Premise’s COVID-19 Snapshot: Public Spaces

Premise’s COVID-19 Snapshot: Public Spaces

An Initial Analysis of COVID-19 Global Impact Study: Economics


In recent days and weeks, you have probably heard terms like “social distancing.” “flatten the curve” and “self quarantine.” These concepts stem from recommendations by the World Health Organization (WHO), among other medical professionals, that one of the best ways to limit the number of infections and subsequent deaths is to slow down the spread of the virus and one way to do that is limit the physical contact between you and anyone else. 

With the continued spread of the Novel Coronavirus across the world, Premise has been working to monitor people’s sentiment toward COVID-19 and understand how their lives are changing as a result. You can check out all of the Global Impact Survey data we have been collecting here.

For this snapshot, we will focus on the United States. With the help of our Data Science team, we were able to determine if there were statistically significant differences in attitudes between respondents in states with the highest number of COVID-19 cases (Group A) and respondents in states with the lowest number of COVID-19 cases (Group B) on topics related to coronavirus. 

The first question we are looking at is: “What effect has the Coronavirus (COVID-19) had on your willingness to be in public spaces?” 

% of people in Group A that said No Effect or Minor Effect = 61.74%

% of people in Group B that said No Effect or Minor Effect = 71.56%

We found that there is a statistically significant difference between the two proportions (p-value < 0.01), suggesting that people in Group A are more reluctant than people in Group B of being in public places. As we collect more data from respondents in the United States, we will see if this willingness changes, and how that relates to the number of COVID-19 cases in those geographic regions. 

Methodology

For each question, we obtained the proportions of Groups A and B. Then, we conducted a 2-sample z-test (a statistical hypothesis test) in Python and calculated a p-value to assess whether there was a statistically significant difference between the two groups’ proportions. 

Group A was comprised of respondents of the three states with the highest number of COVID-19 cases, New York, Washington and California (according to CNN on March 17th, 2020). Group A totaled 1,883 observations,*  

Group B was comprised of respondents from the 14 US states with the lowest number of COVID-19 cases according to CNN on March 17th, 2020—West Virginia, North Dakota, Alaska, Wyoming, Missouri, Idaho, Montana, Hawaii, Delaware, Vermont, Oklahoma, South Dakota, Kansas and Mississippi. We chose to use 14 states in order to not have a huge disparity between the two sample sizes of the two groups. Group B totaled 1,151 observations.*

 

*Total Observations for the United States: 12,861  [As of 12:13 PM on Tuesday, March 17, 2020]