Higher hospitalization and mortality rates among SARS-CoV-2-infected persons in rural America

Vaccination status and disease severity of COVID-19 in different phases of the pandemic

This study aimed to explore the clinical profile and the impact of vaccination status on various health outcomes among COVID-19 patients diagnosed in different phases of the pandemic, during which several variants of concern (VOCs) circulated in South Carolina (SC). The current study included 861,526 adult COVID-19 patients diagnosed between January 2021 and April 2022. We extracted their information about demographic characteristics, vaccination, and clinical outcomes from a statewide electronic health record database. Multiple logistic regression models were used to compare clinical outcomes by vaccination status in different pandemic phases, accounting for key covariates (e.g. historical comorbidities). A reduction in mortality was observed among COVID-19 patients during the whole study period, although there were fluctuations during the Delta and Omicron dominant periods. Compared to non-vaccinated patients, full-vaccinated COVID-19 patients had lower mortality in all dominant variants, including Pre-alpha (adjusted odds ratio [aOR]: 0.33; 95%CI: 0.15-0.72), Alpha (aOR: 0.58; 95%CI: 0.42-0.82), Delta (aOR: 0.28; 95%CI: 0.25-0.31), and Omicron (aOR: 0.29; 95%CI: 0.26-0.33) phases. Regarding hospitalization, full-vaccinated parties showed lower risk of hospitalization than non-vaccinated patients in Delta (aOR: 0.44; 95%CI: 0.41-0.47) and Omicron (aOR: 0.53; 95%CI: 0.50-0.57) dominant periods. The findings demonstrated the protection effect of the COVID-19 vaccines against all VOCs, although some of the full-vaccinated population still have symptoms to varying degrees from COVID-19 disease at different phases of the pandemic.

Prediction models for COVID-19 disease outcomes

SARS-CoV-2 has caused over 6.9 million deaths and continues to produce lasting health consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective cross-sectional study, we developed personalized risk assessment models that predict clinical outcomes for individuals with COVID-19 and inform targeted interventions. We sequenced viruses from SARS-CoV-2-positive nasopharyngeal swab samples between July 2020 and July 2022 from 4450 individuals in Missouri and retrieved associated disease courses, clinical history, and urban-rural classification. We integrated this data to develop machine learning-based predictive models to predict hospitalization, ICU admission, and long COVID.The mean age was 38.3 years (standard deviation = 21.4) with 55.2% (N = 2453) females and 44.8% (N = 1994) males (not reported, N = 4). Our analyses revealed a comprehensive set of predictors for each outcome, encompassing human, environment, and virus genome-wide genetic markers. Immunosuppression, cardiovascular disease, older age, cardiac, gastrointestinal, and constitutional symptoms, rural residence, and specific amino acid substitutions were associated with hospitalization. ICU admission was associated with acute respiratory distress syndrome, ventilation, bacterial co-infection, rural residence, and non-wild type SARS-CoV-2 variants. Finally, long COVID was associated with hospital admission, ventilation, and female sex.Overall, we developed risk assessment models that offer the capability to identify patients with COVID-19 necessitating enhanced monitoring or early interventions. Of importance, we demonstrate the value of including key elements of virus, host, and environmental factors to predict patient outcomes, serving as a valuable platform in the field of personalized medicine with the potential for adaptation to other infectious diseases.

Associations between COVID-19 therapies and outcomes in rural and urban America: A multisite, temporal analysis from the Alpha to Omicron SARS-CoV-2 variants

PURPOSE

To investigate the enduring disparities in adverse COVID-19 events between urban and rural communities in the United States, focusing on the effects of SARS-CoV-2 vaccination and therapeutic advances on patient outcomes.

METHODS

Using National COVID Cohort Collaborative (N3C) data from 2021 to 2023, this retrospective cohort study examined COVID-19 hospitalization, inpatient death, and other adverse events. Populations were categorized into urban, urban-adjacent rural (UAR), and nonurban-adjacent rural (NAR). Adjustments included demographics, variant-dominant waves, comorbidities, region, and SARS-CoV-2 treatment and vaccination. Statistical methods included Kaplan-Meier survival estimates, multivariable logistic, and Cox regression.

FINDINGS

The study included 3,018,646 patients, with rural residents constituting 506,204. These rural dwellers were older, had more comorbidities, and were less vaccinated than their urban counterparts. Adjusted analyses revealed higher hospitalization odds in UAR and NAR (aOR 1.07 [1.05-1.08] and 1.06 [1.03-1.08]), greater inpatient death hazard (aHR 1.30 [1.26-1.35] UAR and 1.37 [1.30-1.45] NAR), and greater risk of other adverse events compared to urban dwellers. Delta increased, while Omicron decreased, inpatient adverse events relative to pre-Delta, with rural disparities persisting throughout. Treatment effectiveness and vaccination were similarly protective across all cohorts, but dexamethasone post-ventilation was effective only in urban areas. Nirmatrelvir/ritonavir and molnupiravir better protected rural residents against hospitalization.

CONCLUSIONS

Despite advancements in treatment and vaccinations, disparities in adverse COVID-19 outcomes persist between urban and rural communities. The effectiveness of some therapeutic agents appears to vary based on rurality, suggesting a nuanced relationship between treatment and geographic location while highlighting the need for targeted rural health care strategies.

Effects of rurality and distance to care on perinatal outcomes over a 1-year period during the COVID-19 pandemic

PURPOSE

Our aim was to investigate the roles of rurality and distance to care on adverse perinatal outcomes and COVID-19 seroprevalence at the time of delivery over a 1-year period.

METHODS

Data were collected from the electronic medical record on all pregnant patients who delivered at a single, large, Midwest academic medical center over 1 year. Rurality was classified using standard Rural-Urban Commuting Area codes. Geographic Information System tools were used to map outcomes. Data were analyzed with univariate and multivariate models, controlling for Body Mass Index (BMI), insurance status, and parity.

FINDINGS

A total of 2,497 patients delivered during the study period; 20% of patients were rural (n = 499), 18.6% were micropolitan (n = 466), and 61.4% were metropolitan (n = 1,532). 10.4% of patients (n = 259) were COVID-19 seropositive. Rural patients did not experience higher rates of any measured adverse outcomes than metropolitan patients; micropolitan patients had increased odds of preterm labor (OR = 1.41, P = .022) and pre-eclampsia (OR = 1.78, P<.001). Patients living 30+ miles away from the medical center had increased odds of preterm labor (OR = 1.94, P<.001), pre-eclampsia (OR = 1.73, P = .002), and infant admission to the neonatal intensive care unit (OR = 2.12, P<.001), as well as lower gestational age at delivery (β = -9.2 days, P<.001) and birth weight (β = -206 grams, P<.001).

CONCLUSION

Distance to care, rather than rurality, was the key predictor of multiple adverse perinatal outcomes in this cohort of deliveries over a 1-year period. Our study suggests that rurality should not be used as a standalone indicator of access to care without further knowledge of the specific barriers affecting a given population.

Rural-urban Differences in Long-term Mortality and Readmission Following COVID-19 Hospitalization, 2020 to 2023

Background

We compared long-term mortality and readmission rates after COVID-19 hospitalization based on rural-urban status and assessed the impact of COVID-19 vaccination introduction on clinical outcomes by rurality.

Methods

The study comprised adults hospitalized for COVID-19 at 17 hospitals in 4 US states between March 2020 and July 2022, followed until May 2023. The main analysis included all patients, whereas a sensitivity analysis focused on residents from 4 states containing 17 hospitals. Additional analyses compared the pre- and postvaccination periods.

Results

The main analysis involved 9325 COVID-19 hospitalized patients: 31% were from 187 rural counties in 31 states; 69% from 234 urban counties in 44 states; the mean age was 65 years (rural, 66 years; urban, 64 years); 3894 women (rural, 41%; urban, 42%); 8007 Whites (rural, 87%; urban, 83%); 1738 deaths (rural, 21%; urban, 17%); and 2729 readmissions (rural, 30%; urban, 29%). During a median follow-up of 602 days, rural residence was associated with a 22% higher all-cause mortality (log-rank, P < .001; hazard ratio, 1.22; 95% confidence interval, 1.10-1.34, P < .001), and a trend toward a higher readmission rate (log-rank, P = .038; hazard ratio, 1.06; 95% confidence interval, .98-1.15; P = .130). The results remained consistent in the sensitivity analysis and in both pre- and postvaccination time periods.

Conclusions and Relevance

Patients from rural counties experienced higher mortality and tended to be readmitted more frequently following COVID-19 hospitalization over the long term compared with those from urban counties, a difference that remained even after the introduction of COVID-19 vaccines.

Newborn Hospitalizations Before and During COVID-19 Pandemic in Poland: A Comparative Study Based on a National Hospital Registry

Objectives: There are limited data on the impact of the COVID-19 outbreak in Poland on newborn health. The aim of the study is to show recent information on hospitalizations of newborns in Poland in the pre-pandemic and COVID-19 pandemic era. Methods: A retrospective, population-based study was conducted using data from hospital discharge records of patients hospitalized in 2017-2021. Results: The data on which the study was based consisted of a substantial number of 104,450 hospitalization records. Annual hospitalization rate was estimated to be 50.3-51.9 per 1,000 in 2017-2019, 56 per 1,000 in 2020 and it rose to 77.7 per 1,000 in 2021. In comparison to the pre-pandemic period, in the COVID-19 era, we observed significantly more hospitalization cases of newborns affected by maternal renal and urinary tract diseases (p < 0.001), syndrome of infant of mother with gestational diabetes (p < 0.001), maternal complications of pregnancy (p < 0.001). In the COVID-19 era, the prevalence of COVID-19 among newborns was 4.5 cases per 1,000 newborn hospitalizations. Conclusion: The COVID-19 pandemic outbreak could significantly contribute to qualitative and quantitative changes in hospitalizations among newborns.

Rural populations facilitated early SARS-CoV-2 evolution and transmission in Missouri, USA

In the United States, rural populations comprise 60 million individuals and suffered from high COVID-19 disease burdens. Despite this, surveillance efforts are biased toward urban centers. Consequently, how rurally circulating SARS-CoV-2 viruses contribute toward emerging variants remains poorly understood. In this study, we aim to investigate the role of rural communities in the evolution and transmission of SARS-CoV-2 during the early pandemic. We collected 544 urban and 435 rural COVID-19-positive respiratory specimens from an overall vaccine-naïve population in Southwest Missouri between July and December 2020. Genomic analyses revealed 53 SARS-CoV-2 Pango lineages in our study samples, with 14 of these lineages identified only in rural samples. Phylodynamic analyses showed that frequent bi-directional diffusions occurred between rural and urban communities in Southwest Missouri, and that four out of seven Missouri rural-origin lineages spread globally. Further analyses revealed that the nucleocapsid protein (N):R203K/G204R paired substitutions, which were detected disproportionately across multiple Pango lineages, were more associated with urban than rural sequences. Positive selection was detected at N:204 among rural samples but was not evident in urban samples, suggesting that viruses may encounter distinct selection pressures in rural versus urban communities. This study demonstrates that rural communities may be a crucial source of SARS-CoV-2 evolution and transmission, highlighting the need to expand surveillance and resources to rural populations for COVID-19 mitigation.

The rural mortality penalty in U.S. hospital patients with COVID-19

Background

The COVID-19 pandemic brought greater focus to the rural mortality penalty in the U.S., which describes the greater mortality rate in rural compared to urban areas. Although it is understood that issues such as access to care, age structure of the population, and differences in behavior are likely drivers of the rural mortality penalty, it is critical to try and understand these factors to enable more effective public health policy.

Methods

We performed a cross-sectional analysis of a population of patients with COVID-19 who were admitted to hospitals in the United States between 3/1/2020 and 2/26/2023 to better understand factors leading to outcome disparities amongst groups that all had some level of access to hospital care, hypothesizing that deteriorated patient condition at admission likely explained some of the observed difference in mortality between rural and urban populations.

Results

Our results supported our hypothesis, showing that the rural mortality penalty persists in this population and that by multiple measures, rural patients were likely to be admitted in worse condition, had worse overall health, and were older.

Conclusions

Although the pandemic threw the rural mortality penalty into sharp relief, it is important to remember that it existed prior to the pandemic and will continue to exist until effective interventions are implemented. This study demonstrates the critical need to address the underlying factors that resulted in rural-dwelling patients being admitted to the hospital in worse condition than their urban-dwelling counterparts during the COVID-19 pandemic, which likely affected other healthcare outcomes as well.

Nationwide Genomic Surveillance and Response to COVID-19: The VA SeqFORCE and SeqCURE Consortiums

Background

The US Department of Veterans Affairs (VA) has dedicated significant resources toward countering the COVID-19 pandemic. Sequencing for Research Clinical and Epidemiology (SeqFORCE) and Sequencing Collaborations United for Research and Epidemiology (SeqCURE) were developed as clinical and research consortiums, respectively, focused on the genetic COVID-19 surveillance.

Observations

Through genetic sequencing, VA SeqFORCE and SeqCURE collaborations contributed to the COVID-19 pandemic response and scientific understanding. Future directions for each program include the assessment of the unique impact of COVID-19 on the veteran population, as well as the adaptation of these programs to future infectious disease threats. We foresee the use of these established platforms beyond infectious diseases.

Conclusions

VA SeqFORCE and SeqCURE were established as clinical and research programs dedicated to sequencing COVID-19 as part of ongoing clinical and surveillance efforts. In the future, we anticipate that having these programs embedded within the largest integrated health care system in the US will enable the study of pathogens and pandemics beyond COVID-19 and at an unprecedented scale. The investment in these programs will form an integral part of our nation's response to emerging infectious diseases, with future applications to precision medicine and beyond.

Dynamics of SARS-CoV-2 Seroprevalence in a Large US population Over a Period of 12 Months

Due to a combination of asymptomatic or undiagnosed infections, the proportion of the United States population infected with SARS-CoV-2 was unclear from the beginning of the pandemic. We previously established a platform to screen for SARS-CoV-2 positivity across a representative proportion of the US population, from which we reported that almost 17 million Americans were estimated to have had undocumented infections in the Spring of 2020. Since then, vaccine rollout and prevalence of different SARS-CoV-2 variants have further altered seropositivity trends within the United States population. To explore the longitudinal impacts of the pandemic and vaccine responses on seropositivity, we re-enrolled participants from our baseline study in a 6- and 12- month follow-up study to develop a longitudinal antibody profile capable of representing seropositivity within the United States during a critical period just prior to and during the initiation of vaccine rollout. Initial measurements showed that, since July 2020, seropositivity elevated within this population from 4.8% at baseline to 36.2% and 89.3% at 6 and 12 months, respectively. We also evaluated nucleocapsid seropositivity and compared to spike seropositivity to identify trends in infection versus vaccination relative to baseline. These data serve as a window into a critical timeframe within the COVID-19 pandemic response and serve as a resource that could be used in subsequent respiratory illness outbreaks.

Rural-Urban Disparities in Hospital Admissions and Mortality Among Patients with COVID-19: Evidence from South Carolina from 2021 to 2022

Although rural communities have been hard-hit by the COVID-19 pandemic, there is limited evidence on COVID-19 outcomes in rural America using up-to-date data. This study aimed to estimate the associations between hospital admissions and mortality and rurality among COVID-19 positive patients who sought hospital care in South Carolina. We used all-payer hospital claims, COVID-19 testing, and vaccination history data from January 2021 to January 2022 in South Carolina. We included 75,545 hospital encounters within 14 days after positive and confirmatory COVID-19 testing. Associations between hospital admissions and mortality and rurality were estimated using multivariable logistic regressions. About 42% of all encounters resulted in an inpatient hospital admission, while hospital-level mortality was 6.3%. Rural residents accounted for 31.0% of all encounters for COVID-19. After controlling for patient-level, hospital, and regional characteristics, rural residents had higher odds of overall hospital mortality (Adjusted Odds Ratio - AOR = 1.19, 95% Confidence Intervals - CI = 1.04-1.37), both as inpatients (AOR = 1.18, 95% CI = 1.05-1.34) and as outpatients (AOR = 1.63, 95% CI = 1.03-2.59). Sensitivity analyses using encounters with COVID-like illness as the primary diagnosis only and encounters from September 2021 and beyond - a period when the Delta variant was dominant and booster vaccination was available - yielded similar estimates. No significant differences were observed in inpatient hospitalizations (AOR = 1.00, 95% CI = 0.75-1.33) between rural and urban residents. Policymakers should consider community-based public health approaches to mitigate geographic disparities in health outcomes among disadvantaged population subgroups.

COVID-19 vaccination willingness and uptake among rural Black/African American, Latino, and White adults

PURPOSE

The purpose of this study was to assess differences in COVID-19 vaccine willingness and uptake between rural and nonrural adults, and within rural racial-ethnic groups.

METHODS

We utilized data from the COVID-19's Unequal Racial Burden online survey, which included 1,500 Black/African American, Latino, and White rural adults (n = 500 each). Baseline (12/2020-2/2021) and 6-month follow-up (8/2021-9/2021) surveys were administered. A cohort of nonrural Black/African American, Latino, and White adults (n = 2,277) was created to compare differences between rural and nonrural communities. Multinomial logistic regression was used to assess associations between rurality, race-ethnicity, and vaccine willingness and uptake.

FINDINGS

At baseline, only 24.9% of rural adults were extremely willing to be vaccinated and 28.4% were not at all willing. Rural White adults were least willing to be vaccinated, compared to nonrural White adults (extremely willing: aOR = 0.44, 95% CI = 0.30-0.64). At follow-up, 69.3% of rural adults were vaccinated; however, only 25.3% of rural adults who reported being unwilling to vaccinate were vaccinated at follow-up, compared to 95.6% of adults who were extremely willing to be vaccinated and 76.3% who were unsure. Among those unwilling to vaccinate at follow-up, almost half reported distrust in the government (52.3%) and drug companies (46.2%); 80% reported that nothing would change their minds regarding vaccination.

CONCLUSIONS

By August 2021, almost 70% of rural adults were vaccinated. However, distrust and misinformation were prevalent among those unwilling to vaccinate at follow-up. To continue to effectively combat COVID-19 in rural communities, we need to address misinformation to increase COVID-19 vaccination rates.

Using wastewater to overcome health disparities among rural residents

The SARS-CoV-2 pandemic highlighted the need for novel tools to promote health equity. There has been a historical legacy around the location and allocation of public facilities (such as health care) focused on efficiency, which is not attainable in rural, low-density, United States areas. Differences in the spread of the disease and outcomes of infections have been observed between urban and rural populations throughout the COVID-19 pandemic. The purpose of this article was to review rural health disparities related to the SARS-CoV-2 pandemic while using evidence to support wastewater surveillance as a potentially innovative tool to address these disparities more widely. The successful implementation of wastewater surveillance in resource-limited settings in South Africa demonstrates the ability to monitor disease in underserved areas. A better surveillance model of disease detection among rural residents will overcome issues around the interactions of a disease and social determinants of health. Wastewater surveillance can be used to promote health equity, particularly in rural and resource-limited areas, and has the potential to identify future global outbreaks of endemic and pandemic viruses.

Occupational COVID-19 Exposures and Illnesses among Workers in California-Analysis of a New Occupational COVID-19 Surveillance System

Little is known about occupational SARS-CoV-2 exposures and COVID-19 outcomes. We established a Doctor's First Reports of Occupational Injury or Illness (DFR)-based surveillance system to study cases of work-related COVID-19 exposures and disease. The surveillance data included demographics, occupation, industry, exposure, and illness, details including hospitalization and lost work. We classified workers into 'healthcare', non-healthcare 'public-facing', or 'other' worker groups, and rural-urban commuting areas (RUCAs). We describe worker exposures and outcomes overall by worker group and RUCA. We analyzed 2848 COVID-19 DFRs representing workers in 22 detailed occupation groups and 19 industry groups. Most DFRs were for workers in metropolitan RUCAs (89%) and those in healthcare (42%) and public-facing (24%) worker groups. While DFRs were from 382 unique worksites, 52% were from four hospitals and one prison. Among 1063 DFRs with a suspected exposure, 73% suspected exposure to a patient or client. Few DFRs indicated hospitalization (3.9%); however, the proportion hospitalized was higher among nonmetropolitan (7.4%) and public-facing (6.7%) workers. While 56% of DFRs indicated some lost work time, the proportion was highest among public-facing (80%) workers. Healthcare and prison workers were the majority of reported occupational COVID-19 exposures and illnesses. The risk of COVID-19 hospitalization and lost work may be highest among nonmetropolitan and public-facing workers.

A review of disparities in peripheral artery disease and diabetes-related amputations during the COVID-19 pandemic

The COVID-19 pandemic has profoundly affected health care delivery. In addition to the significant morbidity and mortality associated with acute illness from COVID-19, the indirect impact has been far-reaching, including substantial disruptions in chronic disease care. As a result of pandemic disruptions in health care, vulnerable and minority populations have faced health inequalities. The aim of this review was to investigate how the COVID-19 pandemic has impacted vulnerable populations with limb-threatening peripheral artery disease and diabetic foot infections.

Sex differences in determinants of COVID-19 severe outcomes - findings from the National COVID Cohort Collaborative (N3C)

OBJECTIVE

The impact of comorbidities and biomarkers on COVID-19 severity vary by sex but have not yet been verified in population-based studies. We examined the association of comorbidities, inflammatory biomarkers, and severe outcomes in men and women hospitalized for COVID-19.

DESIGN

This is a retrospective cohort analysis based on the National COVID Cohort Collaborative (N3C). We included 574,391 adult patients admitted for COVID-19 at hospitals or emergency rooms between 01/01/2020 and 12/31/2021.

METHODS

We defined comorbidities at or before the first admission for COVID-19 by Charlson Comorbidity Index (CCI) and CCI components. We used the averaged lab values taken within 15 days before or after the admission date to measure biomarkers including c-reactive protein (CRP), ferritin, procalcitonin, N-terminal pro b-type natriuretic peptide (NT proBNP), d-dimer, absolute lymphocyte counts, absolute neutrophil counts, and platelets. Our primary outcome was all-cause mortality; secondary outcomes were invasive mechanical ventilation (IMV) and hospital length of stay (LOS). We used logistic regression adjusted for age, race, ethnicity, visit type, and medications to assess the association of comorbidities, biomarkers, and mortality disaggregating by sex.

RESULTS

Moderate to severe liver disease, renal disease, metastatic solid tumor, and myocardial infarction were the top four fatal comorbidities among patients who were hospitalized for COVID-19 (adjusted odds ratio [aOR] > 2). These four comorbid conditions remained the most lethal in both sexes, with a higher magnitude of risk in women than in men (p-interaction < 0.05). Abnormal elevations of CRP, ferritin, procalcitonin, NT proBNP, neutrophil, and platelet counts, and lymphocytopenia were significantly associated with the risk of death, with procalcitonin and NT proBNP as the strongest predictors (aOR > 2). The association between the abnormal biomarkers and death was stronger in women than in men (p-interaction < 0.05).

CONCLUSION

There are sex differences in inpatient mortality associated with comorbidities and biomarkers. The significant impact of these clinical determinants in women with COVID-19 may be underappreciated as previous studies stressed the increased death rate in male patients that is related to comorbidities or inflammation. Our study highlights the importance and the need for sex-disaggregated research to understand the risk factors of poor outcomes and health disparities in COVID-19.