Dynamics of COVID-malaria co-infection with optimal control and cost-effectiveness analysis
Due to the geographic overlap between the distributions of COVID-19 and malaria, co-infection between these diseases is highly possible and could result in severe health issues. To understand the disease dynamics of the co-infection, a new mathematical model, which incorporates vaccination as an intervention, is formulated. Theoretical analysis suggests that both the sub-models (COVID-19-only and malaria-only sub-models) and the full model undergo backward bifurcation when their respective reproduction number is less than unity. It further suggests that in the absence of re-infection both the sub-models and the full model have a globally asymptotically stable disease free equilibrium whenever the corresponding reproduction number is less than unity. The study further reveals that malaria infection may increase the risk of COVID-19, whereas COVID-19 infection may not always increase the risk of malaria. Numerical simulation also suggests that COVID-19 fatality rate increases by approximately 5 folds due to co-infection with malaria while co-infection with COVID-19 may not have significant effect on malaria fatality rate. It again shows that malaria cases can be reduced by approximately 60% if 90% individuals use non-pharmaceutical interventions (NPIs), such as nets and repellents of 90% efficacy. Using the expression of the vaccine-induced herd immunity threshold and contour plot it is shown that at least 75% individuals should be vaccinated with a vaccine of 85% efficacy to achieve herd immunity against malaria. The study also shows that strategy C (prevention strategy for both COVID-19 and malaria) is the most cost-effective strategy to mitigate the burden of co-infection.
Authors
- Shikha Saha (ORCID: https://orcid.org/0000-0003-0647-6918)
- Amit Kumar Saha (ORCID: https://orcid.org/0000-0002-7915-1084)
- Chandra Nath Podder
Institutions
- Bangladesh University of Engineering and Technology (BD)
- University of Dhaka (BD)
Publication Details
- Journal
- Partial Differential Equations in Applied Mathematics
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1016/j.padiff.2025.101217
- Citations
- 1
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 1.37