Muzhinyi, K.Garira, W.Mathebula, D.Maphiri, Azwindini Delinah2024-10-012024-10-012024-09-06Maphiri, A.D. 2024. Multiscale Modelling of Foodborne Diseases. . .https://univendspace.univen.ac.za/handle/11602/2689Ph.D. (Mathematics)Department of Mathematical and Computational SciencesInfectious disease systems are essentially multiscale complex system wherein pathogens multiply within hosts, spread across people, and infect entire populations of hosts. The description of most biological processes involves multiple, interconnected phenomena occurring on different spatial and temporal scales in the human body. Traditional approaches for modelling infectious disease systems rely on the principles and concepts of the transmission mechanism theory that considers transmission to be the primary cause of infectious disease spread at the macroscale. Modellers of infectious diseases are increasingly using multiscale modelling approach in response to this challenge. Multiscale models of infectious disease systems encompass intricate structures that revolve around the interplay of three distinct sub-systems: the host, the pathogen, and the environmental subsystems. The replication-transmission relativity theory is a novel theory designed for the purpose of multiscale modeling of infectious disease systems, accounting for variations in time and space by incorporating pathogen replication that leads to transmission. Replicationtransmission relativity theory consists of seven distinct levels of organization within an infectious disease system, each level including the within-host scale (microscale) and between-host scale (macroscale). Five separate classifications of multiscale models can be formulated that integrate the microscale and macroscale. A research gap has been created in an attempt to establish a multiscale framework in order to understand the mechanisms on how foodborne pathogens cause infections on human beings and animals, as very little has been done in modelling of foodborne disease. The primary goal of this study is to create multiscale models for foodborne diseases to examine whether a mutual influence exists between the microscale and macroscale, guided by the principles of replication-relativity theory. The multiscale models are developed by considering three environmental transmitted diseases at host level caused by pathogens: norovirus, E. coli O157:H7 and taenia solium. We start by developing a single-scale model of foodborne diseases caused by viruses in general, which is then extended to create a multiscale model for norovirus. We formulate a non-standard finite difference scheme for the single-scale model, norovirus, and E. coli O157:H7. For taenia solium, we use ODE solvers in Python, specifically, ODE int function in the sci.integrate. The numerical findings from the study confirm the applicability of the replication-transmission relativity theory in cases where the reciprocal impact between the within-host scale and the between-host scale involves both infection/super-infection (for the effect of the between-host scale on the within-host scale) and pathogen excretion/shedding (for the effect of the within-host scale on the between-host scale). We expect that our study will help modellers integrate microscale and macroscale dynamics across various levels of organization within infectious disease systems.1 online resource (xiii, )enUniversity of VendaUCTD615.954Foodborne diseasesFood poisoningCommunicable diseasesAnisakiasisThesisMaphiri AD. Multiscale Modelling of Foodborne Diseases. []. , 2024 [cited yyyy month dd]. Available from:Maphiri, A. D. (2024). <i>Multiscale Modelling of Foodborne Diseases</i>. (). . Retrieved fromMaphiri, Azwindini Delinah. <i>"Multiscale Modelling of Foodborne Diseases."</i> ., , 2024.TY - Thesis AU - Maphiri, Azwindini Delinah AB - Infectious disease systems are essentially multiscale complex system wherein pathogens multiply within hosts, spread across people, and infect entire populations of hosts. The description of most biological processes involves multiple, interconnected phenomena occurring on different spatial and temporal scales in the human body. Traditional approaches for modelling infectious disease systems rely on the principles and concepts of the transmission mechanism theory that considers transmission to be the primary cause of infectious disease spread at the macroscale. Modellers of infectious diseases are increasingly using multiscale modelling approach in response to this challenge. Multiscale models of infectious disease systems encompass intricate structures that revolve around the interplay of three distinct sub-systems: the host, the pathogen, and the environmental subsystems. The replication-transmission relativity theory is a novel theory designed for the purpose of multiscale modeling of infectious disease systems, accounting for variations in time and space by incorporating pathogen replication that leads to transmission. Replicationtransmission relativity theory consists of seven distinct levels of organization within an infectious disease system, each level including the within-host scale (microscale) and between-host scale (macroscale). Five separate classifications of multiscale models can be formulated that integrate the microscale and macroscale. A research gap has been created in an attempt to establish a multiscale framework in order to understand the mechanisms on how foodborne pathogens cause infections on human beings and animals, as very little has been done in modelling of foodborne disease. The primary goal of this study is to create multiscale models for foodborne diseases to examine whether a mutual influence exists between the microscale and macroscale, guided by the principles of replication-relativity theory. The multiscale models are developed by considering three environmental transmitted diseases at host level caused by pathogens: norovirus, E. coli O157:H7 and taenia solium. We start by developing a single-scale model of foodborne diseases caused by viruses in general, which is then extended to create a multiscale model for norovirus. We formulate a non-standard finite difference scheme for the single-scale model, norovirus, and E. coli O157:H7. For taenia solium, we use ODE solvers in Python, specifically, ODE int function in the sci.integrate. The numerical findings from the study confirm the applicability of the replication-transmission relativity theory in cases where the reciprocal impact between the within-host scale and the between-host scale involves both infection/super-infection (for the effect of the between-host scale on the within-host scale) and pathogen excretion/shedding (for the effect of the within-host scale on the between-host scale). We expect that our study will help modellers integrate microscale and macroscale dynamics across various levels of organization within infectious disease systems. DA - 2024-09-06 DB - ResearchSpace DP - Univen LK - https://univendspace.univen.ac.za PY - 2024 T1 - Multiscale Modelling of Foodborne Diseases TI - Multiscale Modelling of Foodborne Diseases UR - ER -