A systematic review of mathematical models of the Ebola virus disease
Abstract
Several studies have surveyed the literature of mathematical modelling of the Ebola virus disease (EVD). However, most of these reviews did not report any work published after January 2016. Furthermore, those that have considered such work focused on particular types of models, presented only findings for some models, or included just a few articles published in 2016. Additionally, these reviews did not focus on examining models by systematically identifying advantages and limitations. In light of this, we conduct a systematic review of mathematical models of EVD. We focus on the PubMed publications between January 2016 and December 2018. The objectives of this review are to present an overview of the mathematical modelling literature on EVD, identify gaps, and improve prospective models by addressing current models’ constraints. The reported studies are categorised broadly in terms of the modelling approaches, model conclusions and constraints. Crucial modelling gaps are identified, and future research motivated.
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Waters, E., Gibbs, L., Tadic, M., Ukoumunne, O. C., Magarey, A., Okely, A. D., de Silva, A., Armit, C., Green, J., O’Connor, T., et al. (2018) · BMC Public Health · doi:10.1186/s12889-017-4625-9 · Cited by 94 · see citing works
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Marburg virus disease outbreaks, mathematical models, and disease parameters: a systematic review
Cuomo-Dannenburg, G., McCain, K., McCabe, R., Unwin, H. J. T., Doohan, P., Nash, R. K., Hicks, J. T., Charniga, K., Geismar, C., Lambert, B., et al. (2024) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(23)00515-7 · Cited by 59 · see citing works
“This systematic review presents a comprehensive set of mathematical models, outbreaks, and epidemiological parameters of MVD. Historical outbreaks and case reports in the peer-reviewed literature for MVD were rare and small in size, relative to many other pathogens, including other viral hemorrhagic fevers such as Ebo…”
InfluentialEbola virus disease mathematical models and epidemiological parameters: a systematic review
Nash, R. K., Bhatia, S., Morgenstern, C., Doohan, P., Jorgensen, D., McCain, K., McCabe, R., Nikitin, D., Forna, A., Cuomo-Dannenburg, G., et al. (2024) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(24)00374-8 · Cited by 35 · see citing works
- Authors
- Abdalla, S. J. M., Chirove, F., & Govinder, K. S.
- Affiliations
- University of KwaZulu-Natal (ZA)
- University of Johannesburg (ZA)
- Corresponding author
- Abdalla, Suliman Jamiel M.
- Venue
- International Journal of Modelling and Simulation
- Publisher
- Informa UK Limited
- Published
- 2021-09-28
- Volume
- 42
- Issue
- 5
- Pages
- 814-830
- ISSN
- 0228-6203 (ISSN-L)
- 1925-7082
- OpenAlex
- W3203925742
- Cited by
- 13
- References
- 1
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 4 · 2023: 3 · 2022: 2
- FWCI
- 0.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Modelling and Simulation (publishedVersion)
- Funders
- National Research Foundation - South Africa (110931)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- Ebola virus disease, mathematical model, epidemic modeling, model limitations, research gaps, infectious disease transmission
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