MS07 - MEPI-2
Cartoon Room 2 (#3147) in The Ohio Union

Disease Dynamics Across Scales

Thursday, July 20 at 04:00pm

SMB2023 SMB2023 Follow Thursday during the "MS07" time block.
Room assignment: Cartoon Room 2 (#3147) in The Ohio Union.
Note: this minisymposia has multiple sessions. The other session is MS06-MEPI-2 (click here).

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Joshua Caleb Macdonald, Hayriye Gulbudak


Infectious disease dynamics operate across biological scales: pathogens replicate within hosts, but transmit among populations. Functional changes in the pathogen-host interaction thus generate cascading effects across organizational scales. Management strategies and the degree to which these strategies are successfully implemented may create selection pressures which drive evolution and which in turn impact the efficacy of management strategies. Thus in both ecology and epidemiology improved mechanistic understanding of cross-scale effects represents a challenge of critical importance. Growing human populations and ecosystem destruction is bringing humans into closer contact with other animals. As such epidemics and pandemics are expected to increase in frequency in the coming decades. Thus increased understanding of methods to control the spread of disease at the population level and of the mechanisms by which diseases replicate and interact with the immune system at the within-host level are of critical importance.In this mini-symposium we present talks that seek to understand disease dynamics within and across differing organizational scales.

Summer Atkins

Louisiana State University (Department of Mathematics and Statistics)
"An immuno-epidemiological model of foot-and-mouth disease in African buffalo"
We present a novel immuno-epidemiological model of Foot-and-Mouth Disease (FMD) in African buffalo host population. Upon infection, the hosts can undergo two phases, namely the acute and the carrier stages. In our model, we divide the infectious population based upon these two stages so that we can dynamically capture the immunological characteristics of both phases of the disease and to better understand the carrier’s role in transmission. We first define the within-host immune kinetics dependent basic disease reproduction R0 and show that it is a threshold condition for the local stability of the disease-free equilibrium and existence of endemic equilibrium. By using a sensitivity analysis (SA) approach developed for multi-scale models, we assess the impact of the acute infection and carrier phase immunological parameters on R0. Interestingly, our numerical results show that the within-carrier infected host immune kinetics parameters and the susceptible individual recruitment rates play significant roles in disease persistence, which are consistent with experimental and field studies.
Additional authors: Hayriye Gulbudak, University of Louisiana at Lafayetter; Shane Welker, University of North Alabama; Houston Smith, University of Louisiana

Leah LeJeune

Virginia Tech (Department of Mathematics)
"Cross-immunity and transmission influences in a multistrain host-pathogen cholera model"
We investigate possible long-term outcomes of the spread of cholera in a human population by considering the effects of pathogen growth in the environment and strain diversity on human transmission and recovery dynamics. The bacteria Vibrio cholerae relies heavily upon an aquatic reservoir as a transmission route. There are two main cholera strains, called serotypes, which induce distinct host immune response, with a degree of cross-immunity upon recovery. To better understand disease dynamics to combat future outbreaks, this work combines and extends two previously studied ordinary differential equation epidemiological models to consider interactions between the host population and two strains of the pathogen in an aquatic reservoir. Of particular interest are undamped, anti-phase periodic solutions which display a type of coexistence observed in past outbreaks where strains routinely switch dominance. Equilibria analysis and simulations show cross-immunity and transmission pathways are key influencers of oscillatory dynamics and should be considered when constructing efficient control measures against outbreaks.
Additional authors: Cameron Browne

Alun L. Lloyd

North Carolina State University (Biomathematics Graduate Program and Department of Mathematics)
"Spatial Spread of Dengue Virus: Appropriate Spatial Scales for Transmission"
Dengue virus is the most significant viral mosquito-borne infection in terms of its human impact. Mathematical modeling has contributed to our understanding of its transmission and control strategies aimed at halting its spread. We consider the spread of dengue at the level of a city. Because the Aedes aegypti mosquito that transmits dengue has relatively low dispersal over its lifetime, human movement plays a major role in its spread and the household is a key spatial scale on which transmission occurs. Simple multi-patch deterministic models---metapopulation models, which consider the population to be described as a network of well-mixed patches---have been used to model city-level spatial spread and can provide expressions for key epidemiological quantities such as the basic reproduction number, $R_0$. We compare dynamics predicted by such models with results from individual-based network models and illustrate several discrepancies. We argue that the small size of households and local depletion of susceptibles are key features of the dynamics that are not captured in the standard $R_0$ analysis of the ODE model. In order to gain analytic understanding, we propose the use of household-level models, which can be analyzed using branching process theory. Our work, which echoes results previously found for directly-transmitted infections, highlights the importance of correctly accounting for the relevant spatial scales on which transmission occurs.

Erin Gorsich

University of Warwick (Zeeman Institute for Systems Biology and Infectious Disease Epidemiology)
"Modelling endemic Rift Valley fever virus"
Rift Valley fever (RVF) is a mosquito-borne virus that causes haemorrhagic fever in livestock and wildlife, as well as spill-over infections in humans. Large-scale epidemics occur sporadically in Africa following heavy rainfall. In some regions, infection also cycles endemically at low levels in livestock, yet the mechanisms influencing transmission and the scale at which they occur remains relatively unknown. Here, we integrate a mathematical model with longitudinal infection, entomological and climate data from multiple villages in Kwazulu-Natal, South Africa. Our modelling approach accounts for nonlinearities in the risk of exposure, susceptible depletion, and variable sampling effort to evaluate potential drivers of infection. Hypotheses representing high heterogeneity in RVF incidence across the study villages were supported, and variation was mechanistically explained by climatic and entomological data. This highlights the value of methods that harness statistical model selection in a mechanistic framework.

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