COVID-19–Associated Hospitalizations Among Health Care Personnel — COVID-NET, 13 States, March 1–May 31, 2020 – ScienceOpen
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      COVID-19–Associated Hospitalizations Among Health Care Personnel — COVID-NET, 13 States, March 1–May 31, 2020

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      , MPH 1 , , , MSPH 1 , , MPH 1 , 2 , , MD, PhD 3 , , MD 3 , , MD 4 , 5 , , MPH 4 , , MD 6 , , MPH 6 , , MPH 7 , , MPH 7 , , MD 8 , 9 , , DrPH 8 , 9 , 10 , , MPH 11 , , MS 11 , , MPH 12 , 12 , , MPH 13 , , PhD 13 , , MPH 14 , , PhD 15 , , MPH 16 , , MPH 16 , , MD 17 , , MPH 17 , , MPH 18 , , MPH 18 , , MD 19 , , MPH 19 , , MD 20 , , MD 20 , , MPH 21 , , MPH 21 , , MPH 1 , , MD 1 , , DVM 1 , , MD 1 , , MD 1 , , MD 1 , COVID-NET Surveillance Team COVID-NET Surveillance Team COVID-NET Surveillance Team , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
      Morbidity and Mortality Weekly Report
      Centers for Disease Control and Prevention

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          Abstract

          Health care personnel (HCP) can be exposed to SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), both within and outside the workplace, increasing their risk for infection. Among 6,760 adults hospitalized during March 1–May 31, 2020, for whom HCP status was determined by the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET), 5.9% were HCP. Nursing-related occupations (36.3%) represented the largest proportion of HCP hospitalized with COVID-19. Median age of hospitalized HCP was 49 years, and 89.8% had at least one underlying medical condition, of which obesity was most commonly reported (72.5%). A substantial proportion of HCP with COVID-19 had indicators of severe disease: 27.5% were admitted to an intensive care unit (ICU), 15.8% required invasive mechanical ventilation, and 4.2% died during hospitalization. HCP can have severe COVID-19–associated illness, highlighting the need for continued infection prevention and control in health care settings as well as community mitigation efforts to reduce transmission. COVID-NET conducts population-based surveillance for laboratory-confirmed COVID-19–associated hospitalizations among persons of all ages in 99 counties in 14 states ( 1 ). Hospitalized patients who are residents of the surveillance catchment area and have a positive SARS-CoV-2 molecular test result during their hospitalization or within 14 days before admission are included in COVID-NET. SARS-CoV-2 testing is performed at the discretion of health care providers or according to hospital testing policies. Trained surveillance officers conduct medical chart abstractions for COVID-19 patients using a standardized case report form, which includes HCP status. Data on HCP status collected by sites representing 98* counties in 13 states (California, Colorado, Connecticut, Georgia, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah) are included in this analysis. HCP were defined as persons working in health care settings, home health care services, or health care occupations within other settings (e.g., school nurses) who have potential for exposure to patients or infectious materials ( 2 ). HCP were stratified into two groups for analyses according to presumed level of patient contact (i.e., those generally expected and those generally not expected to have direct patient contact) based on reported occupation. † Because of high case counts, nine of 13 sites conducted in-depth medical chart abstractions for an age-stratified random sample of all reported COVID-19 patients hospitalized during March 1–May 31. § Six sites completed chart abstractions for all patients aged <50 years (including all pregnant patients), 20% of patients aged 50–64 years, and 10% of patients aged ≥65 years. Three sites completed abstractions for 10% of patients aged ≥18 years, in addition to all pregnant patients. The remaining four sites completed chart abstractions for all reported patients. As of September 12, chart abstractions were complete for 86% of sampled patients identified through COVID-NET. Descriptive statistics were calculated for all sampled HCP aged ≥18 years hospitalized with COVID-19 during March 1–May 31, 2020, for whom full chart abstraction was completed. Weights were applied to reflect the probability of being sampled for complete chart abstraction; weighted percentages and unweighted case counts are presented throughout this report. Analyses were conducted using SAS (version 9.4; SAS Institute), and 95% confidence intervals (CIs) were generated using the Taylor series linearization method in SUDAAN (version 11; RTI International). COVID-NET activities were determined by CDC to meet the requirements of public health surveillance. ¶ All sites participating in COVID-NET obtained approval from their respective state and local Institutional Review Boards, as applicable. During March 1–May 31, 2020, COVID-NET received reports of 28,972 hospitalized adult patients, 8,515 of whom were sampled for complete chart abstraction (Figure 1). HCP status was documented for 6,760 sampled patients, 438 of whom were HCP, yielding a weighted estimate of 5.9% (95% CI = 5.1%–6.8%). The median age of HCP hospitalized with COVID-19 was 49 years (interquartile range [IQR] = 38–57 years), and 71.9% were female; 52.0% were non-Hispanic Black (Black), 27.4% were non-Hispanic White, and 8.6% were Hispanic or Latino persons (Table). More than two thirds (67.4%) of HCP hospitalized with COVID-19 worked in occupations in which they were generally expected to have direct patient contact; 36.3% of HCP hospitalized with COVID-19 worked in nursing-related occupations, including nurses (27.8%) and certified nursing assistants (CNAs) (8.5%). Patient aides and caregivers (6.6%) accounted for the next largest proportion of HCP hospitalized with COVID-19 (Figure 2). FIGURE 1 Selection of cases for analysis of COVID-19–associated hospitalizations among health care personnel (HCP)* — COVID-NET, 13 states, † March 1–May 31, 2020 Abbreviations: COVID-19 = coronavirus disease 2019; COVID–NET = COVID–19–Associated Hospitalization Surveillance Network. * All case counts are unweighted. † Sites located in the following 13 states: California, Colorado, Connecticut, Georgia, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah. The figure is a flow chart showing the selection of cases for analysis of COVID-19–associated hospitalizations among health care personnel (HCP), using data from COVID-NET, in 13 states, during March 1–May 31, 2020. TABLE Demographic and clinical characteristics of health care personnel (HCP) with COVID-19-associated hospitalizations, overall and by type of patient contact* — COVID-NET, 13 states, † March 1–May 31, 2020 Characteristic Overall (N = 438) Direct patient contact (N = 293) No direct patient contact (N = 145) Unweighted no. (weighted %) 95% CI Unweighted no. (weighted %) 95% CI Unweighted no. (weighted %) 95% CI Type of patient contact Direct patient contact 293 (67.4) (59.9–74.1) — — — — No direct patient contact 145 (32.6) (25.9–40.1) — — — — Age group (N = 438) 18–49 yrs 278 (46.4) (39.1–53.7) 183 (44.4) (35.7–53.4) 95 (50.5) (37.6–63.4) 50–64 yrs 139 (46.1) (38.9–53.5) 99 (51.0) (42.0–59.9) 40 (36.0) (24.7–49.2) ≥65 yrs 21 (7.5) (4.1–13.3) 11 (4.7) (2.0–10.7) 10 (13.4) (5.9–27.7) Median age in years (IQR) 49 (38–57) — 52 (38–57) — 48 (37–57) — Race/Ethnicity (N = 438) White, non-Hispanic 142 (27.4) (21.5–34.1) 104 (33.3) (25.5–42.2) 38 (15.0) (8.9–24.3) Black, non-Hispanic 184 (52.0) (44.5–59.5) 113 (44.7) (35.6–54.1) 71 (67.3) (55.2–77.4) Hispanic or Latino 48 (8.6) (5.3–13.8) 30 (9.8) (5.3–17.3) 18 (6.3) (3.4–11.3) American Indian or Alaska Native, non-Hispanic 39 (6.8) (4.2–10.8) 29 (6.8) (4.0–11.5) 10 (6.7) (2.5–16.9) Asian or Pacific Islander, non-Hispanic 12 (3.2) (1.5–6.6) 10 (4.4) (2.0–9.6) 2 (0.6) (0.1–2.3) Multiple races 1 (0.1) (0.0–0.7) 1 (0.1) (0.0–1.0) — — Unknown 12 (1.9) (0.7–4.9) 6 (0.8) (0.4–1.9) 6 (4.1) (1.1–14.1) Sex (N = 438) Male 131 (28.1) (21.8–35.3) 88 (29.5) (21.8–38.6) 43 (25.2) (15.6–37.9) Female 307 (71.9) (64.7–78.2) 205 (70.5) (61.4–78.2) 102 (74.8) (62.1–84.4) Underlying conditions (N = 438) Any underlying condition§ 377 (89.8) (85.0–93.2) 248 (87.8) (81.0–92.4) 129 (94.0) (88.5–97.0) Obesity (n = 396) 270 (72.5) (65.2–78.7) 177 (68.3) (58.8–76.4) 93 (80.9) (70.3–88.4) Hypertension 158 (40.6) (33.5–48.2) 103 (36.9) (28.6–46.1) 55 (48.3) (35.4–61.4) Chronic metabolic disease 136 (36.7) (29.6–44.3) 88 (32.6) (24.6–41.9) 48 (45.1) (32.3–58.5) Diabetes 115 (30.9) (24.3–38.3) 72 (24.7) (17.8–33.3) 43 (43.6) (31.0–57.2) Chronic lung disease 125 (26.7) (20.6–33.9) 88 (26.6) (19.5–35.3) 37 (26.9) (16.6–40.6) Asthma 92 (18.3) (13.3–24.7) 66 (17.4) (11.9–24.8) 26 (20.2) (11.1–33.9) Cardiovascular disease¶ 45 (13.3) (8.7–19.9) 27 (8.4) (4.8–14.4) 18 (23.5) (13.0–38.6) Pregnancy (n = 189)** 34 (9.6) (6.5–14.0) 22 (9.5) (5.8–15.2) 12 (9.7) (4.9–18.4) Immunocompromised condition 28 (7.0) (4.1–11.8) 17 (6.7) (3.5–12.5) 11 (7.7) (2.9–19.0) Signs and symptoms upon admission (N = 438) Any symptoms 411 (96.6) (94.4–98.0) 276 (96.4) (93.1–98.1) 135 (97.1) (94.5–98.5) Shortness of breath 339 (79.0) (72.0–84.5) 226 (77.9) (69.1–84.7) 113 (81.2) (68.8–89.5) Cough 324 (76.6) (69.7–82.3) 218 (75.1) (66.2–82.3) 106 (79.8) (68.6–87.7) Fever/Chills 323 (73.9) (66.7–80.1) 220 (75.0) (66.0–82.2) 103 (71.8) (58.6–82.2) Muscle aches/Myalgias 177 (35.9) (29.2–43.3) 126 (38.4) (30.0–47.5) 51 (30.9) (20.4–43.8) Nausea/Vomiting 145 (31.6) (25.0–39.1) 99 (33.8) (25.5–43.1) 46 (27.2) (17.3–40.1) Headache 123 (29.3) (22.8–36.7) 79 (27.6) (20.0–36.8) 44 (32.8) (21.7–46.2) Diarrhea 114 (24.8) (19.1–31.4) 75 (27.7) (20.4–36.5) 39 (18.6) (11.9–28.0) Chest pain 105 (23.9) (18.0–31.0) 67 (25.6) (18.2–34.8) 38 (20.5) (12.3–32.2) Congested/Runny nose 65 (14.6) (10.2–20.5) 46 (14.5) (9.4–21.8) 19 (14.8) (7.6–26.8) Sore throat 66 (14.2) (9.7–20.3) 51 (17.1) (11.1–25.4) 15 (8.1) (3.6–17.2) Abdominal pain 46 (12.4) (8.1–18.6) 32 (13.3) (7.9–21.3) 14 (10.8) (4.9–21.9) Anosmia/Decreased smell 40 (9.4) (5.7–15.1) 26 (11.4) (6.3–19.7) 14 (5.2) (2.6–10.1) Dysgeusia/Decreased taste 36 (6.8) (4.0–11.6) 20 (5.7) (2.6–12.1) 16 (9.2) (4.4–18.3) Wheezing 29 (5.7) (3.2–10.1) 19 (4.6) (2.1–9.6) 10 (8.2) (3.3–18.9) Hospital length of stay (median days, IQR) 4 (3–9) — 4 (2–9) — 5 (3–9) — Chest radiograph findings (N = 327) Infiltrate/Consolidation 288 (86.9) (79.3–92.0) 201 (91.4) (84.3–95.5) 87 (76.8) (58.9–88.4) Bronchopneumonia/Pneumonia 84 (32.0) (24.1–41.0) 58 (35.1) (25.3–46.3) 26 (24.9) (13.9–40.5) Pleural effusion 11 (6.3) (3.0–13.1) 5 (2.6) (0.8–7.6) 6 (14.8) (5.8–33.0) Chest CT/MRI findings (N = 94) Infiltrate/Consolidation 56 (61.2) (45.4–75.0) 38 (53.5) (34.9–71.1) 18 (77.0) (47.4–92.6) Ground glass opacities 57 (59.9) (44.0–73.9) 40 (61.4) (42.4–77.5) 17 (56.7) (29.5–80.3) Bronchopneumonia/Pneumonia 41 (46.5) (31.5–62.2) 29 (41.0) (24.1–60.2) 12 (57.9) (31.7–80.4) Pleural effusion 10 (9.3) (3.4–23.2) 9 (10.7) (3.3–29.8) 1 (6.4) (0.9–34.7) COVID–19 investigational treatments (N = 438)†† Received treatment 212 (48.2) (40.8–55.8) 140 (47.5) (38.5–56.7) 72 (49.8) (36.8–62.8) Hydroxychloroquine§§ 152 (35.5) (28.8–42.8) 96 (35.4) (27.3–44.4) 56 (35.6) (24.4–48.6) Azithromycin¶¶ 104 (25.9) (19.8–32.9) 71 (25.6) (18.6–34.2) 33 (26.3) (16.2–39.8) Remdesivir §§ 54 (10.6) (7.1–15.6) 43 (11.0) (7.0–17.0) 11 (9.8) (4.2–21.2) Vitamins/minerals (i.e., vitamin C, zinc) 14 (8.9) (5.0–15.6) 12 (10.4) (5.4–19.0) 2 (6.0) (1.5–20.8) IL–6 inhibitors (i.e., tocilizumab, sarilumab) §§ 46 (8.2) (5.6–12.0) 24 (5.6) (3.2–9.4) 22 (13.7) (7.8–23.0) Convalescent plasma 19 (5.1) (2.5–10.0) 14 (5.4) (2.4–11.4) 5 (4.5) (1.0–17.7) Protease inhibitors (i.e., atazanavir, lopinavir/ritonavir)*** 8 (1.7) (0.6–4.3) 4 (0.6) (0.2–1.5) 4 (4.0) (1.2–12.5) Other††† 8 (1.7) (0.6–4.2) 8 (2.5) (0.9–6.2) — — ICU admission (N = 438) 116 (27.5) (21.3–34.7) 80 (29.6) (21.9–38.6) 36 (23.2) (14.2–35.6) ICU length of stay (median days, IQR) 6 (3–20) — 6 (4–19) — 5 (3–21) — Interventions/Treatments (N = 438)§§§ Invasive mechanical ventilation¶¶¶ 65 (15.8) (11.1–22.0) 44 (15.6) (10.2–23.1) 21 (16.3) (8.5–28.9) BIPAP/CPAP¶¶¶ 13 (2.4) (1.2–5.0) 9 (3.1) (1.3–7.0) 4 (1.2) (0.4–3.1) High flow nasal cannula¶¶¶ 28 (5.2) (2.8–9.6) 21 (6.8) (3.4–13.2) 7 (2.0) (0.9–4.3) Systemic steroids 74 (17.7) (12.6–24.1) 47 (16.9) (11.1–24.9) 27 (19.2) (10.9–31.7) Vasopressor (n = 436) 60 (14.4) (10.0–20.3) 41 (15.2) (9.9–22.8) 19 (12.8) (6.4–23.9) Renal replacement therapy 13 (2.1) (1.0–4.6) 9 (1.9) (0.8–4.8) 4 (2.6) (0.7–9.7) Clinical discharge diagnoses (N = 438) Pneumonia (n = 437) 213 (56.7) (49.3–63.8) 148 (56.8) (47.7–65.4) 65 (56.5) (43.5–68.7) Acute respiratory failure 170 (42.9) (35.6–50.6) 117 (45.9) (36.8–55.2) 53 (36.8) (25.1–50.2) Sepsis (n = 437) 63 (13.2) (9.0–18.8) 44 (14.9) (9.6–22.4) 19 (9.6) (4.4–19.6) Acute renal failure (n = 437) 46 (9.7) (6.4–14.3) 28 (7.7) (4.6–12.5) 18 (13.7) (7.1–24.8) Acute respiratory distress syndrome (n = 437) 38 (9.0) (5.5–14.4) 24 (7.8) (4.3–13.7) 14 (11.5) (4.9–24.3) Deep vein thrombosis (n = 159) 6 (7.4) (2.9–17.4) 4 (7.9) (2.7–21.0) 2 (6.3) (1.0–30.1) Pulmonary embolism (n = 159) 6 (6.0) (2.5–14.0) 5 (7.7) (2.9–18.8) 1 (2.5) (0.3–15.8) Died during hospitalization (N = 438) 16 (4.2) (2.2–7.7) 11 (4.1) (1.9–8.6) 5 (4.3) (1.4–12.5) Abbreviations: BIPAP = bilevel positive airway pressure; CI = confidence interval; COVID–19 = coronavirus disease 2019; COVID–NET = COVID–19–Associated Hospitalization Surveillance Network; CPAP = continuous positive airway pressure; CT = computed tomography; ICU = intensive care unit; IQR = interquartile range; MRI = magnetic resonance imaging. * Reported HCP were categorized as those generally expected and those generally not expected to have direct patient contact based on HCP type. † Sites located in the following 13 states: California, Colorado, Connecticut, Georgia, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah. § Defined as any of the following: chronic lung disease, chronic metabolic disease, blood disorder/hemoglobinopathy, cardiovascular disease, neurologic disorder, immunocompromised condition, renal disease, gastrointestinal/liver disease, rheumatologic/autoimmune/inflammatory condition, obesity (body mass index ≥30 kg/m2), and pregnancy. ¶ Excluding hypertension. ** Pregnancy was assessed among female patients aged 18–49 years; two pregnant patients were admitted to the ICU, and one required invasive mechanical ventilation. †† Assessed as nonmutually exclusive treatment categories. §§ Includes treatments administered as off–label, for compassionate use, or as part of randomized controlled trials (RCTs) for which the patient might have received treatment or a placebo: hydroxychloroquine (two), remdesivir (six), tocilizumab (one), and sarilumab (two). ¶¶ Given with at least one other COVID-19 investigational treatment. *** Not given for human immunodeficiency virus infection. ††† Eight patients received at least one of the following treatments: RCT for baricitinib (three), dexamethasone (three), cyclosporine (one), RCT for losartan (one), and RCT for LY3127804 (one). §§§ Five (1.9%) patients received extracorporeal membrane oxygenation, and two (0.2%) received intravenous immunoglobulin. ¶¶¶ Highest level of respiratory support for each patient that needed respiratory support. FIGURE 2 Weighted percentage of personnel types*, † among reported health care personnel (HCP) with COVID-19–associated hospitalizations (N = 438) — COVID–NET, 13 states, § March 1–May 31, 2020 Abbreviations: CNA = certified nursing assistant; COVID-19 = coronavirus disease 2019; COVID–NET = COVID–19–Associated Hospitalization Surveillance Network; EMS = emergency medical services; HR = human resources; LTCF = long-term care facility; OT = occupational therapist; PCA = patient care assistant; PT = physical therapist. * HCP categorized as “unspecified” or “other” have not been included in the figure but are included in the denominator. † Error bars represent 95% confidence intervals. § Sites located in the following 13 states: California, Colorado, Connecticut, Georgia, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah. The figure is a bar chart showing the weighted percentage of personnel types among reported health care personnel (HCP) with COVID-19–associated hospitalizations (N = 438), using data from COVID–NET, in 13 states, during March 1–May 31, 2020. Overall, 89.8% of HCP hospitalized with COVID-19 had documentation of at least one underlying condition (Table). The most commonly reported conditions included obesity (body mass index ≥30 kg per m2) (72.5%), hypertension (40.6%), and diabetes (30.9%). Compared with HCP generally expected to have direct patient contact, those generally not expected to have direct patient contact had higher prevalences of obesity (80.9% versus 68.3%) and cardiovascular disease (excluding hypertension) (23.5% versus 8.4%). Among female HCP aged 18–49 years hospitalized with COVID-19, 9.6% were pregnant during hospitalization. Upon hospital admission, 96.6% of HCP reported COVID-19–associated signs and symptoms; shortness of breath (79.0%), cough (76.6%), and fever or chills (73.9%) were those most commonly reported. The median length of hospitalization among HCP with COVID-19 was 4 days (IQR = 3–9 days). COVID-19 investigational treatments were administered to 48.2% of HCP hospitalized with COVID-19. Overall, 27.5% of HCP were admitted to an ICU for a median of 6 days (IQR = 3–20 days), and 15.8% required invasive mechanical ventilation. Pneumonia was a documented discharge diagnosis for 56.7% of HCP hospitalized with COVID-19 and acute respiratory failure for 42.9%. Sixteen (4.2%) HCP with COVID-19 died during hospitalization. Discussion During March 1–May 31, 2020, HCP accounted for approximately 6% of adults hospitalized with COVID-19 for whom HCP status was documented in COVID-NET. The median age of hospitalized HCP (49 years) was substantially lower than that previously reported for hospitalized adults (62 years) ( 3 ). More than two thirds (67.4%) of HCP hospitalized with COVID-19 were generally expected to have direct patient contact, and over one third (36.3%) were in nursing-related occupations. Similar to the proportion of underlying conditions among all hospitalized adults reported to COVID-NET during March–May,** approximately 90% of hospitalized HCP reported at least one underlying condition, with obesity being the most common and reported for over two thirds (72.5%) of patients. A high proportion of hospitalized HCP had indications of severe disease: approximately one in four were admitted to an ICU, and approximately 4% died. The proportion of HCP with these severe clinical outcomes was similar to that of adults aged 18–64 years hospitalized with COVID-19 during March–May. †† Findings from this analysis are comparable to those reported among HCP with COVID-19 in China, which found that nursing-related occupations accounted for the largest proportion of COVID-19 cases among HCP ( 4 ). COVID-NET does not specifically collect information on exposure history; however, nurses are frontline workers and might be at particular risk for exposure because of their frequent and close patient contact, leading to extended cumulative exposure time. Nursing-related occupations also account for a large proportion of the U.S. health care workforce: in 2019, registered nurses alone represented approximately one third of health care practitioners ( 5 ). This has implications for the capacity of the health care system, specifically nursing staff members, to respond to increases in COVID-19 cases in the community. To decrease the risk for SARS-CoV-2 transmission in health care facilities, CDC recommends that HCP use face masks (i.e., medical masks, such as surgical or procedure masks) at all times while they are in health care facilities, including patient-care areas, staff member rooms, and areas where other HCP might be present ( 2 ). In addition, in areas with moderate to substantial community transmission of SARS-CoV-2, CDC recommends that HCP wear eye protection for all patient care encounters. An N95-equivalent or higher-level respirator is recommended for aerosol-generating procedures and certain surgical procedures to provide optimal protection against potentially infectious respiratory secretions and aerosols ( 2 ). Similar to the distribution of the U.S. health care workforce overall, a majority of hospitalized HCP in this report were female ( 5 ). However, compared with previously reported demographic characteristics of U.S. HCP with COVID-19, HCP identified by COVID-NET were older, and a larger proportion were Black ( 6 ). Given that COVID-NET conducts surveillance specifically for hospitalized patients, these differences might reflect the association between increased age and severe outcomes associated with SARS-CoV-2 infection as well as disproportionate effects among Black populations ( 1 , 3 , 7 , 8 ). These results are consistent with previously reported data suggesting that underlying conditions, including obesity, diabetes, and cardiovascular disease, are risk factors for COVID-19–associated hospitalization and ICU admission ( 3 , 9 , 10 ). Among the approximately 90% of HCP in this analysis with at least one underlying condition, obesity was most commonly reported. A recent study found that obesity was highly associated with risk for death among COVID-19 patients who sought health care, even after adjusting for other obesity-related underlying conditions ( 10 ). The findings in this report highlight the need for prevention and management of obesity through evidence-based clinical care as well as policies, systems, and environmental changes to support HCP in healthy lifestyles to reduce their risk for poor COVID-19–related outcomes. §§ The findings in this report are subject to at least five limitations. First, HCP status is determined through medical chart review, and although chart abstractions will be completed on all sampled cases, abstraction was pending at the time of analysis for approximately 14% of sampled cases hospitalized during March–May. Thus, the proportion of identified HCP among all adults hospitalized with COVID-19 from March–May might represent an overestimate or underestimate of HCP in this population. Second, because of small sample sizes for some variables, some estimates might be unstable, as evidenced by wider confidence intervals. Third, although COVID-NET collects HCP status, data on the degree, frequency, and duration of contact with patients are not collected. HCP were stratified by presumed level of patient contact, based on general understanding of health care professions; the level of patient contact for some HCP might have thus been misclassified. Fourth, COVID-NET does not collect data regarding exposure history. It is unknown whether HCP were exposed to SARS-CoV-2 in the workplace or community, highlighting the need for community prevention efforts as well as infection prevention and control measures in health care settings. Finally, laboratory confirmation is dependent on clinician-ordered testing and hospital testing policies for SARS-CoV-2; as a result, COVID-19–associated hospitalizations might have been underestimated. Findings from this analysis of data from a multisite surveillance network highlight the prevalence of severe COVID-19–associated illness among HCP and potential for transmission of SARS-CoV-2 among HCP, which could decrease the workforce capacity of the health care system. HCP, regardless of any patient contact, should adhere strictly to recommended infection prevention and control guidance at all times in health care facilities to reduce transmission of SARS-CoV-2, including proper use of recommended personal protective equipment, hand hygiene, and physical distancing ( 2 ). Community mitigation and prevention efforts in households and congregate settings are also necessary to reduce overall SARS-CoV-2 transmission. Continued surveillance of hospitalized HCP is necessary to document the prevalence and characteristics of COVID-19 among this population. Further understanding of exposure risks for SARS-CoV-2 infection among HCP is important to inform additional prevention strategies for these essential workers. Summary What is already known about this topic? Data on characteristics and outcomes of U.S. health care personnel (HCP) hospitalized with COVID-19 are limited. What is added by this report? Analysis of COVID-19 hospitalization data from 13 sites indicated that 6% of adults hospitalized with COVID-19 were HCP. Among HCP hospitalized with COVID-19, 36% were in nursing-related occupations, and 73% had obesity. Approximately 28% of these patients were admitted to an intensive care unit, 16% required invasive mechanical ventilation, and 4% died. What are the implications for public health practice? HCP can have severe COVID-19–associated illness, highlighting the need for continued infection prevention and control in health care settings as well as community mitigation efforts to reduce SARS-CoV-2 transmission.

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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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            Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) — United States, February 12–March 16, 2020

            On March 18, 2020, this report was posted online as an MMWR Early Release. Globally, approximately 170,000 confirmed cases of coronavirus disease 2019 (COVID-19) caused by the 2019 novel coronavirus (SARS-CoV-2) have been reported, including an estimated 7,000 deaths in approximately 150 countries ( 1 ). On March 11, 2020, the World Health Organization declared the COVID-19 outbreak a pandemic ( 2 ). Data from China have indicated that older adults, particularly those with serious underlying health conditions, are at higher risk for severe COVID-19–associated illness and death than are younger persons ( 3 ). Although the majority of reported COVID-19 cases in China were mild (81%), approximately 80% of deaths occurred among adults aged ≥60 years; only one (0.1%) death occurred in a person aged ≤19 years ( 3 ). In this report, COVID-19 cases in the United States that occurred during February 12–March 16, 2020 and severity of disease (hospitalization, admission to intensive care unit [ICU], and death) were analyzed by age group. As of March 16, a total of 4,226 COVID-19 cases in the United States had been reported to CDC, with multiple cases reported among older adults living in long-term care facilities ( 4 ). Overall, 31% of cases, 45% of hospitalizations, 53% of ICU admissions, and 80% of deaths associated with COVID-19 were among adults aged ≥65 years with the highest percentage of severe outcomes among persons aged ≥85 years. In contrast, no ICU admissions or deaths were reported among persons aged ≤19 years. Similar to reports from other countries, this finding suggests that the risk for serious disease and death from COVID-19 is higher in older age groups. Data from cases reported from 49 states, the District of Columbia, and three U.S. territories ( 5 ) to CDC during February 12–March 16 were analyzed. Cases among persons repatriated to the United States from Wuhan, China and from Japan (including patients repatriated from cruise ships) were excluded. States and jurisdictions voluntarily reported data on laboratory-confirmed cases of COVID-19 using previously developed data collection forms ( 6 ). The cases described in this report include both COVID-19 cases confirmed by state or local public health laboratories as well as those with a positive test at the state or local public health laboratories and confirmation at CDC. No data on serious underlying health conditions were available. Data on these cases are preliminary and are missing for some key characteristics of interest, including hospitalization status (1,514), ICU admission (2,253), death (2,001), and age (386). Because of these missing data, the percentages of hospitalizations, ICU admissions, and deaths (case-fatality percentages) were estimated as a range. The lower bound of these percentages was estimated by using all cases within each age group as denominators. The corresponding upper bound of these percentages was estimated by using only cases with known information on each outcome as denominators. As of March 16, a total of 4,226 COVID-19 cases had been reported in the United States, with reports increasing to 500 or more cases per day beginning March 14 (Figure 1). Among 2,449 patients with known age, 6% were aged ≥85, 25% were aged 65–84 years, 18% each were aged 55–64 years and 45–54 years, and 29% were aged 20–44 years (Figure 2). Only 5% of cases occurred in persons aged 0–19 years. FIGURE 1 Number of new coronavirus disease 2019 (COVID-19) cases reported daily*,† (N = 4,226) — United States, February 12–March 16, 2020 * Includes both COVID-19 cases confirmed by state or local public health laboratories, as well as those testing positive at the state or local public health laboratories and confirmed at CDC. † Cases identified before February 28 were aggregated and reported during March 1–3. The figure is a histogram, an epidemiologic curve showing 4,226 coronavirus disease 2019 (COVID-19) cases, by date of case report, in the United States during February 12–March 16, 2020. Figure 2 Coronavirus disease 2019 (COVID-19) hospitalizations,* intensive care unit (ICU) admissions, † and deaths, § by age group — United States, February 12– March 16, 2020 * Hospitalization status missing or unknown for 1,514 cases. † ICU status missing or unknown for 2,253 cases. § Illness outcome or death missing or unknown for 2,001 cases. The figure is a bar chart showing the number of coronavirus disease 2019 (COVID-19) hospitalizations, intensive care unit admissions, and deaths, by age group, in the United States during February 12– March 16, 2020. Among 508 (12%) patients known to have been hospitalized, 9% were aged ≥85 years, 36% were aged 65–84 years, 17% were aged 55–64 years, 18% were 45–54 years, and 20% were aged 20–44 years. Less than 1% of hospitalizations were among persons aged ≤19 years (Figure 2). The percentage of persons hospitalized increased with age, from 2%–3% among persons aged ≤19 years, to ≥31% among adults aged ≥85 years. (Table). TABLE Hospitalization, intensive care unit (ICU) admission, and case–fatality percentages for reported COVID–19 cases, by age group —United States, February 12–March 16, 2020 Age group (yrs) (no. of cases) %* Hospitalization ICU admission Case-fatality 0–19 (123) 1.6–2.5 0 0 20–44 (705) 14.3–20.8 2.0–4.2 0.1–0.2 45–54 (429) 21.2–28.3 5.4–10.4 0.5–0.8 55–64 (429) 20.5–30.1 4.7–11.2 1.4–2.6 65–74 (409) 28.6–43.5 8.1–18.8 2.7–4.9 75–84 (210) 30.5–58.7 10.5–31.0 4.3–10.5 ≥85 (144) 31.3–70.3 6.3–29.0 10.4–27.3 Total (2,449) 20.7–31.4 4.9–11.5 1.8–3.4 * Lower bound of range = number of persons hospitalized, admitted to ICU, or who died among total in age group; upper bound of range = number of persons hospitalized, admitted to ICU, or who died among total in age group with known hospitalization status, ICU admission status, or death. Among 121 patients known to have been admitted to an ICU, 7% of cases were reported among adults ≥85 years, 46% among adults aged 65–84 years, 36% among adults aged 45–64 years, and 12% among adults aged 20–44 years (Figure 2). No ICU admissions were reported among persons aged ≤19 years. Percentages of ICU admissions were lowest among adults aged 20–44 years (2%–4%) and highest among adults aged 75–84 years (11%–31%) (Table). Among 44 cases with known outcome, 15 (34%) deaths were reported among adults aged ≥85 years, 20 (46%) among adults aged 65–84 years, and nine (20%) among adults aged 20–64 years. Case-fatality percentages increased with increasing age, from no deaths reported among persons aged ≤19 years to highest percentages (10%–27%) among adults aged ≥85 years (Table) (Figure 2). Discussion Since February 12, 4,226 COVID-19 cases were reported in the United States; 31% of cases, 45% of hospitalizations, 53% of ICU admissions, and 80% of deaths occurred among adults aged ≥65 years with the highest percentage of severe outcomes among persons aged ≥85 years. These findings are similar to data from China, which indicated >80% of deaths occurred among persons aged ≥60 years ( 3 ). These preliminary data also demonstrate that severe illness leading to hospitalization, including ICU admission and death, can occur in adults of any age with COVID-19. In contrast, persons aged ≤19 years appear to have milder COVID-19 illness, with almost no hospitalizations or deaths reported to date in the United States in this age group. Given the spread of COVID-19 in many U.S. communities, CDC continues to update current recommendations and develop new resources and guidance, including for adults aged ≥65 years as well as those involved in their care ( 7 , 8 ). Approximately 49 million U.S. persons are aged ≥65 years ( 9 ), and many of these adults, who are at risk for severe COVID-19–associated illness, might depend on services and support to maintain their health and independence. To prepare for potential COVID-19 illness among persons at high risk, family members and caregivers of older adults should know what medications they are taking and ensure that food and required medical supplies are available. Long-term care facilities should be particularly vigilant to prevent the introduction and spread of COVID-19 ( 10 ). In addition, clinicians who care for adults should be aware that COVID-19 can result in severe disease among persons of all ages. Persons with suspected or confirmed COVID-19 should monitor their symptoms and call their provider for guidance if symptoms worsen or seek emergency care for persistent severe symptoms. Additional guidance is available for health care providers on CDC’s website (https://www.cdc.gov/coronavirus/2019-nCoV/hcp/index.html). This report describes the current epidemiology of COVID-19 in the United States, using preliminary data. The findings in this report are subject to at least five limitations. First, data were missing for key variables of interest. Data on age and outcomes, including hospitalization, ICU admission, and death, were missing for 9%–53% of cases, which likely resulted in an underestimation of these outcomes. Second, further time for follow-up is needed to ascertain outcomes among active cases. Third, the initial approach to testing was to identify patients among those with travel histories or persons with more severe disease, and these data might overestimate the prevalence of severe disease. Fourth, data on other risk factors, including serious underlying health conditions that could increase risk for complications and severe illness, were unavailable at the time of this analysis. Finally, limited testing to date underscores the importance of ongoing surveillance of COVID-19 cases. Additional investigation will increase the understanding about persons who are at risk for severe illness and death from COVID-19 and inform clinical guidance and community-based mitigation measures.* The risk for serious disease and death in COVID-19 cases among persons in the United States increases with age. Social distancing is recommended for all ages to slow the spread of the virus, protect the health care system, and help protect vulnerable older adults. Further, older adults should maintain adequate supplies of nonperishable foods and at least a 30-day supply of necessary medications, take precautions to keep space between themselves and others, stay away from those who are sick, avoid crowds as much as possible, avoid cruise travel and nonessential air travel, and stay home as much as possible to further reduce the risk of being exposed ( 7 ). Persons of all ages and communities can take actions to help slow the spread of COVID-19 and protect older adults. † Summary What is already known about this topic? Early data from China suggest that a majority of coronavirus disease 2019 (COVID-19) deaths have occurred among adults aged ≥60 years and among persons with serious underlying health conditions. What is added by this report? This first preliminary description of outcomes among patients with COVID-19 in the United States indicates that fatality was highest in persons aged ≥85, ranging from 10% to 27%, followed by 3% to 11% among persons aged 65–84 years, 1% to 3% among persons aged 55-64 years, <1% among persons aged 20–54 years, and no fatalities among persons aged ≤19 years. What are the implications for public health practice? COVID-19 can result in severe disease, including hospitalization, admission to an intensive care unit, and death, especially among older adults. Everyone can take actions, such as social distancing, to help slow the spread of COVID-19 and protect older adults from severe illness.
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              Preliminary Estimates of the Prevalence of Selected Underlying Health Conditions Among Patients with Coronavirus Disease 2019 — United States, February 12–March 28, 2020

              On March 11, 2020, the World Health Organization declared Coronavirus Disease 2019 (COVID-19) a pandemic ( 1 ). As of March 28, 2020, a total of 571,678 confirmed COVID-19 cases and 26,494 deaths have been reported worldwide ( 2 ). Reports from China and Italy suggest that risk factors for severe disease include older age and the presence of at least one of several underlying health conditions ( 3 , 4 ). U.S. older adults, including those aged ≥65 years and particularly those aged ≥85 years, also appear to be at higher risk for severe COVID-19–associated outcomes; however, data describing underlying health conditions among U.S. COVID-19 patients have not yet been reported ( 5 ). As of March 28, 2020, U.S. states and territories have reported 122,653 U.S. COVID-19 cases to CDC, including 7,162 (5.8%) for whom data on underlying health conditions and other known risk factors for severe outcomes from respiratory infections were reported. Among these 7,162 cases, 2,692 (37.6%) patients had one or more underlying health condition or risk factor, and 4,470 (62.4%) had none of these conditions reported. The percentage of COVID-19 patients with at least one underlying health condition or risk factor was higher among those requiring intensive care unit (ICU) admission (358 of 457, 78%) and those requiring hospitalization without ICU admission (732 of 1,037, 71%) than that among those who were not hospitalized (1,388 of 5,143, 27%). The most commonly reported conditions were diabetes mellitus, chronic lung disease, and cardiovascular disease. These preliminary findings suggest that in the United States, persons with underlying health conditions or other recognized risk factors for severe outcomes from respiratory infections appear to be at a higher risk for severe disease from COVID-19 than are persons without these conditions. Data from laboratory-confirmed COVID-19 cases reported to CDC from 50 states, four U.S. territories and affiliated islands, the District of Columbia, and New York City with February 12–March 28, 2020 onset dates were analyzed. Cases among persons repatriated to the United States from Wuhan, China, and the Diamond Princess cruise ship were excluded. For cases with missing onset dates, date of onset was estimated by subtracting 4 days (median interval from symptom onset to specimen collection date among cases with known dates in these data) from the earliest specimen collection. Public health departments reported cases to CDC using a standardized case report form that captures information (yes, no, or unknown) on the following conditions and potential risk factors: chronic lung disease (inclusive of asthma, chronic obstructive pulmonary disease [COPD], and emphysema); diabetes mellitus; cardiovascular disease; chronic renal disease; chronic liver disease; immunocompromised condition; neurologic disorder, neurodevelopmental, or intellectual disability; pregnancy; current smoking status; former smoking status; or other chronic disease ( 6 ). Data reported to CDC are preliminary and can be updated by health departments over time; critical data elements might be missing at the time of initial report; thus, this analysis is descriptive, and no statistical comparisons could be made. The percentages of patients of all ages with underlying health conditions who were not hospitalized, hospitalized without ICU admission, and hospitalized with ICU admission were calculated. Percentages of hospitalizations with and without ICU admission were estimated for persons aged ≥19 years with and without underlying health conditions. This part of the analysis was limited to persons aged ≥19 years because of the small sample size of cases in children with reported underlying health conditions (N = 32). To account for missing data among these preliminary reports, ranges were estimated with a lower bound including cases with both known and unknown status for hospitalization with and without ICU admission as the denominator and an upper bound using only cases with known outcome status as the denominator. Because of small sample size and missing data on underlying health conditions among COVID-19 patients who died, case-fatality rates for persons with and without underlying conditions were not estimated. As of March 28, 2020, a total of 122,653 laboratory-confirmed COVID-19 cases (Figure) and 2,112 deaths were reported to CDC. Case report forms were submitted to CDC for 74,439 (60.7%) cases. Data on presence or absence of underlying health conditions and other recognized risk factors for severe outcomes from respiratory infections (i.e., smoking and pregnancy) were available for 7,162 (5.8%) patients (Table 1). Approximately one third of these patients (2,692, 37.6%), had at least one underlying condition or risk factor. Diabetes mellitus (784, 10.9%), chronic lung disease (656, 9.2%), and cardiovascular disease (647, 9.0%) were the most frequently reported conditions among all cases. Among 457 ICU admissions and 1,037 non-ICU hospitalizations, 358 (78%) and 732 (71%), respectively occurred among persons with one or more reported underlying health condition. In contrast, 1,388 of 5,143 (27%) COVID-19 patients who were not hospitalized were reported to have at least one underlying health condition. FIGURE Daily number of reported COVID-19 cases* — United States, February 12–March 28, 2020† * Cases among persons repatriated to the United States from Wuhan, China, and the Diamond Princess cruise ship are excluded. † Cumulative number of COVID-19 cases reported daily by jurisdictions to CDC using aggregate case count was 122,653 through March 28, 2020. The figure is a histogram, an epidemiologic curve showing the number of COVID-19 cases, by date of report, in the United States during February 12–March 28, 2020. TABLE 1 Reported outcomes among COVID-19 patients of all ages, by hospitalization status, underlying health condition, and risk factor for severe outcome from respiratory infection — United States, February 12–March 28, 2020 Underlying health condition/Risk factor for severe outcomes from respiratory infection (no., % with condition) No. (%) Not hospitalized Hospitalized, non-ICU ICU admission Hospitalization status unknown Total with case report form (N = 74,439) 12,217 5,285 1,069 55,868 Missing or unknown status for all conditions (67,277) 7,074 4,248 612 55,343 Total with completed information (7,162) 5,143 1,037 457 525 One or more conditions (2,692, 37.6%) 1,388 (27) 732 (71) 358 (78) 214 (41) Diabetes mellitus (784, 10.9%) 331 (6) 251 (24) 148 (32) 54 (10) Chronic lung disease* (656, 9.2%) 363 (7) 152 (15) 94 (21) 47 (9) Cardiovascular disease (647, 9.0%) 239 (5) 242 (23) 132 (29) 34 (6) Immunocompromised condition (264, 3.7%) 141 (3) 63 (6) 41 (9) 19 (4) Chronic renal disease (213, 3.0%) 51 (1) 95 (9) 56 (12) 11 (2) Pregnancy (143, 2.0%) 72 (1) 31 (3) 4 (1) 36 (7) Neurologic disorder, neurodevelopmental, intellectual disability (52, 0.7%)† 17 (0.3) 25 (2) 7 (2) 3 (1) Chronic liver disease (41, 0.6%) 24 (1) 9 (1) 7 (2) 1 (0.2) Other chronic disease (1,182, 16.5%)§ 583 (11) 359 (35) 170 (37) 70 (13) Former smoker (165, 2.3%) 80 (2) 45 (4) 33 (7) 7 (1) Current smoker (96, 1.3%) 61 (1) 22 (2) 5 (1) 8 (2) None of the above conditions¶ (4,470, 62.4%) 3,755 (73) 305 (29) 99 (22) 311 (59) Abbreviation: ICU = intensive care unit. * Includes any of the following: asthma, chronic obstructive pulmonary disease, and emphysema. † For neurologic disorder, neurodevelopmental, and intellectual disability, the following information was specified: dementia, memory loss, or Alzheimer’s disease (17); seizure disorder (5); Parkinson’s disease (4); migraine/headache (4); stroke (3); autism (2); aneurysm (2); multiple sclerosis (2); neuropathy (2); hereditary spastic paraplegia (1); myasthenia gravis (1); intracranial hemorrhage (1); and altered mental status (1). § For other chronic disease, the following information was specified: hypertension (113); thyroid disease (37); gastrointestinal disorder (32); hyperlipidemia (29); cancer or history of cancer (29); rheumatologic disorder (19); hematologic disorder (17); obesity (17); arthritis, nonrheumatoid, including not otherwise specified (16); musculoskeletal disorder other than arthritis (10); mental health condition (9); urologic disorder (7); cerebrovascular disease (7); obstructive sleep apnea (7); fibromyalgia (7); gynecologic disorder (6); embolism, pulmonary or venous (5); ophthalmic disorder (2); hypertriglyceridemia (1); endocrine (1); substance abuse disorder (1); dermatologic disorder (1); genetic disorder (1). ¶ All listed chronic conditions, including other chronic disease, were marked as not present. Among patients aged ≥19 years, the percentage of non-ICU hospitalizations was higher among those with underlying health conditions (27.3%–29.8%) than among those without underlying health conditions (7.2%–7.8%); the percentage of cases that resulted in an ICU admission was also higher for those with underlying health conditions (13.3%–14.5%) than those without these conditions (2.2%–2.4%) (Table 2). Small numbers of COVID-19 patients aged <19 years were reported to be hospitalized (48) or admitted to an ICU (eight). In contrast, 335 patients aged <19 years were not hospitalized and 1,342 had missing data on hospitalization. Among all COVID-19 patients with complete information on underlying conditions or risk factors, 184 deaths occurred (all among patients aged ≥19 years); 173 deaths (94%) were reported among patients with at least one underlying condition. TABLE 2 Hospitalization with and without intensive care unit (ICU) admission, by age group among COVID-19 patients aged ≥19 years with and without reported underlying health conditions — United States, February 12–March 28, 2020* Age group (yrs) Hospitalized without ICU admission, No. (% range†) ICU admission, No. (% range†) Underlying condition present/reported§ Underlying condition present/reported§ Yes No Yes No 19–64 285 (18.1–19.9) 197 (6.2–6.7) 134 (8.5–9.4) 58 (1.8–2.0) ≥65 425 (41.7–44.5) 58 (16.8–18.3) 212 (20.8–22.2) 20 (5.8–6.3) Total ≥19 710 (27.3–29.8) 255 (7.2–7.8) 346 (13.3–14.5) 78 (2.2–2.4) * Includes COVID-19 patients aged ≥19 years with known status on underlying conditions. † Lower bound of range = number of persons hospitalized or admitted to an ICU among total in row stratum; upper bound of range = number of persons hospitalized or admitted to an ICU among total in row stratum with known outcome status: hospitalization or ICU admission status. § Includes any of following underlying health conditions or risk factors: chronic lung disease (including asthma, chronic obstructive pulmonary disease, and emphysema); diabetes mellitus; cardiovascular disease; chronic renal disease; chronic liver disease; immunocompromised condition; neurologic disorder, neurodevelopmental, or intellectual disability; pregnancy; current smoker; former smoker; or other chronic disease. Discussion Among 122,653 U.S. COVID-19 cases reported to CDC as of March 28, 2020, 7,162 (5.8%) patients had data available pertaining to underlying health conditions or potential risk factors; among these patients, higher percentages of patients with underlying conditions were admitted to the hospital and to an ICU than patients without reported underlying conditions. These results are consistent with findings from China and Italy, which suggest that patients with underlying health conditions and risk factors, including, but not limited to, diabetes mellitus, hypertension, COPD, coronary artery disease, cerebrovascular disease, chronic renal disease, and smoking, might be at higher risk for severe disease or death from COVID-19 ( 3 , 4 ). This analysis was limited by small numbers and missing data because of the burden placed on reporting health departments with rapidly rising case counts, and these findings might change as additional data become available. It is not yet known whether the severity or level of control of underlying health conditions affects the risk for severe disease associated with COVID-19. Many of these underlying health conditions are common in the United States: based on self-reported 2018 data, the prevalence of diagnosed diabetes among U.S. adults was 10.1% ( 7 ), and the U.S. age-adjusted prevalence of all types of heart disease (excluding hypertension without other heart disease) was 10.6% in 2017 ( 8 ). The age-adjusted prevalence of COPD among U.S. adults is 5.9% ( 9 ), and in 2018, the U.S. estimated prevalence of current asthma among persons of all ages was 7.9% ( 7 ). CDC continues to develop and update resources for persons with underlying health conditions to reduce the risk of acquiring COVID-19 ( 10 ). The estimated higher prevalence of these conditions among those in this early group of U.S. COVID-19 patients and the potentially higher risk for more severe disease from COVID-19 associated with the presence of underlying conditions highlight the importance of COVID-19 prevention in persons with underlying conditions. The findings in this report are subject to at least six limitations. First, these data are preliminary, and the analysis was limited by missing data related to the health department reporting burden associated with rapidly rising case counts and delays in completion of information requiring medical chart review; these findings might change as additional data become available. Information on underlying conditions was only available for 7,162 (5.8%) of 122,653 cases reported to CDC. It cannot be assumed that those with missing information are similar to those with data on either hospitalizations or underlying health conditions. Second, these data are subject to bias in outcome ascertainment because of short follow-up time. Some outcomes might be underestimated, and long-term outcomes cannot be assessed in this analysis. Third, because of the limited availability of testing in many jurisdictions during this period, this analysis is likely biased toward more severe cases, and findings might change as testing becomes more widespread. Fourth, because of the descriptive nature of these data, attack rates among persons with and without underlying health conditions could not be compared, and thus the risk difference of severe disease with COVID-19 between these groups could not be estimated. Fifth, no conclusions could be drawn about underlying conditions that were not included in the case report form or about different conditions that were reported in a single, umbrella category. For example, asthma and COPD were included in a chronic lung disease category. Finally, for some underlying health conditions and risk factors, including neurologic disorders, chronic liver disease, being a current smoker, and pregnancy, few severe outcomes were reported; therefore, conclusions cannot be drawn about the risk for severe COVID-19 among persons in these groups. Persons in the United States with underlying health conditions appear to be at higher risk for more severe COVID-19, consistent with findings from other countries. Persons with underlying health conditions who have symptoms of COVID-19, including fever, cough, or shortness of breath, should immediately contact their health care provider. These persons should take steps to protect themselves from COVID-19, through washing their hands; cleaning and disinfecting high-touch surfaces; and social distancing, including staying at home, avoiding crowds, gatherings, and travel, and avoiding contact with persons who are ill. Maintaining at least a 30-day supply of medication, a 2-week supply of food and other necessities, and knowledge of COVID-19 symptoms are recommended for those with underlying health conditions ( 10 ). All persons should take steps to protect themselves from COVID-19 and to protect others. All persons who are ill should stay home, except to get medical care; should not go to work; and should stay away from others. This is especially important for those who work with persons with underlying conditions or who otherwise are at high risk for severe outcomes from COVID-19. Community mitigation strategies, which aim to slow the spread of COVID-19, are important to protect all persons from COVID-19, especially persons with underlying health conditions and other persons at risk for severe COVID-19–associated disease (https://www.cdc.gov/coronavirus/2019-ncov/downloads/community-mitigation-strategy.pdf). Summary What is already known about this topic? Published reports from China and Italy suggest that risk factors for severe COVID-19 disease include underlying health conditions, but data describing underlying health conditions among U.S. COVID-19 patients have not yet been reported. What is added by this report? Based on preliminary U.S. data, persons with underlying health conditions such as diabetes mellitus, chronic lung disease, and cardiovascular disease, appear to be at higher risk for severe COVID-19–associated disease than persons without these conditions. What are the implications for public health practice? Strategies to protect all persons and especially those with underlying health conditions, including social distancing and handwashing, should be implemented by all communities and all persons to help slow the spread of COVID-19.
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                Contributors
                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
                30 October 2020
                30 October 2020
                : 69
                : 43
                : 1576-1583
                Affiliations
                CDC COVID-NET Team; Eagle Global Scientific, Atlanta, Georgia; Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, CDC; California Emerging Infections Program, Oakland, California; Career Epidemiology Field Officer Program, CDC; Colorado Department of Public Health and Environment; Connecticut Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut; Departments of Pediatrics and Medicine, Emory University School of Medicine, Atlanta, Georgia; Emerging Infections Program, Atlanta Veterans Affairs Medical Center, Atlanta, Georgia; Foundation for Atlanta Veterans Education and Research, Decatur, Georgia; Maryland Department of Health; Michigan Department of Health and Human Services; Minnesota Department of Health; New Mexico Emerging Infections Program, University of New Mexico, Albuquerque, New Mexico; New Mexico Department of Health; New York State Department of Health; University of Rochester School of Medicine and Dentistry, Rochester, New York; Ohio Department of Health; Public Health Division, Oregon Health Authority; Vanderbilt University Medical Center, Nashville, Tennessee; Salt Lake County Health Department, Salt Lake City, Utah.
                Colorado Department of Public Health and Environment
                New Mexico Emerging Infections Program
                California Emerging Infections Program
                Maryland Department of Health
                Maryland Department of Health
                California Emerging Infections Program
                Rochester Emerging Infections Program
                University of Rochester Medical Center
                Minnesota Department of Health
                New Mexico Emerging Infections Program
                California Emerging Infections Program
                New York State Department of Health
                , New Mexico Emerging Infections Program
                California Emerging Infections Program
                Rochester Emerging Infections Program
                University of Rochester Medical Center
                Salt Lake County Health Department
                New Mexico Emerging Infections Program
                New Mexico Emerging Infections Program
                California Emerging Infections Program
                California Emerging Infections Program
                New Mexico Emerging Infections Program
                Rochester Emerging Infections Program
                University of Rochester Medical Center
                Minnesota Department of Health
                Vanderbilt University Medical Center
                Salt Lake County Health Department
                CDC
                New York State Department of Health
                California Emerging Infections Program
                New Mexico Emerging Infections Program
                Salt Lake County Health Department
                Public Health Division, Oregon Health Authority
                Maryland Emerging Infections Program
                The Johns Hopkins Bloomberg School of Public Health
                CDC
                Cherokee Nation Assurance
                Salt Lake County Health Department
                California Emerging Infections Program
                California Emerging Infections Program
                California Emerging Infections Program
                New Mexico Emerging Infections Program
                Salt Lake County Health Department
                Salt Lake County Health Department
                Maryland Emerging Infections Program
                The Johns Hopkins Bloomberg School of Public Health.
                Author notes
                Corresponding author: Anita K. Kambhampati, wyc4@ 123456cdc.gov .
                Article
                mm6943e3
                10.15585/mmwr.mm6943e3
                7659917
                33119554
                5680b6de-693a-4578-9c8f-3d2a8e459b35

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