Since the United States recorded its first case of COVID-19 in January of 2020 it has rapidly spread across the country. In its wake we have seen first hand the controversy that a global pandemic can cause, first among which is the debated necessity of masks. Below is a snapshot of the current pandemic situation (As of the 27th of July 2020) along with a deep dive into how mask usage is helping to stem the tide of further infections. Designed by Samuel Grindon-Ekins using data sourced from New York Times on Github with some manipulation on my end found on my Github Repo.
To the left is a choropleth map showing Covid-19 infections broken down by state. There is a convenient time slider that you can use to select a specific number of days since the first recorded case. As you mouse over each state you can see the actual number of cases reported in the respective state on that date. As one might expect, more populated areas tend to have higher case numbers, however upon exploration we can see that some areas have a greater than expected share of cases. While there are probably a collection of explanations for this, I believe the most likely explanation is mask usage, something we will explore in the following visualisations. The base map file is sourced from lewster1's github and is based on the Albers map projection
To the right is a stacked bar chart showing the responses to a New York Times survey about mask usage. 2000 participants from each US county were asked “How often do you wear a mask in public” to which they could respond “Always”, “Frequently”, “Sometimes”, “Rarely” or “Never”. I have aggregated these responses by state for easier viewing, and if you hover over the visualisation you can see the exact breakdown for each response.
To the left are two stacked bar charts, showing the 10 best and worst mask wearing states. A state is considered a good mask wearing state if the sum of the average responses “Always” and “Frequently” were within the 10 highest responses. Conversely, A state is considered a poor mask wearing state if the sum of the average responses “Rarely” and “Never” were within the 10 highest responses.
To the right is a stacked line chart, showing the mean cumulative cases per 10000 people broken down by mark usage performance. You can use the smaller graph to zoom in on a particular time period. This visualisation shows clearly the preventative effect that judicious mask usage has on the spread of Covid-19. The high mask usage cases plateau and eventually drop under the poor and moderate usage cases as the pandemic continues, a clear indication that masks are an effective preventive measure for combating Covid-19
Having seen these visualisations hopefully you have a greater understanding of the pandemic and the measures we as individuals can take to protect ourselves and our community. This visualisation was designed and created by Samuel Grindon-Ekins, using data sourced from The New York Times on Github, The US census bureau and lewster1's github.