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      Recent Increase in COVID-19 Cases Reported Among Adults Aged 18–22 Years — United States, May 31–September 5, 2020

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          Abstract

          Although children and young adults are reportedly at lower risk for severe disease and death from infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), than are persons in other age groups ( 1 ), younger persons can experience infection and subsequently transmit infection to those at higher risk for severe illness ( 2 – 4 ). Although at lower risk for severe disease, some young adults experience serious illness, and asymptomatic or mild cases can result in sequelae such as myocardial inflammation ( 5 ). In the United States, approximately 45% of persons aged 18–22 years were enrolled in colleges and universities in 2019 ( 6 ). As these institutions reopen, opportunities for infection increase; therefore, mitigation efforts and monitoring reports of COVID-19 cases among young adults are important. During August 2–September 5, weekly incidence of COVID-19 among persons aged 18–22 years rose by 55.1% nationally; across U.S. Census regions,* increases were greatest in the Northeast, where incidence increased 144.0%, and Midwest, where incidence increased 123.4%. During the same period, changes in testing volume for SARS-CoV-2 in this age group ranged from a 6.2% decline in the West to a 170.6% increase in the Northeast. In addition, the proportion of cases in this age group among non-Hispanic White (White) persons increased from 33.8% to 77.3% during May 31–September 5. Mitigation and preventive measures targeted to young adults can likely reduce SARS-CoV-2 transmission among their contacts and communities. As colleges and universities resume operations, taking steps to prevent the spread of COVID-19 among young adults is critical ( 7 ). CDC receives patient-level COVID-19 data from jurisdictional health departments through a standardized CDC COVID-19 case report form. † Data on probable and confirmed cases from 50 states, the District of Columbia (DC), and four territories (Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands) were analyzed to determine national trends among demographic groups during May 31–September 5, 2020. § When available, date of symptom onset was used in calculations of weekly trends of case data; if symptom onset date was unavailable, an alternative date was used in the following descending order: specimen collection date, date reported to CDC, or episode date (California only). ¶ Trends were analyzed nationally and by U.S. Census region. Measures of weekly SARS-CoV-2 real-time reverse transcription–polymerase chain reaction (RT-PCR) testing volumes by age were obtained from COVID-19 electronic laboratory reporting data submitted by state health departments (37 states) and from data submitted directly by public health, commercial, and reference laboratories (13 states and DC)** when age was unavailable in state-submitted data. Testing data from U.S. territories were not included. Total number of tests was calculated as the sum of negative and positive test results. Testing volume represents individual tests, not the number of persons tested. Date of specimen collection or test order date was used in calculations of weekly trends in testing volume. †† Data on COVID-19 cases and RT-PCR tests were aggregated by calendar week. Subgroup analyses of case reports and tests were analyzed using two measures: 1) number of reported cases (or tests) per 100,000 population per week (termed incidence for cases), which accounts for differences in underlying population size but is affected by reporting lags and underreporting; and 2) percentage of all cases (or all tests) each week, which does not account for differences in population size but is less affected by reporting lags or underreporting (assuming that reported data do not differ in important ways from lagged data). §§ All analyses were conducted using R software (version 4.0.2; The R Foundation). During August 2–September 5, 2020, a total 999,579 persons with COVID-19 with case report data were reported to CDC, 15.6% of whom were aged 18–22 years. National weekly COVID-19 incidence among persons aged 18–22 years increased 62.7% (95% confidence interval [CI] = 60.0%–65.3%) during the 4-week period August 2–August 29 from 110 to 180 cases per 100,000 before declining to 171 during August 30–September 5 (Figure 1). During August 2–September 5, weekly incidence increased most in the Northeast (144.0%; 95% CI = 131.5%–157.3%) from 53 to 130 per 100,000, and in the Midwest (123.4%; 95% CI = 116.1%–131.0%), from 111 to 247 (Supplementary Figure 1, https://stacks.cdc.gov/view/cdc/94198). Notably, in the Northeast, weekly incidence has remained below 53 cases per 100,000 in all other age groups since July 4. In the South, weekly incidence among persons aged 18–22 years increased 43.8% (95% CI = 40.0%–47.6%) from 115 to 166 cases per 100,000. Weekly increases were smallest in the West, where incidence declined initially until August 22 and then increased through September 5, but, overall, declined 1.7% during August. During August 2–September 5, the proportion of all cases per week that occurred among persons aged 18–22 years approximately doubled (2.1-fold; 95% CI = 2.1–2.2), from 10.5% to 22.5%. FIGURE 1 Weekly COVID-19 incidence in case surveillance data,* by age group — United States,† May 31–September 5, 2020 Abbreviation: COVID-19 = coronavirus 2019. * From CDC COVID-19 case report surveillance systems. Case report surveillance systems record 76% of national aggregate case counts reported to CDC, based on an analysis of data reported during March15–August 15. † Includes cases in 50 states, District of Columbia, and four territories: Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. The figure consists of two panels showing weekly COVID-19 incidence in case surveillance data, by age group nationally, during May 31–September 5, 2020. The number of weekly tests performed among persons aged 18–22 years increased 49.3% (95% CI = 48.7%–49.9%) from 1,877 tests per 100,000 during the week of August 2–August 8 to 2,802 during the week of August 30–September 5 (Figure 2). The largest increase in testing relative to population size was in the Northeast, where weekly tests increased 170.6% (95% CI = 168.3%–172.9%) from 1,975 per 100,000 to 5,345, and in the Midwest, where weekly tests increased 65.2% (95% CI = 63.9%–66.5%) from 2,264 per 100,000 to 3,740 (Supplementary Figure 2, https://stacks.cdc.gov/view/cdc/94197). In contrast, more modest increases were observed in the South (7.0% [95% CI = 6.3%–7.7%], from 2,041 to 2,183 per 100,000); and in the West, testing volume declined 6.2% (95% CI = 5.1%–7.2%), from 1,191 per 100,000 to 1,118. At the end of this period, the proportion of all tests performed nationally among persons aged 18–22 years had increased from 9.4% to 14.4% (1.5-fold [95% CI = 1.53–1.54] higher than at the beginning). FIGURE 2 Total weekly SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) test volume and percentage of weekly tests,* by age group — United States,† May 31–September 5, 2020 Abbreviation: COVID-19 = coronavirus 2019. * Percentage of weekly tests was calculated as number of tests within each age group divided by number of tests in all age groups. Specimen collection date or test order date was used for analysis. Tests volume data were obtained from COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and, when age was not available in state-submitted data, from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia. The data might not include results from all testing sites within a jurisdiction (e.g., point-of-care test sites) and therefore reflect the majority of, but not all, SARS-CoV-2 RT-PCR tests in the United States. † Includes tests conducted in 50 states and District of Columbia. The figure consists of two panels showing total weekly SARS-CoV-2 reverse transcription–polymerase chain reaction test volume and percentage of weekly tests, by age group nationally, during May 31–September 5, 2020. When examined by race and ethnicity nationally, during August 2–September 5, the weekly incidence among White persons aged 18-22 years increased 149.7% (95% CI = 78.8%–248.7%), from 48 per 100,000 to 120 (Figure 3). During May 31–June 20, the proportion of weekly cases that occurred among White persons aged 18–22 years increased from 33.8%% to 50.8%. Then, during August 2–September 5, the proportion was 1.5-fold that during May 31–June 20 (95% CI = 0.2–12.9), having increased from 52.1% to 77.3%. At the same time, incidence among persons of other racial and ethnic minority groups remained stable or declined. The largest increases in incidence among White persons were in the Midwest (198.2%; from 65 to 195 per 100,000) and the Northeast (168.4%; from 14 to 37 per 100,000) (Supplementary Figure 3, https://stacks.cdc.gov/view/cdc/94196). FIGURE 3 Weekly COVID-19 incidence in case surveillance data* among persons aged 18–22 years, by race/ethnicity † , § — United States,¶ May 31–September 5, 2020. Abbreviation: COVID-19 = coronavirus 2019. * From CDC COVID-19 case report surveillance systems. Case report surveillance systems record 76% of national aggregate case counts reported to CDC, based on an analysis of data reported during March 15–August 15. † Race/ethnicity data were not reported for 2,476,317 (48.5%) case reports; these cases were excluded from this subgroup analysis. § Race categories include persons of non-Hispanic ethnicity. ¶ Includes cases in 50 states, District of Columbia, and four territories: Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. The figure consists of two panels showing weekly COVID-19 incidence in case surveillance data among persons aged 18–22 years, by race/ethnicity nationally, during May 31–September 5, 2020. Discussion In August 2020, CDC and case-reporting jurisdictions identified an increase in the percentage of COVID-19 cases among persons aged 18–22 years. Incidence in this age group changed 2.1-fold during this time, compared with a 1.5-fold change in testing (possibly related to new screening practices as colleges and universities reopened). Although increased incidence was likely driven in part by an increase in COVID-19 diagnostic testing, this is unlikely to be the sole reason for the observed increases in incidence. The observed increases in COVID-19 cases among persons aged 18–22 years could be driven by many factors, including changes in behavior or risk profiles resulting from multiple social, economic, and public policy changes during this period. Because approximately 45% of persons aged 18–22 years attend colleges and universities and 55% of those attending identified as White persons ( 6 ), it is likely that some of this increase is linked to resumption of in-person attendance at some colleges and universities. Detailed exposure information from patients in this age group (e.g., through targeted epidemiologic studies) can help identify the specific drivers of the observed trends. The findings in this report are subject to at least four limitations. First, race/ethnicity data were complete for only one half of cases reported to CDC; changes in completeness of race/ethnicity data over time call for caution in interpretation of the observed trends in race/ethnicity. Second, data-reporting lags can delay recognition and reporting of trends in case surveillance data; for this reason, this report examines COVID-19 cases occurring through September 5, which might be more completely reported than are cases in more recent weeks. Third, a revised COVID-19 case definition introduced by the Council of State and Territorial Epidemiologists on August 5,¶¶ which updated definitions of probable cases, was gradually adopted by approximately one half of reporting jurisdictions during the period of this analysis and might have introduced additional variability in case reporting. Finally, trends in case surveillance data need to be interpreted in the context of laboratory testing patterns (e.g., repeat testing of all students in some university settings)*** and trends in other age groups and with evidence from other data sources; however, linking testing data with case surveillance remains a challenge because person-level data are deidentified before aggregation or analysis. Previous reports identified young adults as being less likely than are other age groups to adhere to some COVID-19 prevention measures ( 8 ), which places them and their close contacts at higher risk for COVID-19. Approximately 71% of persons aged 18–22 years reside with a parent, nearly one half attend colleges and universities, and 33% live with a parent while enrolled ( 6 , 9 ). To prevent cases on campuses and broader spread within communities, it is critically important for students, faculty, and staff members at colleges and universities to remain vigilant and take steps to reduce the risk for SARS-CoV-2 transmission in these settings. Transmission by young adults is not limited to those who attend colleges and universities but can occur throughout communities where young adults live, work, or socialize and to other members of their households ( 3 – 4 ), some of whom might be at high risk for severe COVID-19–associated illness because of age or underlying medical conditions. Mitigation and preventive measures targeted to young adults (e.g., social media toolkits discussing the importance of mask wearing, social distancing, and hand hygiene) ( 10 ), including those attending colleges and universities, can likely reduce SARS-CoV-2 transmission among their contacts and communities. Institutions of higher education should support students and communities by taking action to promote healthy environments ( 7 ). Summary What is already known about this topic? Young adults with COVID-19 can spread infection to their contacts and communities. What is added by this report? During August 2–September 5, 2020, weekly COVID-19 cases among persons aged 18–22 years increased 55% nationally. Increases were greatest in the Northeast (144%) and Midwest (123%). Increases in cases were not solely attributable to increased testing. What are the implications for public health practice? Young adults, including those enrolled in colleges and universities, should take precautions, including mask wearing, social distancing, and hand hygiene, and follow local, state, and federal guidance for minimizing the spread of COVID-19. Institutions of higher education should take action to promote healthy environments.

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          Hospitalization Rates and Characteristics of Patients Hospitalized with Laboratory-Confirmed Coronavirus Disease 2019 — COVID-NET, 14 States, March 1–30, 2020

          Since SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in December 2019 ( 1 ), approximately 1.3 million cases have been reported worldwide ( 2 ), including approximately 330,000 in the United States ( 3 ). To conduct population-based surveillance for laboratory-confirmed COVID-19–associated hospitalizations in the United States, the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET) was created using the existing infrastructure of the Influenza Hospitalization Surveillance Network (FluSurv-NET) ( 4 ) and the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET). This report presents age-stratified COVID-19–associated hospitalization rates for patients admitted during March 1–28, 2020, and clinical data on patients admitted during March 1–30, 2020, the first month of U.S. surveillance. Among 1,482 patients hospitalized with COVID-19, 74.5% were aged ≥50 years, and 54.4% were male. The hospitalization rate among patients identified through COVID-NET during this 4-week period was 4.6 per 100,000 population. Rates were highest (13.8) among adults aged ≥65 years. Among 178 (12%) adult patients with data on underlying conditions as of March 30, 2020, 89.3% had one or more underlying conditions; the most common were hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). These findings suggest that older adults have elevated rates of COVID-19–associated hospitalization and the majority of persons hospitalized with COVID-19 have underlying medical conditions. These findings underscore the importance of preventive measures (e.g., social distancing, respiratory hygiene, and wearing face coverings in public settings where social distancing measures are difficult to maintain) † to protect older adults and persons with underlying medical conditions, as well as the general public. In addition, older adults and persons with serious underlying medical conditions should avoid contact with persons who are ill and immediately contact their health care provider(s) if they have symptoms consistent with COVID-19 (https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html) ( 5 ). Ongoing monitoring of hospitalization rates, clinical characteristics, and outcomes of hospitalized patients will be important to better understand the evolving epidemiology of COVID-19 in the United States and the clinical spectrum of disease, and to help guide planning and prioritization of health care system resources. COVID-NET conducts population-based surveillance for laboratory-confirmed COVID-19–associated hospitalizations among persons of all ages in 99 counties in 14 states (California, Colorado, Connecticut, Georgia, Iowa, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah), distributed across all 10 U.S Department of Health and Human Services regions. § The catchment area represents approximately 10% of the U.S. population. Patients must be residents of a designated COVID-NET catchment area and hospitalized within 14 days of a positive SARS-CoV-2 test to meet the surveillance case definition. Testing is requested at the discretion of treating health care providers. Laboratory-confirmed SARS-CoV-2 is defined as a positive result by any test that has received Emergency Use Authorization for SARS-CoV-2 testing. ¶ COVID-NET surveillance officers in each state identify cases through active review of notifiable disease and laboratory databases and hospital admission and infection control practitioner logs. Weekly age-stratified hospitalization rates are estimated using the number of catchment area residents hospitalized with laboratory-confirmed COVID-19 as the numerator and National Center for Health Statistics vintage 2018 bridged-race postcensal population estimates for the denominator.** As of April 3, 2020, COVID-NET hospitalization rates are being published each week at https://gis.cdc.gov/grasp/covidnet/COVID19_3.html. For each case, trained surveillance officers conduct medical chart abstractions using a standard case report form to collect data on patient characteristics, underlying medical conditions, clinical course, and outcomes. Chart reviews are finalized once patients have a discharge disposition. COVID-NET surveillance was initiated on March 23, 2020, with retrospective case identification of patients admitted during March 1–22, 2020, and prospective case identification during March 23–30, 2020. Clinical data on underlying conditions and symptoms at admission are presented through March 30; hospitalization rates are updated weekly and, therefore, are presented through March 28 (epidemiologic week 13). The COVID-19–associated hospitalization rate among patients identified through COVID-NET for the 4-week period ending March 28, 2020, was 4.6 per 100,000 population (Figure 1). Hospitalization rates increased with age, with a rate of 0.3 in persons aged 0–4 years, 0.1 in those aged 5–17 years, 2.5 in those aged 18–49 years, 7.4 in those aged 50–64 years, and 13.8 in those aged ≥65 years. Rates were highest among persons aged ≥65 years, ranging from 12.2 in those aged 65–74 years to 17.2 in those aged ≥85 years. More than half (805; 54.4%) of hospitalizations occurred among men; COVID-19-associated hospitalization rates were higher among males than among females (5.1 versus 4.1 per 100,000 population). Among the 1,482 laboratory-confirmed COVID-19–associated hospitalizations reported through COVID-NET, six (0.4%) each were patients aged 0–4 years and 5–17 years, 366 (24.7%) were aged 18–49 years, 461 (31.1%) were aged 50–64 years, and 643 (43.4%) were aged ≥65 years. Among patients with race/ethnicity data (580), 261 (45.0%) were non-Hispanic white (white), 192 (33.1%) were non-Hispanic black (black), 47 (8.1%) were Hispanic, 32 (5.5%) were Asian, two (0.3%) were American Indian/Alaskan Native, and 46 (7.9%) were of other or unknown race. Rates varied widely by COVID-NET surveillance site (Figure 2). FIGURE 1 Laboratory-confirmed coronavirus disease 2019 (COVID-19)–associated hospitalization rates,* by age group — COVID-NET, 14 states, † March 1–28, 2020 Abbreviation: COVID-NET = Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. * Number of patients hospitalized with COVID-19 per 100,000 population. † Counties included in COVID-NET surveillance: California (Alameda, Contra Costa, and San Francisco counties); Colorado (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); Connecticut (New Haven and Middlesex counties); Georgia (Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale counties); Iowa (one county represented); Maryland (Allegany, Anne Arundel, Baltimore, Baltimore City, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Garrett, Harford, Howard, Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, and Worcester counties); Michigan (Clinton, Eaton, Genesee, Ingham, and Washtenaw counties); Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties); New Mexico (Bernalillo, Chaves, Dona Ana, Grant, Luna, San Juan, and Santa Fe counties); New York (Albany, Columbia, Genesee, Greene, Livingston, Monroe, Montgomery, Ontario, Orleans, Rensselaer, Saratoga, Schenectady, Schoharie, Wayne, and Yates counties); Ohio (Delaware, Fairfield, Franklin, Hocking, Licking, Madison, Morrow, Perry, Pickaway and Union counties); Oregon (Clackamas, Multnomah, and Washington counties); Tennessee (Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties); and Utah (Salt Lake County). The figure is a bar chart showing laboratory-confirmed COVID-19–associated hospitalization rates, by age group, in 14 states during March 1–28, 2020 according to the Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. FIGURE 2 Laboratory-confirmed coronavirus disease 2019 (COVID-19)–associated hospitalization rates,* by surveillance site † — COVID-NET, 14 states, March 1–28, 2020 Abbreviation: COVID-NET = Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. * Number of patients hospitalized with COVID-19 per 100,000 population. † Counties included in COVID-NET surveillance: California (Alameda, Contra Costa, and San Francisco counties); Colorado (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); Connecticut (New Haven and Middlesex counties); Georgia (Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale counties); Iowa (one county represented); Maryland (Allegany, Anne Arundel, Baltimore, Baltimore City, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Garrett, Harford, Howard, Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, and Worcester counties); Michigan (Clinton, Eaton, Genesee, Ingham, and Washtenaw counties); Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties); New Mexico (Bernalillo, Chaves, Dona Ana, Grant, Luna, San Juan, and Santa Fe counties); New York (Albany, Columbia, Genesee, Greene, Livingston, Monroe, Montgomery, Ontario, Orleans, Rensselaer, Saratoga, Schenectady, Schoharie, Wayne, and Yates counties); Ohio (Delaware, Fairfield, Franklin, Hocking, Licking, Madison, Morrow, Perry, Pickaway and Union counties); Oregon (Clackamas, Multnomah, and Washington counties); Tennessee (Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties); and Utah (Salt Lake County). The figure is a bar chart showing laboratory-confirmed COVID-19–associated hospitalization rates, by surveillance site, in 14 states during March 1–28, 2020 according to the Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. During March 1–30, underlying medical conditions and symptoms at admission were reported through COVID-NET for approximately 180 (12.1%) hospitalized adults (Table); 89.3% had one or more underlying conditions. The most commonly reported were hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). Among patients aged 18–49 years, obesity was the most prevalent underlying condition, followed by chronic lung disease (primarily asthma) and diabetes mellitus. Among patients aged 50–64 years, obesity was most prevalent, followed by hypertension and diabetes mellitus; and among those aged ≥65 years, hypertension was most prevalent, followed by cardiovascular disease and diabetes mellitus. Among 33 females aged 15–49 years hospitalized with COVID-19, three (9.1%) were pregnant. Among 167 patients with available data, the median interval from symptom onset to admission was 7 days (interquartile range [IQR] = 3–9 days). The most common signs and symptoms at admission included cough (86.1%), fever or chills (85.0%), and shortness of breath (80.0%). Gastrointestinal symptoms were also common; 26.7% had diarrhea, and 24.4% had nausea or vomiting. TABLE Underlying conditions and symptoms among adults aged ≥18 years with coronavirus disease 2019 (COVID-19)–associated hospitalizations — COVID-NET, 14 states,* March 1–30, 2020† Underlying condition Age group (yrs), no./total no. (%) Overall 18–49 50–64 ≥65 years Any underlying condition 159/178 (89.3) 41/48 (85.4) 51/59 (86.4) 67/71 (94.4) Hypertension 79/159 (49.7) 7/40 (17.5) 27/57 (47.4) 45/62 (72.6) Obesity§ 73/151 (48.3) 23/39 (59.0) 25/51 (49.0) 25/61 (41.0) Chronic metabolic disease¶ 60/166 (36.1) 10/46 (21.7) 21/56 (37.5) 29/64 (45.3)    Diabetes mellitus 47/166 (28.3) 9/46 (19.6) 18/56 (32.1) 20/64 (31.3) Chronic lung disease 55/159 (34.6) 16/44 (36.4) 15/53 (28.3) 24/62 (38.7)    Asthma 27/159 (17.0) 12/44 (27.3) 7/53 (13.2) 8/62 (12.9)    Chronic obstructive pulmonary disease 17/159 (10.7) 0/44 (0.0) 3/53 (5.7) 14/62 (22.6) Cardiovascular disease** 45/162 (27.8) 2/43 (4.7) 11/56 (19.6) 32/63 (50.8)    Coronary artery disease 23/162 (14.2) 0/43 (0.0) 7/56 (12.5) 16/63 (25.4)    Congestive heart failure 11/162 (6.8) 2/43 (4.7) 3/56 (5.4) 6/63 (9.5) Neurologic disease 22/157 (14.0) 4/42 (9.5) 4/55 (7.3) 14/60 (23.3) Renal disease 20/153 (13.1) 3/41 (7.3) 2/53 (3.8) 15/59 (25.4) Immunosuppressive condition 15/156 (9.6) 5/43 (11.6) 4/54 (7.4) 6/59 (10.2) Gastrointestinal/Liver disease 10/152 (6.6) 4/42 (9.5) 0/54 (0.0) 6/56 (10.7) Blood disorder 9/156 (5.8) 1/43 (2.3) 1/55 (1.8) 7/58 (12.1) Rheumatologic/Autoimmune disease 3/154 (1.9) 1/42 (2.4) 0/54 (0.0) 2/58 (3.4) Pregnancy†† 3/33 (9.1) 3/33 (9.1) N/A N/A Symptom §§ Cough 155/180 (86.1) 43/47 (91.5) 54/60 (90.0) 58/73 (79.5) Fever/Chills 153/180 (85.0) 38/47 (80.9) 53/60 (88.3) 62/73 (84.9) Shortness of breath 144/180 (80.0) 40/47 (85.1) 50/60 (83.3) 54/73 (74.0) Myalgia 62/180 (34.4) 20/47 (42.6) 23/60 (38.3) 19/73 (26.0) Diarrhea 48/180 (26.7) 10/47 (21.3) 17/60 (28.3) 21/73 (28.8) Nausea/Vomiting 44/180 (24.4) 12/47 (25.5) 17/60 (28.3) 15/73 (20.5) Sore throat 32/180 (17.8) 8/47 (17.0) 13/60 (21.7) 11/73 (15.1) Headache 29/180 (16.1) 10/47 (21.3) 12/60 (20.0) 7/73 (9.6) Nasal congestion/Rhinorrhea 29/180 (16.1) 8/47 (17.0) 13/60 (21.7) 8/73 (11.0) Chest pain 27/180 (15.0) 9/47 (19.1) 13/60 (21.7) 5/73 (6.8) Abdominal pain 15/180 (8.3) 6/47 (12.8) 6/60 (10.0) 3/73 (4.1) Wheezing 12/180 (6.7) 3/47 (6.4) 2/60 (3.3) 7/73 (9.6) Altered mental status/Confusion 11/180 (6.1) 3/47 (6.4) 2/60 (3.3) 6/73 (8.2) Abbreviations: COVID-NET = Coronavirus Disease 2019–Associated Hospitalization Surveillance Network; N/A = not applicable. * Counties included in COVID-NET surveillance: California (Alameda, Contra Costa, and San Francisco counties); Colorado (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); Connecticut (New Haven and Middlesex counties); Georgia (Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale counties); Iowa (one county represented); Maryland (Allegany, Anne Arundel, Baltimore, Baltimore City, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Garrett, Harford, Howard, Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, and Worcester counties); Michigan (Clinton, Eaton, Genesee, Ingham, and Washtenaw counties); Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties); New Mexico (Bernalillo, Chaves, Dona Ana, Grant, Luna, San Juan, and Santa Fe counties); New York (Albany, Columbia, Genesee, Greene, Livingston, Monroe, Montgomery, Ontario, Orleans, Rensselaer, Saratoga, Schenectady, Schoharie, Wayne, and Yates counties); Ohio (Delaware, Fairfield, Franklin, Hocking, Licking, Madison, Morrow, Perry, Pickaway and Union counties); Oregon (Clackamas, Multnomah, and Washington counties); Tennessee (Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties); and Utah (Salt Lake County). † COVID-NET included data for one child aged 5–17 years with underlying medical conditions and symptoms at admission; data for this child are not included in this table. This child was reported to have chronic lung disease (asthma). Symptoms included fever, cough, gastrointestinal symptoms, shortness of breath, chest pain, and a sore throat on admission. § Obesity is defined as calculated body mass index (BMI) ≥30 kg/m2, and if BMI is missing, by International Classification of Diseases discharge diagnosis codes. Among 73 patients with obesity, 51 (69.9%) had obesity defined as BMI 30–<40 kg/m2, and 22 (30.1%) had severe obesity defined as BMI ≥40 kg/m2. ¶ Among the 60 patients with chronic metabolic disease, 45 had diabetes mellitus only, 13 had thyroid dysfunction only, and two had diabetes mellitus and thyroid dysfunction. ** Cardiovascular disease excludes hypertension. †† Restricted to women aged 15–49 years. §§ Symptoms were collected through review of admission history and physical exam notes in the medical record and might be determined by subjective or objective findings. In addition to the symptoms in the table, the following less commonly reported symptoms were also noted for adults with information on symptoms (180): hemoptysis/bloody sputum (2.2%), rash (1.1%), conjunctivitis (0.6%), and seizure (0.6%). Discussion During March 1–28, 2020, the overall laboratory-confirmed COVID-19–associated hospitalization rate was 4.6 per 100,000 population; rates increased with age, with the highest rates among adults aged ≥65 years. Approximately 90% of hospitalized patients identified through COVID-NET had one or more underlying conditions, the most common being obesity, hypertension, chronic lung disease, diabetes mellitus, and cardiovascular disease. Using the existing infrastructure of two respiratory virus surveillance platforms, COVID-NET was implemented to produce robust, weekly, age-stratified hospitalization rates using standardized data collection methods. These data are being used, along with data from other surveillance platforms (https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview.html), to monitor COVID-19 disease activity and severity in the United States. During the first month of surveillance, COVID-NET hospitalization rates ranged from 0.1 per 100,000 population in persons aged 5–17 years to 17.2 per 100,000 population in adults aged ≥85 years, whereas cumulative influenza hospitalization rates during the first 4 weeks of each influenza season (epidemiologic weeks 40–43) over the past 5 seasons have ranged from 0.1 in persons aged 5–17 years to 2.2–5.4 in adults aged ≥85 years ( 6 ). COVID-NET rates during this first 4-week period of surveillance are preliminary and should be interpreted with caution; given the rapidly evolving nature of the COVID-19 pandemic, rates are expected to increase as additional cases are identified and as SARS-CoV-2 testing capacity in the United States increases. In the COVID-NET catchment population, approximately 49% of residents are male and 51% of residents are female, whereas 54% of COVID-19-associated hospitalizations occurred in males and 46% occurred in females. These data suggest that males may be disproportionately affected by COVID-19 compared with females. Similarly, in the COVID-NET catchment population, approximately 59% of residents are white, 18% are black, and 14% are Hispanic; however, among 580 hospitalized COVID-19 patients with race/ethnicity data, approximately 45% were white, 33% were black, and 8% were Hispanic, suggesting that black populations might be disproportionately affected by COVID-19. These findings, including the potential impact of both sex and race on COVID-19-associated hospitalization rates, need to be confirmed with additional data. Most of the hospitalized patients had underlying conditions, some of which are recognized to be associated with severe COVID-19 disease, including chronic lung disease, cardiovascular disease, diabetes mellitus ( 5 ). COVID-NET does not collect data on nonhospitalized patients; thus, it was not possible to compare the prevalence of underlying conditions in hospitalized versus nonhospitalized patients. Many of the documented underlying conditions among hospitalized COVID-19 patients are highly prevalent in the United States. According to data from the National Health and Nutrition Examination Survey, hypertension prevalence among U.S. adults is 29% overall, ranging from 7.5%–63% across age groups ( 7 ), and age-adjusted obesity prevalence is 42% (range across age groups = 40%–43%) ( 8 ). Among hospitalized COVID-19 patients, hypertension prevalence was 50% (range across age groups = 18%–73%), and obesity prevalence was 48% (range across age groups = 41%–59%). In addition, the prevalences of several underlying conditions identified through COVID-NET were similar to those for hospitalized influenza patients identified through FluSurv-NET during influenza seasons 2014–15 through 2018–19: 41%–51% of patients had cardiovascular disease (excluding hypertension), 39%–45% had chronic metabolic disease, 33%–40% had obesity, and 29%–31% had chronic lung disease ( 6 ). Data on hypertension are not collected by FluSurv-NET. Among women aged 15–49 years hospitalized with COVID-19 and identified through COVID-NET, 9% were pregnant, which is similar to an estimated 9.9% of the general population of women aged 15–44 years who are pregnant at any given time based on 2010 data. †† Similar to other reports from the United States ( 9 ) and China ( 1 ), these findings indicate that a high proportion of U.S. patients hospitalized with COVID-19 are older and have underlying medical conditions. The findings in this report are subject to at least three limitations. First, hospitalization rates by age and COVID-NET site are preliminary and might change as additional cases are identified from this surveillance period. Second, whereas minimum case data to produce weekly age-stratified hospitalization rates are usually available within 7 days of case identification, availability of detailed clinical data are delayed because of the need for medical chart abstractions. As of March 30, chart abstractions had been conducted for approximately 200 COVID-19 patients; the frequency and distribution of underlying conditions during this time might change as additional data become available. Clinical course and outcomes will be presented once the number of cases with complete medical chart abstractions are sufficient; many patients are still hospitalized at the time of this report. Finally, testing for SARS-CoV-2 among patients identified through COVID-NET is performed at the discretion of treating health care providers, and testing practices and capabilities might vary widely across providers and facilities. As a result, underascertainment of cases in COVID-NET is likely. Additional data on testing practices related to SARS-CoV-2 will be collected in the future to account for underascertainment using described methods ( 10 ). Early data from COVID-NET suggest that COVID-19–associated hospitalizations in the United States are highest among older adults, and nearly 90% of persons hospitalized have one or more underlying medical conditions. These findings underscore the importance of preventive measures (e.g., social distancing, respiratory hygiene, and wearing face coverings in public settings where social distancing measures are difficult to maintain) to protect older adults and persons with underlying medical conditions. Ongoing monitoring of hospitalization rates, clinical characteristics, and outcomes of hospitalized patients will be important to better understand the evolving epidemiology of COVID-19 in the United States and the clinical spectrum of disease, and to help guide planning and prioritization of health care system resources. Summary What is already known about this topic? Population-based rates of laboratory-confirmed coronavirus disease 2019 (COVID-19)–associated hospitalizations are lacking in the United States. What is added by this report? COVID-NET was implemented to produce robust, weekly, age-stratified COVID-19–associated hospitalization rates. Hospitalization rates increase with age and are highest among older adults; the majority of hospitalized patients have underlying conditions. What are the implications for public health practice? Strategies to prevent COVID-19, including social distancing, respiratory hygiene, and face coverings in public settings where social distancing measures are difficult to maintain, are particularly important to protect older adults and those with underlying conditions. Ongoing monitoring of hospitalization rates is critical to understanding the evolving epidemiology of COVID-19 in the United States and to guide planning and prioritization of health care resources.
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            Cardiovascular Magnetic Resonance Findings in Competitive Athletes Recovering From COVID-19 Infection

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              Changing Age Distribution of the COVID-19 Pandemic — United States, May–August 2020

              As of September 21, 2020, the coronavirus disease 2019 (COVID-19) pandemic had resulted in more than 6,800,000 reported U.S. cases and more than 199,000 associated deaths.* Early in the pandemic, COVID-19 incidence was highest among older adults ( 1 ). CDC examined the changing age distribution of the COVID-19 pandemic in the United States during May–August by assessing three indicators: COVID-19–like illness-related emergency department (ED) visits, positive reverse transcription–polymerase chain reaction (RT-PCR) test results for SARS-CoV-2, the virus that causes COVID-19, and confirmed COVID-19 cases. Nationwide, the median age of COVID-19 cases declined from 46 years in May to 37 years in July and 38 in August. Similar patterns were seen for COVID-19–like illness-related ED visits and positive SARS-CoV-2 RT-PCR test results in all U.S. Census regions. During June–August, COVID-19 incidence was highest in persons aged 20–29 years, who accounted for >20% of all confirmed cases. The southern United States experienced regional outbreaks of COVID-19 in June. In these regions, increases in the percentage of positive SARS-CoV-2 test results among adults aged 20–39 years preceded increases among adults aged ≥60 years by an average of 8.7 days (range = 4–15 days), suggesting that younger adults likely contributed to community transmission of COVID-19. Given the role of asymptomatic and presymptomatic transmission ( 2 ), strict adherence to community mitigation strategies and personal preventive behaviors by younger adults is needed to help reduce their risk for infection and subsequent transmission of SARS-CoV-2 to persons at higher risk for severe illness. CDC examined age trends during May–August for 50 states and the District of Columbia (DC) using three indicators: 1) COVID-19–like illness-related ED visits; 2) positive SARS-CoV-2 RT-PCR test results; and 3) confirmed COVID-19 cases. COVID-19–like illness-related ED visits, reported by health facilities to the National Syndromic Surveillance Program (NSSP), † had fever with cough, shortness of breath, or difficulty breathing in the chief complaint text or a discharge diagnostic code for COVID-19 and no diagnostic codes for influenza. § Analyses of COVID-19–like illness-related ED visits were based on the ED visit date. SARS-CoV-2 RT-PCR test results were obtained from COVID-19 electronic laboratory reporting data submitted by state health departments (37 states) and, when age was unavailable in state-submitted data, from data submitted directly by public health, commercial, and reference laboratories (13 states and DC). ¶ Data represent the number of specimens tested, not individual persons who received testing. Analyses were based on the specimen collection date or test order date.** The daily percentage of positive SARS-CoV-2 test results (percent positivity) was calculated as the number of positive test results divided by the sum of positive and negative test results. Confirmed COVID-19 cases were identified from individual-level case reports submitted by state health departments †† ; analyses were based on the date the case was reported to CDC. §§ Confirmed COVID-19 cases had a positive SARS-CoV-2 RT-PCR test result. Case data represent individual persons (some of whom might have had multiple positive test results). Monthly incidence was calculated using 2018 U.S. Census population estimates. National case counts, percentage distributions, and estimated incidence of confirmed COVID-19 cases were calculated by 10-year age increments and by month (May–August). The weekly median age of persons with COVID-19–like illness-related ED visits, positive SARS-CoV-2 test results, and confirmed COVID-19 cases, as well as that of persons for whom all SARS-CoV-2 tests were conducted, were plotted nationally for the four U.S. Census regions. To minimize the impact of testing availability on findings, the early pandemic period (January–April) was excluded. The southern United States experienced regional COVID-19 outbreaks during June–July 2020. For U.S. Department of Health and Human Services (HHS) Regions 4, 6, and 9, ¶¶ daily percent positivity was plotted for four age groups (0–19 years, 20–39 years, 40–59 years, and ≥60 years). The segmented package (version 1.2-0) in R software (version 3.6.0; The R Foundation) was used to segment the age group-specific trend lines and identify inflection points when the slopes changed. National incidence of confirmed COVID-19 increased from 185 cases per 100,000 persons in May to 316 in July, then declined to 275 in August (Table). During May–July, incidence increased among persons in all age groups 20%). Similar age shifts were observed nationwide. TABLE Reported number of confirmed* COVID-19 cases and estimated incidence, † by age group § and month — United States, May 1–Aug 31, 2020 Age group (yrs) May 2020 June 2020 July 2020 Aug 2020 No. (%) Incidence† No. (%) Incidence† No. (%) Incidence† No. (%) Incidence† 0–9 13,987 (2.3) 35.0 24,772 (3.3) 61.9 40,093 (3.9) 100.2 35,612 (4.0) 89.0 10–19 31,053 (5.1) 74.0 55,596 (7.5) 132.4 104,048 (10.1) 247.9 103,637 (11.5) 246.9 20–29 93,741 (15.5) 206.3 149,761 (20.2) 329.6 240,105 (23.2) 528.5 189,366 (21.0) 416.8 30–39 101,917 (16.9) 233.2 130,415 (17.6) 298.4 183,478 (17.8) 419.9 148,500 (16.5) 339.8 40–49 98,982 (16.4) 244.6 119,043 (16.0) 294.2 157,019 (15.2) 388.1 134,288 (14.9) 331.9 50–59 99,058 (16.4) 231.3 108,509 (14.6) 253.4 139,004 (13.4) 324.6 124,835 (13.9) 291.5 60–69 72,115 (11.9) 192.7 73,225 (9.9) 195.7 89,586 (8.7) 239.4 84,247 (9.4) 225.1 70–79 42,476 (7.0) 187.3 40,714 (5.5) 179.6 47,851 (4.6) 211.1 47,060 (5.2) 207.6 ≥80 51,241 (8.5) 404.4 41,023 (5.5) 323.7 32,370 (3.1) 255.4 33,005 (3.7) 260.5 Total 604,570 (100.0) 184.8 743,058 (100.0) 227.1 1,033,554 (100.0) 315.9 900,550 (100.0) 275.3 Abbreviation: COVID-19 = coronavirus disease 2019. * A confirmed COVID-19 case required detection of SARS-CoV-2 RNA in a clinical specimen using a molecular amplification detection test. † Cases per 100,000 population calculated using 2018 U.S. Census population estimates. § Data from individual-level case reports submitted by state health departments, using date case was reported to CDC. Case report data were available for approximately 68% of the total aggregate counts of confirmed cases submitted by state health departments. Case reports with missing information on age (3,845) were not included. The median age trend lines for all three indicators (COVID-19–like illness-related ED visits, positive SARS-CoV-2 test results, and confirmed COVID-19 cases) followed similar patterns in the national data (Figure 1) and within each U.S. Census region (Figure 2); however, patterns differed by region. Nationally and in the South and Midwest, median age decreased until mid- to late June, increased during July, and decreased in the latter half of August. In the West, median age declined from May to mid-June and then remained relatively stable or slightly increased during July–August. In the Northeast, median age of persons with positive test results and confirmed cases was stable in May, decreased sharply in June, increased slightly in July, and decreased in August; median age for persons with COVID-19–like illness-related ED visits declined steadily from mid-June to mid-August. In all four U.S. Census regions, the median age of persons for whom all SARS-CoV-2 tests were conducted was relatively stable in May (whereas median age of persons with positive test results and confirmed cases declined in May) and began to decrease following declines in the other three indicators. FIGURE 1 Weekly median age of persons with COVID-19–like illness-related emergency department (ED) visits, * positive SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) test results, † and confirmed COVID-19 cases, § and of persons for whom all SARS-CoV-2 RT-PCR tests were conducted ¶ — United States, May 3–August 29, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * From CDC National Syndromic Surveillance Program (NSSP), using date of ED visit. NSSP records 73% of all emergency department visits in the United States. † From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, based on specimen collection or test order date. The data might not include results from all testing sites within a jurisdiction (e.g., point-of-care test sites) and therefore reflect the majority of, but not all, SARS-CoV-2 RT-PCR tests in the United States. § From case reports with individual-level information submitted by state health departments, using date case was reported to CDC. Case report data were available for approximately 68% of the total daily aggregate number of confirmed cases submitted by state health departments. ¶ From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, based on specimen collection or test order date. The data might not include results from all testing sites within a jurisdiction (e.g., point-of-care test sites) and therefore reflect the majority of, but not all, SARS-CoV-2 RT-PCR tests in the United States. The figure is a line chart showing weekly median age of persons with COVID-19–like illness-related emergency department visits, positive SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) test results, and confirmed COVID-19 cases and median age of persons for whom all SARS-CoV-2 RT-PCR tests were conducted in the United States during May 3–August 29, 2020. FIGURE 2 Weekly median age of persons with COVID-19–like illness-related emergency department (ED) visits, * positive SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) test results, † and confirmed COVID-19 cases, § and of persons for whom all SARS-CoV-2 RT-PR tests were conducted, ¶ by U.S. Census region ** — United States May 3–August 29, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * From CDC National Syndromic Surveillance Program (NSSP), using date of ED visit. NSSP records 73% of all emergency department visits in the United States. † From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, based on specimen collection or test order date. The data might not include results from all testing sites within a jurisdiction (e.g., point-of-care test sites) and therefore reflect the majority, but not all, SARS-CoV-2 RT-PCR tests in the United States. § From case reports with individual-level information submitted by state health departments, using date case was reported to CDC. Case report data were available for approximately 68% of the total daily aggregate number of confirmed cases submitted by state health departments. ¶ From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, based on specimen collection or test order date. The data might not include results from all testing sites within a jurisdiction (e.g., point-of-care test sites) and therefore reflect the majority, but not all, SARS-CoV-2 RT-PCR tests in the United States. ** West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia; Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. The figure is a series of four panels, each a line chart showing weekly median age of persons with COVID-19–like illness-related emergency department visits, positive SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) test results, and confirmed COVID-19 cases and median age of persons for whom all SARS-CoV-2 RT-PCR tests were conducted, by U.S. Census region in the United States during May 3–August 29, 2020. During June 2020 in HHS Regions 4, 6, and 9, the change to an upward slope in percent positivity among persons aged 20–39 years occurred an average of 8.7 days (range 4–15 days) before the change to an upward slope among persons aged ≥60 years (Supplementary Figure, https://stacks.cdc.gov/view/cdc/93914). This pattern was most evident in Region 4 (Southeast) where the increase in percent positivity among persons aged 20–39 years preceded increases among persons aged 40–59 years by 9 days and those aged ≥60 years by 15 days; percent positivity among persons aged 0–19 years increased steadily from early May to early July. Within HHS Regions 6 and 9 (Southcentral and Southwest), the percent positivity among persons aged 0–19, 20–39, and 40–59 years increased at approximately the same time and preceded increases among persons aged ≥60 years by approximately 7 days in Region 6 and 4 days in Region 9. Discussion During June–August, the COVID-19 pandemic in the United States affected a larger proportion of younger persons than during January–May 2020 ( 1 ). The shift toward younger ages occurred in all four U.S. Census regions, regardless of changes in incidence during this period, and was reflected in COVID-19–like illness-related ED visits, positive SARS-CoV-2 RT-PCR test results, and confirmed COVID-19 cases. A similar age shift occurred in Europe, where the median age of COVID-19 cases declined from 54 years during January–May to 39 years during June–July, during which time persons aged 20–29 years constituted the largest proportion of cases (19.5%) ( 3 ). Case and laboratory surveillance are based on consistent availability of diagnostic testing to all segments of the population, and changes in testing across age groups could affect the age distribution of positive SARS-CoV-2 test results and confirmed cases. Although testing availability has varied by place, time, and test provider, it is unlikely that the observed age shift resulted solely from changes in testing availability. First, the decline in median age of persons for whom all SARS-CoV-2 tests were conducted lagged behind declines in median age of persons with positive test results and confirmed cases, suggesting that infection patterns drove testing patterns. Second, the age distribution of persons for whom all SARS-CoV-2 tests were conducted shifted toward younger groups from May to June but remained relatively consistent during June–August. Third, the percent positivity continued to increase in the face of increased testing volume; this was most evident in HHS Regions 4 and 6 among persons aged 20–39 years during early to mid-June (Supplementary Figure, https://stacks.cdc.gov/view/cdc/93914). Fourth, the median age of persons with COVID-19–like illness-related ED visits, which is not dependent on testing availability, showed similar patterns to those of persons with positive test results and confirmed cases. This report provides preliminary evidence that younger adults contributed to community transmission of COVID-19 to older adults. Across the southern United States in June 2020, the increase in SARS-CoV-2 infection among younger adults preceded the increase among older adults by 4–15 days (or approximately one to three incubation periods). Similar observations have been reported by the World Health Organization.*** Further investigation of community transmission dynamics across age groups to identify factors that might be driving infection among younger adults and subsequent transmission to older adults is warranted. These findings have important clinical and public health implications. First, occupational and behavioral factors might put younger adults at higher risk for exposure to SARS-CoV-2. Younger adults make up a large proportion of workers in frontline occupations (e.g., retail stores, public transit, child care, and social services) and highly exposed industries (e.g., restaurants/bars, entertainment, and personal services) ( 4 , 5 ), where consistent implementation of prevention strategies might be difficult or not possible. In addition, younger adults might also be less likely to follow community mitigation strategies, such as social distancing and avoiding group gatherings ( 6 , 7 ). Second, younger adults, who are more likely to have mild or no symptoms, ††† can unknowingly contribute to presymptomatic or asymptomatic transmission to others ( 2 ), including to persons at higher risk for severe illness. Finally, SARS-CoV-2 infection is not benign in younger adults, especially among those with underlying medical conditions, §§§ who are at risk for hospitalization, severe illness, and death ( 8 ). The findings in this report are subject to at least five limitations. First, case report data submitted to CDC by state health departments underestimates true incidence. Second, batch reporting of historical cases by some states might have led to spikes in median age trend lines, such as the increase seen in the Midwest region in June. Third, the report’s three data sources varied in their geographic coverage, with laboratory data being the most comprehensive. Nevertheless, consistent patterns and trends were observed across the three indicators. Fourth, analyzing data at a regional level could minimize differences in age group–specific trends that might otherwise be observed at the state or local level. Finally, use of ten- and twenty-year age groups might mask age patterns among smaller age groups and those that cross decades, such as recent increases in COVID-19 cases among college and university students. ¶¶¶ Increased prevalence of SARS-CoV-2 infection among younger adults likely contributes to community transmission of COVID-19, including to persons at higher risk for severe illness, such as older adults. Emphasis should be placed on targeted mitigation strategies to reduce infection and transmission among younger adults, including age-appropriate prevention messages ( 7 ), restricting in-person gatherings and events,**** recommending mask use and social distancing in settings where persons socialize, †††† implementing safe practices at on-site eating and drinking venues ( 9 ), and enforcing protection measures for essential and service industry workers. §§§§ Given the role of asymptomatic and presymptomatic transmission ( 2 ), all persons, including young adults, should take extra precautions to avoid transmission to family and community members who are older or who have underlying medical conditions. Strict adherence to community mitigation strategies and personal preventive behaviors by younger adults is needed to help reduce their risk for infection and minimize subsequent transmission of SARS-CoV-2 to persons at higher risk for severe COVID-19. Summary What is already known about this topic? Early in the pandemic, COVID-19 incidence was highest among older adults. What is added by this report? During June–August 2020, COVID-19 incidence was highest in persons aged 20–29 years, who accounted for >20% of all confirmed cases. Younger adults likely contribute to community transmission of COVID-19. Across the southern United States in June 2020, increases in percentage of positive SARS-CoV-2 test results among adults aged 20–39 years preceded increases among those aged ≥60 years by 4–15 days. What are the implications for public health practice? Strict adherence to community mitigation strategies and personal preventive behaviors by younger adults is needed to help reduce infection and subsequent transmission to persons at higher risk for severe illness.
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                Author and article information

                Journal
                MMWR Morb Mortal Wkly Rep
                MMWR Morb Mortal Wkly Rep
                WR
                Morbidity and Mortality Weekly Report
                Centers for Disease Control and Prevention
                0149-2195
                1545-861X
                02 October 2020
                02 October 2020
                : 69
                : 39
                : 1419-1424
                Affiliations
                Epidemic Intelligence Service, CDC; CDC COVID-19 Response Team; Oak Ridge Institute for Science and Engineering, Oak, Ridge, Tennessee.
                Author notes
                Corresponding author: Phillip P. Salvatore, PSalvatore@ 123456cdc.gov .
                Article
                mm6939e4
                10.15585/mmwr.mm6939e4
                7537557
                33006586
                c048e8a8-2a56-424d-92ee-5d43e8975f96

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