Projecting Food Insecurity in Southwest Virginia
| dc.contributor.author | Hamilton, Nicholas | en |
| dc.contributor.author | Jones, Mia | en |
| dc.contributor.author | Gard, Emily | en |
| dc.contributor.author | Zimmerman, Piper | en |
| dc.contributor.author | Chen, Susan | en |
| dc.contributor.author | Cary, Michael | en |
| dc.contributor.author | Kaufman, Eric K. | en |
| dc.coverage.country | United States | en |
| dc.coverage.state | Virginia | en |
| dc.date.accessioned | 2024-07-26T12:38:28Z | en |
| dc.date.available | 2024-07-26T12:38:28Z | en |
| dc.date.issued | 2024-07-25 | en |
| dc.description.abstract | Food insecurity is a socioeconomic condition in which a household does not have access to enough nutritious food to sustain a healthy lifestyle for all its members. In Virginia, food insecurity rates are highest in the southwest region of the state. This project aims to support food banks, including Feeding Southwest Virginia, by simulating food insecurity rates through 2027 in Southwest Virginia. Drawing from the literature on food insecurity, we selected relevant variables related to food insecurity from the American Community Survey and Bureau of Labor Statistics data. These variables were then forecasted at the county level using a time series forecasting model. The historical data was used to train a machine learning model which utilizes these factors to predict food insecurity rates. The forecasted data was then fed into the machine learning model to create projected food insecurity rates across Southwest Virginia. In addition to projecting food insecurity rates, we simulated future scenarios by altering the values for key factors individually. We displayed these findings on an online interactive map that allows the user to compare the food insecurity rates for each county or city by year and see the changes between years. The user can also see the locations of farmers markets, grocery and dollar stores, and food distribution centers in the area to consider their potential impact. This map will serve as a tool for Feeding Southwest Virginia in determining their resource allocation and to demonstrate the need for more aid in particular areas. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.orcid | Kaufman, Eric [0000-0001-8009-0066] | en |
| dc.identifier.uri | https://hdl.handle.net/10919/120703 | en |
| dc.language.iso | en | en |
| dc.relation.uri | https://www.research.undergraduate.vt.edu/present-and-publish/student-present-and-publish/virginia-tech-conferences/summer-research-conference.html | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.title | Projecting Food Insecurity in Southwest Virginia | en |
| dc.type | Poster | en |
| dc.type.dcmitype | Text | en |
| pubs.organisational-group | /Virginia Tech | en |
| pubs.organisational-group | /Virginia Tech/Agriculture & Life Sciences | en |
| pubs.organisational-group | /Virginia Tech/Agriculture & Life Sciences/Agricultural Leadership and Community Education | en |
| pubs.organisational-group | /Virginia Tech/All T&R Faculty | en |
| pubs.organisational-group | /Virginia Tech/Agriculture & Life Sciences/CALS T&R Faculty | en |