1. Differences in rapid increases in county-level COVID-19 incidence by implementation of statewide closures and mask mandates — United States, June 1–September 30, 2020
- Author
-
Catherine Clodfelter, Michael A. Tynan, Amanda Moreland, Maxim Gakh, Gi Jeong, Christina Vaughan Watson, Gregory Sunshine, Mara Howard-Williams, Sebnem Dugmeoglu, Brandy L. Peterson Maddox, Adebola Popoola, Julia Shelburne, Kelly Fletcher, Sharoda Dasgupta, Regen Weber, Gloria J. Kang, Michael Williams, Ryan Cramer, Siobhan Gilchrist, Alexa Limeres, Amanda Savage Brown, Rachel Silver, Ahmed M. Kassem, Lisa Landsman, Trieste Musial, Dawn Pepin, Tiebin Liu, Carol Y. Rao, Rachel Hulkower, Russell F. McCord, and Charles E. Rose
- Subjects
2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,Epidemiology ,Mitigation strategies ,01 natural sciences ,Article ,03 medical and health sciences ,symbols.namesake ,0302 clinical medicine ,Environmental health ,Medicine ,Humans ,030212 general & internal medicine ,Poisson regression ,0101 mathematics ,County level ,Estimation ,Mask mandates ,business.industry ,Incidence (epidemiology) ,Incidence ,010102 general mathematics ,State government ,Masks ,COVID-19 ,Limiting ,United States ,Communicable Disease Control ,symbols ,Closures ,business - Abstract
Background and Objective Community mitigation strategies could help reduce COVID-19 incidence, but there are few studies that explore associations nationally and by urbanicity. In a national county-level analysis, we examined the probability of being identified as a county with rapidly increasing COVID-19 incidence (rapid riser identification) during the summer of 2020 by implementation of mitigation policies prior to the summer, overall and by urbanicity. Methods We analyzed county-level data on rapid riser identification during June 1–September 30, 2020 and statewide closures and statewide mask mandates starting March 19 (obtained from state government websites). Poisson regression models with robust standard error estimation were used to examine differences in the probability of rapid riser identification by implementation of mitigation policies (P-value Results Counties in states that closed for 0–59 days were more likely to become a rapid riser county than those that closed for >59 days, particularly in nonmetropolitan areas. The probability of becoming a rapid riser county was 43% lower among counties that had statewide mask mandates at reopening (adjusted prevalence ratio = 0.57; 95% confidence intervals = 0.51–0.63); when stratified by urbanicity, associations were more pronounced in nonmetropolitan areas. Conclusions These results underscore the potential value of community mitigation strategies in limiting the COVID-19 spread, especially in nonmetropolitan areas.
- Published
- 2021