Abstract
State-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.
Original language | English (US) |
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Pages (from-to) | 958-960 |
Number of pages | 3 |
Journal | American Journal of Infection Control |
Volume | 48 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2020 |
Keywords
- Coronavirus
- Epidemiology
- Nonpharmaceutical intervention
ASJC Scopus subject areas
- Epidemiology
- Health Policy
- Public Health, Environmental and Occupational Health
- Infectious Diseases