COVID-19 Deaths and Variables

Dublin Core


COVID-19 Deaths and Variables


This collection shows various possible contributors to COVID-19 deaths in the 4 corners by county.


While the the main source of data come from the American Community Survey, it appears after analysis that the variables of lack of running water, lack of cellphone service, and poverty level are all indicators of COVID-19 deaths.


Janice Hall


Lacking of Plumbing Facilities: This data comes from the CDC's American Community Survey from 2019. It is the premier source for detailed population and housing information about our nation.

Cellphone Service Data: This data comes from the CDC's American Community Survey from 2019.

Poverty Population:This data comes from the CDC's American Community Survey from 2019.

COVID-19 Death data: The death counts were downloaded from New York Times GitHub on April 14, 2021.


[Website maintained by Chantel Sloan, Associate Professor in the Public Health Department at Brigham Young University].


Dates are included from 2019 and deaths from January 2020 until April 14, 2021.


Janice Hall


Esri, HERE, Garmin, FAO, NOAA, USGS, EPA,








Arcgis 2.7.1


The map shows all of Arizona, Colorado, New Mexico, and Utah.

Collection Items

Number of COVID-19 Deaths per County
There is a large amount of missing data, this comes over a year after the initial 'quarantines'. There is a clear limitation to understanding with such large gaps of data, but we are still given a clear understanding of the death rate on American…

Percent of the Population Lacking Access to Complete Plumbing Facilities.
The highest percentage of those that are lacking running water are located in the American Indian Reservations which can be seen on the map. This data has some limitations as it is from a survey, that cannot be proven if theses statistics are…

Percent of Population without Cell Phone Service at their Home
The map shows that the percentage of homes that do not have access to cellular service are generally on the outskirts of the state, that typically have a lower population. Or are considered urban.

Again this data is from a survey, because of this…

COVID-19 Moran's I Residuals
The residuals of this map were ran in SAS based on Poisson to be more accurate. From there they were put back into ArcGis. Moran's I shows that the model is almost perfectly random with a score of 0.012.

COVID-19 Deaths GWR
The map shows the residuals and the linear relationship between the variables. As well as a normal distribution of deviations.
View all 5 items