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Mathematical models of malaria--a review
Sandip Mandal1, Ram Rup Sarkar, Somdatta Sinha
1Centre for Cellular and Molecular Biology (CSIR), Uppal Road, Hyderabad, India.
Malaria Journal
|July 23, 2011
Summary
Mathematical models offer a framework for understanding malaria transmission. This review assesses their evolution and efficacy in controlling the disease, crucial for public health strategies.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- Malaria transmission dynamics have been studied using mathematical models for over a century.
- Despite progress, malaria remains a significant global health threat due to environmental and socioeconomic factors.
- Critical assessment of existing models is needed to understand their efficacy in host-parasite biology.
Purpose of the Study:
- To develop a hierarchical structure of deterministic malaria transmission models.
- To elaborate on the evolution of modeling strategies incorporating host-vector-parasite interactions.
- To provide a comprehensive survey of malaria modeling for researchers and public health professionals.
Main Methods:
- Review of key mathematical models, starting from the basic Ross model.
- Focus on deterministic differential equation-based epidemiological compartment models.
- Inclusion of data-based statistical models for a broader perspective.
Main Results:
- Discussion of the evolution of malaria modeling from basic to complex structures.
- Elaboration on how models incorporate host-vector-parasite interactions to describe disease incidence.
- Summary of modeling approaches to aid in understanding malaria transmission and control.
Conclusions:
- Mathematical models are essential for understanding and controlling malaria transmission.
- The evolution of models reflects increasing complexity in capturing host-vector-parasite interactions.
- This survey facilitates interdisciplinary collaboration for improved malaria control strategies.
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