Qimin Huang

My research interests lie in modeling and analysis of problems originated in biological and life sciences, in particular (i) modeling of infectious diseases, and (ii) developing optimal strategies to control diseases in public health practice. The tools I have been using are differential equations, statistical analysis, and scientific computing. I’m open to developing new skills and ideas, such as big data analytics, required in interdisciplinary research.

I have experience in dealing with real data analysis, involving parameter estimation, dynamic model development, numerical simulations, and optimal control. I have also been involved in collaboration with the School of Medicine, Center for Global Health and Diseases, and the Department of Computer and Data Sciences, to study major public health problems arising from COVID-19, antimicrobial drug resistance & phage therapy, Schistosomiasis, Children diseases, and vaccination.

• Linear Algebra
• Math in Contemporary Society
• Applied Integral Calculus

1. Q. Huang, D. Gurarie, M. Ndeffo-Mbah, N. Lo, and C. H. King, Schistosoma transmission in a dynamic seasonal environment and its impact on the effectiveness of disease control, The Journal of Infectious Diseases, 225.6 (2022): 1050-1061. https://doi.org/10.1093/infdis/jiaa746
2. D. Cator, Q. Huang, A. Mondal. M. Ndeffo-Mbah, D. Gurarie, Individual-based modeling of COVID-19 transmission in college communities, Mathematical Biosciences and Engineering, 19.12 (2022): 13861-13877. doi: 10.3934/mbe.2022646
3. K. Yin, A. Mondal, M. Ndeffo-Mbah, P. Banerjee, Q. Huang, D. Gurarie, Bayesian inference for COVID-19 transmission dynamics in India using a modified SEIR model, mathematics, 10.21 (2022): 4037.  https://doi.org/10.3390/math10214037
4. Q. Huang, A. Mondal, X. Jiang, M. A. Horn, F. Fan, P. Fu, X. Wang, H. Zhao, M. Ndeffo-Mbah, D. Gurarie, SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study, Royal Society Open Science 8.3 (2021): 201895.https://doi.org/10.1098/rsos.201895
5. X. Wang, X. Jiang, Q. Huang, H. Wang, D. Gurarie, M. Ndeffo-Mbah, F. Fan, P. Fu, M. A. Horn, S. Xu, A. Mondal, H. Zhao, and Y. Bai, Risk factors of SARS-CoV-2 infection in healthcare workers: a retrospective study of a nosocomial outbreak, Sleep Medicine: X 2 (2020): 100028. https://doi.org/10.1016/j.sleepx.2020.100028
6. H. Kang, Q. Huang, and S. Ruan, Periodic solutions of an age-structured epidemic model with periodic infection rate, Communications on Pure & Applied Analysis, 19.10 (2020) : 4955-4972. Doi: 10.3934/cpaa.2020220
7. S. Banuelos, H. Gulbudak, M. A. Horn, Q. Huang, A. Nandi, H. Ryu, and R. Segal, Investigating the impact of combination phage and antibiotic therapy: a modeling study, 2021. in book: Using Mathematics to Understand Biological Complexity, Association for Women in Mathematics Series, vol 22. Springer. DOI: 10.1007/978-3-030-57129-0_6
8. Q. Huang, X. Huo, and S. Ruan, Optimal control in an epidemiological model of Methicillin-resistant Staphylococcus aureus infections in hospitals, Mathematical Biosciences, 311 (2019), 13–30. https://doi.org/10.1016/j.mbs.2019.01.013
9. Q. Huang, M. A. Horn, and S. Ruan, Modeling the effect of antibiotic exposure on the transmission of Methicillin-resistant Staphylococcus aureus in hospitals with environmental contamination, Mathematical Biosciences and Engineering, 16.5 (2019), 3641-3673. doi: 10.3934/mbe.2019181
10. Q. Huang, X. Huo, D. Miller, and S. Ruan, Modeling the seasonality of Methicillin-resistant Staphylococcus aureus infections in hospitals with environmental contamination, Journal of Biological Dynamics, 13 (2018), s99-s122. https://doi.org/10.1080/17513758.2018.1510049