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Dr. Zhilan Feng of Purdue University
Thursday, March 1 from *3:00-4:00 PM in ECA 375 (*note time change from originally scheduled 2 PM start)
Title: Mathematical models of Ebola—Consequences of underlying assumptions
Mathematical models have been used to study Ebola disease transmission dynamics and control for the recent epidemics in West Africa. Many of the models used in these studies are based on the model of Legrand et al. , and most failed to accurately project the outbreak’s course. Although there could be many reasons for this, including incomplete and unreliable data on Ebola epidemiology and lack of empirical data on how disease-control measures quantitatively affect Ebola transmission, we examine the underlying assumptions of the Legrand model, and provide alternate formulations that are simpler and provide additional information regarding the epidemiology of Ebola during an outbreak. We developed three models with different assumptions about disease stage durations, one of which simplifies to the Legrand model while the others have more realistic distributions . Numerical demonstrate the differences in model evaluations of control strategies. Control and basic reproduction numbers for all three models are derived for arbitrary distributions of disease stages.
 Legrand, J., Grais, R.F., Boelle, P.Y., Valleron, A.J., Understanding the dynamics of Ebola epidemics, Epidemiology & Infection, 135, 610-621, 2007.
 Feng, Z., Zheng, Y., Hernandez-Ceron, N., Zhao, H., Glasser, J.W., Hill, A.N., Mathematical models of Ebola - Consequences of underlying assumptions, MBS, 277, 89-107, 2016.
Dr. Fred Brauer of University of British Colombia
Friday, March 2 from 2:00-3:00 PM in ECA 375
Title: Models for Diseases Transmitted by Vectors
Abstract: We give a basic model for vector-transmitted diseases and show how to calculate the reproduction number. We also extend the model to diseases transmitted both by a vector and directly, such as the Zika virus.
Bryan Brooks, Distinguished Professor and Director, Environmental Health Science Program Department of Environmental Science Institute of Biomedical Studies Center for Reservoir and Aquatic Systems Research at Baylor University
Title: Urbanization, Environment and Pharmaceuticals: Advancing Comparative Physiology, Pharmacology and Toxicology
Abstract: Pharmaceuticals are routinely reported in the environment, which indicates an increasingly urban water cycle and highlights a global megatrend. Physicochemical properties and intrinsic biological activity of medicines routinely differ from conventional organic contaminants; thus, diverging applicability domains often challenge environmental chemistry and toxicology computational tools and biological assays originally developed to address historical chemical stressors. Because pharmacology and toxicology information is more readily available for these contaminants of emerging concern than other chemicals in the environment, and many drug targets are conserved across species, leveraging mammalian drug discovery, safety testing and clinical pharmacology information appears useful to define environmental risks and to design less hazardous industrial chemicals. Research is needed to advance biological read across, which promises to reduce uncertainties during chemical assessment aimed at protecting public health and the environment. Whereas such comparative information has been critical to advance an understanding of pharmaceutical hazards and risks in urban ecosystems, studies of medicines with fish and other ecotoxicological models are reciprocally benefiting basic and translational efforts, advancing comparative mechanistic toxicology, and providing robust comparative bridges for integrating conservation and toxicology.
Richard Cordova, Graduate Student in Criminology and Criminal Justice at ASU
Title: The impact of public mass shootings on the publics arming configuration habits
Abstract: The annual incidence of public mass shootings in the US is higher than any other developed country. These incidents receive extreme amounts of media attention, which has been shown to impact the public behavior; past studies have found, for example, that firearm sales significantly increase following high profile massacres. However, the impact these incidences have on firearm storage and carry habits of the public has been poorly studied.
The focus of this study is to analyze how public mass shooting events have impacted the firearm carrying configuration habits of the population through the examination of Transportation Security Administration (TSA) data and USA Today Mass Shooting data. We created for the first time a metric which indicates how members of society carry their firearms and what factors influence their carrying configuration habits. We examine temporal changes in the probability that detected firearms are found loaded and loaded with a round chambered, and we examine how temporal changes in the probabilities possibly relate to the timing of public mass shootings. From the results of this study we find that people appear to be "infected" with a moral panic through exposure to media outlets during the occurrences of public mass shootings. This "infection" was shown to have a substantial correlation to temporal changes in the increased probability of firearms detected at TSA security check points nationwide being found loaded with a round chambered. As time increased from the day of the shooting, it was also seen that there was an exponential decay of firearms being found loaded with a round chambered, indicating the presumed threat of being involved in a future mass shooting lessened. These findings have immediate and impactful implications on public health and crime.
Asma Azizi Boroojeni, Graduate student in Applied Mathematics at Tulane University
Title: An Agent Based Model for the Transmission of Chlamydia through a Heterosexual Network Embedded in Social Contact Network
Abstract: We describe how to generate a bipartite heterosexual network with prescribed joint-degree distribution embedded in prescribed large-scale social contact network. The structure of a sexual network plays an important role in how sexually transmitted infections (STIs) spread. Generating an ensemble of networks which resemble the realworld is crucial to evaluating robust mitigation strategies for public health staff to control STIs. Most of the current algorithms to generate sexual networks only use sexual activity data, such as number of partners per month, to generate the sexual network. Real-world networks also depend on biased mixing based on age, location, and social and work activities. We describe an approach to use a broad range of social activity data to generate possible heterosexual networks of partners. We start with a large-scale simulation of thousands of people in a city as they go through their daily activities, including work, school, shopping, and activities at home. We extract a social network from these activities where the nodes are the people and the edges indicate a social interaction, such as working in the same location. This social network accounts for the correlations between people of different ages, lining in different locations, economic status, and other demographic factors. We then identify a heterosexual bipartite supergraph to define our sexual network. This approach enables us to generate a more realistic sexual network and to extend notification strategies by tracing social friends of infected individuals. We use the heterosexual bipartite sexual network embedded in a social network to study the spread of chlamydia. We evaluate the effectiveness of notifying partners of infected people that they may be infected, as well as the effectiveness of notifying nonsexual social friends that the infection is prevalent. We observed that a person's risk of infection is highly correlated to both their number of concurrent sexual partners and number of partners of partners and beyond that. We observed that when a person is found to be infected, then a combination of both sexual partner and social friend notification is an effective approach to mitigation an epidemic.
Bechir Amdouni, AMLSS Grad student
Cesar Montalvo, AMLSS Grad student
Dustin Padilla, AMLSS Grad student
Vardayani Ratti, John Wesley Young Research Instructor at Dartmouth
Priscilla (Cindy) Greenwood, Professor Emerita Department of Mathematics, University of British Columbia
Title: A stochastic avian flu model with seasonal forcing
Abstract: In a persistent disease such as avian flu, disease transmission rate may vary seasonally. A corresponding model for the number of infectives may have a stable limit cycle. If we incorporate stochasticity in the model, we find that the random fluctuations around the limit cycle have an interesting structure which we identify.