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Research Areas

Mathematical Biology, Optimal Control, Computational Mathematics, and Foodborne Disease

Education

University of Johannesburg, PhD Applied Mathematics 
University of California, San Diego, Postdoc

Publications

1. Chukwu, C.W., Tchoumi, S.Y., Koutou, O. et al. Exploring the epidemiological impact of Pneumonia–Listeriosis co-infection in the human population: a modeling and optimal control study. Int. J. Dynam. Control 13, 197 (2025)..
   
2. Dipo Aldila, Chidozie Williams Chukwu, Eka D. A. Ginting, F. Fatmawati, Faishal Farrel Herdicho, Mohammad Ivan Azis, S. Sutrisno. Backward bifurcation and periodic dynamics in a tuberculosis model with integrated control strategies. Mathematical Biosciences and Engineering, 2025, 22(10): 2720–2760, .https://doi: 10.3934/mbe.2025100.
   
3.  Chukwu C.W., Chazuka Z., Safdar S., Alida D., Assessing Syphilis transmission among MSM population incorporating low and high-risk infection: a modeling study. Comp. Appl. Math. 43, 205 (2024), .
   
4. Chukwu, CW, Stephane Yanick Tchoumi, Z. Chazuka, M. L. Juga, and G. Obaido. “Assessing the impact of human behavior towards preventative measures on COVID-19 dynamics for Gauteng, South Africa: a simulation and forecasting approach.” (2024). doi: .
   
5. Obaido, G., Achilonu, O., Ogbuokiri, B., Amadi, C.S., Habeebullahi, L., Ohalloran, T., Chukwu, C.W., Mienye, E.D., Aliyu, M., Fasawe, O. and Modupe, I.A., 2024. An improved framework for detecting thyroid disease using filter-based feature selection and stacking ensemble. IEEE Access, 12, pp.89098-89112. DOI: .
   
6. Agusto FB, Fabris-Rotelli I, Edholm CJ, Maposa I, Chirove F, Chukwu CW, et al. (2025) An agent-based model for household COVID-19 transmission in Gauteng, South Africa. PLoS One 20(7): e0325619. .

Funding

Current Grants

1. AMS-Simon Travel Grant, 2024-2026, Awarded $5000

Previous Grants (If Any)

Research Projects

Modeling the Transmission Dynamics and Health Burden of Campylobacteriosis in the United States: Integrating Environmental Determinants and Comorbidities

This project develops a mathematical model to understand how environmental factors and health conditions influence the spread of Campylobacteriosis in the U.S. The study integrates surveillance and environmental data to quantify infection risk, identify vulnerable populations, and simulate targeted interventions. By linking environmental determinants and host comorbidities, the model provides new insight into foodborne disease dynamics and supports evidence-based prevention strategies.

Time Series Analysis and Application of Machine learning approach in the Prediction of Maize Leaf Disease

This study combines time-series analysis and machine-learning methods to forecast maize leaf disease outbreaks. Using historical disease data, the research develops hybrid models that enhance early detection and improve prediction accuracy. The approach supports sustainable agriculture by providing farmers and extension workers with practical forecasting tools for timely disease management.

A Stochastic Delay Differential Model of Chlamydia Transmission Incorporating Behavioral Change Dynamics

We formulate a stochastic delay model to study Chlamydia transmission in the context of behavioral responses and reporting delays. The framework captures random effects, treatment lags, and changes in individual behavior, such as the adoption of safer practices or increased testing. Through analysis and simulation, the project examines how delays and uncertainties impact outbreak persistence and control, guiding effective behavioral and public health interventions.

Research Group

Undergraduate Students

• Luke MacPhee
• Bianco Delaney

Graduate Students

• Duncan Kishoyian