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1.
MMWR Morb Mortal Wkly Rep ; 72(14): 372-376, 2023 Apr 07.
Article in English | MEDLINE | ID: covidwho-2270912

ABSTRACT

Improving ventilation has been one of several COVID-19 prevention strategies implemented by kindergarten through grade 12 (K-12) schools to stay open for safe in-person learning. Because transmission of SARS-CoV-2 occurs through inhalation of infectious viral particles, it is important to reduce the concentration of and exposure time to infectious aerosols (1-3). CDC examined reported ventilation improvement strategies among U.S. K-12 public school districts using telephone survey data collected during August-December 2022. Maintaining continuous airflow through school buildings during active hours was the most frequently reported strategy by school districts (50.7%); 33.9% of school districts reported replacement or upgrade of heating, ventilation, and air conditioning (HVAC) systems; 28.0% reported installation or use of in-room air cleaners with high-efficiency particulate air (HEPA) filters; and 8.2% reported installation of ultraviolet (UV) germicidal irradiation (UVGI) devices, which use UV light to kill airborne pathogens, including bacteria and viruses. School districts in National Center for Education Statistics (NCES) city locales, the West U.S. Census Bureau region, and those designated by U.S. Census Bureau Small Area Income Poverty Estimates (SAIPE) as high-poverty districts reported the highest percentages of HVAC system upgrades and HEPA-filtered in-room air cleaner use, although 28%-60% of all responses were unknown or missing. Federal funding remains available to school districts to support ventilation improvements. Public health departments can encourage K-12 school officials to use available funding to improve ventilation and help reduce transmission of respiratory diseases in K-12 settings.


Subject(s)
Air Pollution, Indoor , COVID-19 , Humans , United States/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2 , Ventilation , Air Conditioning , Schools , Air Pollution, Indoor/prevention & control
2.
MMWR Morb Mortal Wkly Rep ; 70(1): 14-19, 2021 Jan 08.
Article in English | MEDLINE | ID: covidwho-1395388

ABSTRACT

During early August 2020, county-level incidence of coronavirus disease 2019 (COVID-19) generally decreased across the United States, compared with incidence earlier in the summer (1); however, among young adults aged 18-22 years, incidence increased (2). Increases in incidence among adults aged ≥60 years, who might be more susceptible to severe COVID-19-related illness, have followed increases in younger adults (aged 20-39 years) by an average of 8.7 days (3). Institutions of higher education (colleges and universities) have been identified as settings where incidence among young adults increased during August (4,5). Understanding the extent to which these settings have affected county-level COVID-19 incidence can inform ongoing college and university operations and future planning. To evaluate the effect of large colleges or universities and school instructional format* (remote or in-person) on COVID-19 incidence, start dates and instructional formats for the fall 2020 semester were identified for all not-for-profit large U.S. colleges and universities (≥20,000 total enrolled students). Among counties with large colleges and universities (university counties) included in the analysis, remote-instruction university counties (22) experienced a 17.9% decline in mean COVID-19 incidence during the 21 days before through 21 days after the start of classes (from 17.9 to 14.7 cases per 100,000), and in-person instruction university counties (79) experienced a 56.2% increase in COVID-19 incidence, from 15.3 to 23.9 cases per 100,000. Counties without large colleges and universities (nonuniversity counties) (3,009) experienced a 5.9% decline in COVID-19 incidence, from 15.3 to 14.4 cases per 100,000. Similar findings were observed for percentage of positive test results and hotspot status (i.e., increasing among in-person-instruction university counties). In-person instruction at colleges and universities was associated with increased county-level COVID-19 incidence and percentage test positivity. Implementation of increased mitigation efforts at colleges and universities could minimize on-campus COVID-19 transmission.


Subject(s)
COVID-19/epidemiology , Universities/organization & administration , Adolescent , Adult , COVID-19/diagnosis , COVID-19/transmission , COVID-19 Testing/statistics & numerical data , Humans , Incidence , Middle Aged , United States/epidemiology , Young Adult
3.
Ann Epidemiol ; 57: 46-53, 2021 05.
Article in English | MEDLINE | ID: covidwho-1081247

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< .05); associations were adjusted for county population size. 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.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control/legislation & jurisprudence , Humans , Incidence , Masks , United States/epidemiology
4.
MMWR Morb Mortal Wkly Rep ; 69(42): 1535-1541, 2020 Oct 23.
Article in English | MEDLINE | ID: covidwho-890753

ABSTRACT

Poverty, crowded housing, and other community attributes associated with social vulnerability increase a community's risk for adverse health outcomes during and following a public health event (1). CDC uses standard criteria to identify U.S. counties with rapidly increasing coronavirus disease 2019 (COVID-19) incidence (hotspot counties) to support health departments in coordinating public health responses (2). County-level data on COVID-19 cases during June 1-July 25, 2020 and from the 2018 CDC social vulnerability index (SVI) were analyzed to examine associations between social vulnerability and hotspot detection and to describe incidence after hotspot detection. Areas with greater social vulnerabilities, particularly those related to higher representation of racial and ethnic minority residents (risk ratio [RR] = 5.3; 95% confidence interval [CI] = 4.4-6.4), density of housing units per structure (RR = 3.1; 95% CI = 2.7-3.6), and crowded housing units (i.e., more persons than rooms) (RR = 2.0; 95% CI = 1.8-2.3), were more likely to become hotspots, especially in less urban areas. Among hotspot counties, those with greater social vulnerability had higher COVID-19 incidence during the 14 days after detection (212-234 cases per 100,000 persons for highest SVI quartile versus 35-131 cases per 100,000 persons for other quartiles). Focused public health action at the federal, state, and local levels is needed not only to prevent communities with greater social vulnerability from becoming hotspots but also to decrease persistently high incidence among hotspot counties that are socially vulnerable.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Residence Characteristics/statistics & numerical data , Social Determinants of Health , COVID-19 , Crowding , Humans , Incidence , Pandemics , Poverty , Risk Assessment , United States/epidemiology
5.
MMWR Morb Mortal Wkly Rep ; 69(33): 1127-1132, 2020 Aug 21.
Article in English | MEDLINE | ID: covidwho-725246

ABSTRACT

The geographic areas in the United States most affected by the coronavirus disease 2019 (COVID-19) pandemic have changed over time. On May 7, 2020, CDC, with other federal agencies, began identifying counties with increasing COVID-19 incidence (hotspots) to better understand transmission dynamics and offer targeted support to health departments in affected communities. Data for January 22-July 15, 2020, were analyzed retrospectively (January 22-May 6) and prospectively (May 7-July 15) to detect hotspot counties. No counties met hotspot criteria during January 22-March 7, 2020. During March 8-July 15, 2020, 818 counties met hotspot criteria for ≥1 day; these counties included 80% of the U.S. population. The daily number of counties meeting hotspot criteria peaked in early April, decreased and stabilized during mid-April-early June, then increased again during late June-early July. The percentage of counties in the South and West Census regions* meeting hotspot criteria increased from 10% and 13%, respectively, during March-April to 28% and 22%, respectively, during June-July. Identification of community transmission as a contributing factor increased over time, whereas identification of outbreaks in long-term care facilities, food processing facilities, correctional facilities, or other workplaces as contributing factors decreased. Identification of hotspot counties and understanding how they change over time can help prioritize and target implementation of U.S. public health response activities.


Subject(s)
Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , COVID-19 , Humans , Incidence , United States/epidemiology
6.
MMWR Morb Mortal Wkly Rep ; 69(33): 1122-1126, 2020 Aug 21.
Article in English | MEDLINE | ID: covidwho-725128

ABSTRACT

During January 1, 2020-August 10, 2020, an estimated 5 million cases of coronavirus disease 2019 (COVID-19) were reported in the United States.* Published state and national data indicate that persons of color might be more likely to become infected with SARS-CoV-2, the virus that causes COVID-19, experience more severe COVID-19-associated illness, including that requiring hospitalization, and have higher risk for death from COVID-19 (1-5). CDC examined county-level disparities in COVID-19 cases among underrepresented racial/ethnic groups in counties identified as hotspots, which are defined using algorithmic thresholds related to the number of new cases and the changes in incidence.† Disparities were defined as difference of ≥5% between the proportion of cases and the proportion of the population or a ratio ≥1.5 for the proportion of cases to the proportion of the population for underrepresented racial/ethnic groups in each county. During June 5-18, 205 counties in 33 states were identified as hotspots; among these counties, race was reported for ≥50% of cumulative cases in 79 (38.5%) counties in 22 states; 96.2% of these counties had disparities in COVID-19 cases in one or more underrepresented racial/ethnic groups. Hispanic/Latino (Hispanic) persons were the largest group by population size (3.5 million persons) living in hotspot counties where a disproportionate number of cases among that group was identified, followed by black/African American (black) persons (2 million), American Indian/Alaska Native (AI/AN) persons (61,000), Asian persons (36,000), and Native Hawaiian/other Pacific Islander (NHPI) persons (31,000). Examining county-level data disaggregated by race/ethnicity can help identify health disparities in COVID-19 cases and inform strategies for preventing and slowing SARS-CoV-2 transmission. More complete race/ethnicity data are needed to fully inform public health decision-making. Addressing the pandemic's disproportionate incidence of COVID-19 in communities of color can reduce the community-wide impact of COVID-19 and improve health outcomes.


Subject(s)
Coronavirus Infections/ethnology , Ethnicity/statistics & numerical data , Health Status Disparities , Pneumonia, Viral/ethnology , Racial Groups/statistics & numerical data , COVID-19 , Coronavirus Infections/epidemiology , Humans , Incidence , Pandemics , Pneumonia, Viral/epidemiology , United States/epidemiology
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