Stephanie Mundis
Pronouns: she/her
Quantitative Disease Ecology & Conservation Lab
Emerging Pathogens Institute
CDC Southeastern Center of Excellence in Vector Borne Diseases
Graduate Representative 2019/2020
University of Florida

Adviser: Dr. Sadie Ryan

Focus Area: Medical Geography in Global Health (MGGH)

Research Statement: My research interests are in the application of GIS to understand vector-borne transmission. My past work has focused on range expansions of Ae. aegypti and Ae. albopictus, two mosquito vectors of dengue, chikungunya, and Zika virus. Moving forward, I plan to study spatial factors affecting vector distributions, insecticide resistance, and virus transmission in order to build spatial models of current and future arthropod-borne disease transmission.

Who is she?
Stephanie Mundis is a fourth year PhD student in the Geography Department. She moved to Florida to pursue her PhD in the Quantitative Disease Ecology & Conservation Lab (QDEC Lab) and has served as a Graduate Representative for the 2019/2020 academic year.

How did she get here?
Growing up in Harvard, Illinois with high school teachers for parents, Stephanie was steeped in the value of education. Although Harvard is a small town (population of 9,447 at the 2010 census), it is remarkably cosmopolitan – hosting many international students through the AFS program which is committed to the idea that fostering international relationships fosters peace. Stephanie’s parents have hosted students from Spain, Norway, Thailand, and Hong Kong and, while in High School, Stephanie was able to spend a year abroad in Temuco, Chile.

Stephanie started a B.A. in Anthropology at the University of Illinois at Urbana-Champaign in Fall 2010. When she took an introductory course on the geography of developing countries, she was hooked and decided to add Geography as a second major. She liked using GIS and saw geography as a field that used both qualitative and quantitative methods to investigate an important and diverse array of questions. While an undergrad, she started studying socio-cultural anthropology, but became interested in physical anthropology when she worked in a human genetics lab that focused on Native American population genetics looking into the peopling of the Americas. She also began to study medical geography in a lab looking at West Nile Virus with GeoGator alumna Marilyn O’Hara. Combining her interests in genetics and geospatial science, Stephanie also spent a summer in the Genomics Research Laboratory designing a geodatabase that used genetics to determine the provenance of illegal elephant ivory. Her undergraduate thesis involved GIS and genetics – exploring the spatial relationships between different indigenous communities in Central and South America.

After completing her undergraduate studies, Stephanie took a year off school, and worked on mosquito control, as a laboratory technician in a medical entomology lab as a tech and did a 3 month GIS technician internship.

With some practical experience in hand, Stephanie was ready to move to Las Cruces, NM and enroll in a Master’s program at New Mexico State University. She was initially pursuing an interdisciplinary Master’s degree, but wound up earning a M.S. in Biology and a Master of Applied Geography on the strength of a single thesis, exploring the species distribution of Aedes aegypti mosquitoes in New Mexico. She was working with a species distribution model of data from the southern ¾ of the state – asking where are the mosquitoes and where might they be in different climate change scenarios. While pursuing her Master’s degree, Stephanie coauthored a paper looking at mosquito composition in different land cover types in Borneo based on land surface temperature.

Upon completing her Master’s degree at New Mexico State University, Stephanie applied to join the Quantitative Disease Ecology & Conservation Lab (QDEC Lab) and moved to the University of Florida in 2017.

What’s she been doing at UF?
As a GeoGator, Stephanie has been keeping up the hard work – building skills, teaching courses, doing fieldwork, writing papers, and winning scholarships.

By taking applied courses like Dr. Blackburn’s Applications of GIS for Disease Ecology and Zoonosis and Dr. Mao’s GIS Models for Public Health, Stephanie has developed her GIS and statistics toolkit and prepared to ask even more complicated geospatial health questions.

Since the beginning of her undergrad, Stephanie has wanted to be a professor. She brings that passion to the (now virtual) classroom, teaching sections of Introduction to Medical Geography as well as the Introduction to Physical Geography Lab.

Image courtesy CDC Southeastern Center of Excellence in Vector Borne Disease

As part of her work with the CDC Southeastern Center of Excellence in Vector Borne Diseases, Stephanie has been able to get into the field, studying local scale variability of insecticide resistance in Aedes aegypti with the Orange County Mosquito Control District. This fieldwork has come to a halt with the COVID-19 pandemic, but she continues to work with data from Orange County, working on a local scale project studying mosquito abundance and climate, using data that has already been collected from sentinel chickens in Orange County.

So far, Stephanie has published two papers since she’s been in the department – Seasonal and geographic variation in insecticide resistance in Aedes aegypti in southern Ecuador and Spatial variation in the frequency of knockdown resistance genotypes in Florida Aedes aegypti populations. These are building toward her dissertation, Spatial Variation in Mosquito Populations that Mediate Vector-Borne Disease Risk.

Stephanie has also received the T.W. Miller Scholarship from the Florida Mosquito Control Association as well as a US Geospatial Intelligence Foundation Graduate Student for an essay exploring how mosquito borne disease is a threat to health and security.

How has she been holding up during the pandemic?
As an introvert, Stephanie is happy to not leave her house – it’s her favorite place. She has been okay with staying home as much as possible, spending time reading, cooking, and going for walks with her dogs.

Helpful pets do science

LinkedIn
ResearchGate
Follow Stephanie on Twitter

 

Course description

It is often the case that real-world systems can be represented as networks of many interacting components. This course teaches the fundamental concepts, models, and techniques for describing, visualizing, measuring, and analyzing networks. It also introduces their applications in geography, transportation, social science, etc. A series of labs using the popular network analysis package Gephi and GIS software ArcGIS are also designed to help students gain hands-on experience in visualizing and analyzing networks.

Course Objectives

After successful completion of this course students should be able to:

  • Have a solid grasp of the vocabulary, central concepts, measures and techniques relating to networks;
  • Conduct experiments within the Gephi and ArcGIS software environment;
  • Apply their knowledge to visualize and analyze a real network data set of their choosing.

Dr. Yujie Hu – yujiehu@ufl.edu

No place on earth is completely safe from meteorological, climatological, hydrological, and geophysical hazard phenomena. Yet, we can anticipate disasters by mapping the potential intersection of hazard phenomena with human settlements. This knowledge can be used to reduce or avoid hazard impacts in our communities.

This course provides students with knowledge & skills to model hazard vulnerability using ArcGIS Pro. We will discover where to obtain data and explore different methods for integrating social & physical vulnerability analyses within a geospatial model.

Semester: Fall 2020
Instructor: Dr. Kevin Ash
Contact: kash78@ufl.edu

 

No textbook
No exams

Fall 2020 100% online, asynchronous

Course Organization
Lab exercises Skills quizzes Presentations
Final project

*Counts for Certificates in Applied Atmospheric Science and Meteorology and Climatology*

Instructor: Dr. Corene Matyas
matyas@ufl.edu

Emphasis on using GIS for spatial data analysis

Basic terminology for atmospheric science
Global and regional reanalysis datasets
Doppler radar
Satellite-based rainfall estimates
Spatial analysis using GIS

Pick your case for:
Researchers using GIS
Landfalling hurricane
Final project related to your
thesis/ dissertation research

Course description:

Medical geography deals with human-environment interactions and the influence of these interactions on public health. This course provides a broad-based, comprehensive survey of geographic topics and approaches in medical sciences. Hands-on experiences will be emphasized through GIS labs.

Successful students will be able to:

Apply geographic concepts and principles widely used in medical studies.
Investigate health problems with a systematic approach and spatial analysis methods.
Analyze real-world health problems using geographic information systems (GIS) software.

Semester: Fall 2020
Time and Location: This courses is facilitated 100% online.
Prerequisites: Sophomore standing or higher.
Contact information: Dr. Liang Mao via liangmao@ufl.edu


Course description:
This is an advanced-level course for medical geography, and sister disciplines (epidemiology, public health, ecology). It can serve as an undergraduate level major or minor requirement. Focus is on GIS applications in spatial analysis and ecology to address common research issues related to zoonotic diseases (those affecting animals and humans). Food security and patterns of food resources will also be discussed. This course is designed to learn and apply GIS-based tools directly to zoonoses and public health issues. Examples will range from wildlife diseases to human food inequity and food security, through the lens of disease ecology.
Successful students will be able to:
How to map disease and map statistical outputs (graphically and with maps)
How to employ local measures of local spatial autocorrelation to evaluate disease or health patterns
A primer on ecological niche modeling and predicting disease distributions

Semester: Fall 2020
Time and Location: Online and UFO; asynchronous lectures and material delivery
Prerequisites: GIS 3043 or equivalent & Geography 6161C or equivalent or consent of instructor or Students from public health backgrounds can inquire about course equivalents Contact information: Dr. Jason K. Blackburn jkblackburn@ufl.edu

 

A new course for Fall 2020!

Course description

Introduces a range of transportation concepts, theories, and models, including networks, modes, terminals, freight transportation, urban transportation, and environmental impacts. Also covers core methods and tools often used to study and analyze transportation systems, including spatial accessibility, spatial interaction, spatial networks, and GIS for transportation (GIS-T).

Course Objectives

After successful completion of this course students should be able to:
Have knowledge of the history and evolution of the U.S. transportation system;
Understand the geographic nature of transportation systems;
Investigate and solve various transportation problems using analytical methods and tools discussed in class and applied in labs.
prerequisites
Sophomore standing or higher. Entry level knowledge of GIS is preferred but not required.

Instructor: Dr. Yujie Hu – yujiehu@ufl.edu

Our Senior Profile for UF Geography today features GeoGator Sara Shir

Future Plans:
In the next year I am looking to find a GIS job before attending medical school. I plan to start medical school in Fall 2021.

What is your favorite thing from your time at UF?
Getting Krishna lunch with friends in the Plaza of the Americas

What was your favorite Geography class?
GIS Disease Ecology

What is your favorite Geography memory?
Going to Belize with a doctoral candidate and a few other students to help with his project.

In what ways has Geography prepared you for your next steps?
It has to think outside the box and to explore viewpoints outside my own when trying to understand global issues and trying to find a solution to a problem.

What would your ideal job be?
My goal is to be an Infectious Disease doctor. It was something I already had in mind but the pandemic definitely highlighted the value of the field.

What will you miss most about Gainesville/UF?
Gator Salsa (club that teaches latin dancing)

What will you miss least about Gainesville/UF?
The weather!

What well wishes or words of wisdom would you like to share with your classmates and fellow students?
I wish you all the best in everything you do!

UF Geography wishes Sara and all our graduating seniors all the best as they embark on their next journey. Congratulations from all our GeoGator family and please be sure to stay in touch! #Geogators#UFGEOG#CLASGrads2020

Image courtesy Spatial and Spatio-temporal Epidemiology

HUAutomated delineation of cancer service areas in northeast region of the United States: A network optimization approach

Fahui Wang, Changzhen Wang, Yujie Hu, Julie Weiss, Jennifer Alford-Teaster, and Tracy Onega

Article first published online: 06 MAR 2020 Spatial and Spatio-temporal Epidemiology

DOI: 10.1016/j.sste.2020.100338

ABSTRACT:

Objective
Derivation of service areas is an important methodology for evaluating healthcare variation, which can be refined to more robust, condition-specific, and empirically-based automated regions, using cancer service areas as an exemplar.

Data sources/study setting
Medicare claims (2014–2015) for the nine-state Northeast region were used to develop a ZIP-code-level origin-destination matrix for cancer services (surgery, chemotherapy, and radiation). This population-based study followed a utilization-based approach to delineate cancer service areas (CSAs) to develop and test an improved methodology for small area analyses.

Data collection/extraction methods
Using the cancer service origin-destination matrix, we estimated travel time between all ZIP-code pairs, and applied a community detection method to delineate CSAs, which were tested for localization, modularity, and compactness, and compared to existing service areas.

Principal findings
Delineating 17 CSAs in the Northeast yielded optimal parameters, with a mean localization index (LI) of 0.88 (min: 0.60, max: 0.98), compared to the 43 Hospital Referral Regions (HRR) in the region (mean LI: 0.68; min: 0.18, max: 0.97). Modularity and compactness were similarly improved for CSAs vs. HRRs.

Conclusions
Deriving cancer-specific service areas with an automated algorithm that uses empirical and network methods showed improved performance on geographic measures compared to more general, hospital-based service areas.

Read the full publication at Spatial and Spatio-temporal Epidemiology.

 

 

 

 

Image courtesy Journal of Infrastructure Systems

HUImpact of Coastal Hazards on Residents’ Spatial Accessibility to Health Services

Georgios P. Balomenos, Yujie Hu, Jamie E. Padgett, and Kyle Shelton

Article first published online: 1 DEC 2019 Journal of Infrastructure Systems

DOI: 10.1061/(ASCE)IS.1943-555X.0000509

ABSTRACT: The mobility of residents and their access to essential services can be highly affected by transportation network closures that occur during and after coastal hazard events. Few studies have used geographic information systems coupled with infrastructure vulnerability models to explore how spatial accessibility to goods and services shifts after a hurricane. Models that explore spatial accessibility to health services are particularly lacking. This study provides a framework to examine how the disruption of transportation networks during and after a hurricane can impact a resident’s ability to access health services over time. Two different bridge-closure conditions—inundation and structural failure—along with roadway inundation are used to quantify posthurricane accessibility at short- and long-term temporal scales. Inundation may close a bridge for hours or days, but a structural failure may close a route for weeks or months. Both forms of closure are incorporated using probabilistic vulnerability models coupled with GIS-based models to assess spatial accessibility in the aftermath of a coastal hazard. Harris County, an area in southeastern Texas prone to coastal hazards, is used as a case study. The results indicate changes in the accessibility scores of specific areas depending on the temporal scale of interest and intensity of the hazard scenario. Sociodemographic indicators are also examined for the study region, revealing the populations most likely to suffer from lack of accessibility. Overall, the presented framework helps to understand how both short-term functionality loss and long-term damage affect access to critical services such as healthcare after a hazard. This information, in turn, can shape decisions about future mitigation and planning efforts, and the presented framework can be expanded to other hazard-prone areas.

Read the full publication at Journal of Infrastructure Systems