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Mapping the novel coronavirus

By Nolan Kelly


Understanding the progression of COVID-19 across the United States is vital for policy makers and health officials. Thankfully, the New York Times has regularly updated data on GitHub which allows us to visualize infections across the country. In the interest of mental health as we are all social distancing, today's post will start with the bad news and end with some good news.


The bad news is clear: 


Infections and deaths are rising. It is less clear where infections and deaths are outsize in relation to the rest of the country.  Figure 1 depicts where the most cases have been identified. Figure 2 depicts where the most deaths have been identified in blue. The sheer number of cases in cities like New York and Seattle make their outbreaks obvious. Other regions with smaller outbreaks are not so readily apparent without adjusting the data. Areas like Southern California, Arizona, Denver, Detroit, and New Orleans all show heightened incidences of COVID-19.



Figure 1



Figure 2


This list of outbreaks, however, is incomplete. Imagine a huge city with 500 cases and a rural county with an equal number of cases. Clearly the county is experiencing a more profound outbreak as its population is much smaller. Additional rural regions with outbreaks are identified in Figure 3, Northern Arizona, Southwest Georgia, Central Idaho, Southeast Washington, Central Indiana, the Yellowstone area of Wyoming, and the entire Northeast Megalopolis. These regions are experiencing outbreaks that are, relative to their low population, quite large yet receive significantly less coverage in the broader media.



Figure 3


The United States is often portrayed as a country divided along rural and urban lines. These depictions of outbreaks give us a clearer picture of where outbreaks are occurring across that divide and can inform our understanding of how our countrymen are faring in regions outside the oft-discussed major cities. 


Now the good news:


Figure 4 illustrates the progression of infection growth rates from March 20th to April 4th. The metric shown is the number of days needed to double the number of infections in each state based on each day’s case diagnosis numbers. Red indicates the number of days to double infections closer to 1 (a very fast infection rate) while green shows the number of days to double inflections closer to 10 (a slower, but still positive infection rate). The color scale is held constant across the progression of maps to show how the infectivity changes over time.



Figure 4


Although infections across the United States are increasing, the growth of new infections appears to be slowing based on this diagnosis data. The average number of days to double the diagnoses across the country has gone from ~2.4 days to ~6 days between March 20th and April 4th. Although these numbers are approximations based on incomplete diagnosis data (testing capacity has been slow to develop), they are conservative as testing capacity has only increased, which we would expect to lead to increasing growth in diagnosis rates. This may reflect unprecedented government efforts to slow infection rates as well as public participation in social distancing. Nevertheless, it is a positive sign during a particularly difficult time.



Nolan Kelly is a graduate student at UC San Diego in the School of Global policy and Strategy. His background is in technical consulting for electric utilities and regulatory agencies. He hopes to pursue consulting after graduation in 2021.

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