A statewide population-based approach to examining Long COVID symptom prevalence and predictors in Michigan

Minority health social vulnerability index and long COVID illness among a statewide, population-based study of adults with polymerase chain reaction-confirmed SARS-CoV-2

BACKGROUND

The COVID-19 pandemic has disproportionately affected socially vulnerable communities. Some individuals experience persistent symptoms and conditions of COVID-19 illness known as long COVID. As little research has examined how social vulnerability is related to long COVID, we studied this topic using Minority Health Social Vulnerability Index (MHSVI), specifically created for the COVID-19 pandemic in the U.S.

METHODS

We merged county-level MHSVI data with population-based data of Michigan adults with PCR-confirmed SARS-CoV-2 infection between March 2020 and May 2022 based on respondents' county of residence. We examined the relationship between county-level MHSVI (binary: high social vulnerability ≥ 75th percentile) and two long COVID measurements, assessed a median of 18.8 months after their initial infection: (1) ongoing long COVID (yes/no) and (2) long COVID diagnosis (yes/no). We conducted modified Poisson regression models with robust standard errors to estimate prevalence ratio (PR) between associations of MHSVI and long COVID overall and by six MHSVI themes (socioeconomic status, household composition/disability, minority/language, housing type/transportation, healthcare access, medical vulnerability), adjusting for individual-level and county-level covariates.

RESULTS

Living in high MHSVI counties was not associated with ongoing long COVID or long COVID diagnosis. However, the associations differed by theme of MHSVI: respondents in highly socially vulnerable counties assessed by medical vulnerability had 1.32 times higher prevalence of long COVID diagnosis (95% CI:1.12 - 1.57). There were no statistically significant associations in other themes after the adjustment for covariates.

CONCLUSIONS

Our findings suggest the importance of upstream social determinants of health during public health emergencies and provide evidence that medically vulnerable communities need additional public health resources to cope with long COVID among their residents.

Associations Between Acute COVID-19 Symptom Profiles and Long COVID Prevalence: Population-Based Cross-Sectional Study

Background

Growing evidence suggests that severe acute COVID-19 illness increases the risk of long COVID (also known as post-COVID-19 condition). However, few studies have examined associations between acute symptoms and long COVID onset.

Objective

This study aimed to examine associations between acute COVID-19 symptom profiles and long COVID prevalence using a population-based sample.

Methods

We used a dual mode (phone and web-based) population-based probability survey of adults with polymerase chain reaction-confirmed SARS-CoV-2 between June 2020 and May 2022 in the Michigan Disease Surveillance System to examine (1) how acute COVID-19 symptoms cluster together using latent class analysis, (2) sociodemographic and clinical predictors of symptom clusters using multinomial logistic regression accounting for classification uncertainties, and (3) associations between symptom clusters and long COVID prevalence using modified Poisson regression.

Results

In our sample (n=4169), 15.9% (n=693) had long COVID, defined as new or worsening symptoms at least 90 days post SARS-CoV-2 infection. We identified 6 acute COVID-19 symptom clusters resulting from the latent class analysis, with flu-like symptoms (24.7%) and fever (23.6%) being the most prevalent in our sample, followed by nasal congestion (16.4%), multi-symptomatic (14.5%), predominance of fatigue (10.8%), and predominance of shortness of breath (10%) clusters. Long COVID prevalence was highest in the multi-symptomatic (39.7%) and predominance of shortness of breath (22.4%) clusters, followed by the flu-like symptom (15.8%), predominance of fatigue (14.5%), fever (6.4%), and nasal congestion (5.6%) clusters. After adjustment, females (vs males) had greater odds of membership in the multi-symptomatic, flu-like symptom, and predominance of fatigue clusters, while adults who were Hispanic or another race or ethnicity (vs non-Hispanic White) had greater odds of membership in the multi-symptomatic cluster. Compared with the nasal congestion cluster, the multi-symptomatic cluster had the highest prevalence of long COVID (adjusted prevalence ratio [aPR] 6.1, 95% CI 4.3-8.7), followed by the predominance of shortness of breath (aPR 3.7, 95% CI 2.5-5.5), flu-like symptom (aPR 2.8, 95% CI 1.9-4.0), and predominance of fatigue (aPR 2.2, 95% CI 1.5-3.3) clusters.

Conclusions

Researchers and clinicians should consider acute COVID-19 symptom profiles when evaluating subsequent risk of long COVID, including potential mechanistic pathways in a research context, and proactively screen high-risk patients during the provision of clinical care.

Long COVID among US adults from a population-based study: Association with vaccination, cigarette smoking, and the modifying effect of chronic obstructive pulmonary disease (COPD)

OBJECTIVE

Post-COVID Conditions (or Long COVID) have been widely reported, but population-based studies exploring the relationship between its risk factors are lacking. We examined the associations between Long COVID, chronic obstructive pulmonary disease [COPD], vaccination status, and cigarette smoking. We also tested for the modifying effect of COPD status.

METHODS

Data from the 2022 US nationwide Behavioral Risk Factor Surveillance System (BRFSS) were analyzed. Our primary outcome was Long COVID (Yes/No) after a positive COVID-19 diagnosis. Predictor variables were COPD, coronary heart disease (CHD), diabetes, asthma, body mass index, cigarette smoking status, and number of COVID-19 vaccinations (0-4). Weighted multivariable logistic regression models were used and adjusted for sociodemographic factors. Regression models were used to explore the modifying effects of COPD status.

RESULTS

The weighted prevalence of Long COVID among survivors (N = 121,379) was 21.8% (95%CI: 21.4, 22.3), with tiredness/fatigue (26.2% [95%:25.1, 27.2]) as the most common symptom. Respondents with COPD (aOR: 1.71 [95%CI: 1.45, 2.02]), current daily smokers (aOR: 1.23 [95%CI:1.01, 1.49]), and former smokers (aOR: 1.24 [95%CI:1.12, 1.38]) (vs. never established smokers) had higher odds of Long COVID. However, respondents who had received three (aOR: 0.75 [95%CI:0.65, 0.85]) and four (aOR: 0.71 [95%CI:0.58, 0.86]) vaccine doses (vs. no vaccine) had lower odds of Long COVID. COPD had a modifying effect on the relationship between cigarette smoking and Long COVID (p-value: 0.013).

CONCLUSION

Our findings underscore a complex interaction between COPD, cigarette smoking, and Long COVID. Further, COVID-19 vaccination may be protective against Long COVID.

Association between acquiring SARS-CoV-2 during pregnancy and post-acute sequelae of SARS-CoV-2 infection: RECOVER electronic health record cohort analysis

Background

Little is known about post-acute sequelae of SARS-CoV-2 infection (PASC) after acquiring SARS-CoV-2 infection during pregnancy. We aimed to evaluate the association between acquiring SARS-CoV-2 during pregnancy compared with acquiring SARS-CoV-2 outside of pregnancy and the development of PASC.

Methods

This retrospective cohort study from the Researching COVID to Enhance Recovery (RECOVER) Initiative Patient-Centred Clinical Research Network (PCORnet) used electronic health record (EHR) data from 19 U.S. health systems. Females aged 18-49 years with lab-confirmed SARS-CoV-2 infection from March 2020 through June 2022 were included. Validated algorithms were used to identify pregnancies with a delivery at >20 weeks' gestation. The primary outcome was PASC, as previously defined by computable phenotype in the adult non-pregnant PCORnet EHR dataset, identified 30-180 days post-SARS-CoV-2 infection. Secondary outcomes were the 24 component diagnoses contributing to the PASC phenotype definition. Univariable comparisons were made for baseline characteristics between individuals with SARS-CoV-2 infection acquired during pregnancy compared with outside of pregnancy. Using inverse probability of treatment weighting to adjust for baseline differences, the association between SARS-CoV-2 infection acquired during pregnancy and the selected outcomes was modelled. The incident risk is reported as the adjusted hazard ratio (aHR) with 95% confidence intervals.

Findings

In total, 83,915 females with SARS-CoV-2 infection acquired outside of pregnancy and 5397 females with SARS-CoV-2 infection acquired during pregnancy were included in analysis. Non-pregnant females with SARS-CoV-2 infection were more likely to be older and have comorbid health conditions. SARS-CoV-2 infection acquired in pregnancy as compared with acquired outside of pregnancy was associated with a lower incidence of PASC (25.5% vs 33.9%; aHR 0.85, 95% CI 0.80-0.91). SARS-CoV-2 infection acquired in pregnant females was associated with increased risk for some PASC component diagnoses including abnormal heartbeat (aHR 1.67, 95% CI 1.43-1.94), abdominal pain (aHR 1.34, 95% CI 1.16-1.55), and thromboembolism (aHR 1.88, 95% CI 1.17-3.04), but decreased risk for other diagnoses including malaise (aHR 0.35, 95% CI 0.27-0.47), pharyngitis (aHR 0.36, 95% CI 0.26-0.48) and cognitive problems (aHR 0.39, 95% CI 0.27-0.56).

Interpretation

SARS-CoV-2 infection acquired during pregnancy was associated with lower risk of development of PASC at 30-180 days after incident SARS-CoV-2 infection in this nationally representative sample. These findings may be used to counsel pregnant and pregnant capable individuals, and direct future prospective study.

Funding

National Institutes of Health (NIH) Other Transaction Agreement (OTA) OT2HL16184.

Prevalence and Predictors of Post-Acute COVID-19 Symptoms in Italian Primary Care Patients

BACKGROUND

Despite all the progress in the management of acute COVID-19, it is still not clear why some people continue to experience symptoms after recovery. Using data from a self-administered online survey, we assessed the prevalence and predictors of post-acute COVID-19 in an unselected population followed by GPs.

METHODS

Patients ≥18 years with a confirmed COVID-19 diagnosis were included. The survey collected information on demographics, risk factors, COVID-19 course and symptomatology. Fatigue and Quality of Life questionnaires were also administered. Descriptive statistics were used to describe patients' characteristics, stratified as acute and post-acute COVID-19. Logistic regression models were used to assess the association between clinical characteristics and post-acute COVID-19.

RESULTS

A total of 1108 surveys were analyzed. Nearly 29% of patients reported post-acute COVID-19. The more persistent symptoms were fatigue, memory and concentration impairment. Adjusted Odds Ratio (OR) showed a significantly higher probability of post-acute COVID-19 for women compared to men (OR 1.9, 95% CI 1.4-2.5), for age >50 years than ≤50 years (OR 1.6, 95% CI 1.2-2.2), for BMI > 25 compared to BMI ≤ 25 (OR 1.6, 95% CI 1.1-2.1) and those with autoimmune diseases, compared to those without (OR 1.8 95% CI 1.1-2.9). In addition, a significant association was found with COVID-19 hospitalization, anxiety and allergies. We found that post-acute COVID-19 patients showed a higher fatigue and a worst quality of life.

CONCLUSIONS

These findings suggest the need for tailored personalized strategies to improve the management of patients with post-acute COVID-19.