Li (2020)
Multivariate Analysis of Factors Affecting COVID-19 Case and Death Rate in U.S. Counties: The Significant Effects of Black Race and Temperature
https://doi.org/10.1101/2020.04.17.20069708
https://www.medrxiv.org/content/10.1101/2020.04.17.20069708v2
Other
Average daily temperature (1 unit increase vs. Not applicable)
COVID-19 (any condition)
Odds ratio: 0.810 (0.710-0.910) Adjusted model

United States of America

Ecological study

Medical records

0

This data source contains COVID-19 case number and deaths data from all 3,143 U.S. counties in 50 states and the District of Columbia (D.C.).

not reported

0


COVID-19 (any condition)

0

none


Other

Average daily temperature

Daily temperatures across US countries

Not applicable

1 unit increase


Odds ratio

0.810 (0.710-0.910)

Yes

No

Yes

Results of logistic regression Model 4 is described: Model 1? was a univariate analysis. ?Model 2? added the following county macroeconomic and COVID-19-specific variables: population density, GDP/capita, COVID-19 tests per 100,000 people (state level data), COVID-19 cases/100,000 people (deaths analysis only), a marker for which State the county is in, average percent reduction in cellphone movement from day of first confirmed case to end of study, the percent of population living in overcrowded housing, and the number of days since the first confirmed COVID-19 case. ?Model 3? added these county demographics and environmental variables to Model 2: percent of population over 65, proportion of Black residents, percent of the population that is female, percent of population living in rural areas, the Food Environment Index (a measure of accessibility and affordability of healthy food), the rate of violent crime per 100,000 people, the average temperature from 10 days before the first case to the end of the study, air quality measured as the average annual ambient concentrations of PM2.5, percent of the population considered to be in fair or poor health, and the poverty rate. ?Model 4? was the full model and included medical comorbidities and access to health care variables in addition to all variables in Model 3. Specifically these new variables were: diabetes, obesity, physical inactivity, excessive drinking, and smoking were all reported as percent of the population; liver disease, hypertension, coronary heart disease, and chronic respiratory disease were reported as mortality per 100,000 people; and the patient to primary care physician ratio, the percent of people sleeping fewer than seven hours per night, the percent of the population without health insurance and the percent of the population who received the flu vaccine were also included


none

Good

Yes