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      Difference in mortality among individuals admitted to hospital with COVID-19 during the first and second waves in South Africa: a cohort study

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          Abstract

          Background

          The first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves.

          Methods

          In this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression.

          Findings

          Peak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240·4 cases per 100 000 people vs 136·0 cases per 100 000 people; admissions, 27·9 admissions per 100 000 people vs 16·1 admissions per 100 000 people; deaths, 8·3 deaths per 100 000 people vs 3·6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1·19, 95% CI 1·18–1·20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40–64 years (adjusted odds ratio [aOR] 1·22, 95% CI 1·14–1·31), and older than 65 years (aOR 1·38, 1·25–1·52), compared with younger than 40 years; of Mixed race (aOR 1·21, 1·06–1·38) compared with White race; and admitted in the public sector (aOR 1·65, 1·41–1·92); and less likely to be Black (aOR 0·53, 0·47–0·60) and Indian (aOR 0·77, 0·66–0·91), compared with White; and have a comorbid condition (aOR 0·60, 0·55–0·67). For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1·31, 95% CI 1·28–1·35). In-hospital case-fatality risk increased from 17·7% in weeks of low admission (<3500 admissions) to 26·9% in weeks of very high admission (>8000 admissions; aOR 1·24, 1·17–1·32).

          Interpretation

          In South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage.

          Funding

          DATCOV as a national surveillance system is funded by the National Institute for Communicable Diseases and the South African National Government.

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          Most cited references41

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          Dexamethasone in Hospitalized Patients with Covid-19 — Preliminary Report

          Abstract Background Coronavirus disease 2019 (Covid-19) is associated with diffuse lung damage. Glucocorticoids may modulate inflammation-mediated lung injury and thereby reduce progression to respiratory failure and death. Methods In this controlled, open-label trial comparing a range of possible treatments in patients who were hospitalized with Covid-19, we randomly assigned patients to receive oral or intravenous dexamethasone (at a dose of 6 mg once daily) for up to 10 days or to receive usual care alone. The primary outcome was 28-day mortality. Here, we report the preliminary results of this comparison. Results A total of 2104 patients were assigned to receive dexamethasone and 4321 to receive usual care. Overall, 482 patients (22.9%) in the dexamethasone group and 1110 patients (25.7%) in the usual care group died within 28 days after randomization (age-adjusted rate ratio, 0.83; 95% confidence interval [CI], 0.75 to 0.93; P<0.001). The proportional and absolute between-group differences in mortality varied considerably according to the level of respiratory support that the patients were receiving at the time of randomization. In the dexamethasone group, the incidence of death was lower than that in the usual care group among patients receiving invasive mechanical ventilation (29.3% vs. 41.4%; rate ratio, 0.64; 95% CI, 0.51 to 0.81) and among those receiving oxygen without invasive mechanical ventilation (23.3% vs. 26.2%; rate ratio, 0.82; 95% CI, 0.72 to 0.94) but not among those who were receiving no respiratory support at randomization (17.8% vs. 14.0%; rate ratio, 1.19; 95% CI, 0.91 to 1.55). Conclusions In patients hospitalized with Covid-19, the use of dexamethasone resulted in lower 28-day mortality among those who were receiving either invasive mechanical ventilation or oxygen alone at randomization but not among those receiving no respiratory support. (Funded by the Medical Research Council and National Institute for Health Research and others; RECOVERY ClinicalTrials.gov number, NCT04381936; ISRCTN number, 50189673.)
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            Remdesivir for the Treatment of Covid-19 — Final Report

            Abstract Background Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (Covid-19), none have yet been shown to be efficacious. Methods We conducted a double-blind, randomized, placebo-controlled trial of intravenous remdesivir in adults hospitalized with Covid-19 with evidence of lower respiratory tract involvement. Patients were randomly assigned to receive either remdesivir (200 mg loading dose on day 1, followed by 100 mg daily for up to 9 additional days) or placebo for up to 10 days. The primary outcome was the time to recovery, defined by either discharge from the hospital or hospitalization for infection-control purposes only. Results A total of 1063 patients underwent randomization. The data and safety monitoring board recommended early unblinding of the results on the basis of findings from an analysis that showed shortened time to recovery in the remdesivir group. Preliminary results from the 1059 patients (538 assigned to remdesivir and 521 to placebo) with data available after randomization indicated that those who received remdesivir had a median recovery time of 11 days (95% confidence interval [CI], 9 to 12), as compared with 15 days (95% CI, 13 to 19) in those who received placebo (rate ratio for recovery, 1.32; 95% CI, 1.12 to 1.55; P<0.001). The Kaplan-Meier estimates of mortality by 14 days were 7.1% with remdesivir and 11.9% with placebo (hazard ratio for death, 0.70; 95% CI, 0.47 to 1.04). Serious adverse events were reported for 114 of the 541 patients in the remdesivir group who underwent randomization (21.1%) and 141 of the 522 patients in the placebo group who underwent randomization (27.0%). Conclusions Remdesivir was superior to placebo in shortening the time to recovery in adults hospitalized with Covid-19 and evidence of lower respiratory tract infection. (Funded by the National Institute of Allergy and Infectious Diseases and others; ACTT-1 ClinicalTrials.gov number, NCT04280705.)
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              Delay or Avoidance of Medical Care Because of COVID-19–Related Concerns — United States, June 2020

              Temporary disruptions in routine and nonemergency medical care access and delivery have been observed during periods of considerable community transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) ( 1 ). However, medical care delay or avoidance might increase morbidity and mortality risk associated with treatable and preventable health conditions and might contribute to reported excess deaths directly or indirectly related to COVID-19 ( 2 ). To assess delay or avoidance of urgent or emergency and routine medical care because of concerns about COVID-19, a web-based survey was administered by Qualtrics, LLC, during June 24–30, 2020, to a nationwide representative sample of U.S. adults aged ≥18 years. Overall, an estimated 40.9% of U.S. adults have avoided medical care during the pandemic because of concerns about COVID-19, including 12.0% who avoided urgent or emergency care and 31.5% who avoided routine care. The estimated prevalence of urgent or emergency care avoidance was significantly higher among the following groups: unpaid caregivers for adults* versus noncaregivers (adjusted prevalence ratio [aPR] = 2.9); persons with two or more selected underlying medical conditions † versus those without those conditions (aPR = 1.9); persons with health insurance versus those without health insurance (aPR = 1.8); non-Hispanic Black (Black) adults (aPR = 1.6) and Hispanic or Latino (Hispanic) adults (aPR = 1.5) versus non-Hispanic White (White) adults; young adults aged 18–24 years versus adults aged 25–44 years (aPR = 1.5); and persons with disabilities § versus those without disabilities (aPR = 1.3). Given this widespread reporting of medical care avoidance because of COVID-19 concerns, especially among persons at increased risk for severe COVID-19, urgent efforts are warranted to ensure delivery of services that, if deferred, could result in patient harm. Even during the COVID-19 pandemic, persons experiencing a medical emergency should seek and be provided care without delay ( 3 ). During June 24–30, 2020, a total of 5,412 (54.7%) of 9,896 eligible adults ¶ completed web-based COVID-19 Outbreak Public Evaluation Initiative surveys administered by Qualtrics, LLC.** The Human Research Ethics Committee of Monash University (Melbourne, Australia) reviewed and approved the study protocol on human subjects research. This activity was also reviewed by CDC and was conducted consistent with applicable federal law and CDC policy. †† Respondents were informed of the study purposes and provided electronic consent before commencement, and investigators received anonymized responses. The 5,412 participants included 3,683 (68.1%) first-time respondents and 1,729 (31.9%) persons who had completed a related survey §§ during April 2–8, 2020. Among the 5,412 participants, 4,975 (91.9%) provided complete data for all variables in this analysis. Quota sampling and survey weighting ¶¶ were employed to improve cohort representativeness of the U.S. population by gender, age, and race/ethnicity. Respondents were asked “Have you delayed or avoided medical care due to concerns related to COVID-19?” Delay or avoidance was evaluated for emergency (e.g., care for immediate life-threatening conditions), urgent (e.g., care for immediate non–life-threatening conditions), and routine (e.g., annual check-ups) medical care. Given the potential for variation in interpretation of whether conditions were life-threatening, responses for urgent and emergency care delay or avoidance were combined for analysis. Covariates included gender; age; race/ethnicity; disability status; presence of one or more selected underlying medical conditions known to increase risk for severe COVID-19; education; essential worker status***; unpaid adult caregiver status; U.S. census region; urban/rural classification ††† ; health insurance status; whether respondents knew someone who had received a positive SARS-CoV-2 test result or had died from COVID-19; and whether the respondents believed they were at high risk for severe COVID-19. Comparisons within all these subgroups were evaluated using multivariable Poisson regression models §§§ with robust standard errors to estimate prevalence ratios adjusted for all covariates, 95% confidence intervals, and p-values to evaluate statistical significance (α = 0.05) using the R survey package (version 3.29) and R software (version 4.0.2; The R Foundation). As of June 30, 2020, among 4,975 U.S. adult respondents, 40.9% reported having delayed or avoided any medical care, including urgent or emergency care (12.0%) and routine care (31.5%), because of concerns about COVID-19 (Table 1). Groups of persons among whom urgent or emergency care avoidance exceeded 20% and among whom any care avoidance exceeded 50% included adults aged 18–24 years (30.9% for urgent or emergency care; 57.2% for any care), unpaid caregivers for adults (29.8%; 64.3%), Hispanic adults (24.6%; 55.5%), persons with disabilities (22.8%; 60.3%), persons with two or more selected underlying medical conditions (22.7%; 54.7%), and students (22.7%; 50.3%). One in four unpaid caregivers reported caring for adults who were at increased risk for severe COVID-19. TABLE 1 Estimated prevalence of delay or avoidance of medical care because of concerns related to COVID-19, by type of care and respondent characteristics — United States, June 30, 2020 Characteristic No. (%)† Type of medical care delayed or avoided* Urgent or emergency Routine Any %† P-value§ %† P-value§ %† P-value§ All respondents 4,975 (100) 12.0 — 31.5 — 40.9 — Gender Female 2,528 (50.8) 11.7 0.598 35.8 <0.001 44.9 <0.001 Male 2,447 (49.2) 12.3 27.0 36.7 Age group, yrs 18–24 650 (13.1) 30.9 <0.001 29.6 0.072 57.2 <0.001 25–44 1,740 (35.0) 14.9 34.2 44.8 45–64 1,727 (34.7) 5.7 30.0 34.5 ≥65 858 (17.3) 4.4 30.3 33.5 Race/Ethnicity White, non-Hispanic 3,168 (63.7) 6.7 <0.001 30.9 0.020 36.2 <0.001 Black, non-Hispanic 607 (12.2) 23.3 29.7 48.1 Asian, non-Hispanic 238 (4.8) 8.6 31.3 37.7 Other race or multiple races, non-Hispanic¶ 150 (3.0) 15.5 23.9 37.3 Hispanic, any race or races 813 (16.3) 24.6 36.4 55.5 Disability** Yes 1,108 (22.3) 22.8 <0.001 42.9 <0.001 60.3 <0.001 No 3,867 (77.7) 8.9 28.2 35.3 Underlying medical condition†† No 2,537 (51.0) 8.2 <0.001 27.9 <0.001 34.7 <0.001 One 1,328 (26.7) 10.4 33.0 41.2 Two or more 1,110 (22.3) 22.7 37.7 54.7 2019 household income, USD <25,000 665 (13.4) 13.9 0.416 31.2 0.554 42.8 0.454 25,000–49,999 1,038 (20.9) 11.1 30.9 38.6 50,000–99,999 1,720 (34.6) 12.5 30.5 41.1 ≥100,000 1,552 (31.2) 11.2 33.0 41.4 Education Less than high school diploma 65 (1.3) 15.6 0.442 24.7 0.019 37.9 0.170 High school diploma 833 (16.7) 12.3 28.1 38.1 Some college 1,302 (26.2) 13.6 29.7 40.3 Bachelor's degree 1,755 (35.3) 11.2 34.8 43.6 Professional degree 1,020 (20.5) 10.9 31.2 39.5 Employment status Employed 3,049 (61.3) 14.6 <0.001 31.5 0.407 43.3 <0.001 Unemployed 630 (12.7) 8.7 34.4 39.5 Retired 1,129 (22.7) 5.3 29.9 33.8 Student 166 (3.3) 22.7 30.5 50.3 Essential worker status§§ Essential worker 1,707 (34.3) 19.5 <0.001 32.4 0.293 48.0 <0.001 Nonessential worker 1,342 (27.0) 8.4 30.3 37.3 Unpaid caregiver status¶¶ Unpaid caregiver for adults 1,344 (27.0) 29.8 <0.001 41.0 <0.001 64.3 <0.001 Not unpaid caregiver for adults 3,631 (73.0) 5.4 27.9 32.2 U.S. Census region*** Northeast 1,122 (22.6) 11.0 0.008 33.9 0.203 42.5 0.460 Midwest 936 (18.8) 8.5 32.0 38.7 South 1,736 (34.9) 13.9 29.6 40.7 West 1,181 (23.7) 13.0 31.5 41.5 Rural/Urban classification††† Urban 4,411 (88.7) 12.3 0.103 31.5 0.763 41.2 0.216 Rural 564 (11.3) 9.4 30.9 38.2 Health insurance status Yes 4,577 (92.0) 12.4 0.036 32.6 <0.001 42.3 <0.001 No 398 (8.0) 7.8 18.4 24.8 Know someone with positive test results for SARS-CoV-2§§§ Yes 989 (19.9) 8.8 0.004 40.7 <0.001 46.6 <0.001 No 3,986 (80.1) 12.8 29.2 39.5 Knew someone who died from COVID-19 Yes 364 (7.3) 10.1 0.348 41.4 <0.001 46.3 0.048 No 4,611 (92.7) 12.2 30.7 40.5 Believed to be in group at high risk for severe COVID-19 Yes 981 (19.7) 10.0 0.050 42.5 <0.001 49.4 <0.001 No 3,994 (80.3) 12.5 28.8 38.8 Abbreviations: CI = confidence interval; COVID-19 = coronavirus disease 2019; USD = U.S. dollars. * The types of medical care avoidance are not mutually exclusive; respondents had the option to indicate that they had delayed or avoided more than one type of medical care (i.e., routine medical care and urgent/emergency medical care). † Statistical raking and weight trimming were employed to improve the cross-sectional June cohort representativeness of the U.S. population by gender, age, and race/ethnicity according to the 2010 U.S. Census. § The Rao-Scott adjusted Pearson chi-squared test was used to test for differences in observed and expected frequencies among groups by characteristic for avoidance of each type of medical care (e.g., whether avoidance of routine medical care differs significantly by gender). Statistical significance was evaluated at a threshold of α = 0.05. ¶ “Other” race includes American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or Other. ** Persons who had a disability were defined as such based on a qualifying response to either one of two questions: “Are you limited in any way in any activities because of physical, mental, or emotional condition?” and “Do you have any health conditions that require you to use special equipment, such as a cane, wheelchair, special bed, or special telephone?” https://www.cdc.gov/brfss/questionnaires/pdf-ques/2015-brfss-questionnaire-12-29-14.pdf. †† Selected underlying medical conditions known to increase the risk for severe COVID-19 included in this analysis were obesity, diabetes, high blood pressure, cardiovascular disease, and any type of cancer. Obesity is defined as body mass index ≥30 kg/m2 and was calculated from self-reported height and weight (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html). The remaining conditions were assessed using the question “Have you ever been diagnosed with any of the following conditions?” with response options of 1) “Never”; 2) “Yes, I have in the past, but don’t have it now”; 3) “Yes I have, but I do not regularly take medications or receive treatment”; and 4) “Yes I have, and I am regularly taking medications or receiving treatment.” Respondents who answered that they have been diagnosed and chose either response 3 or 4 were considered as having the specified medical condition. §§ Essential worker status was self-reported. ¶¶ Unpaid caregiver status was self-reported. Unpaid caregivers for adults were defined as having provided unpaid care to a relative or friend aged ≥18 years at any time in the last 3 months. Examples provided to survey respondents included helping with personal needs, household chores, health care tasks, managing a person’s finances, taking them to a doctor’s appointment, arranging for outside services, and visiting regularly to see how they are doing. *** Region classification was determined by using the U.S. Census Bureau’s Census Regions and Divisions. https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf. ††† Rural-urban classification was determined by using self-reported ZIP codes according to the Federal Office of Rural Health Policy definition of rurality. https://www.hrsa.gov/rural-health/about-us/definition/datafiles.html. §§§ For this question, respondents were asked to select the following statement, if applicable: “I know someone who has tested positive for COVID-19.” In the multivariable Poisson regression models, differences within groups were observed for urgent or emergency care avoidance (Figure) and any care avoidance (Table 2). Adjusted prevalence of urgent or emergency care avoidance was significantly higher among unpaid caregivers for adults versus noncaregivers (2.9; 2.3–3.6); persons with two or more selected underlying medical conditions versus those without those conditions (1.9; 1.5–2.4); persons with health insurance versus those without health insurance (1.8; 1.2–2.8); Black adults (1.6; 1.3–2.1) and Hispanic adults (1.5; 1.2–2.0) versus White adults; young adults aged 18–24 years versus adults aged 25–44 years (1.5; 1.2–1.8); and persons with disabilities versus those without disabilities (1.3; 1.1–1.5). Avoidance of urgent or emergency care was significantly lower among adults aged ≥45 years than among younger adults. FIGURE Adjusted prevalence ratios* , † for characteristics § , ¶ , ** , †† associated with delay or avoidance of urgent or emergency medical care because of concerns related to COVID-19 — United States, June 30, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * Comparisons within subgroups were evaluated using Poisson regressions used to calculate a prevalence ratio adjusted for all characteristics shown in figure. † 95% confidence intervals indicated with error bars. § “Other” race includes American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or Other. ¶ Selected underlying medical conditions known to increase the risk for severe COVID-19 were obesity, diabetes, high blood pressure, cardiovascular disease, and any type of cancer. Obesity is defined as body mass index ≥30 kg/m2 and was calculated from self-reported height and weight (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html). The remaining conditions were assessed using the question “Have you ever been diagnosed with any of the following conditions?” with response options of 1) “Never”; 2) “Yes, I have in the past, but don’t have it now”; 3) “Yes I have, but I do not regularly take medications or receive treatment”; and 4) “Yes I have, and I am regularly taking medications or receiving treatment.” Respondents who answered that they have been diagnosed and chose either response 3 or 4 were considered as having the specified medical condition. ** Essential worker status was self-reported. For the adjusted prevalence ratios, essential workers were compared with all other respondents (including those who were nonessential workers, retired, unemployed, and students). †† Unpaid caregiver status was self-reported. Unpaid caregivers for adults were defined as having provided unpaid care to a relative or friend aged ≥18 years to help them take care of themselves at any time in the last 3 months. The figure is a forest plot showing the adjusted prevalence ratios for characteristics associated with delay or avoidance of urgent or emergency medical care because of concerns related to COVID-19, in the United States, as of June 30, 2020. TABLE 2 Characteristics associated with delay or avoidance of any medical care because of concerns related to COVID-19 — United States, June 30, 2020 Characteristic Weighted* no. Avoided or delayed any medical care aPR† (95% CI†) P-value† All respondents 4,975 — — — Gender Female 2,528 Referent — — Male 2,447 0.81 (0.75–0.87)§ <0.001 Age group, yrs 18–24 650 1.12 (1.01–1.25)§ 0.035 25–44 1,740 Referent — — 45–64 1,727 0.80 (0.72–0.88)§ <0.001 ≥65 858 0.72 (0.64–0.81)§ <0.001 Race/Ethnicity White, non-Hispanic 3,168 Referent — — Black, non-Hispanic 607 1.07 (0.96–1.19) 0.235 Asian, non-Hispanic 238 1.04 (0.91–1.18) 0.567 Other race or multiple races, non-Hispanic¶ 150 0.87 (0.71–1.07) 0.196 Hispanic, any race or races 813 1.15 (1.03–1.27)§ 0.012 Disability** Yes 1,108 1.33 (1.23–1.43)§ <0.001 No 3,867 Referent — — Underlying medical condition†† No 2,537 Referent — — One 1,328 1.15 (1.05–1.25)§ 0.004 Two or more 1,110 1.31 (1.20–1.42)§ <0.001 Education Less than high school diploma 65 0.72 (0.53–0.98)§ 0.037 High school diploma 833 0.79 (0.71–0.89)§ <0.001 Some college 1,302 0.85 (0.78–0.93)§ 0.001 Bachelor's degree 1,755 Referent — — Professional degree 1,020 0.90 (0.82–0.98)§ 0.019 Essential workers vs others§§ Essential workers 1,707 1.00 (0.92–1.09) 0.960 Other respondents (nonessential workers, retired persons, unemployed persons, and students) 3,268 Referent — — Unpaid caregiver status¶¶ Unpaid caregiver for adults 1,344 1.64 (1.52–1.78)§ <0.001 Not unpaid caregiver for adults 3,631 Referent — — U.S. Census region*** Northeast 1,122 Referent — — Midwest 936 0.93 (0.83–1.04) 0.214 South 1,736 0.90 (0.82–0.99)§ 0.028 West 1,181 0.99 (0.89–1.09) 0.808 Rural/Urban classification††† Urban 4,411 1.00 (0.89–1.12) 0.993 Rural 564 Referent — — Health insurance status Yes 4,577 1.61 (1.31–1.98)§ <0.001 No 398 Referent — — Know someone with positive test results for SARS-CoV-2§§§ Yes 989 1.22 (1.12–1.33)§ <0.001 No 3,986 Referent — — Knew someone who died from COVID-19 Yes 364 0.99 (0.88–1.12) 0.860 No 4,611 Referent — — Believed to be in a group at high risk for severe COVID-19 Yes 981 1.33 (1.23–1.44)§ <0.001 No 3,994 Referent — — Abbreviations: aPR = adjusted prevalence ratio; CI = confidence interval; COVID-19 = coronavirus disease 2019. * Statistical raking and weight trimming were employed to improve the cross-sectional June cohort representativeness of the U.S. population by gender, age, and race/ethnicity according to the 2010 U.S. Census. † Comparisons within subgroups were evaluated using Poisson regressions used to calculate a prevalence ratio adjusted for all characteristics listed, as well as a 95% CI and p-value. Statistical significance was evaluated at a threshold of α = 0.05. § P-value calculated using Poisson regression among respondents within a characteristic is statistically significant at levels of p<0.05. ¶ “Other” race includes American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or Other. ** Persons who had a disability were defined based on a qualifying response to either one of two questions: “Are you limited in any way in any activities because of physical, mental, or emotional condition?” and “Do you have any health conditions that require you to use special equipment, such as a cane, wheelchair, special bed, or special telephone?” https://www.cdc.gov/brfss/questionnaires/pdf-ques/2015-brfss-questionnaire-12-29-14.pdf. †† Selected underlying medical conditions known to increase the risk for severe COVID-19 were obesity, diabetes, high blood pressure, cardiovascular disease, and any type of cancer. Obesity is defined as body mass index ≥30 kg/m2 and was calculated from self-reported height and weight (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html). The remaining conditions were assessed using the question “Have you ever been diagnosed with any of the following conditions?” with response options of 1) “Never”; 2) “Yes, I have in the past, but don’t have it now”; 3) “Yes I have, but I do not regularly take medications or receive treatment”; and 4) “Yes I have, and I am regularly taking medications or receiving treatment.” Respondents who answered that they have been diagnosed and chose either response 3 or 4 were considered as having the specified medical condition. §§ Essential worker status was self-reported. For the adjusted prevalence ratios, essential workers were compared with all other respondents (including those who were nonessential workers, retired, unemployed, and students). ¶¶ Unpaid caregiver status was self-reported. Unpaid caregivers for adults were defined as having provided unpaid care to a relative or friend aged ≥18 years at any time in the last 3 months. Examples provided to survey respondents included helping with personal needs, household chores, health care tasks, managing a person’s finances, taking them to a doctor’s appointment, arranging for outside services, and visiting regularly to see how they are doing. *** Region classification was determined by using the U.S. Census Bureau’s Census Regions and Divisions. https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf. ††† Rural/urban classification was determined by using self-reported ZIP codes according to the Federal Office of Rural Health Policy definition of rurality. https://www.hrsa.gov/rural-health/about-us/definition/datafiles.html. §§§ For this question, respondents were asked to select the following statement, if applicable: “I know someone who has tested positive for COVID-19.” Discussion As of June 30, 2020, an estimated 41% of U.S. adults reported having delayed or avoided medical care during the pandemic because of concerns about COVID-19, including 12% who reported having avoided urgent or emergency care. These findings align with recent reports that hospital admissions, overall emergency department (ED) visits, and the number of ED visits for heart attack, stroke, and hyperglycemic crisis have declined since the start of the pandemic ( 3 – 5 ), and that excess deaths directly or indirectly related to COVID-19 have increased in 2020 versus prior years ( 2 ). Nearly one third of adult respondents reported having delayed or avoided routine medical care, which might reflect adherence to community mitigation efforts such as stay-at-home orders, temporary closures of health facilities, or additional factors. However, if routine care avoidance were to be sustained, adults could miss opportunities for management of chronic conditions, receipt of routine vaccinations, or early detection of new conditions, which might worsen outcomes. Avoidance of both urgent or emergency and routine medical care because of COVID-19 concerns was highly prevalent among unpaid caregivers for adults, respondents with two or more underlying medical conditions, and persons with disabilities. For caregivers who reported caring for adults at increased risk for severe COVID-19, concern about exposure of care recipients might contribute to care avoidance. Persons with underlying medical conditions that increase their risk for severe COVID-19 ( 6 ) are more likely to require care to monitor and treat these conditions, potentially contributing to their more frequent report of avoidance. Moreover, persons at increased risk for severe COVID-19 might have avoided health care facilities because of perceived or actual increased risk of exposure to SARS-CoV-2, particularly at the onset of the pandemic. However, health care facilities are implementing important safety precautions to reduce the risk of SARS-CoV-2 infection among patients and personnel. In contrast, delay or avoidance of care might increase risk for life-threatening medical emergencies. In a recent study, states with large numbers of COVID-19–associated deaths also experienced large proportional increases in deaths from other underlying causes, including diabetes and cardiovascular disease ( 7 ). For persons with disabilities, accessing medical services might be challenging because of disruptions in essential support services, which can result in adverse health outcomes. Medical services for persons with disabilities might also be disrupted because of reduced availability of accessible transportation, reduced communication in accessible formats, perceptions of SARS-CoV-2 exposure risk, and specialized needs that are difficult to address with routine telehealth delivery during the pandemic response. Increasing accessibility of medical and telehealth services ¶¶¶ might help prevent delay of needed care. Increased prevalences of reported urgent or emergency care avoidance among Black adults and Hispanic adults compared with White adults are especially concerning given increased COVID-19-associated mortality among Black adults and Hispanic adults ( 8 ). In the United States, the age-adjusted COVID-19 hospitalization rates are approximately five times higher among Black persons and four times higher among Hispanic persons than are those among White persons ( 9 ). Factors contributing to racial and ethnic disparities in SARS-CoV-2 exposure, illness, and mortality might include long-standing structural inequities that influence life expectancy, including prevalence and underlying medical conditions, health insurance status, and health care access and utilization, as well as work and living circumstances, including use of public transportation and essential worker status. Communities, health care systems, and public health agencies can foster equity by working together to ensure access to information, testing, and care to assure maintenance and management of physical and mental health. The higher prevalence of medical care delay or avoidance among respondents with health insurance versus those without insurance might reflect differences in medical care-seeking behaviors. Before the pandemic, persons without insurance sought medical care much less frequently than did those with insurance ( 10 ), resulting in fewer opportunities for medical care delay or avoidance. The findings in this report are subject to at least five limitations. First, self-reported data are subject to recall, response, and social desirability biases. Second, the survey did not assess reasons for COVID-19–associated care avoidance, such as adherence to public health recommendations; closure of health care provider facilities; reduced availability of public transportation; fear of exposure to infection with SARS-CoV-2; or availability, accessibility, and acceptance or recognition of telemedicine as a means of providing care in lieu of in-person services. Third, the survey did not assess baseline patterns of care-seeking or timing or duration of care avoidance. Fourth, perceptions of whether a condition was life-threatening might vary among respondents. Finally, although quota sampling methods and survey weighting were employed to improve cohort representativeness, this web-based survey might not be fully representative of the U.S. population for income, educational attainment, and access to technology. However, the findings are consistent with reported declines in hospital admissions and ED visits during the pandemic ( 3 – 5 ). CDC has issued guidance to assist persons at increased risk for severe COVID-19 in staying healthy and safely following treatment plans**** and to prepare health care facilities to safely deliver care during the pandemic. †††† Additional public outreach in accessible formats tailored for diverse audiences might encourage these persons to seek necessary care. Messages could highlight the risks of delaying needed care, especially among persons with underlying medical conditions, and the importance of timely emergency care. Patient concerns related to potential exposure to SARS-CoV-2 in health care settings could be addressed by describing facilities’ precautions to reduce exposure risk. Further exploration of underlying reasons for medical care avoidance is needed, including among persons with disabilities, persons with underlying health conditions, unpaid caregivers for adults, and those who face structural inequities. If care were avoided because of concern about SARS-CoV-2 exposure or if there were closures or limited options for in-person services, providing accessible telehealth or in-home health care could address some care needs. Even during the COVID-19 pandemic, persons experiencing a medical emergency should seek and be provided care without delay ( 3 ). Summary What is already known about this topic? Delayed or avoided medical care might increase morbidity and mortality associated with both chronic and acute health conditions. What is added by this report? By June 30, 2020, because of concerns about COVID-19, an estimated 41% of U.S. adults had delayed or avoided medical care including urgent or emergency care (12%) and routine care (32%). Avoidance of urgent or emergency care was more prevalent among unpaid caregivers for adults, persons with underlying medical conditions, Black adults, Hispanic adults, young adults, and persons with disabilities. What are the implications for public health practice? Understanding factors associated with medical care avoidance can inform targeted care delivery approaches and communication efforts encouraging persons to safely seek timely routine, urgent, and emergency care.
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                Author and article information

                Journal
                Lancet Glob Health
                Lancet Glob Health
                The Lancet. Global Health
                The Author(s). Published by Elsevier Ltd.
                2214-109X
                9 July 2021
                9 July 2021
                Affiliations
                [a ]National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
                [b ]School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
                [c ]School of Pathology, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
                [d ]Health Impact Assessment Directorate, Western Cape Government, Cape Town, South Africa
                [e ]Clinton Health Access Initiative, Pretoria, South Africa
                [f ]National Department of Health, Pretoria, South Africa
                Author notes
                [* ]Correspondence to: Waasila Jassat, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg 2031, South Africa
                Article
                S2214-109X(21)00289-8
                10.1016/S2214-109X(21)00289-8
                8270522
                34252381
                7d61af27-74ee-4fb5-ac3d-7d2ff42c672f
                © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license

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