Advances in Infectious Disease Modeling

Tuesday, June 15 at 05:45pm (PDT)
Wednesday, June 16 at 01:45am (BST)
Wednesday, June 16 09:45am (KST)

SMB2021 SMB2021 Follow Tuesday (Wednesday) during the "MS09" time block.
Note: this minisymposia has multiple sessions. The second session is MS08-MEPI (click here).

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Lihong Zhao (University of California Merced, United States), Ling Xue (Harbin Engineering University, China), Suzanne Sindi (University of California Merced, United States)


This mini-symposium will bring together established and up-and-coming researchers to explore how mathematical and computational models can be applied to address public health challenges for a wide range of infectious diseases, including Wolbachia, Ebola, COVID-19, etc. The presentations will range from theoretical perspective, such as developing models to better understand the transmission dynamics and spatiotemporal patterns, to more applied aspects, such as fitting models to evaluate the impact of control strategies. Current mathematical and computational modeling challenges will also be discussed.

Steve Krone

(Department of Mathematics and Statistical Sciences, University of Idaho, United States)
"The Timing and Nature of Behavioral Responses Affect the Course of an Epidemic"
During an epidemic, the interplay of disease and opinion dynamics can lead to outcomes that are different from those predicted based on disease dynamics alone. Opinions and the behaviours they elicit are complex, so modelling them requires a measure of abstraction and simplification. Here, we develop a differential equation model that couples SIR-type disease dynamics with opinion dynamics. We assume a spectrum of opinions that change based on current levels of infection as well as interactions that to some extent amplify the opinions of like-minded individuals. Susceptibility to infection is based on the level of prophylaxis (disease avoidance) that an opinion engenders. In this setting, we observe how the severity of an epidemic is influenced by the distribution of opinions at disease introduction, the relative rates of opinion and disease dynamics, and the amount of opinion amplification. Some insight is gained by considering how the effective reproduction number is influenced by the combination of opinion and disease dynamics.

Skylar Grey

(University of Wisconsin Madison)
"Contact Tracing during an Ebola Outbreak"
Be it Ebola, MERS, or SARS-CoV-2, contact tracing plays a key role in controlling an outbreak. To examine the role of contact tracers, we developed a system of ordinary differential equations to model the 2014-2016 Ebola outbreak in Sierra Leone. In the model we incorporated novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Utilizing data and simulations, we explore the role contact tracing played in eventually ending the outbreak and examine the potential impact of improved contact tracing on the death toll.

Lihong Zhao

(Department of Applied Mathematics, University of California Merced, United States)
"Association of Microbiome Dynamics with Chlamydia Infection"
Chlamydia trachomatics (C. trachomatics) is a major cause of bacterial sexually transmitted disease in the United States and is associated with adverse outcomes in the upper genital tract of women. It is unclear why some women are more likely to develop asymptomatic infection, have severe infection, or stay uninfected after exposure to C. trachomatics. Prior studies have shown a relationship between vaginal microbial composition and susceptibility to sexually transmitted infections including Chlamydia. However, little is known about the microbiome dynamics, especially in the upper genital tract, and its association with Chlamydia infection. We use mice as a model organism, seek to elucidate the association of genital tract microbiome dynamics with Chlamydia infection, and determining whether the time of infection affects the genital tract microbiome over time via analyzing the data collected before and over the course of infection.

Xiaotian Wu

(College of Arts and Sciences, Shanghai Maritime University, China)
"Modelling Triatomine Bug Population and Trypanosoma Rangeli Transmission: Co-feeding, Pathogenic Effect and Linkage with Chagas Disease"
A parasite of Trypanosoma rangeli is not pathogenic to human but pathogenic to the same vector species of Chagas disease. This parasite can induce the behavior changes of the infected vectors and subsequently impact the transmission dynamics of Chagas disease. In this talk, a mathematical model incorporating both systemic and co-feeding transmission routes and accounting for the pathogenic effect using infection-induced fecundity and fertility change of the triatomine bugs is presented. In terms of basic reproduction numbers R_v and R_0, the dynamical behaviors of the ecological and epidemiological systems are characterized. Moreover, when both R_v and R_0 are greater than unity, a unique parasite positive equilibrium E* appears which can be unstable and periodic oscillations can be observed where the pathogenic effect plays a significant role.

Hosted by SMB2021 Follow
Virtual conference of the Society for Mathematical Biology, 2021.