Hi everyone, I am excited to share a working paper coauthored with colleagues at Ball State University and the University of Wisconsin-Oshkosh. On April 7th, Wisconsin opened polls for its primary election. Long lines of voters at consolidated voting locations led to the concern that in-person voting was contributing to COVID-19 spread. We use SafeGraph POI/Patterns data, Wisconsin voting data, and infection data from the Wisconsin Department of Health Services to study the effects of in-person voting on the spread of COVID-19. We find a positive relationship between in-person voting and the spread of COVID-19 two to three weeks after the election.
Hi @Paul_Niekamp, thanks for sharing! This is important research and could be informative moving forward. Can you help me to understand Figures 1a, 1b, and 1c? The way I’m interpreting it, there are only a couple counties in 1c that are darker (higher positive rate) than 1b.
Hi @Paul_Niekamp Thanks for sharing, excellent paper! I agree with @Ryan_Kruse_MN_State that the overlaps of Figure 1a, b and c didn’t seem that obvious. Is there a way to quantify the similarities of these graphs? For Table 1 findings, how did you control for the potential confounding of population density? I really like Figure 2, it is simple and makes a really compelling case. Did you just arbitrarily decide 50 meters as the cut-off for increased visits? In table 2 and 3, how did you operationalize the social distancing metrics from SafeGraph? Just curious about what variables you used.