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Brief Review Open Access December 22, 2025

Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology

Olabisi Promise Lawal 1,*, Debra Ukamaka Okeh 2, Patra Chisom Ezeamii 3, Adepeju Kafayat Olowookere 4, Ismaila Muhammed 5, Chukwuebuka Victor Ugwu 6 and Ayodele Blessing Ayo-ige 7
1
Department of Medical Laboratory Science, University of Benin, Benin City, Nigeria
2
Health Division, Corona Management Systems, Abuja, Nigeria
3
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, USA
4
Department of Nanoscience, University of North Carolina at Greensboro, Greensboro, USA
5
Department of Mathematics, Khalifa University, United Arab Emirates
6
Vaccine Research Centre, University of Nigeria, Enugu State, Nigeria
7
Department of Epidemiology in Infectious Diseases, School of Public Health, Yale University, Connecticut, USA
Publihed in: Current Research in Public Health (Volume 5, Issue 1, 2025)
Page(s): 43-53
DOI: 10.31586/gjeid.2025.6242
Received
October 31, 2025
Revised
December 01, 2025
Accepted
December 19, 2025
Published
December 22, 2025
Keywords
Mathematical Modeling; Infectious Disease Epidemiology; Real-time Data Integration; Interdisciplinary and Participatory Approaches; Equity and Co-production
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2025. Published by Scientific Publications
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APA Style
Lawal, O. P. , Lawal, O. P. Okeh, D. U. , Okeh, D. U. Ezeamii, P. C. , Ezeamii, P. C. Olowookere, A. K. , Olowookere, A. K. Muhammed, I. , Muhammed, I. Ugwu, C. V. , & Ugwu, C. V. (2025). Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology. Current Research in Public Health, 5(1), 43-53. https://doi.org/10.31586/gjeid.2025.6242
ACS Style
Lawal, O. P. ; Lawal, O. P. Okeh, D. U. ; Okeh, D. U. Ezeamii, P. C. ; Ezeamii, P. C. Olowookere, A. K. ; Olowookere, A. K. Muhammed, I. ; Muhammed, I. Ugwu, C. V. ; Ugwu, C. V. Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology. Current Research in Public Health 2025 5(1), 43-53. https://doi.org/10.31586/gjeid.2025.6242
Chicago/Turabian Style
Lawal, Olabisi Promise, Olabisi Promise Lawal. Debra Ukamaka Okeh, Debra Ukamaka Okeh. Patra Chisom Ezeamii, Patra Chisom Ezeamii. Adepeju Kafayat Olowookere, Adepeju Kafayat Olowookere. Ismaila Muhammed, Ismaila Muhammed. Chukwuebuka Victor Ugwu, and Chukwuebuka Victor Ugwu. 2025. "Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology". Current Research in Public Health 5, no. 1: 43-53. https://doi.org/10.31586/gjeid.2025.6242
AMA Style
Lawal OP, Lawal OPOkeh DU, Okeh DUEzeamii PC, Ezeamii PCOlowookere AK, Olowookere AKMuhammed I, Muhammed IUgwu CV, Ugwu CV. Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology. Current Research in Public Health. 2025; 5(1):43-53. https://doi.org/10.31586/gjeid.2025.6242 
@Article{crph6242,
AUTHOR = {Lawal, Olabisi Promise and Okeh, Debra Ukamaka and Ezeamii, Patra Chisom and Olowookere, Adepeju Kafayat and Muhammed, Ismaila and Ugwu, Chukwuebuka Victor and Ayo-ige, Ayodele Blessing},
TITLE = {Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology},
JOURNAL = {Current Research in Public Health},
VOLUME = {5},
YEAR = {2025},
NUMBER = {1},
PAGES = {43-53},
URL = {https://www.scipublications.com/journal/index.php/GJEID/article/view/6242},
ISSN = {2831-5162},
DOI = {10.31586/gjeid.2025.6242},
ABSTRACT = {Mathematical modeling plays a central role in infectious disease epidemiology, shaping outbreak response strategies and informing public health policy. The COVID-19 pandemic demonstrated the value of these models but also exposed persistent limitations related to data fragility, lack of transparency, limited stakeholder engagement, and insufficient consideration of social and political contexts. Rather than critiquing modeling as a discipline, this perspective argues for a reorientation of infectious disease modeling toward a more responsive, equity-centered, and participatory paradigm. We propose a conceptual framework built on three interrelated principles: adaptability through real-time data integration, transparency via open-source and reproducible practices, and relevance through interdisciplinary and co-produced model design. Drawing on illustrative examples from COVID-19 and dengue control efforts, we highlight how integrating behavioral dynamics, local knowledge, and policy feedback can improve model usefulness and public trust. Reconceptualizing models as dynamic systems of inquiry rather than static forecasting tools can enhance decision-making and promote more equitable and effective responses to future public health emergencies.},
}
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%A Lawal, Olabisi Promise
%A Okeh, Debra Ukamaka
%A Ezeamii, Patra Chisom
%A Olowookere, Adepeju Kafayat
%A Muhammed, Ismaila
%A Ugwu, Chukwuebuka Victor
%A Ayo-ige, Ayodele Blessing
%D 2025
%J Current Research in Public Health

%@ 2831-5162
%V 5
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%T Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology
%M doi:10.31586/gjeid.2025.6242
%U https://www.scipublications.com/journal/index.php/GJEID/article/view/6242

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AU  - Lawal, Olabisi Promise
AU  - Okeh, Debra Ukamaka
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AU  - Olowookere, Adepeju Kafayat
AU  - Muhammed, Ismaila
AU  - Ugwu, Chukwuebuka Victor
AU  - Ayo-ige, Ayodele Blessing
TI  - Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology
T2  - Current Research in Public Health
PY  - 2025
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SN  - 2831-5162
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UR  - https://www.scipublications.com/journal/index.php/GJEID/article/view/6242
AB  - Mathematical modeling plays a central role in infectious disease epidemiology, shaping outbreak response strategies and informing public health policy. The COVID-19 pandemic demonstrated the value of these models but also exposed persistent limitations related to data fragility, lack of transparency, limited stakeholder engagement, and insufficient consideration of social and political contexts. Rather than critiquing modeling as a discipline, this perspective argues for a reorientation of infectious disease modeling toward a more responsive, equity-centered, and participatory paradigm. We propose a conceptual framework built on three interrelated principles: adaptability through real-time data integration, transparency via open-source and reproducible practices, and relevance through interdisciplinary and co-produced model design. Drawing on illustrative examples from COVID-19 and dengue control efforts, we highlight how integrating behavioral dynamics, local knowledge, and policy feedback can improve model usefulness and public trust. Reconceptualizing models as dynamic systems of inquiry rather than static forecasting tools can enhance decision-making and promote more equitable and effective responses to future public health emergencies.
DO  - Reimagining Mathematical Modeling for a Responsive and Integrated Future in Infectious Disease Epidemiology
TI  - 10.31586/gjeid.2025.6242
ER  -