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      Impact of COVID-19 on Cancer Care: How the Pandemic Is Delaying Cancer Diagnosis and Treatment for American Seniors

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          PURPOSE

          While the immediate care and access disruptions associated with the COVID-19 pandemic have received growing attention in certain areas, the full range of gaps in cancer screenings and treatment is not yet well understood or well documented throughout the country comprehensively.

          METHODS

          This study used a large medical claims clearinghouse database representing 5%-7% of the Medicare fee-for-service population to characterize changes in the utilization of cancer care services and gain insight into the impact of COVID-19 on the US cancer population, including identification of new patients, gaps in access to care, and disruption of treatment journeys.

          RESULTS

          In March-July 2020, in comparison with the baseline period of March-July 2019, there is a substantial decrease in cancer screenings, visits, therapy, and surgeries, with variation by cancer type and site of service. At the peak of the pandemic in April, screenings for breast, colon, prostate, and lung cancers were lower by 85%, 75%, 74%, and 56%, respectively. Significant utilization reductions were observed in April for hospital outpatient evaluation and management (E&M) visits (−74%), new patient E&M visits (−70%), and established patient E&M visits (−60%). A decrease in billing frequency was observed for the top physician-administered oncology products, dropping in both April (−26%) and July (−31%). Mastectomies were reduced consistently in April through July, with colectomies similarly reduced in April and May and prostatectomies dipping in April and July.

          CONCLUSION

          The current impact of the COVID-19 pandemic on cancer care in the United States has resulted in decreases and delays in identifying new cancers and delivery of treatment. These problems, if unmitigated, will increase cancer morbidity and mortality for years to come.

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          The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study

          Summary Background Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types. Methods In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15–84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data. Findings We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9–9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266–295) and 344 (329–358) additional deaths. For colorectal cancer, we estimate 1445 (1392–1591) to 1563 (1534–1592) additional deaths, a 15·3–16·6% increase; for lung cancer, 1235 (1220–1254) to 1372 (1343–1401) additional deaths, a 4·8–5·3% increase; and for oesophageal cancer, 330 (324–335) to 342 (336–348) additional deaths, 5·8–6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291–3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204–63 229 years. Interpretation Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer. Funding UK Research and Innovation Economic and Social Research Council.
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            Coronavirus Disease 2019 Case Surveillance — United States, January 22–May 30, 2020

            The coronavirus disease 2019 (COVID-19) pandemic resulted in 5,817,385 reported cases and 362,705 deaths worldwide through May, 30, 2020, † including 1,761,503 aggregated reported cases and 103,700 deaths in the United States. § Previous analyses during February–early April 2020 indicated that age ≥65 years and underlying health conditions were associated with a higher risk for severe outcomes, which were less common among children aged 10% of persons in this age group. TABLE 2 Reported underlying health conditions* and symptoms † among persons with laboratory-confirmed COVID-19, by sex and age group — United States, January 22–May 30, 2020 Characteristic No. (%) Total Sex Age group (yrs) Male Female ≤9 10–19 20–29 30–39 40–49 50–59 60–69 70–79 ≥80 Total population 1,320,488 646,358 674,130 20,458 49,245 182,469 214,849 219,139 235,774 179,007 105,252 114,295 Underlying health condition§ Known underlying medical condition status* 287,320 (21.8) 138,887 (21.5) 148,433 (22.0) 2,896 (14.2) 7,123 (14.5) 27,436 (15.0) 33,483 (15.6) 40,572 (18.5) 54,717 (23.2) 50,125 (28.0) 34,400 (32.7) 36,568 (32.0) Any cardiovascular disease¶ 92,546 (32.2) 47,567 (34.2) 44,979 (30.3) 78 (2.7) 164 (2.3) 1,177 (4.3) 3,588 (10.7) 8,198 (20.2) 16,954 (31.0) 21,466 (42.8) 18,763 (54.5) 22,158 (60.6) Any chronic lung disease 50,148 (17.5) 20,930 (15.1) 29,218 (19.7) 363 (12.5) 1,285 (18) 4,537 (16.5) 5,110 (15.3) 6,127 (15.1) 8,722 (15.9) 9,200 (18.4) 7,436 (21.6) 7,368 (20.1) Renal disease 21,908 (7.6) 12,144 (8.7) 9,764 (6.6) 21 (0.7) 34 (0.5) 204 (0.7) 587 (1.8) 1,273 (3.1) 2,789 (5.1) 4,764 (9.5) 5,401 (15.7) 6,835 (18.7) Diabetes 86,737 (30.2) 45,089 (32.5) 41,648 (28.1) 12 (0.4) 225 (3.2) 1,409 (5.1) 4,106 (12.3) 9,636 (23.8) 19,589 (35.8) 22,314 (44.5) 16,594 (48.2) 12,852 (35.1) Liver disease 3,953 (1.4) 2,439 (1.8) 1,514 (1.0) 5 (0.2) 19 (0.3) 132 (0.5) 390 (1.2) 573 (1.4) 878 (1.6) 1,074 (2.1) 583 (1.7) 299 (0.8) Immunocompromised 15,265 (5.3) 7,345 (5.3) 7,920 (5.3) 61 (2.1) 146 (2.0) 646 (2.4) 1,253 (3.7) 2,005 (4.9) 3,190 (5.8) 3,421 (6.8) 2,486 (7.2) 2,057 (5.6) Neurologic/Neurodevelopmental disability 13,665 (4.8) 6,193 (4.5) 7,472 (5.0) 41 (1.4) 113 (1.6) 395 (1.4) 533 (1.6) 734 (1.8) 1,338 (2.4) 2,006 (4.0) 2,759 (8.0) 5,746 (15.7) Symptom§ Known symptom status† 373,883 (28.3) 178,223 (27.6) 195,660 (29.0) 5,188 (25.4) 12,689 (25.8) 51,464 (28.2) 59,951 (27.9) 62,643 (28.6) 70,040 (29.7) 52,178 (29.1) 28,583 (27.2) 31,147 (27.3) Fever, cough, or shortness of breath 260,706 (69.7) 125,768 (70.6) 134,938 (69.0) 3,278 (63.2) 7,584 (59.8) 35,072 (68.1) 42,016 (70.1) 45,361 (72.4) 51,283 (73.2) 37,701 (72.3) 19,583 (68.5) 18,828 (60.4) Fever †† 161,071 (43.1) 80,578 (45.2) 80,493 (41.1) 2,404 (46.3) 4,443 (35.0) 20,381 (39.6) 25,887 (43.2) 28,407 (45.3) 32,375 (46.2) 23,591 (45.2) 12,190 (42.6) 11,393 (36.6) Cough 187,953 (50.3) 89,178 (50.0) 98,775 (50.5) 1,912 (36.9) 5,257 (41.4) 26,284 (51.1) 31,313 (52.2) 34,031 (54.3) 38,305 (54.7) 27,150 (52.0) 12,837 (44.9) 10,864 (34.9) Shortness of breath 106,387 (28.5) 49,834 (28.0) 56,553 (28.9) 339 (6.5) 2,070 (16.3) 13,649 (26.5) 16,851 (28.1) 18,978 (30.3) 21,327 (30.4) 16,018 (30.7) 8,971 (31.4) 8,184 (26.3) Myalgia 135,026 (36.1) 61,922 (34.7) 73,104 (37.4) 537 (10.4) 3,737 (29.5) 21,153 (41.1) 26,464 (44.1) 28,064 (44.8) 28,594 (40.8) 17,360 (33.3) 6,015 (21.0) 3,102 (10.0) Runny nose 22,710 (6.1) 9,900 (5.6) 12,810 (6.5) 354 (6.8) 1,025 (8.1) 4,591 (8.9) 4,406 (7.3) 4,141 (6.6) 4,100 (5.9) 2,671 (5.1) 923 (3.2) 499 (1.6) Sore throat 74,840 (20.0) 31,244 (17.5) 43,596 (22.3) 664 (12.8) 3,628 (28.6) 14,493 (28.2) 14,855 (24.8) 14,490 (23.1) 13,930 (19.9) 8,192 (15.7) 2,867 (10.0) 1,721 (5.5) Headache 128,560 (34.4) 54,721 (30.7) 73,839 (37.7) 785 (15.1) 5,315 (41.9) 23,723 (46.1) 26,142 (43.6) 26,245 (41.9) 26,057 (37.2) 14,735 (28.2) 4,163 (14.6) 1,395 (4.5) Nausea/Vomiting 42,813 (11.5) 16,549 (9.3) 26,264 (13.4) 506 (9.8) 1,314 (10.4) 6,648 (12.9) 7,661 (12.8) 8,091 (12.9) 8,737 (12.5) 5,953 (11.4) 2,380 (8.3) 1,523 (4.9) Abdominal pain 28,443 (7.6) 11,553 (6.5) 16,890 (8.6) 349 (6.7) 978 (7.7) 4,211 (8.2) 5,150 (8.6) 5,531 (8.8) 6,134 (8.8) 3,809 (7.3) 1,449 (5.1) 832 (2.7) Diarrhea 72,039 (19.3) 32,093 (18.0) 39,946 (20.4) 704 (13.6) 1,712 (13.5) 9,867 (19.2) 12,769 (21.3) 13,958 (22.3) 15,536 (22.2) 10,349 (19.8) 4,402 (15.4) 2,742 (8.8) Loss of smell or taste 31,191 (8.3) 12,717 (7.1) 18,474 (9.4) 67 (1.3) 1,257 (9.9) 6,828 (13.3) 6,907 (11.5) 6,361 (10.2) 5,828 (8.3) 2,930 (5.6) 775 (2.7) 238 (0.8) Abbreviation: COVID-19 = coronavirus disease 2019. * Status of underlying health conditions known for 287,320 persons. Status was classified as “known” if any of the following conditions were reported as present or absent: diabetes mellitus, cardiovascular disease (including hypertension), severe obesity (body mass index ≥40 kg/m2), chronic renal disease, chronic liver disease, chronic lung disease, immunocompromising condition, autoimmune condition, neurologic condition (including neurodevelopmental, intellectual, physical, visual, or hearing impairment), psychologic/psychiatric condition, and other underlying medical condition not otherwise specified. † Symptom status was known for 373,883 persons. Status was classified as “known” if any of the following symptoms were reported as present or absent: fever (measured >100.4°F [38°C] or subjective), cough, shortness of breath, wheezing, difficulty breathing, chills, rigors, myalgia, rhinorrhea, sore throat, chest pain, nausea or vomiting, abdominal pain, headache, fatigue, diarrhea (≥3 loose stools in a 24-hour period), or other symptom not otherwise specified on the form. § Responses include data from standardized fields supplemented with data from free-text fields. Information for persons with loss of smell or taste was exclusively extracted from a free-text field; therefore, persons exhibiting this symptom were likely underreported. ¶ Includes persons with reported hypertension. ** Includes all persons with at least one of these symptoms reported. †† Persons were considered to have a fever if information on either measured or subjective fever variables if “yes” was reported for either variable. Among 287,320 (22%) cases with data on individual underlying health conditions, those most frequently reported were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%) (Table 2); the reported proportions were similar among males and females. The frequency of conditions reported varied by age group: cardiovascular disease was uncommon among those aged ≤39 years but was reported in approximately half of the cases among persons aged ≥70 years. Among 63,896 females aged 15–44 years with known pregnancy status, 6,708 (11%) were reported to be pregnant. Among the 1,320,488 cases, outcomes for hospitalization, ICU admission, and death were available for 46%, 14%, and 36%, respectively. Overall, 184,673 (14%) patients were hospitalized, including 29,837 (2%) admitted to the ICU; 71,116 (5%) patients died (Table 3). Severe outcomes were more commonly reported for patients with reported underlying conditions. Hospitalizations were six times higher among patients with a reported underlying condition than those without reported underlying conditions (45.4% versus 7.6%). Deaths were 12 times higher among patients with reported underlying conditions compared with those without reported underlying conditions (19.5% versus 1.6%). The percentages of males who were hospitalized (16%), admitted to the ICU (3%), and who died (6%) were higher than were those for females (12%, 2%, and 5%, respectively). The percentage of ICU admissions was highest among persons with reported underlying conditions aged 60–69 years (11%) and 70–79 years (12%). Death was most commonly reported among persons aged ≥80 years regardless of the presence of underlying conditions (with underlying conditions 50%; without 30%). TABLE 3 Reported hospitalizations,* , † intensive care unit (ICU) admissions, § and deaths ¶ among laboratory-confirmed COVID-19 patients with and without reported underlying health conditions, ** by sex and age — United States, January 22–May 30, 2020 Characteristic (no.) Outcome, no./total no. (%)†† Reported hospitalizations*,† (including ICU) Reported ICU admission§ Reported deaths¶ Among all patients Among patients with reported underlying health conditions Among patients with no reported underlying health conditions Among all patients Among patients with reported underlying health conditions Among patients with no reported underlying health conditions Among all patients Among patients with reported underlying health conditions Among patients with no reported underlying health conditions Sex Male (646,358) 101,133/646,358 (15.6) 49,503/96,839 (51.1) 3,596/42,048 (8.6) 18,394/646,358 (2.8) 10,302/96,839 (10.6) 864/42,048 (2.1) 38,773/646,358 (6.0) 21,667/96,839 (22.4) 724/42,048 (1.7) Female (674,130) 83,540/674,130 (12.4) 40,698/102,040 (39.9) 3,087/46,393 (6.7) 11,443/674,130 (1.7) 6,672/102,040 (6.5) 479/46,393 (1.0) 32,343/674,130 (4.8) 17,145/102,040 (16.8) 707/46,393 (1.5) Age group (yrs) ≤9 (20,458) 848/20,458 (4.1) 138/619 (22.3) 84/2,277 (3.7) 141/20,458 (0.7) 31/619 (5.0) 16/2,277 (0.7) 13/20,458 (0.1) 4/619 (0.6) 2/2,277 (0.1) 10–19 (49,245) 1,234/49,245 (2.5) 309/2,076 (14.9) 115/5,047 (2.3) 216/49,245 (0.4) 72/2,076 (3.5) 17/5,047 (0.3) 33/49,245 (0.1) 16/2,076 (0.8) 4/5,047 (0.1) 20–29 (182,469) 6,704/182,469 (3.7) 1,559/8,906 (17.5) 498/18,530 (2.7) 864/182,469 (0.5) 300/8,906 (3.4) 56/18,530 (0.3) 273/182,469 (0.1) 122/8,906 (1.4) 24/18,530 (0.1) 30–39 (214,849) 12,570/214,849 (5.9) 3,596/14,854 (24.2) 828/18,629 (4.4) 1,879/214,849 (0.9) 787/14,854 (5.3) 135/18,629 (0.7) 852/214,849 (0.4) 411/14,854 (2.8) 21/18,629 (0.1) 40–49 (219,139) 19,318/219,139 (8.8) 7,151/24,161 (29.6) 1,057/16,411 (6.4) 3,316/219,139 (1.5) 1,540/24,161 (6.4) 208/16,411 (1.3) 2,083/219,139 (1.0) 1,077/24,161 (4.5) 58/16,411 (0.4) 50–59 (235,774) 31,588/235,774 (13.4) 14,639/40,297 (36.3) 1,380/14,420 (9.6) 5,986/235,774 (2.5) 3,335/40,297 (8.3) 296/14,420 (2.1) 5,639/235,774 (2.4) 3,158/40,297 (7.8) 131/14,420 (0.9) 60–69 (179,007) 39,422/179,007 (22.0) 21,064/42,206 (49.9) 1,216/7,919 (15.4) 7,403/179,007 (4.1) 4,588/42,206 (10.9) 291/7,919 (3.7) 11,947/179,007 (6.7) 7,050/42,206 (16.7) 187/7,919 (2.4) 70–79 (105,252) 35,844/105,252 (34.1) 20,451/31,601 (64.7) 780/2,799 (27.9) 5,939/105,252 (5.6) 3,771/31,601 (11.9) 199/2,799 (7.1) 17,510/105,252 (16.6) 10,008/31,601 (31.7) 286/2,799 (10.2) ≥80 (114,295) 37,145/114,295 (32.5) 21,294/34,159 (62.3) 725/2,409 (30.1) 4,093/114,295 (3.6) 2,550/34,159 (7.5) 125/2,409 (5.2) 32,766/114,295 (28.7) 16,966/34,159 (49.7) 718/2,409 (29.8) Total (1,320,488) 184,673/1,320,488 (14.0) 90,201/198,879 (45.4) 6,683/88,441 (7.6) 29,837/1,320,488 (2.3) 16,974/198,879 (8.5) 1,343/88,441 (1.5) 71,116/1,320,488 (5.4) 38,812/198,879 (19.5) 1,431/88,441 (1.6) Abbreviation: COVID-19 = coronavirus disease 2019. * Hospitalization status was known for 600,860 (46%). Among 184,673 hospitalized patients, the presence of underlying health conditions was known for 96,884 (53%). † Includes reported ICU admissions. § ICU admission status was known for 186,563 (14%) patients among the total case population, representing 34% of hospitalized patients. Among 29,837 patients admitted to the ICU, the status of underlying health conditions was known for 18,317 (61%). ¶ Death outcomes were known for 480,565 (36%) patients. Among 71,116 reported deaths through case surveillance, the status of underlying health conditions was known for 40,243 (57%) patients. ** Status of underlying health conditions was known for 287,320 (22%) patients. Status was classified as “known” if any of the following conditions were noted as present or absent: diabetes mellitus, cardiovascular disease including hypertension, severe obesity body mass index ≥40 kg/m2, chronic renal disease, chronic liver disease, chronic lung disease, any immunocompromising condition, any autoimmune condition, any neurologic condition including neurodevelopmental, intellectual, physical, visual, or hearing impairment, any psychologic/psychiatric condition, and any other underlying medical condition not otherwise specified. †† Outcomes were calculated as the proportion of persons reported to be hospitalized, admitted to an ICU, or who died among total in the demographic group. Outcome underreporting could result from outcomes that occurred but were not reported through national case surveillance or through clinical progression to severe outcomes that occurred after time of report. Discussion As of May 30, a total of 1,761,503 aggregate U.S. cases of COVID-19 and 103,700 associated deaths were reported to CDC. Although average daily reported cases and deaths are declining, 7-day moving averages of daily incidence of COVID-19 cases indicate ongoing community transmission. ¶¶¶¶ The COVID-19 case data summarized here are essential statistics for the pandemic response and rely on information systems developed at the local, state, and federal level over decades for communicable disease surveillance that were rapidly adapted to meet an enormous, new public health threat. CDC aggregate counts are consistent with those presented through the Johns Hopkins University (JHU) Coronavirus Resource Center, which reported a cumulative total of 1,770,165 U.S. cases and 103,776 U.S. deaths on May 30, 2020.***** Differences in aggregate counts between CDC and JHU might be attributable to differences in reporting practices to CDC and jurisdictional websites accessed by JHU. Reported cumulative incidence in the case surveillance population among persons aged ≥20 years is notably higher than that among younger persons. The lower incidence in persons aged ≤19 years could be attributable to undiagnosed milder or asymptomatic illnesses among this age group that were not reported. Incidence in persons aged ≥80 years was nearly double that in persons aged 70–79 years. Among cases with known race and ethnicity, 33% of persons were Hispanic, 22% were black, and 1.3% were AI/AN. These findings suggest that persons in these groups, who account for 18%, 13%, and 0.7% of the U.S. population, respectively, are disproportionately affected by the COVID-19 pandemic. The proportion of missing race and ethnicity data limits the conclusions that can be drawn from descriptive analyses; however, these findings are consistent with an analysis of COVID-19–Associated Hospitalization Surveillance Network (COVID-NET) ††††† data that found higher proportions of black and Hispanic persons among hospitalized COVID-19 patients than were in the overall population ( 4 ). The completeness of race and ethnicity variables in case surveillance has increased from 20% to >40% from April 2 to June 2. Although reporting of race and ethnicity continues to improve, more complete data might be available in aggregate on jurisdictional websites or through sources like the COVID Tracking Project’s COVID Racial Data Tracker. §§§§§ The data in this report show that the prevalence of reported symptoms varied by age group but was similar among males and females. Fewer than 5% of persons were reported to be asymptomatic when symptom data were submitted. Persons without symptoms might be less likely to be tested for COVID-19 because initial guidance recommended testing of only symptomatic persons and was hospital-based. Guidance on testing has evolved throughout the response. ¶¶¶¶¶ Whereas incidence among males and females was similar overall, severe outcomes were more commonly reported among males. Prevalence of reported severe outcomes increased with age; the percentages of hospitalizations, ICU admissions, and deaths were highest among persons aged ≥70 years, regardless of underlying conditions, and lowest among those aged ≤19 years. Hospitalizations were six times higher and deaths 12 times higher among those with reported underlying conditions compared with those with none reported. These findings are consistent with previous reports that found that severe outcomes increased with age and underlying condition, and males were hospitalized at a higher rate than were females ( 2 , 4 , 5 ). The findings in this report are subject to at least three limitations. First, case surveillance data represent a subset of the total cases of COVID-19 in the United States; not every case in the community is captured through testing and information collected might be limited if persons are unavailable or unwilling to participate in case investigations or if medical records are unavailable for data extraction. Reported cumulative incidence, although comparable across age and sex groups within the case surveillance population, are underestimates of the U.S. cumulative incidence of COVID-19. Second, reported frequencies of individual symptoms and underlying health conditions presented from case surveillance likely underestimate the true prevalence because of missing data. Finally, asymptomatic cases are not captured well in case surveillance. Asymptomatic persons are unlikely to seek testing unless they are identified through active screening (e.g., contact tracing), and, because of limitations in testing capacity and in accordance with guidance, investigation of symptomatic persons is prioritized. Increased identification and reporting of asymptomatic cases could affect patterns described in this report. Similar to earlier reports on COVID-19 case surveillance, severe outcomes were more commonly reported among persons who were older and those with underlying health conditions ( 1 ). Findings in this report align with demographic and severe outcome trends identified through COVID-NET ( 4 ). Findings from case surveillance are evaluated along with enhanced surveillance data and serologic survey results to provide a comprehensive picture of COVID-19 trends, and differences in proportion of cases by racial and ethnic groups should continue to be examined in enhanced surveillance to better understand populations at highest risk. Since the U.S. COVID-19 response began in January, CDC has built on existing surveillance capacity to monitor the impact of illness nationally. Collection of detailed case data is a resource-intensive public health activity, regardless of disease incidence. The high incidence of COVID-19 has highlighted limitations of traditional public health case surveillance approaches to provide real-time intelligence and supports the need for continued innovation and modernization. Despite limitations, national case surveillance of COVID-19 serves a critical role in the U.S. COVID-19 response: these data demonstrate that the COVID-19 pandemic is an ongoing public health crisis in the United States that continues to affect all populations and result in severe outcomes including death. National case surveillance findings provide important information for targeted enhanced surveillance efforts and development of interventions critical to the U.S. COVID-19 response. Summary What is already known about this topic? Surveillance data reported to CDC through April 2020 indicated that COVID-19 leads to severe outcomes in older adults and those with underlying health conditions. What is added by this report? As of May 30, 2020, among COVID-19 cases, the most common underlying health conditions were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%). Hospitalizations were six times higher and deaths 12 times higher among those with reported underlying conditions compared with those with none reported. What are the implications for public health practice? Surveillance at all levels of government, and its continued modernization, is critical for monitoring COVID-19 trends and identifying groups at risk for infection and severe outcomes. These findings highlight the continued need for community mitigation strategies, especially for vulnerable populations, to slow COVID-19 transmission.
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              A Practical Approach to the Management of Cancer Patients During the Novel Coronavirus Disease 2019 ( COVID ‐19) Pandemic: An International Collaborative Group

              Abstract The outbreak of coronavirus disease 2019 (COVID‐19) has rapidly spread globally since being identified as a public health emergency of major international concern and has now been declared a pandemic by the World Health Organization (WHO). In December 2019, an outbreak of atypical pneumonia, known as COVID‐19, was identified in Wuhan, China. The newly identified zoonotic coronavirus, severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), is characterized by rapid human‐to‐human transmission. Many cancer patients frequently visit the hospital for treatment and disease surveillance. They may be immunocompromised due to the underlying malignancy or anticancer therapy and are at higher risk of developing infections. Several factors increase the risk of infection, and cancer patients commonly have multiple risk factors. Cancer patients appear to have an estimated twofold increased risk of contracting SARS‐CoV‐2 than the general population. With the WHO declaring the novel coronavirus outbreak a pandemic, there is an urgent need to address the impact of such a pandemic on cancer patients. This include changes to resource allocation, clinical care, and the consent process during a pandemic. Currently and due to limited data, there are no international guidelines to address the management of cancer patients in any infectious pandemic. In this review, the potential challenges associated with managing cancer patients during the COVID‐19 infection pandemic will be addressed, with suggestions of some practical approaches. Implications for Practice The main management strategies for treating cancer patients during the COVID‐19 epidemic include clear communication and education about hand hygiene, infection control measures, high‐risk exposure, and the signs and symptoms of COVID‐19. Consideration of risk and benefit for active intervention in the cancer population must be individualized. Postponing elective surgery or adjuvant chemotherapy for cancer patients with low risk of progression should be considered on a case‐by‐case basis. Minimizing outpatient visits can help to mitigate exposure and possible further transmission. Telemedicine may be used to support patients to minimize number of visits and risk of exposure. More research is needed to better understand SARS‐CoV‐2 virology and epidemiology.
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                Author and article information

                Journal
                JCO Clin Cancer Inform
                JCO Clin Cancer Inform
                cci
                CCI
                JCO Clinical Cancer Informatics
                American Society of Clinical Oncology
                2473-4276
                2020
                30 November 2020
                : 4
                : CCI.20.00134
                Affiliations
                [ 1 ]Texas Oncology, Austin, TX
                [ 2 ]Florida Cancer Specialists & Research Institute LLC, Gainesville, FL
                [ 3 ]Community Oncology Alliance, Monroe, CT
                [ 4 ]Avalere Health, Washington, DC
                Author notes
                Debra Patt, PhD, Texas Oncology, 6204 Balcones, Austin, TX 78703; e-mail: Debra.Patt@ 123456USONCOLOGY.COM .
                Article
                2000134
                10.1200/CCI.20.00134
                7713534
                33253013
                bf8ee489-f056-454c-9660-2a1e06cf0e48
                © 2020 by American Society of Clinical Oncology

                Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 6 October 2020
                : 15 October 2020
                : 15 October 2020
                Categories
                ORIGINAL REPORTS
                Patient Care

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