentiment analysis of ivermectin in South Africa and Nigeria as a case study. Journal of the Royal Society Interface. 2023 Sep 13;20(206):20230200.
  9. Sekkak I, Nasri BR, R ́emillard BN, Kong JD, El Fatini M. A stochastic analysis of a SIQR epidemic model with short and long-term prophylaxis. Communications in Nonlinear Science and Numerical Simulation. 2023 Sep 15:107523.
  10. Han Q, Bragazzi N, Asgary A, Orbinski J, Wu J, Kong JD. Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa. Royal Society Open Science. 2023 Sep 20;10(9):230316.
  11. Nia, Z. M., Bragazzi, N. L., Wu, J., & Kong, J. D. (2023). A Twitter Dataset for Monkey- pox, May 2022. Data in Brief, 109118.
  12. Movahedi Nia, Z., Bragazzi, N., Asgary, A., Orbinski, J., Wu, J., & Kong, J. (2023). Mpox Panic, Infodemic, and Stigmatization of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis of a Large, Multilingual Social Media Database. Journal of Medical Internet Research, 25, e45108.
  13. Puce, L., Okwen, P., Yuh, M. N., Akah, G., Pambe Miong, R. H., Kong, J., & Bragazzi, N. L. (2023). Well-being and quality of life in people with disabilities practicing sports, athletes with disabilities, and para-athletes: Insights from a critical review of the literature. Frontiers in Psychology, 14, 242.
  14. Wu, T., Imrit, M. A., Movahedinia, Z., Kong, J., Woolway, R. I., & Sharma, S. (2023). Climate tracking by freshwater fishes suggests that fish diversity in temperate lakes may be increasingly threatened by climate warming. Diversity and Distributions, 29(2), 300-315.
  15. Kong, J. D., Akpudo, U. E., Effoduh, J. O., & Bragazzi, N. L. (2023, February). Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South. In Healthcare (Vol. 11, No. 4, p. 457). MDPI.
  16. Puce, L., Okwen, P., Yuh, M. N., Akah, G., Pambe Miong, R. H., Kong, J., & Bragazzi, N. L. (2023). Well-being and quality of life in people with disabilities practicing sports, athletes with disabilities, and para-athletes: Insights from a critical review of the literature. Frontiers in Psychology, 14, 242.

 

  1. Bragazzi NL, Han Q, Iyaniwura SA, Omame A, Shausan A, Wang X, Woldegerima WA, Wu J, Kong JD. Adaptive changes in sexual behavior in the high-risk population in re- sponse to human monkeypox transmission in Canada can help control the outbreak: Insights from a two-group, two-route epidemic model. J Med Virol. 2023 Apr;95(4):e28575. doi: 10.1002/jmv.28575. PMID: 36772860.
  2. Kaur M, Bragazzi NL, Heffernan J, Tsasis P, Wu J, Kong JD. COVID-19 in Ontario Long-term Care Facilities Project, a manually curated and validated database. Front Pubic Health. 2023 Feb 10;11:1133419. doi: 10.3389/fpubh.2023.1133419. PMID: 36844842; PMCID: PMC9950626.
  3. Bragazzi NL, Kong JD, Mahroum N, Tsigalou C, Khamisy-Farah R, Converti M, Wu J. Epidemiological trends and clinical features of the ongoing monkeypox epidemic: A preliminary pooled data analysis and literature review. Journal of medical virology. 2023 Jan;95(1):e27931.
  4. Bragazzi NL, Kong JD, Wu J. Is monkeypox a new, emerging sexually transmitted disease? A rapid review of the literature. Journal of Medical Virology. 2023 Jan;95(1):e28145.
  5. Ogbuokiri B, Ahmadi A, Nia ZM, Mellado B, Wu J, Orbinski J, Asgary A, Kong J. Vaccine hesitancy hotspots in africa: An insight from geotagged twitter posts.IEEE Transactions on Computational Social Systems. 2023 Jan 19. doi: 10.1109/TCSS.2023.3236368.
  6. Iyaniwura SA, Musa R, Kong JD. A generalized distributed delay model of COVID-19: An en- demic model with immunity waning. Mathematical Biosciences and Engineering. 2023;20(3):5379- 412.
  7. Lieberman B, Kong JD, Gusinow R, Asgary A, Bragazzi NL, Choma J, Dahbi SE, Hayashi K, Kar D, Kawonga M, Mbada M. Big data-and artificial intelligence-based hot-spot analysis of COVID-19: Gauteng, South Africa, as a case study. BMC Medical Informatics and Decision Making. 2023 Dec;23(1):1-5.
  8. Ahmed, H., Cargill, T., Bragazzi, N. L., & Kong, J. Dataset of Non-pharmaceutical inter- ventions and community support measures across Canadian universities and colleges during COVID-19 in 2020. Frontiers in Public Health, 4512.
  9. Alavinejad, M., Mellado, B., Asgary, A., Mbada, M., Mathaha, T., Lieberman∗, B., … & Kong, J. D. (2022). Management of hospital beds and ventilators in the Gauteng province, South Africa, during the COVID-19 pandemic. PLOS Global Public Health, 2(11), e0001113.
  10. Ogbuokiri, B., Ahmadi, A., Bragazzi, N. L., Nia, Z. M., Mellado, B., Wu, J., … & Kong, J. (2022). Public sentiments toward COVID-19 vaccines in South African cities: An analysis of Twitter posts. Frontiers in Public Health, 10.
  11. Nia, Z. M., Ahmadi, A., Bragazzi, N. L., Woldegerima, W. A., Mellado, B., Wu, J., … & Kong, J. D. (2022). A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments. PloS one, 17(8), e0272208.
  12. Dai, H., Younis, A., Kong, J., Puce, L., Jabbour, G., & Bragazzi, N. L. (2022). Big Data in Cardiology: State-of-Art and Future Prospects. Towards a new cardiology: more predictive, personalized, participatory, digital, smarter, and bigger. Frontiers in Cardiovascular Medicine, 606.
  13. Wang X, Han Q, Kong JD. Studying the mixed transmission in a community with age heterogeneity: COVID-19 as a case study. Infectious Disease Modelling. 2022 Jun 1;7(2):250-60.
  14. Kong J, Mellado B, Wu J (2022). Harnessing the power of data: Artificial Intelligence -based pandemic support. UNESCO: https: // unesdoc. unesco. org/ ark: /48223/ pf0000380883. locale= en .
  15. Yuan P, Aruffo E, Li Q, Li J, Tan Y, Zheng T, David J, Ogden N, Gatov E, Gournis E, Collier S, Sander B, Fan G, Heffernan JM, Li J, Kong JD, Arino J, B ́elair J, Watmough J, & Zhu, H. Evaluating the Risk of Reopening the Border: A Case Study of Ontario (Canada) to New York (USA) Using Mathematical Modeling. In Mathematics of Public Health 2022 (pp. 287-301). Springer, Cham.
  16. Yuan P, Li J, Aruffo E, Gatov E, Li Q, Zheng T, Ogden NH, Sander B, Heffernan J, Collier S, Tan Y, Li J, Arino J, Belair J, Watmough J, Kong JD, Moyles I, Zhu H. (2022). Efficacy of a “stay-at-home” policy on SARS-CoV-2 transmission in Toronto, Canada: a mathematical modelling study. Canadian Medical Association Open Access Journal, 10(2), E367-E378.
  17. Behzadifar M, Aalipour A, Kehsvari M, Darvishi Teli B, Ghanbari MK, Gorji HA, Sheikhi A, Azari S, Heydarian M, Ehsanzadeh SJ, Kong JD. The effect of COVID-19 on pub- lic hospital revenues in Iran: An interrupted time-series analysis. PLoS One. 2022 Mar 31;17(3):e0266343.
  18. Bragazzi NL, Bridgewood C, Watad A, Damiani G, Kong JD, McGonagle D. Harnessing Big Data, Smart and Digital Technologies and Artificial Intelligence for Preventing, Early Intercepting, Managing, and Treating Psoriatic Arthritis: Insights From a Systematic Review of the Literature. Front. Immunol. 13: 847312. doi: 10.3389/fimmu. 2022 Mar 10.
  19. Tao S, Bragazzi NL, Wu J, Mellado B, Kong JD. Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world. Scientific reports. 2022 Jan 18;12(1):1-9.
  20. Kazemi M, Bragazzi NL, Kong JD. Assessing Inequities in COVID-19 Vaccine Roll-Out Strategy Programs: A Cross-Country Study Using a Machine Learning Approach. Vaccines. 2022 Feb;10(2):194.
  21. Iyaniwura SA, Rabiu M, David JF, Kong JD. The basic reproduction number of COVID-19 across Africa. Plos one. 2022 Feb 25;17(2):e0264455.
  22. Habees AA, Aldabbas E, Bragazzi NL, Kong JD. Bacteria–bacteriophage cycles facilitate Cholera outbreak cycles: an indirect Susceptible-Infected-Recovered-Bacteria-Phage (iSIRBP) model-based mathematical study. Journal of Biological Dynamics. 2022 Dec 31;16(1):29-43.
  23. Guelmami N, Tannoubi A, Chalghaf N, Saidane M, Kong J, Puce L, Fairouz A, Bragazzi NL, Alroobaea R. Latent Profile Analysis to Survey Positive Mental Health and Well-Being: A Pilot Investigation Insight Tunisian Facebook Users. Front. Psychiatry. 2022 Apr 7;13:824134.
  24. Chen R, Safiri S, Behzadifar M, Kong JD, Zguira MS, Bragazzi NL, Zhong W, Zhang W. Health effects of metabolic risks in the United States from 1990 to 2019. Frontiers in Public Health. 2022 Jan 31;10:751126.
  25. Yan C, Law M, Nguyen S, Cheung J, Kong J. Comparing Public Sentiment Toward COVID- 19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit. Journal of medical Internet research. 2021 Sep 24;23(9):e32685.
  26. Dai H, Tang B, Younis A, Kong JD, Zhong W, Bragazzi NL. Regional and socioeconomic disparities in cardiovascular disease in Canada during 2005–2016: evidence from repeated nationwide cross-sectional surveys. BMJ Global Health. 2021 Nov 1;6(11):e006809.
  27. Cheong Q, Au-Yeung M, Quon S, Concepcion K, Kong JD. Predictive Modeling of Vacci- nation Uptake in US Counties: A Machine Learning–Based Approach. Journal of medical Internet research. 2021 Nov 25;23(11):e33231.
  28. Bragazzi NL, Kolahi A, Nejadghaderi SA, Lochner P, Brigo F, Naldi A, Lanteri P, Garbarino S, Sullman MJM, Dai H, Wu , Kong JD, Jahrami H, Sohrabi M, & Safiri S. Global, regional, and national burden of Guillain–Barr ́e syndrome and its underlying causes from 1990 to 2019. Journal of neuroinflammation. 2021 Dec;18(1):1-1.
  29. Kong JD, Tekwa EW, Gignoux-Wolfsohn SA. Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries. PloS one. 2021 Jun 9;16(6):e0252373.

 

  1. Duhon J, Bragazzi N, Kong JD. The impact of non-pharmaceutical interventions, demo- graphic, social, and climatic factors on the initial growth rate of COVID-19: A cross-country study. Science of The Total Environment. 2021 Mar 15;760:144325.
  2. Dai H, Younis A, Kong JD, Bragazzi NL, Wu J. Trends and Regional Variation in Prevalence of Cardiovascular Risk Factors and Association With Socioeconomic Status in Canada, 2005- 2016. JAMA network open. 2021 Aug 2;4(8):e2121443
  3. Bouba Y, Tsinda EK, Fonkou MD, Mmbando GS, Bragazzi NL, Kong JD. The determinants of the low COVID-19 transmission and mortality rates in Africa: a cross-country analysis. Frontiers in public health. 2021 Oct 21;9:751197.
  4. Mahroum N, Damiani G, Watad A, Amital H, Bragazzi NL, Farah R, Wu JH, Kong JD, Bridgewood C, McGonagle D, Khamisy-Farah R. Higher rates of COVID-19 but less severe infections reported for patients on Dupilumab: a Big Data analysis of the World Health Or- ganization VigiBase. European Review for Medical and Pharmacological Sciences. 2021 Sep 1;25(18):5865-70.
  5. Guelmami N, Khalifa MB, Chalghaf N, Kong JD, Amayra T, Wu J, Azaiez F, Bragazzi NL. Development of the 12-Item Social Media Disinformation Scale and its Association With Social Media Addiction and Mental Health Related to COVID-19 in Tunisia: Survey-Based Pilot Case Study. JMIR Formative Research. 2021 Jun 9;5(6):e27280.
  6. Betti M, Bragazzi N, Heffernan J, Kong J, Raad A. Could a New COVID-19 Mutant Strain Undermine Vaccination Efforts? A Mathematical Modelling Approach for Estimating the Spread of B. 1.1. 7 Using Ontario, Canada, as a Case Study. Vaccines. 2021 Jun;9(6):592.
  7. Guelmami N, ben Khalifa M, Chalghaf N, Kong JD, Amayra T, Wu J, Azaiez F, Bragazzi NL. Preliminary development of the social media disinformation scale (SMDS-12) and its association with social media addiction and mental health: COVID-19 as a pilot case study. JMIR Formative Research. 2021;5(6):e27280.
  8. Bragazzi NL, Mahroum N, Damiani G, Kong JD, Wu J. Effectiveness of community face mask use on COVID-19 epidemiological trends and patterns in Italy: evidence from a” trans- lational” study. Infectious Diseases (London, England). 2021 Mar 9:1-3.

 

  1. Khamisy-Farah R, Damiani G, Kong JD, Wu JH, Bragazzi NL. Safety profile of Dupilumab during pregnancy: a data mining and disproportionality analysis of over 37,000 reports from the WHO individual case safety reporting database (VigiBaseTM). Eur Rev Med Pharmacol Sci. 2021 Sep 1;25(17):5448-51.
  2. Stevenson F, Hayasi K, Bragazzi NL, Kong JD, Asgary A, Lieberman B, Ruan X, Mathaha T, Dahbi SE, Choma J, Kawonga M. Development of an early alert system for an additional wave of covid-19 cases using a recurrent neural network with long short-term memory. International Journal of Environmental Research and Public Health. 2021 Jul 9;18(14):7376.
  3. Botelho, C., Kong, J. D., Lucien, M. A., Shuai, Z., & Wang, H. (2021). A mathematical model for Vibrio-phage interactions. Mathematical Biosciences and Engineering, 18(3).
  4. Moyles IR, Heffernan JM, Kong JD. Cost and social distancing dynamics in a mathematical model of COVID-19 with application to Ontario, Canada. Royal Society open science. 2021 Feb 24;8(2):201770.
  5. Mellado B, Wu J, Kong JD, Bragazzi NL, Asgary A, Kawonga M, Choma N, Hayasi K, Lieberman B, Mathaha T, Mbada M. Leveraging artificial intelligence and big data to optimize COVID-19 clinical public health and vaccination roll-out strategies in Africa. International Journal of Environmental Research and Public Health. 2021 Jul 26;18(15):7890.
  6. Mahroum N, Watad A, Bridgewood C, Mansour M, Nasr A, Hussein A, Khamisy-Farah A, Farah R, Gendelman O, Lidar M, Shoenfeld Y, Amital H, Kong JD, Wu J, Bragazzi NL, & McGonagle D. Systematic Review and Meta-Analysis of Tocilizumab Therapy Versus Standard of Care in over 15,000 COVID-19 Pneumonia Patients during the First Eight Months of the Pandemic. International Journal of Environmental Research and Public Health. 2021 Jan;18(17):9149.
  7. Khamisy-Farah R, Gilbey P, Furstenau LB, Sott MK, Farah R, Viviani M, Bisogni M, Kong JD, Ciliberti R, Bragazzi NL. Big Data for Biomedical Education with a Focus on the COVID- 19 Era: An Integrative Review of the Literature. International Journal of Environmental Research and Public Health. 2021 Jan;18(17):8989.
  8. Mbogning Fonkou MD, Bragazzi NL, Tsinda EK, Bouba Y, Mmbando GS, Kong JD. Covid- 19 pandemic related research in africa: Bibliometric analysis of scholarly output, collaborations and scientific leadership. International journal of environmental research and public health. 2021 Jan;18(14):7273.
  9. Zhong W, Bragazzi NL, Kong JD, Safiri S, Behzadifar M, Liu J, Liu X, Wang W. Bur- den of Respiratory Infection and Tuberculosis Among US States from 1990 to 2019. Clinical Epidemiology. 2021;13:503.
  10. Bragazzi NL, Beamish D, Kong JD, Wu J. Illicit Drug Use in Canada and Implications for Suicidal Behaviors, and Household Food Insecurity: Findings from a Large, Nationally Representative Survey. International Journal of Environmental Research and Public Health. 2021 Jan;18(12):6425.
  11. Sott MK, Nascimento LD, Foguesatto CR, Furstenau LB, Faccin K, Zawislak PA, Mellado B, Kong JD, BragazziNL. A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure. Sensors. 2021 Jan;21(23):7889.
  12. Khamisy-Farah R, Furstenau LB, Kong JD, Wu J, Bragazzi NL. Gynecology meets big data in the disruptive innovation medical era: State-of-art and future prospects. International Journal of Environmental Research and Public Health. 2021 Jan;18(10):5058.
  13. Kong JD, Tchuendom RF, Adeleye SA, David JF, Admasu FS, Bakare EA, Siewe N. SARS- CoV-2 and self-medication in Cameroon: a mathematical model. Journal of Biological Dy- namics. 2021 Jan 1;15(1):137-50.
  14. Betti M, Bragazzi NL, Heffernan JM, Kong J, Raad A. Integrated vaccination and non- pharmaceutical interventions based strategies in Ontario, Canada, as a case study: a mathe- matical modelling study. J R Soc Interface. 2021 Jul;18(180):20210009. doi: 10.1098/rsif.2021.0009. Epub 2021 Jul 14. PMID: 34255985; PMCID: PMC8277469.
  15. Li J, Yuan P, Heffernan J, Zheng T, Ogden N, Sander B, Li J, Li Q, B ́elair J, Kong JD, Aruffo E. Fangcang shelter hospitals during the COVID-19 epidemic, Wuhan, China. Bulletin of the World Health Organization. 2020 Dec 1;98(12):830.
  16. McCarthy Z, Athar S, Alavinejad M, Chow C, Moyles I, Nah K, Kong JD, Agrawal N, Jaber A, Keane L, Liu S. Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach. Theoretical Biology and Medical Modelling. 2020 Dec;17(1):1- 6.
  17. Kong JD, Wang H, Siddique T, Foght J, Semple K, Burkus Z, Lewis MA. Second-generation stoichiometric mathematical model to predict methane emissions from oil sands tailings. Sci- ence of the Total Environment. 2019 Dec 1;694:133645.
  18. Tadiri CP, Kong JD, Fussmann GF, Scott ME, Wang H. A Data-Validated Host-Parasite Model for Infectious Disease Outbreaks. Frontiers in Ecology and Evolution. 2019 Aug 21;7:307.
  19. Kong JD, Salceanu P, Wang H. A stoichiometric organic matter decomposition model in a chemostat culture. Journal of mathematical biology. 2018 Feb;76(3):609-44.

 

  1. Kong JD, Jin C, Wang H. The inverse method for a childhood infectious disease model with its application to pre-vaccination and post-vaccination measles data. Bulletin of mathematical biology. 2015 Dec;77(12):2231-63.
  2. Kong JD, Davis W, Wang H. Dynamics of a cholera transmission model with immunological threshold and natural phage control in reservoir. Bulletin of mathematical biology. 2014 Aug 1;76(8):2025-51.
  3. Kong JD, Davis W, Li X, Wang H. Stability and sensitivity analysis of the iSIR model for indirectly transmitted infectious diseases with immunological threshold. SIAM Journal on Applied Mathematics. 2014;74(5):1418-41.



Selected Refereed Policy Briefs:

  1. Kong J, Mellado B, Wu J (2022). Harnessing the power of data: Artificial Intelligence -based

pandemic support. UNESCO: https: // unesdoc. unesco. org/ ark: /48223/ pf0000380883. locale= en .

Refereed book publication:

  1. Kong JD, Kumar SS, Palumbo P. DDE models of the glucose-insulin system: a useful tool

for the artificial pancreas. In Managing complexity, reducing perplexity 2014 (pp. 109-117). Springer, Cham

  1. 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.

Conference publication:

  1. Palumbo P, Pepe P, Kong JD, Kumar SS, Panunzi S, De Gaetano A. Regulation of the human

plasma glycemia by means of glucose measurements and subcutaneous insulin administration. IFAC Proceedings Volumes. 2013 Jan 1;46(20):524-9.

Block publication

  1. The Power of Collaboration, Artificial Intelligence and Big Data in the fight against COVID-19 in Africa. https: // tinyurl. com/ 5cwjwjws

Other Publications

  1. Global South Artificial Intelligence and Data Innovation Newsletter https://ai4pep.org/news-letter-first-edition/
  2. Global South Artificial Intelligence and Data Innovation podcast; https://ai4pep.org/podcast-series/

Links to preprints of manuscript in press or currently being reviewed on this Theme

  1. Nilgiriwala,K.S., Mahajan, U., Ahmad, R.A., de Castro, R., Lazo, L., Kong, J., Lee, A.S.H., Veerakumarasivam, A., Sharef, N.M., Demidenko, S. (2024). Navigating the Governance of Artificial Intelligence (AI) in Asian Nations: A Focus on India, Indonesia, Malaysia and the Philippines.
  2. Trigui, H., Guerfali, F., Harigua, E., Atri, C., Hammami, K., Souiai, O., Kong, J.D., Sokhn, E., Qasrawi, R., Wu, J., El Morr, C., Znaidi, S. (2024). AI Governance in the MENA Region.
  3. de Carvalho, A., Bonidia, R., Rocha, U., Kong, J.D., Dauhajre, M., Struchiner, C., Goedert, G., Stadler, P.F., Walter, M.E., Sanches, D., Day, T., Castro, M., Edmunds, J., Colom ́e- Hidalgo, M., Morban, D.A.H., Franco, E.F., Ugarte-Gil, C., Espinoza-Lopez, P., Carrasco- Escobar, G. (2024). Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries.
  1. Fonkou, M. D. M., & Kong, J. D. (2024). Phage Therapy: Leveraging Machine Learning and Big Data techniques to Unveil the Evolution, Innovations, and Global Landscape in the Fight Against Antibiotic Resistance.
  2. Ayana, G., Dese, K., Daba, H., Mellado, B., Badu, K., Yamba, E. I., … & Kong, J. D. (2023). Decolonizing global AI governance: Assessment of the state of decolonized AI governance in Sub-Saharan Africa. Available at SSRN 4652444.]
  3. Iyaniwura, S. A., Han, Q., Yong, N. B., Rutayisire, G., Adom-Konadu, A., Mbah, O. P., . . . & Kong, J. D. (2023). Regional variation and epidemiological insights in malaria underesti- mation in Cameroon. medRxiv, 2023-11.
  4. Perikli, N., Bhattacharya, S., Ogbuokiri, B., Nia, Z. M., Lieberman, B., Jude K., Tripathi, N., … & Mellado, B. (2023). COVID-19 South African Vaccine Hesitancy Models Show Boost in Performance Upon Fine-Tuning on M-pox Tweets. arXiv preprint arXiv:2310.04453.
  5. Vasconcelos VV, Marquitti F, Ong T, McManus LC, Aguiar M, Campos AB, Dutta PS, Jo- vanelly K, Junquera V, Kong J, Krueger EH. Rate-Induced Transitions in Networked Com- plex Adaptive Systems: Exploring Dynamics and Management Implications Across Ecological, Social, and Socioecological Systems. arXiv preprint arXiv:2309.07449. 2023 Sep 14.
  6. Qin H, Kong J, Ding W, Ahluwalia R, Morr CE, Engin Z, Effoduh JO, Hwa R, Guo SJ, Seyyed-Kalantari L, Muyingo SK. Towards Trustworthy Artificial Intelligence for Equitable Global Health. arXiv preprint arXiv:2309.05088. 2023 Sep 10.
  7. Perikli N, Bhattacharya S, Ogbuokiri B, Nia ZM, Lieberman B, Tripathi N, Dahbi SE, Steven- son F, Bragazzi N, Kong J, Mellado B. Detecting the Presence of COVID-19 Vaccina- tion Hesitancy from South African Twitter Data Using Machine Learning. arXiv preprint arXiv:2307.15072. 2023 Jul 12.
  8. Avusuglo WS, Han Q, Woldegerima WA, Bragazzi N, Asgary A, Ahmadi A, Orbinski J, Wu J, Mellado B, Kong JD. Impact assessment of self-medication on COVID-19 prevalence in Gauteng, South Africa, using an age-structured disease transmission modelling framework.
  9. Avusuglo W, Han Q, Woldegerima WA, Asgary A, Wu J, Orbinski J, Bragazzi NL, Ahmadi A, Kong JD. COVID-19 and Malaria Co-Infection: Do Stigmatization and Self-Medication Matter? A Case for Nigeria. A Case for Nigeria.
  10. Bragazzi NL, Kong JD, Mahroum N, Tsigalou C, Khamisy-Farah R, Converti M. The ongoing monkeypox epidemic urges the systematic collection of sexual orientation and gender identity data in clinical settings and in electronic health records to monitor and end LGBTQI+ health- related disparities and inequities.
  11. Bragazzi NL, Kong JD, Mahroum N, Tsigalou C, Khamisy-Farah R, Converti M, Wu J. Epidemiological trends and clinical features of the ongoing monkeypox epidemic: A preliminary pooled data analysis and.
  12. Bragazzi NL, Iyaniwura SA, Han Q, Woldegerima WA, Kong JD. Quantifying the Basic Reproduction Number and the Under-Estimated Fraction of Mpox Cases Around the World at the Onset of the Outbreak: A Mathematical Modeling and Machine Learning-Based Study. Available at SSRN 4533567.
  13. Effoduh, J. O., Akpudo, U. E., & Kong, J. D. (2023). Towards an Inclusive Data Governance Policy for the Use of Artificial Intelligence in Africa. Available at SSRN.
  14. Bragazzi, N. L., Kong, J. D., & Wu, J. (2023). Integrated epidemiological, clinical, and molecular evidence points to an earlier origin of the current monkeypox outbreak and a complex route of exposure. Available at SSRN. (Submitted to Journal of medical virology).
  15. Bragazzi, N. L., Kong, J. D., & Wu, J. (2023). A tale of two (and more) stories: smallpox- monkeypox viruses (HIV, and other sexually transmitted disesases) interaction dynamics. Re- searchGate Project: 2022 Monkeypox Epidemic. (Submitted to Journal of medical virol- ogy).
  16. Bragazzi, N. L., Kong, J. D., & Wu, J. (2023). Monkeypox and laboratory medicine: more data are urgenty needed. ResearchGate Preprint. (Submitted to Journal of medical vi- rology).
  17. Avusuglo, W., Han, Q., Woldegerima, W. A., Bragazzi, N. L., Ahmadi, A., Asgary, A., … & Kong, J. D. (2023). COVID-19 and malaria co-infection: do stigmatization and self- medication matter? A mathematical modelling study for Nigeria. A mathematical modelling study for Nigeria (April 21, 2022). (Submitted to Scientific Reports).
  18. Nia, Z. M., Ahmadi, A., Mellado, B., Wu, J., Orbinski, J., Agary, A., & Kong, J. D. (2023). Twitter-Based Gender Recognition Using Transformers. arXiv preprint arXiv:2205.06801. (Submitted to Pattern Recognition Letters).
  19. Sekkak I, Kong JD, El Fatini M. Containing and Managing an Emerging Disease Outbreak: A Stochastic Modelling Approach. Available at SSRN. 2023 Feb 17. (Submitted to SIAM Journal on Applied Mathematics).
  20. Naderi PT, Asgary A, Kong J, Wu J, Taghiyareh F. COVID-19 Vaccine Hesitancy and Information Diffusion: An Agent-based Modeling Approach. arXiv preprint arXiv:2109.01182. (Submitted to Scientific Reports).
  21. Sott MK, da Silva Nascimento L, Foguesatto CR, Furstenau LB, Faccin K, Zawislak PA, Mel- lado B, Kong JD, Bragazzi NL. Agriculture 4.0 and Smart Sensors. The Scientific Evolution of Digital Agriculture: Challenges and Opportunities. (Submitted to Sensors).
  22. Guelmami N, Chalghaf N, Wu J, Kong JD, Mellado B, Jahrami H, Ben Khalifa M, Amayra T, Azaiez F, Bragazzi NL. Social Media COVID-19 Information and Vaccine Decision: A Latent Class Analysis. Available at SSRN 3841301. (Submitted to BMC Medical Infor- matics and Decision Making).
  23. David JF, Iyaniwura SA, Yuan P, Tan Y, Kong JD, Zhu H. Modeling the potential impact of indirect transmission on COVID-19 epidemic. medRxiv. (Submitted to Bulletin of Mathematical Biology).