Burdens of Post-acute Sequelae of COVID-19 by Age, Race, Sex, and Health Status

The Post-Acute Sequelae of SARS-CoV-2 infection (PASC) have been characterized; however, the burden of PASC remains unknown. And whether the burden of individual sequela varies in different population groups is also not clear. Here we estimate that PASC — dened as the presence of at least one sequela in excess of non-infected controls — was 73.43 (72.10, 74.72) per 1000 persons at 6 months. The burden of PASC was 44.51 (43.09, 45.85), 217.08 (212.43, 222.23), and 360.16 (350.53, 369.38) among non-hospitalized, hospitalized, and those who required intensive care during the rst 30-days of infection. Burdens of some sequelae were more pronounced in younger individuals, and some were more pronounced in older adults; the same picture was evident in analyses across race, and sex groups. The burden of individual sequela was consistently higher in people with poorer baseline health and increased in a graded fashion according to care setting of the acute infection. In sum, the burden of PASC is substantial; however, PASC is non-monolithic with sequelae that are differentially expressed in various population groups. Collectively, our results may be useful in informing health systems capacity planning and care strategies of people with PASC. health to estimate of overall and its individual sequelae by age, race, sex, and baseline health status. We comprehensively examined 33 sequelae which were dened based on integrated data from multiple sources including diagnostic codes, medications, and laboratory test results. The simultaneous examination of incident sequelae in the same analytic framework allows the comparative evaluation of risks and burdens of these conditions — providing health care providers, health system planners, public health ocials, and the public at large with a priority list of the post-acute clinical conditions encountered in COVID-19 survivors. For each outcome examined, we built a cohort free of the related outcome at baseline to identify the risk of incident outcome during follow up — this approach allows the identication of incident clinical manifestations and abnormalities following COVID-19 infection. While we conducted analyses to estimate the risk of each outcome examined, we — for each outcome — also estimated the excess burden per 1000 persons due to COVID-19; this measure of risk on the absolute scale also considers baseline and provides a more meaningful estimate of potential harm and can be more effectively communicated to the wider public than measures of relative risks (e.g. hazard ratio).


Introduction
Emerging reports suggest that beyond the acute illness, some COVID-19 survivors experience myriad clinical abnormalities lasting well beyond the rst 30 days of infection [1][2][3][4][5][6] . We recently developed a high dimensional approach to comprehensively and systematically characterize the Post-Acute Sequelae of SARS-CoV-2 infection (PASC) -also referred to as post COVID-19 syndrome, or simply long COVID 1 . Our approach identi ed 33 sequelae in the pulmonary and several extrapulmonary organ systems including nervous system and neurocognitive disorders, mental health disorders, metabolic disorders, cardiovascular disorders, gastrointestinal disorders, and several other clinical manifestations 1 .
However, signi cant knowledge gaps remain. Speci cally, what is the burden of PASC -de ned as having at least one post-acute sequela? And does the burden of individual sequelae differ by age, race, sex, and baseline health status? Addressing these questions has been highlighted as an urgent research priority by stakeholders including the World Health Organization, the United States National Institute of Health, the United Kingdom National Institute for Health and Care Excellence, and several others 2,7−12 .
Addressing these questions will help inform capacity planning and care of people with PASC.
Here, we answer this call for urgent research, where we leverage the breadth and depth of the US Department of Veterans Affairs (VA) electronic healthcare databases -which operates the largest integrated health care delivery system in the US -to undertake comprehensive large-scale analyses of 181,384 people with COVID-19 who survived the rst 30 days of infection and 4,397,509 non-infected controls, and aimed to estimate the burden of PASC in the overall cohort and among non-hospitalized (n = 155,987), hospitalized (n = 19,359), and those admitted to intensive care (n = 6038) and b) burdens of the 33 individual sequelae that comprise PASC -identi ed in prior work 1 -in population groups (by age, race, sex, baseline health status).

Results
We enrolled 181,384 veterans who survived the rst 30  In adjusted analyses, 30-day survivors of COVID-19 exhibited increased risk of a broad range of incident sequelae including pulmonary system disorders and cardiovascular, coagulation, dermatologic, endocrine, gastrointestinal, kidney, mental health, musculoskeletal, and neurologic system disorders; risks and associated burdens for each sequela are provided in Supplementary Fig. 1 Table 4 -5). This analysis showed that the burdens were not uniformly expressed across age, race, sex, and baseline health status. Analyses of differences in burden on the basis of age suggest that while most incident sequelae were higher in older adults; burdens of hyperlipidemia, chest pain, sleep disorders, headache, obesity, mood disorders, cough and smell problems were higher in people younger than 60 years old. Smaller differences of burden on the basis of race were observed where burden of acute kidney injury, diabetes mellitus, chest pain, cough, substance abuse, thromboembolism, headache and tachycardia were slightly higher in Black persons; GERD and smell problems were higher in White persons. Burden of several sequelae in the respiratory system disorders (shortness of breath and cough), cardiovascular system disorders (chest pain, and arrythmias), neurologic system disorders (headache, and smell problems), and dermatologic disorders (hair loss, and skin rash) were higher in females. Nearly all sequelae were more pronounced in persons with higher burden of baseline comorbidities ( Fig. 3 and Supplementary Table 6).
Burden of sequelae by age, race, sex, and baseline health status according to care setting of the acute infection (non-hospitalized, hospitalized, and required intensive care): In the overall cohort, burden of individual sequelae increased according to the care setting of the acute infection from non-hospitalized, hospitalized, and those who required intensive care ( Fig. 4a- Table 10). The examination of negative control in groups according to care setting in non-hospitalized, hospitalized, and admitted to intensive care for COVID-19 also yielded nonsigni cant associations -results that were consistent with a priori expectations (Supplementary Table 10).

Discussion
In this work, we estimate that PASC -de ned as at least one sequela in excess of a non-infected control group -was 73. 43  respectively. PASC is a multifaceted non-monolithic entity; some of its sequelae were more pronounced in younger individuals, and some were more pronounced in older adults. The same picture was evident in analyses across race groups (White and Black participants), and sex (males and females). The burden of individual sequela was consistently higher in people with poorer baseline health status and increased in a graded fashion according to intensity of the care setting of the acute infection. The constellation of ndings shows that among 30-day survivors of COVID-19, the burden of PASC is substantial (7%); PASC is not a monolithic entity with sequelae that are differentially expressed in various population groups. Collectively, our results provide estimates that may be useful in informing health systems capacity planning and care strategies of people with PASC.
The implications of our results are clear. As the number of COVID-19 cases continues to climb across the globe, health systems face the dual challenge of coping with surges in acute infections, and caring for COVID-19 survivors (now accounting for more than 2% of the global population and growing) who will also likely require substantial care to mitigate permanent health loss. This will place additional demands on already strained health systems. Governments and health systems around the globe should be actively devising plans to address the tide of COVID-19 survivors in need of post COVID-19 care. Our estimates of the burden of PASC (around 7% of infected people) and burden of 33 individual sequelae by age, race, sex, and baseline health status may help inform capacity planning and optimal composition of multidisciplinary post COVID-19 clinics 10 .
Estimates of the burden of individual sequela by age, race, sex, and baseline health status suggest a more nuanced picture in that the burden of some sequela was more pronounced in younger adults (e.g. sleep disorders, headache, mood disorders, and smell problems), Black participants (e.g. new onset diabetes mellitus, chest pain, substance abuse, thromboembolism, headache, and tachycardia), females (e.g. chest pain, arrythmias, headache, smell problems, hair loss, and skin rash). These estimates provide insights into the long-term health consequences of COVID-19 and suggest that PASC is a complex nonmonolithic entity that may manifest differently in various population groups.
PASC is a multifaceted entity with broad symptomatology and clinical abnormalities spanning multiple organ system. To date, there is no clear unifying hypothesis for a mechanism that explains the myriad sequelae of post-acute COVID-19. Some of post-acute clinical manifestations may be a direct result of some acute clinical manifestations that morphed into subacute and chronic conditions. It is also possible that some sequelae may be due to the immune response to the initial infection (e.g. through hyperactivated immune response and autoimmunity or persistence of the virus in immune privileged sites 13 . Lessons learned from prior natural disasters and previous pandemics also suggest the putative presence of indirect effects including changes in the broader contextual environment, social (e.g. isolation, quarantine, reduced social contact and loneliness), economic (e.g. nancial distress due to complete loss or reduced income), and behavioral conditions (e.g. changes in dietary habits and physical activity), lived experiences of trauma and grief (from pandemic related happenings) that may be differentially experienced by people with COVID-19 may also shape health outcomes in COVID-19 survivors [14][15][16][17][18][19] . A better understanding of the biologic mechanisms and pathophysiology of PASC will facilitate the development of treatment strategies to lessen the burden of chronic illness and reduce permanent health loss and mortality among people with PASC.
Here we use the term "PASC" to denote the consequences of post-covid in excess of what can be ascertained in the control group; while this de nition is epidemiologically useful to estimate burden of disease, a clinical de nition is needed to guide diagnosis and treatment 20 . Other terms used in the literature include "long COVID-19", "post-COVID-19 syndrome" and "post-acute COVID-19 syndrome", and people with symptoms and clinical manifestations beyond the acute phase have been referred to in the lay vernacular as "long haulers" 3 . We recognize that this matter is subject to intense research by the scienti c community and patient groups with lived experiences of post COVID-19 who hold a broad range of views regarding these terminologies 12,20−22 . Identi cation of scienti cally accurate de nitions and culturally sensitive terms to describe the illness beyond the acute phase will be an important step not only to standardize scienti c communications globally but also to support clear and consistent public health messaging about the long-term consequences of COVID-19 20 .
The study has several strengths. We used the vast electronic health databases of the US Department of Veterans Affairs national health care databases -the largest nationally integrated healthcare delivery system in the US -to estimate burden of overall PASC and its individual sequelae by age, race, sex, and baseline health status. We comprehensively examined 33 sequelae which were de ned based on integrated data from multiple sources including diagnostic codes, medications, and laboratory test results. The simultaneous examination of incident sequelae in the same analytic framework allows the comparative evaluation of risks and burdens of these conditions -providing health care providers, health system planners, public health o cials, and the public at large with a priority list of the post-acute clinical conditions encountered in COVID-19 survivors. For each outcome examined, we built a cohort free of the related outcome at baseline to identify the risk of incident outcome during follow up -this approach allows the identi cation of incident clinical manifestations and abnormalities following COVID-19 infection. While we conducted survival analyses to estimate the risk of each outcome examined, we -for each outcome -also estimated the excess burden per 1000 persons due to COVID-19; this measure of risk on the absolute scale also considers the baseline risk and provides a more meaningful estimate of potential harm and can be more effectively communicated to the wider public than measures of relative risks (e.g. hazard ratio).
This study has several limitations. Our approach does not provide mechanistic insights into PASC nor does it delineate the sequelae that are direct or indirect consequences of the COVID-19 infection. Because of the predominantly male composition of the VA population, our ndings may not identify clinical manifestations of post-acute COVID-19 that may be differentially much more pronounced in females and either non-expressed or rare in males. Finally, COVID-19 patients were enrolled in our cohorts from March 01 to March 15, 2021 and followed until May 01, 2021; as the COVID-19 global pandemic continues to evolve, and as treatment strategies improve, new variants of the virus emerge, and vaccine availability increases, it is likely that the epidemiology, short term, and long term outcomes of COVID-19 will likely also change over time.
In conclusion, we estimate that burden of PASC is around 7%; while the burden of PASC increased according to the severity of the care setting of the acute COVID-19 infection, it was not trivial (4.4%) among those who were not hospitalized for acute COVID-19. Our results also show that PASC is not monolithic; the burden of its individual components may be differentially expressed in various population groups. Together, the estimates provided here suggest that the toll of morbidity of COVID-19 is extends well beyond the acute phase. While, optimism is rising that -as vaccine availability increases -the pandemic may soon be behind us, the focus on the immediate health effects of COVID-19 allows visibility of the tip of the iceberg. The long-term consequences of COVID-19 -as evidenced in our work -are substantial and will reverberate for a long time after the surges in acute infections abate. Long COVID (or as we refer to it in this work PASC) is a complex multifaceted non-monolithic post-viral syndrome; it demands greater attention and a coordinated long-term global response strategy.

Setting:
The study utilized the VA electronic health care databases. The VA provides health care to US Veterans and operates the largest national integrated healthcare system in the United States with 1,255 health care facilities, including 170 VA medical centers and 1,074 outpatient sites located across the United States. Veterans enrolled have access to the Department of Veterans Affairs comprehensive medical bene ts package including inpatient hospital care; outpatient services; preventive, primary, and specialty care; prescriptions; mental healthcare; home healthcare; geriatric and extended care; medical equipment; and prosthetics. VA electronic health care databases are update daily. Negative outcome controls: The use of negative controls in observational studies may help detect the presence of both suspected and unsuspected spurious biases; the application of negative controls will test if shared biases in outcome ascertainment, residual confounding, analytic approach, or other latent biases might have in uenced the results 31,32 . Here we followed the approach outlined by Lipsitch and collaborators to test accidental injuries and neoplasms as negative outcome controls 31 , where based on current knowledge, we would expect no association between COVID-19 infection and these 2 negative outcome controls.

Post-acute sequelae of COVID-19
We examined a set of 33 post-acute COVID-19 outcomes; these outcomes were selected based on prior studies 1,33 , review of the literature 2,3 , and the most recent US National Institute of Health workshop on PASC. Outcomes were de ned based on ICD10 codes recorded from inpatient or outpatient encounters, medication records, or laboratory tests when appropriate using de nitions validated for use with electronic health records [33][34][35][36][37][38][39][40][41][42][43][44] . Detailed de nitions of the outcomes are presented in Supplementary table 11. Cardiovascular outcomes included acute coronary disease, arrythmias, bradycardia, chest pain, heart failure, myocarditis and tachycardia; coagulation outcomes included thromboembolism; dermatologic outcome included hair loss and skin rash; endocrine outcome included diabetes mellitus, hyperlipidemia and obesity; gastrointestinal outcome included constipation, diarrhea and GERD, general outcome include fatigue; kidney outcome include acute kidney injury and chronic kidney disease; mental health outcome included anxiety, depression, mood disorder, sleep disorder and substance abuse; musculoskeletal outcome included joint pain and muscle weakness; neurologic outcome included headache, memory problems, smell problems and stroke; pulmonary outcome included cough, hypoxemia and shortness of breath. Occurrence of incident clinical manifestation was de ned as the occurrence of a manifestation that did not occur within past one year before cohort enrollment. PASC was de ned as the presence of at least one incident clinical manifestation in excess of the non-infected controls. Covariates: Covariates for analyses included age, race (White, Black, and Other), sex, receipt of long-term care, Area Deprivation Index based on patient addresses and proxies of healthcare utilization such as number of outpatient encounters, number of hospital admissions, number of outpatient prescriptions and number of outpatient serum creatinine measurements in the year before enrollment. We also included comorbidities such as chronic lung disease, cancer, cardiovascular disease, cerebrovascular disease, dementia, diabetes mellitus, hypertension, hyperlipidemia, depression, anxiety, chronic kidney disease, hepatitis C and peripheral artery disease. In addition, covariates included overweight, obesity, smoking status (never, former, and current) and the Charlson comorbidity index were also adjusted for. We also adjusted for US geographic region (West, Mid-west, South and Northeast) where the care was received, and additional health system characteristics including total number of beds, number of COVID-19 tests administered, COVID-19 positivity rate, and average hospital bed occupancy during the week of participant enrollment.

Statistical analyses:
Characteristics of the VHA users without COVID-19, and those with COVID-19 according to care setting of the acute infection (non-hospitalized, hospitalized, and admitted to intensive care) were described.
Excess burden of PASC, de ned as having at least one sequela in excess of VHA users without COVID-19, was estimated using Poisson regressions, where burden was de ned as the number of incident sequelae occurring during follow-up. The excess burdens of having 1, 2, to 33 PASC at 6 months, as well as the total excess number of PASC, were estimated in the overall cohort and by care setting of the acute infection.
We then estimated the excess burden of incident individual sequela. For each outcome examined, we built a cohort of participants without a history of the outcome. Cox models adjusting for covariates were used to estimate the hazard ratio of each COVID-19 care setting compared to VHA users, and the survival probability for the 4 groups at 6 months. Cause speci c hazard models were used where occurrence of death was considered as competing risk during the analyses. Excess burden per 1000 patients at 6 months were computed as the difference in survival probability between each COVID-19 care setting and the VHA users. Burden of outcomes in the overall COVID-19 population was computed as the weighted sum of the burden of the three care settings based on the proportion of COVID-19 patients in each care setting. Analyses were also conducted to estimate the excess burden within subgroups by age, race, sex, and baseline health status. Burden differences between subgroups of age≤60 and >70, Black and White, female and male, and 0 and >3 comorbidity score were then estimated.
All analyses were done using SAS Enterprise Guide version 7.

Declarations
Data availability: The data that support the ndings of this study are available from the US Department of Veterans Affairs.
Code Availability: All SAS and R programing codes will be made available upon request.
Acknowledgements: This study used data from the VA COVID-19 Shared Data Resource.
Author Contributions: ZAA and YX contributed to the development of the study concept and design. ZAA and YX contributed to data analysis. ZAA and YX contributed to interpretation of results. ZAA and YX drafted the manuscript. ZAA, YX, and BB contributed to critical revision of the manuscript. ZAA provided administrative, technical, and material support, as well as supervision and mentorship. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. All authors approved the nal version of the report. The corresponding author attests that all the listed authors meet the authorship criteria and that no others meeting the criteria have been omitted. follow-up. Estimates of burdens per 1000 COVID-19 patients and 95% con dence intervals at 6-months are presented.

Figure 2
Burden of Post-acute Sequelae of COVID-19 as a function of the number of sequelae. a) overall cohort, and b) by care setting (non-hospitalized, hospitalized, and admitted to intensive care during the acute phase of the infection). Post-acute sequalae were ascertained from 30 days after infection until end of follow-up. Estimates of burdens per 1000 COVID-19 patients and 95% con dence intervals at 6-months are presented.

Figure 3
Differences in burden of individual Post-acute Sequelae of COVID-19 by age, race, sex, and health status.
Differences in burden per 1000 COVID-19 patients and 95% con dence intervals at 6-months are presented.