Nicole Nova is a PhD student in Ecology and Evolutionary Biology at Stanford University. Nicole is co-advised by Dr. Erin Mordecai and Dr. Dmitri Petrov, and she combines mathematical modeling with empirical work to study the ecology and evolution of infectious diseases in wildlife. Nicole applies theory from subfields such as population dynamics, population genetics, eco-evolutionary dynamics, and comparative genomics to study viral adaptation and cross-species transmission (spillover) in large carnivores (e.g., wolves and bears). She also studies climate drivers of infectious disease dynamics, and environmental predictors of pathogen sharing across taxa. Nicole aims to promote health, biodiversity, conservation of large carnivores and the ecosystem services these top predators provide.
Nicole grew up next to Tyresta National Park in Sweden, and she enjoys spending time in nature (hiking, canoeing, swimming and horseback riding).
Preliminary thesis title: Ecological and evolutionary drivers of emerging wildlife diseases in humans and large carnivores
Committee: Giulio De Leo, Marcus Feldman, Elizabeth Hadly, Erin Mordecai, and Dmitri Petrov
This is a phylogenetic study of a multi-host pathogen, canine distemper virus (CDV), which has caused several outbreaks in the wolf population in Yellowstone National Park since the wolf reintroductions in 1995 and 1996. This study will investigate whether the viral strains that caused the different canine distemper outbreaks are related or not, suggesting either endemic persistence of CDV in Yellowstone reservoir hosts, or new reintroductions of CDV from elsewhere.
Collaborators: Ellen Brandell, Penn State University and United States Geological Survey (USGS)
Doug Smith, Dan Stahler & Erin Stahler, Yellowstone Wolf Project, Yellowstone National Park, National Park Service
This is a cross-species phylodynamic study of canine distemper virus (CDV) in the Alaskan ecosystem. This study will investigate the relatedness of different CDV strains across different carnivore species (grizzly bears, black bears, wolves, coyotes, and wolverines) and mesocarnivores (Arctic foxes, red foxes, river otters) to predict potential transmission pathways and reservoir host species.
Collaborators: Kimberlee Beckmen, Alaska Department of Fish and Game
Martin Gilbert, Cornell University
This is a project to determine when ecological factors (i.e., geographic host overlap, host behavior, host life history, etc.) become more important for predicting pathogen sharing between various host species than their phylogenetic relatedness (evolutionary factor). Determining predictors of pathogen sharing at various evolutionary scales could be useful for detecting plausible spillover pathways to humans (problem: emerging zoonotic diseases) or to endangered carnivore populations, e.g., tigers, snow leopards, and polar bears (problem: disease-induced extinctions).
Collaborators: Sarah Bowden, Centers for Disease Control and Prevention
Tad Dallas, University of Helsinki
Barbara Han, Cary Institute of Ecosystem Studies
This study uses an empirical dynamic modeling (EDM) approach to detect causality between environmental factors (e.g., temperature and precipitation) and dengue incidence in North America (San Juan, Puerto Rico). Dengue is a mosquito-borne disease and environmental changes may affect mosquito survival, abundance, and thus disease transmission.
Collaborators: Ethan Deyle & George Sugihara, UC San Diego
Martin Rypdal, UiT The Arctic University of Norway
Van Wert M, Nova N, Horowitz T, Wolfe J. What does performance on one visual search task tell you about performance on another? Journal of Vision. 2008;8(6):312.
Nova N, Deyle ER, Shocket MS, MacDonald AJ, Childs ML, Rypdal M, Sugihara G, Mordecai EA. Empirical dynamic modeling reveals that temperature and rainfall drive dengue dynamics. [Manuscript in preparation for Ecol. Lett.]
Sokolow SH, Jones IJ, Wood CL, Lafferty KD, Garchitorena A, Hopkins S, Boslough M, Marom L, Lund A, MacDonald AJ, Howard ME, Nova N, Le Boa C, Peel A, Mordecai EA, Chamberlin A, Barry M, Bonds M, De Leo GA. The global burden of environmentally transmitted human infectious diseases. [Manuscript in preparation for Am. J. Trop. Med. Hyg.]
Nova N, Koelle K. Virological and immunological factors impacting the development of antibody breadth during HIV infection. [Manuscript in preparation for Proc. Natl. Acad. Sci.]
Shocket MS, Anderson CB, Caldwell JM, Childs ML, MacDonald AJ, Howard ME, Nova N, Han S, Harris M, Mordecai EA. Environmental drivers of vector-borne diseases. Population Biology of Vector-borne Diseases. [Under review]
Nova N, Alstergren P, Svensson C. Chronic inflammation and pain – assessment of c-Fos and ATF-3 as markers of spinal neuronal activity in a pain model of rheumatoid arthritis. M.Sc. Thesis, Karolinska Institutet, June 2012. Access: Published Thesis
Mathematical Modeling in the Biosciences, 30th Jubilee Symposium of Research Program in Biomedicine, Stockholm, Sweden. June 2015.
Mathematical Modeling of Cancer and Infectious Diseases, NSF REU research program in Mathematical Biology, University of North Carolina at Greensboro (UNCG), Greensboro, NC. June 2015.
Nova N, Deyle ER, Shocket MS, MacDonald AJ, Childs ML, Rypdal M, Sugihara G, Mordecai EA. Environmental factors drive dengue incidence in Puerto Rico. 3rd Annual Stanford Global Health Research Convening. February 2018, Stanford University, Stanford, CA.
Nova N, Shocket M, MacDonald A, Childs M, Rypdal M, Sugihara G, Mordecai E. Environmental factors driving dengue incidence in Central and South America. Ecology and Evolution of Infectious Diseases (EEID) Conference. June 2017, University of California, Santa Barbara, CA.
Nova N, Koelle K. Modeling the development of neutralizing antibody breadth in chronic-stage HIV infection. Triangle Center for Evolutionary Medicine Symposium. November 2015, The Solution Center in Research Triangle Park, Durham, NC.
Mideus G, Nova N, Härenstam-Nielsen L, Enqvist A, Tomaszuk M, Rojas C. Autonomous Robot Accomplishing Standstill Balance and Forward Motion Using Segway Technology. Annual Electrical Engineering Symposium. May 2013, Royal Institute of Technology, Stockholm, Sweden.
Nova N, Bas D, Svensson K. Assessment of c-Fos as a marker of spinal neuronal activity in a pain model of rheumatoid arthritis. Medical Sciences Symposium, August 2010, Karolinska Institutet, Stockholm, Sweden.
Nova N, Robertson K. Activation of Liver X Receptor affects the function and differentiation of osteoclasts. Biomedical Sciences Symposium, August 2006, Karolinska Institutet, Stockholm, Sweden.
RSI is a summer research program for high school students at Massachusetts Institute of Technology (MIT) and co-sponsored by the Center for Excellence in Education (CEE). Nicole attended RSI as a student in 2007 and she worked with Prof. Jeremy Wolfe in the Visual Attention Lab in the Department of Brain and Cognitive Sciences at Harvard Medical School and Brigham and Women's Hospital. She was investigating whether a simple search task (i.e. looking for a green line among red lines) was correlated with the search for objects in the real world, in particular, the search for weapons in airport security (X-ray images of luggage). The work was later published in the Journal of Vision. As an RSI alum, Nicole has been involved with the RSI program for several years and served as the Director of RSI in 2016. For more information, see the CEE Alumni Spotlight press release page (see PDF).
Rays is a summer research program for high school students, similar to Research Science Institute (RSI), but located in Sweden and it was founded in 2011. The first couple of years were run by Swedish RSI alumni (including Nicole), before Rays alumni could also hold staff positions. Mentorships are being held at various universities in Stockholm, such as Karolinska Institutet, Stockholm University and the Royal Institute of Technology. After a summer-long internship in a research lab, the Rays students present their projects in the Swedish Museum of Science and Technology.
In 2012, Nicole earned a degree in dental surgery from Karolinska Institutet in Sweden. As an EU Erasmus Mundus scholar, she also studied at Queen Mary University of London as an exchange student in 2011. Nicole also earned a M.Sc. and she completed her Master's thesis in the Molecular Pain Lab in the Department of Physiology and Pharmacology and the Department of Oral Physiology at Karolinska Institutet. Her thesis was on the pathophysiology of chronic pain in rheumatoid arthritis studied in vivo using a mouse model (more information can be found here).
Nicole also completed a clinical internship in the Department of Head and Neck Surgery at the Medical University of Vienna in Austria in 2010. She worked on several head and neck cancer cases and became interested in the evolution of cancer on a cell population level. That spark of interest led her to the field of evolutionary medicine, and eventually to the broader field of ecology and evolutionary biology.
During her years of clinical work and biomedical research, she became fascinated by mathematical biology and how one could build mathematical models to run in silico experiments (computer simulations), which could replace time-consuming, expensive and/or infeasible empirical studies. She obtained her quantitative foundation by studying electrical engineering at the Royal Institute of Technology in Sweden. On the left, there is a video of a robot that she and a team of engineering students built using Segway technology.
In 2014, Nicole started working in the Michor Lab, Department of Biostatistics and Computational Biology at Dana-Farber/Harvard Cancer Center (Dana-Farber Cancer Institute, Harvard Medical School and Harvard T.H. Chan School of Public Health). She worked on mathematical modeling of cancer development and progression using theories from evolutionary dynamics, population genetics and stochastic processes.
Then, she worked as a Research Associate in the Koelle Research Group in the Department of Biology at Duke University. She formulated a mathematical model to study the development of broadly neutralizing antibodies (BnAbs) in chronic HIV-infections. Understanding the co-evolution between the potent BnAbs and HIV could potentially provide useful insights for developing effective HIV vaccines.