After taking data examining meat prices and disease spread, we identified the primary issues and proposed an accordingly appropriate solution. We based our solution on the similarities between declining crop prices and the current drop in meat prices, taking inspiration from the already existing subsidies given to farmers by the government and proposing a solution similar to what is already in place for farmers.
Our team was inspired to choose this challenge because of how ordinary and prevalent eating is within everyone's life every day. Of the challenges provided this topic has the greatest amount of impact as it deals with consumers, processing facilities, and farmers. Our topic also impacts everyone as the current surplus in meat supply directly affects the economy, causing a rippling effect across it due to shutdowns in meat-producing facilities. These shutdowns have led to job losses for those who worked at meat producing facilities and thus, diminished growth in the economy.
We first analyzed meat price indexes to determine whether a strong downward trend existed since the first community transmission of Covid-19 in American society and whether that trend was clear as Covid-19 exponentially grew to catastrophic proportions. We also combed through data collected from credible universities that showed us direct, tangible, numerical losses in revenue. We then pondered whether there was an established link between the two that could be mitigated through governmental intervention and then began researching and developing solutions from there.
We utilized space agency data in our project by looking at the Covid-19 infection graph which plotted the death counts and case counts of Covid-19 over time and found an inverse relationship between the number of Covid-19 cases and the meat price index, signaling that due to the Covid-19 outbreak more people are saving money and staying indoors, decreasing the demand for a good that is more expensive like meat and resulting in lower prices and a lower meat price index.
The Panditos used Autodesk SketchBook to design the artwork for our team logo, Python and the data science library Pandas to reorganize our data for analysis, Microsoft PowerPoint in order develop the slides for the project, excel to create the graphs and organize our data and Microsoft Word to organize our explanations for this project.
The first problem our team ran into was trying to solve Human Factors when it was not the right topic for our team. Instead, we pivoted to the topic Food for Thought because we believed that it would be the topic that we would be more invested and engaged in, as well as the topic we would be better prepared to work on. Finishing the PowerPoint was a massive achievement for the team as we had managed to organize an effective and efficient method of communication and collaboration and the PowerPoint was a testament to this.
https://drive.google.com/file/d/1xYu-69xW_TeuBclrWyqZTJsKowvXGlZD/view
https://sedac.ciesin.columbia.edu/mapping/popest/covid-19/
https://beta.sedac.ciesin.columbia.edu/repository/covid19/covid19_trend_graphs/US_covid_trend.png
https://www.ncba.org/CMDocs/BeefUSA/Publications/OSU%20NCBA%20Beef_COVID_Impacts_Full.pdf
http://www.fao.org/worldfoodsituation/foodpricesindex/en/
https://data.bls.gov/timeseries/LNS14000000
https://coronavirus.jhu.edu/map.html