The tutor is required to watch 3 videos, each 50 minutes long, and write whatever the professor says in the video. Here are the supporting articles, but I'll use dropbox to upload the video links. Y

Working Paper Series

Political lean: A crucial variable for monitoring COVID-19

in the United States

N. Krieger, PhD1, J. T. Chen, ScD1, C. Testa, BS1, P. D. Waterman, MPH1,

and W. P. Hanage2

October 8, 2021

HCPDS Working Paper Volume 21, Number 5

Abstract

Descriptions and monitoring of the social and spatial population distribution of COVID-19 cases and

deaths in the US have largely relied on individual- and county-level sociodemographic data and

vulnerability indices that draw primarily or exclusively from data available in US health records and US

census data. In this brief report, using US data from September 1, 2020 to September 15, 2021, we

provide empirical evidence demonstrating that county-level data on political lean (Republican vs.

Democrat for the 2020 US presidential election) adds critical information to understanding population

distributions of COVID cases and deaths – and also document the importance of socioeconomic variables

in addition to data on racialized groups. In particular, during the period from July 1, 2021-September 15

(corresponding to the delta surge, occurring when COVID-19 vaccines were authorized for all US adults

for at least 3 months or more), the two county level variables that most sharply differentiated risk

comparing the highest to lowest quintiles for COVID-19 rates (per 100,000 person-years) were: (a)

political lean: highest Republican lean vs. highest Democratic lean, for cases: rate ratio (RR) = 2.39 (95%

confidence interval [CI] 2.25, 2.55) and for deaths: RR = 3.34 (95% CI 2.99, 3.73), and (b) percent below

poverty line, for cases: RR 1.93 (95% CI 1.15, 2.4) and for deaths: RR = 5.08 (95% CI 3.14, 8.97). By

contrast, the least differentiation was provided by % people of color (highest vs. lowest quintile): for

cases, RR = 0.95 (95% CI 0.89, 1.02), and for deaths: 0.83 (95% CI 0.74, 0.93). However, combining

these single variables with political lean magnified the risk contrast between county quintiles. Thus,

people residing in the counties jointly with the highest poverty and highest political lean toward

Republicans were nearly 6 times more likely to die (rate ratio: 5.90; 95% CI 4.95, 7.07) from COVID-19

compared to those residing in the counties jointly with the lowest poverty and highest political lean

toward Democrats. Additionally, people residing in counties jointly with the highest % people of color

and highest political lean toward Republicans were almost 5 times more likely to die (rate ratio: 4.77,

95% CI 3.70, 6.20) from COVID-19 compared to people residing in counties jointly with the lowest %

people of color and highest political lean toward Democrats. We accordingly posit that county-level

political lean is a crucial variable that should be used routinely to monitor county-level trends in COVID-

19 cases and mortality, alongside and in conjunction with sociodemographic and socioeconomic data.