Project 20:
Our team is building an advanced spatial modeling framework that will allow academics and public health practitioners to collaborate more easily to construct models of infectious disease dynamics that are robust and can predict future spread of disease. The goal of this study is to build a spatial disease model that will examine the interplay between climatic factors (e.g., regional variation in climate), mosquito and bird movement, and their effects on regional spread of West Nile virus. First, we will build upon a current mathematical model, and then we will simulate scenarios of disease spread and to test the model’s performance under climate change scenarios. This research will ultimately help facilitate public health decision-making at local scales to improve interventions, while also promoting the mission of NASA with regards to animal movement, climate, and infectious disease.
The research has a two-semester timeline. The first week will be for onboarding, team integration and establish connection with lab members (Mihaljevic lab), School of Informatics, Computing and Cyber Systems, Northern Arizona University. Fall semester (10 hours per week for 15weeks) In the first three weeks, the candidate will receive training on disease transmission models and the computer coding that is required to build these simulation models. After that, the intern will help our team develop a new animal movement strategy to include in the model. The student will also integrate climate change scenario data sets. Spring semester (10 hours per week for 15weeks) This semester, the candidate will receive additional training to develop a simulation experiment using the newly developed model. Specifically, the student will use a clustering technique to create several regional clusters of disease foci based on infectious disease data, climate data and mobility data. Our hypothesis is that by building a model that identifies regions with similar climate, mobility patterns, and disease transmission dynamics, we will improve our model’s ability to predict spread.
The chosen student will be integrated into the Mihaljevic lab and will build relationships with Dr. Mihaljevic, Postdoctoral Researchers, PhD and MS students, and other undergraduates. The student will learn key biological concepts in infectious disease and apply computational techniques to integrate that knowledge into simulation models. We expect the student will present their collaborative work during weekly lab meetings. We will also support the student in developing a poster for the UGRADs symposium, and we hope that the student would be able to present this poster at a regional or national conference. Ultimately, we expect the work to be publishable in a peer-reviewed journal.