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- All Subjects: Mathematical Modeling
In late 2019, COVID-19, a new disease caused by a novel (or new) coronavirus began to take over the lives of many people. This study centers on how members of the Latinx community have been affected by COVID-19. Both quantitative and qualitative data were utilized to analyze the perceived risk of infection, preventative behaviors, and acceptability of the COVID-19 vaccine for individuals that identify as Latinx. Analysis of the survey and interview analysis found the majority of participants expressed abiding by recommended measures and becoming hypervigilant about their activities, and their desire to get vaccinated against COVID-19 when they are eligible. Individuals who did not express the desire to be vaccinated mentioned worries including side effects, costs, safety, and efficacy of the vaccine. Results from this research could aid in the creation of public health initiatives in order to increase the uptake of the vaccine tailored for the Latinx community.
The ongoing Global Coronavirus Pandemic has been upheaving social norms for over a<br/>year at this point. For countless people, our lives look very different at this point in time<br/>then they did before the pandemic began. Quarantine, Shelter in Place, Work from<br/>Home, and Online classes have led global populations to become less active leading to<br/>an increase in sedentary lifestyles. The final impact of this consequence is unknown,<br/>but emerging studies have led to concrete evidence of decreased physical and mental<br/>wellbeing, particularly in children. VirusFreeSports was the brainchild of three ASU<br/>Honors students who sought to remedy these devastating consequences by creating<br/>environments where children can participate in sports and exercise safely, free of the<br/>threat COVID-19 or other transmissible illnesses. The ultimate goal for the project team<br/>was to build traction for their idea, which culminated in a video pitch sent to potential<br/>investors. Although largely created as an exercise and we did not create a full<br/>certification course, merely a prototype through a website with sample questions to<br/>gauge interest, the project was a success as a large target market for this product was<br/>identified that showed great promise. Our team believes that early entrance to the<br/>market, as well as the lack of any other competitors would give the team a tremendous<br/>advantage in creating an impactful and influential service.
Studying the effects of viruses and toxins on honey bees is important in order to understand the danger these important pollinators are exposed to. Hives exist in various environments, and different colonies are exposed to varying environmental conditions and dangers. To properly study the changes and effects of seasonality and pesticides on the population dynamics of honey bees, the presence of each of these threats must be considered. This study aims to analyze how infected colonies grapple more deeply with changing, seasonal environments, and how toxins in pesticides affect population dynamics. Thus, it addresses the following questions: How do viruses within a colony affect honey bee population dynamics when the environment is seasonal? How can the effects of pesticides be modeled to better understand the spread of toxins? This project is a continuation of my own undergraduate work in a previous class, MAT 350: Techniques and Applications of Applied Mathematics, with Dr. Yun Kang, and also utilizes previous research conducted by graduate students. Original research focused on the population dynamics of honey bee disease interactions (without considering seasonality), and a mathematical modeling approach to analyze the effects of pesticides on honey bees. In order to pursue answers to the main research questions, the model for honey bee virus interaction was adapted to account for seasonality. The adaptation of this model allowed the new model to account for the effects of seasonality on infected colony population dynamics. After adapting the model, simulations with arbitrary data were run using RStudio in order to gain insight into the specific ways in which seasonality affected the interaction between a honey bee colony and viruses. The second portion of this project examines a system of ordinary differential equations that represent the effect of pesticides on honey bee population dynamics, and explores the process of this model’s formulation. Both systems of equations used as the basis for each model’s research question are from previous research reports. This project aims to further that research, and explore the applications of applied mathematics to biological issues.
This outlines a mathematical model created in MATLAB for the purposes of predicting nitrous oxide emissions from wastewater treatment plants with updated an updated understanding of AOB metabolic pathway.