2026-09-22T11:46:15Zhttps://univendspace.univen.ac.za/server/oai/requestoai:univendspace.univen.ac.za:11602/30092026-02-10T06:17:16Zcom_11602_1927com_11602_1914com_11602_1897com_11602_737col_11602_2138col_11602_738
Netshikweta, R.
Garira, W.
Mahada, Awelani Sydney
2025
2025-10-16T08:21:47Z
2025-10-16T08:21:47Z
2025-09-05
Mahada, A.S. 2025. A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics. . .
https://univendspace.univen.ac.za/handle/11602/3009
Mahada AS. A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics. []. , 2025 [cited yyyy month dd]. Available from:
Mahada, A. S. (2025). <i>A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics</i>. (). . Retrieved from
Mahada, Awelani Sydney. <i>"A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics."</i> ., , 2025.
TY - Dissertation
AU - Mahada, Awelani Sydney
AB - Introduction: Malaria is among the World’s most lethal infectious disease. It is
caused by a parasitic pathogen transmitted by the Anopheles mosquito, which
inoculates sporozoites into the human host during a blood meal. The population
dynamics of malaria are well-known for their complexity, stemming not only from
the parasite’s lifecycle, which involves two hosts (humans and mosquitoes)but
also from the intricate replication and transmission cycles across different levels
of the infectious disease system organization. Like other infectious disease systems,
malaria infections inherit multilevel and multiscale systems, which pose significant
challenges to efforts aimed at eliminating and ultimately eradicating the
infection in a malaria-endemic population.
Methodology Mathematical modeling in the study of complex system has proven
to be an invaluable tool for understanding and predicting the behaviour and dynamics
of a complex system within the domain of complexity science. Thus, in
this study, we propose a multiscale modelling framework that captures the dynamics
of malaria across three organizational levels within infectious disease
systems implicated in the spread of malaria in a community. We begin by formulating
a mathematical model to describe the development and progression of
malaria parasites within the liver and tissue(blood) stages of an infected human
host. This is followed by the formulation of a multiscale model that integrates both
the inside(i.e.,the organ-tissue level)host and the outside (i.e., the host level) host
malaria dynamics.
Results Mathematical analysis for both the malaria models presented in this
study was carried out and proved that all the models are mathematically and
epidemiologically well-posed. We also compute the basic reproduction number
R0 for both models and use the R0 to determine the local and global stability of
the disease-free equilibriumas well as the local stability of endemic equilibrium
of both models, respectively. We demonstrate that if R0 < 1, then the diseasefree
equilibrium pointy of both models is locally and globally asymptotically stable,
respevctively. However, if R0 > 1 the endemic equilibrium point of both models
is locally asymptotically stable. The numerical results for both the models have
demonstrated that the goal of intervention during malaria infection should be to
reduce the rates at which merozoites and gametocytes invade healthy liver tissue
as well as the blood cells. Hence it is recommended that interventions during malaria
infection be directed on reducing the pace at which merozoites infect healthy
blood cells and the density of merozoites in circulation.
Conclusion The study presents a method that incoporates the complexity of malaria
pathogens which is significant not only for malaria treatment but also for other
vector-borne disease system control treatment strategies.
DA - 2025-09-05
DB - ResearchSpace
DP - Univen
KW - Merozoites
KW - Gametocyctes
KW - Sporozoites
KW - Anopheles
KW - Gametes
KW - Schizonts
KW - Oocysts
LK - https://univendspace.univen.ac.za
PY - 2025
T1 - A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics
TI - A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics
UR -
ER -
MSC in Applied Mathematics
Department of Mathematical and Computational Sciences
Introduction: Malaria is among the World’s most lethal infectious disease. It is
caused by a parasitic pathogen transmitted by the Anopheles mosquito, which
inoculates sporozoites into the human host during a blood meal. The population
dynamics of malaria are well-known for their complexity, stemming not only from
the parasite’s lifecycle, which involves two hosts (humans and mosquitoes)but
also from the intricate replication and transmission cycles across different levels
of the infectious disease system organization. Like other infectious disease systems,
malaria infections inherit multilevel and multiscale systems, which pose significant
challenges to efforts aimed at eliminating and ultimately eradicating the
infection in a malaria-endemic population.
Methodology Mathematical modeling in the study of complex system has proven
to be an invaluable tool for understanding and predicting the behaviour and dynamics
of a complex system within the domain of complexity science. Thus, in
this study, we propose a multiscale modelling framework that captures the dynamics
of malaria across three organizational levels within infectious disease
systems implicated in the spread of malaria in a community. We begin by formulating
a mathematical model to describe the development and progression of
malaria parasites within the liver and tissue(blood) stages of an infected human
host. This is followed by the formulation of a multiscale model that integrates both
the inside(i.e.,the organ-tissue level)host and the outside (i.e., the host level) host
malaria dynamics.
Results Mathematical analysis for both the malaria models presented in this
study was carried out and proved that all the models are mathematically and
epidemiologically well-posed. We also compute the basic reproduction number
R0 for both models and use the R0 to determine the local and global stability of
the disease-free equilibriumas well as the local stability of endemic equilibrium
of both models, respectively. We demonstrate that if R0 < 1, then the diseasefree
equilibrium pointy of both models is locally and globally asymptotically stable,
respevctively. However, if R0 > 1 the endemic equilibrium point of both models
is locally asymptotically stable. The numerical results for both the models have
demonstrated that the goal of intervention during malaria infection should be to
reduce the rates at which merozoites and gametocytes invade healthy liver tissue
as well as the blood cells. Hence it is recommended that interventions during malaria
infection be directed on reducing the pace at which merozoites infect healthy
blood cells and the density of merozoites in circulation.
Conclusion The study presents a method that incoporates the complexity of malaria
pathogens which is significant not only for malaria treatment but also for other
vector-borne disease system control treatment strategies.
1 online resource (x, 97 leaves): illustrations
en
PDF
University of Venda
Merozoites
Gametocyctes
Sporozoites
Anopheles
Gametes
Schizonts
Oocysts
UCTD
616.9362
Malaria
Fever
Protozoan disease
Plasmodium
Plasmodium falciparum
Anopheles
Mosquitoes
A Multi-level Model for a Vector-Borne Organ to Tissue life Cycle Dynamics
Dissertation
embargo