The effect of state-level stay-at-home orders on COVID-19 infection rates
- Published:May 24, 2020DOI:https://doi.org/10.1016/j.ajic.2020.05.017
- •We examined the effect of state-level stay-at-home orders on COVID-19 diagnoses.
- •Rates of confirmed cases were tracked before and after orders were put in place.
- •Logged infection rates were 0.113/day pre-order and 0.047/day post-order.
- •Results were consistent across states supporting the use of stay-at-home orders.
AbstractState-level stay-at-home orders were monitored to determine their effect on the rate of confirmed COVID-19 diagnoses. Confirmed cases were tracked before and after state-level stay-at-home orders were put in place. Linear regression techniques were used to determine slopes for log case count data, and meta analyses were conducted to combine data across states. The results were remarkably consistent across states and support the usefulness of stay-at-home orders in reducing COVID-19 infection rates.
Carol graduated from Riverside White Cross School of Nursing in Columbus, Ohio and received her diploma as a registered nurse. She attended Bowling Green State University where she received a Bachelor of Arts Degree in History and Literature. She attended the University of Toledo, College of Nursing, and received a Master’s of Nursing Science Degree as an Educator.
She has traveled extensively, is a photographer, and writes on medical issues. Carol has three children RJ, Katherine, and Stephen – one daughter-in-law; Katie – two granddaughters; Isabella Marianna and Zoe Olivia – and one grandson, Alexander Paul. She also shares her life with her husband Gordon Duff, many cats, and two rescues.