Pennsylvania COVID-19 Visualizations


Please be advised that the data presented on this page may be a few days out-of-date. Beginning on June 9, the state has been posting their county data in PDF form, which has complicated my automated scraping. I have managed to scrape most of the PDFs, but due to inconsistencies in their structure, some cannot be parsed. If the data is out of date, it means that there has been a technical issue with the scraping that I need to address before I can add new data.

Please remain patient. I hope to stay on top of this.

Also, keep wearing your masks. It's not a political issue; it is an issue of public health.

-Adam Fosbenner

Select counties from below. For clarity, it is suggested that selections are limited to 5 or 6 counties. Click submit to view the graphs.

Top 5 PA Counties:


This graph simply shows the number of cases in each county by date.


Using the number of cases and the estimated population of each county, it is possible to calculate the percentage of each county's population with the illness. This helps to account for differences in population between counties. It seems reasonable that more populous counties will likely have more cases, so percentages may be a better metric by which to compare counties with vastly differing populations.


This graph depicts the rate of growth with respect to the number of cases in each county. Each point represents the average daily increase in cases for the week prior to the date shown. If the graph appears to slope upwards, it means that the rate of growth in cases is increasing. If it appears flat, the rate of growth is remaining consistent. If graph appears to point downward, it means that the number of cases are still growing, but at a decreasing rate.


This graph is similar to the previous one, but it shows the rate of growth within the county's population. Each point represents the average daily increase of percent of population for the week prior to the date shown. As with the last graph, if the points appear to be moving downward, the virus is still spreading among the population, just not as rapidly as when the graph is flat or pointing upwards.