Facilitators of Organizational Resilience Within South Carolina AIDS Service Organizations: Lessons Learned from the COVID-19 Pandemic.

HIV care services have been interrupted by the COVID-19 pandemic in many states in the U.S. including South Carolina (SC). However, many HIV care facilities demonstrated organizational resilience (i.e., the ability to maintain needed health services amid rapidly changing circumstances) by addressing challenges to maintaining care during the pandemic. This study, therefore, aims to identify key facilitators for organizational resilience among AIDS Services Organizations (ASOs) in SC. In-depth interviews were conducted among 11 leaders, from 8 ASOs, across SC during the summer of 2020. The interviews were recorded after receiving proper consent and then transcribed. Utilizing a codebook based upon the interview guide, a thematic analysis approach was utilized to analyze the data. All data management and analysis were conducted in NVivo 11.0. Our findings demonstrate several facilitators of organizational resilience, including (1) accurate and timely crisis information dissemination; (2) clear and preemptive protocols; (3) effective healthcare system policies, management, and leadership; (4) prioritization of staff psychological wellbeing; (5) stable access to personal protective equipment (PPE); (6) adequate and flexible funding; and (7) infrastructure that supports telehealth. Given the facilitators of organizational resilience among ASOs in SC during the COVID-19 pandemic, it is recommended that organizations implement and maintain coordinated and informed responses based upon preemptive protocols and emerging needs. ASO funders are encouraged to allow a flexibility in spending. The lessons learned from the participating leaders enable ASOs to develop and strengthen their organizational resilience and experience fewer disruptions in the future.

Impact of HIV on COVID-19 Outcomes: A Propensity Score Matching Analysis with Varying Age Differences.

To exploratorily test (1) the impact of HIV and aging process among PLWH on COVID-19 outcomes; and (2) whether the effects of HIV on COVID-19 outcomes differed by immunity level. The data used in this study was retrieved from the COVID-19 positive cohort in National COVID Cohort Collaborative (N3C). Multivariable logistic regression models were conducted on populations that were matched using either exact matching or propensity score matching (PSM) with varying age difference between PLWH and non-PLWH to examine the impact of HIV and aging process on all-cause mortality and hospitalization among COVID-19 patients. Subgroup analyses by CD4 counts and viral load (VL) levels were conducted using similar approaches. Among the 2,422,864 adults with a COVID-19 diagnosis, 15,188 were PLWH. PLWH had a significantly higher odds of death compared to non-PLWH until age difference reached 6 years or more, while PLWH were still at an elevated risk of hospitalization across all matched cohorts. The odds of both severe outcomes were persistently higher among PLWH with CD4 < 200 cells/mm3. VL ≥ 200 copies/ml was only associated with higher hospitalization, regardless of the predefined age differences. Age advancement in HIV might significantly contribute to the higher risk of COVID-19 mortality and HIV infection may still impact COVID-19 hospitalization independent of the age advancement in HIV.

Protocol for developing a personalised prediction model for viral suppression among under-represented populations in the context of the COVID-19 pandemic.

INTRODUCTION: Sustained viral suppression, an indicator of long-term treatment success and mortality reduction, is one of four strategic areas of the 'Ending the HIV Epidemic' federal campaign launched in 2019. Under-represented populations, like racial or ethnic minority populations, sexual and gender minority groups, and socioeconomically disadvantaged populations, are disproportionately affected by HIV and experience a more striking virological failure. The COVID-19 pandemic might magnify the risk of incomplete viral suppression among under-represented people living with HIV (PLWH) due to interruptions in healthcare access and other worsened socioeconomic and environmental conditions. However, biomedical research rarely includes under-represented populations, resulting in biased algorithms. This proposal targets a broadly defined under-represented HIV population. It aims to develop a personalised viral suppression prediction model using machine learning (ML) techniques by incorporating multilevel factors using All of Us (AoU) data. METHODS AND ANALYSIS: This cohort study will use data from the AoU research programme, which aims to recruit a broad, diverse group of US populations historically under-represented in biomedical research. The programme harmonises data from multiple sources on an ongoing basis. It has recruited ~4800 PLWH with a series of self-reported survey data (eg, Lifestyle, Healthcare Access, COVID-19 Participant Experience) and relevant longitudinal electronic health records data. We will examine the change in viral suppression and develop personalised viral suppression prediction due to the impact of the COVID-19 pandemic using ML techniques, such as tree-based classifiers (classification and regression trees, random forest, decision tree and eXtreme Gradient Boosting), support vector machine, naïve Bayes and long short-term memory. ETHICS AND DISSEMINATION: The institutional review board approved the study at the University of South Carolina (Pro00124806) as a Non-Human Subject study. Findings will be published in peer-reviewed journals and disseminated at national and international conferences and through social media.

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.

Incidence of Chronic Kidney Disease Following Acute Coronavirus Disease 2019 Based on South Carolina Statewide Data.

BACKGROUND: Coronavirus disease 2019 (COVID-19) was associated with severe acute illness including multiple organ failure. Acute kidney injury (AKI) was a common finding, often requiring dialysis support. OBJECTIVE: Define the incidence of new clinically identified chronic kidney disease (CKD) among patients with COVID-19 and no pre-existing kidney disease. DESIGN PARTICIPANTS: The South Carolina (SC) Department of Health and Environmental Control (DHEC) COVID-19 mandatory reporting registry of SC residents testing for COVID-19 between March 2020 and October 2021 was included. DESIGN MAIN MEASURES: The primary outcome was a new incidence of a CKD diagnosis (N18.x) in those without a pre-existing diagnosis of CKD during the follow-up period of March 2020 to January 14, 2022. Patients were stratified by severity of illness (hospitalized or not, intensive care unit needed or not). The new incidence of CKD diagnosis was examined using logistic regression and cox proportional hazards analyses. KEY RESULTS: Among patients with COVID-19 (N = 683,958) without a pre-existing CKD diagnosis, 8322 (1.2 %) were found to have a new diagnosis of CKD. The strongest predictors for subsequent CKD diagnosis were age ≥ 60 years hazard ratio (HR) 31.5 (95% confidence interval [95%CI] 25.5-38.8), and intervening (between COVID-19 and CKD diagnoses) AKI diagnosis HR 20.7 (95%CI 19.7-21.7). The presence of AKI was associated with an HR of 23.6, 95% CI 22.3-25.0, among those not hospitalized, and HR of 6.2, 95% CI 5.7-6.8 among those hospitalized, for subsequent CKD. COVID-19 was not significantly associated with subsequent CKD after accounting for the severity of illness and comorbidities. CONCLUSION: Among SC residents, COVID-19 was not associated with CKD independent from indicators of the severity of illness, especially AKI diagnosis. Kidney-specific follow-up testing may be reserved for those high-risk for CKD development. Further prospective registries should examine the long-term kidney consequences to confirm these findings.

Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A case study of South Carolina

Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has emerged as a valuable data source for revealing fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate the second wave spreading of COVID-19 in January 2021 in three major metropolitan statistical areas (Columbia, Greenville, and Charleston) in South Carolina, United States. Based on the simulation, the number of historical county-level COVID-19 cases was allocated to neighborhoods (Census block groups) and points of interest (POIs), and the transmission rate of each allocated place was estimated. The result reveals that the COVID-19 infections during the study period mainly occurred in neighborhoods (86%), and the number is approximately proportional to the neighborhood's population. Restaurants and elementary and secondary schools contributed more COVID-19 infections than other POI categories. The simulation results for the coastal tourism Charleston area show high transmission rates in POIs related to travel and leisure activities. The results suggest that neighborhood-level infectious controlling measures are critical in reducing COVID-19 infections. We also found that households of lower socioeconomic status may be an umbrella against infection due to fewer visits to places such as malls and restaurants associated with their low financial status. Control measures should be tailored to different geographic locations since transmission rates and infection counts of POI categories vary among metropolitan areas.

Examining Cancer Patients' Perceptions of the Impact of COVID-19 on Teleoncology: Findings From 15 Nigerian Outpatient Cancer Clinics.

PURPOSE: To examine cancer patients' perspectives on the impact of COVID-19 on teleoncology in Nigeria. METHODS: Data from a multicenter survey conducted at 15 outpatient clinics to 1,097 patients with cancer from April and July 2020 were analyzed. The study outcome was telemedicine, defined as patients who reported their routine follow-up visits were converted to virtual visits because of COVID-19 (coded yes/no). Covariates included patient age, ethnicity, marital status, income, cancer treatment, service disruption, and cancer diagnosis/type. Stata/SE.v.17 (StataCorp, College Station, TX) was used to perform chi-square and logistic regression analyses. P values ≤ .05 were considered statistically significant. RESULTS: The majority of the 1,097 patients with cancer were female (65.7%) and age 55 years and older (35.0%). Because of COVID-19, 12.6% of patients' routine follow-ups were converted to virtual visits. More patients who canceled/postponed surgery (17.7% v 7.5%; P ≤ .001), radiotherapy (16.9% v 5.3%; P ≤ .001), and chemotherapy (22.8% v 8.5%; P ≤ .001), injection chemotherapy (20.6% v 8.7%; P ≤ .001) and those who reported being seen less by their doctor/nurse (60.3% v 11.4%; P ≤ .001) reported more follow-up conversions to virtual visits. In multivariate analyses, patients seen less by their doctors/nurses were 14.3 times more likely to have their routine follow-ups converted to virtual visits than those who did not (odds ratio, 14.33; 95% CI, 8.36 to 24.58). CONCLUSION: COVID-19 caused many patients with cancer in Nigeria to convert visits to a virtual format. These conversions were more common in patients whose surgery, radiotherapy, chemotherapy, and injection chemotherapy treatments were canceled or postponed. Our findings suggest how COVID-19 affects cancer treatment services and the importance of collecting teleoncological care data in Nigeria.

Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A case study of South Carolina.

Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has emerged as a valuable data source for revealing fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate the second wave spreading of COVID-19 in January 2021 in three major metropolitan statistical areas (Columbia, Greenville, and Charleston) in South Carolina, United States. Based on the simulation, the number of historical county-level COVID-19 cases was allocated to neighborhoods (Census block groups) and points of interest (POIs), and the transmission rate of each allocated place was estimated. The result reveals that the COVID-19 infections during the study period mainly occurred in neighborhoods (86%), and the number is approximately proportional to the neighborhood's population. Restaurants and elementary and secondary schools contributed more COVID-19 infections than other POI categories. The simulation results for the coastal tourism Charleston area show high transmission rates in POIs related to travel and leisure activities. The results suggest that neighborhood-level infectious controlling measures are critical in reducing COVID-19 infections. We also found that households of lower socioeconomic status may be an umbrella against infection due to fewer visits to places such as malls and restaurants associated with their low financial status. Control measures should be tailored to different geographic locations since transmission rates and infection counts of POI categories vary among metropolitan areas.

Risk for stillbirth among pregnant individuals with SARS-CoV-2 infection varied by gestational age.

BACKGROUND: Despite previous research findings on higher risks of stillbirth among pregnant individuals with SARS-CoV-2 infection, it is unclear whether the gestational timing of viral infection modulates this risk. OBJECTIVE: This study aimed to examine the association between timing of SARS-CoV-2 infection during pregnancy and risk of stillbirth. STUDY DESIGN: This retrospective cohort study used multilevel logistic regression analyses of nationwide electronic health records in the United States. Data were from 75 healthcare systems and institutes across 50 states. A total of 191,403 pregnancies of 190,738 individuals of reproductive age (15-49 years) who had childbirth between March 1, 2020 and May 31, 2021 were identified and included. The main outcome was stillbirth at ≥20 weeks of gestation. Exposures were the timing of SARS-CoV-2 infection: early pregnancy (<20 weeks), midpregnancy (21-27 weeks), the third trimester (28-43 weeks), any time before delivery, and never infected (reference). RESULTS: We identified 2342 (1.3%) pregnancies with COVID-19 in early pregnancy, 2075 (1.2%) in midpregnancy, and 12,697 (6.9%) in the third trimester. After adjusting for maternal and clinical characteristics, increased odds of stillbirth were observed among pregnant individuals with SARS-CoV-2 infection only in early pregnancy (odds ratio, 1.75, 95% confidence interval, 1.25-2.46) and midpregnancy (odds ratio, 2.09; 95% confidence interval, 1.49-2.93), as opposed to pregnant individuals who were never infected. Older age, Black race, hypertension, acute respiratory distress syndrome or acute respiratory failure, and placental abruption were found to be consistently associated with stillbirth across different trimesters. CONCLUSION: Increased risk of stillbirth was associated with COVID-19 only when pregnant individuals were infected during early and midpregnancy, and not at any time before the delivery or during the third trimester, suggesting the potential vulnerability of the fetus to SARS-CoV-2 infection in early pregnancy. Our findings underscore the importance of proactive COVID-19 prevention and timely medical intervention for individuals infected with SARS-CoV-2 during early and midpregnancy.

The impact of COVID-19 pandemic on the dynamic HIV care engagement among people with HIV: real-world evidence.

INTRODUCTION: Existing studies examining the impact of the COVID-19 pandemic on engagement in HIV care often capture cross-sectional status, while lacking longitudinal evaluations. This study examined the impact of the pandemic on the longitudinal dynamic change of retention in care and viral suppression status. METHODS: The electronic health record (EHR) data of this population-level cohort study were retrieved from the statewide electronic HIV/AIDS reporting system in South Carolina. The study population was people with HIV (PWH) who had at least one year's symmetric follow-up observation record before and after the pandemic. Multivariable generalized linear mixed regression models were employed to analyze the impact of the pandemic on these outcomes, adjusting for socio-demographic characteristics and preexisting comorbidities. RESULTS: In the adjusted models, PWH had a lower likelihood of retention in care (adjusted odds ratio [aOR]: 0.806, 95% confidence interval [CI]: 0.769, 0.844) and a higher probability of virological failure (aOR: 1.240, 95% CI: 1.169, 1.316) during the peri-pandemic period than pre-pandemic period. Results from interaction effect analysis from each cohort revealed that the negative effect of the pandemic on retention in care was more severe among PWH with high comorbidity burden than those without any comorbidity; meanwhile, a more striking virological failure was observed among PWH who reside in urban areas than in rural areas. CONCLUSION: The COVID-19 pandemic has a negative impact on retention in care and viral suppression among PWH in South Carolina, particularly for individuals with comorbidities and residing in urban areas.

Investigating the relationships between concentrated disadvantage, place connectivity, and COVID-19 fatality in the United States over time.

BACKGROUND: Concentrated disadvantaged areas have been disproportionately affected by COVID-19 outbreak in the United States (US). Meanwhile, highly connected areas may contribute to higher human movement, leading to higher COVID-19 cases and deaths. This study examined the associations between concentrated disadvantage, place connectivity, and COVID-19 fatality in the US over time. METHODS: Concentrated disadvantage was assessed based on the spatial concentration of residents with low socioeconomic status. Place connectivity was defined as the normalized number of shared Twitter users between the county and all other counties in the contiguous US in a year (Y = 2019). COVID-19 fatality was measured as the cumulative COVID-19 deaths divided by the cumulative COVID-19 cases. Using county-level (N = 3,091) COVID-19 fatality over four time periods (up to October 31, 2021), we performed mixed-effect negative binomial regressions to examine the association between concentrated disadvantage, place connectivity, and COVID-19 fatality, considering potential state-level variations. The moderation effects of county-level place connectivity and concentrated disadvantage were analyzed. Spatially lagged variables of COVID-19 fatality were added to the models to control for the effect of spatial autocorrelations in COVID-19 fatality. RESULTS: Concentrated disadvantage was significantly associated with an increased COVID-19 fatality in four time periods (p < 0.01). More importantly, moderation analysis suggested that place connectivity significantly exacerbated the harmful effect of concentrated disadvantage on COVID-19 fatality in three periods (p < 0.01), and this significant moderation effect increased over time. The moderation effects were also significant when using place connectivity data from the previous year. CONCLUSIONS: Populations living in counties with both high concentrated disadvantage and high place connectivity may be at risk of a higher COVID-19 fatality. Greater COVID-19 fatality that occurs in concentrated disadvantaged counties may be partially due to higher human movement through place connectivity. In response to COVID-19 and other future infectious disease outbreaks, policymakers are encouraged to take advantage of historical disadvantage and place connectivity data in epidemic monitoring and surveillance of the disadvantaged areas that are highly connected, as well as targeting vulnerable populations and communities for additional intervention.

Analysis of Residential Segregation and Racial and Ethnic Disparities in Severe Maternal Morbidity Before and During the COVID-19 Pandemic.

Importance: Persistent racial and ethnic disparities in severe maternal morbidity (SMM) in the US remain a public health concern. Structural racism leaves women of color in a disadvantaged situation especially during COVID-19, leading to disproportionate pandemic afflictions among racial and ethnic minority women. Objective: To examine racial and ethnic disparities in SMM rates before and during the COVID-19 pandemic and whether the disparities varied with level of Black residential segregation. Design, Setting, and Participants: A statewide population-based retrospective cohort study used birth certificates linked to all-payer childbirth claims data in South Carolina. Participants included women who gave birth between January 2018 and June 2021. Data were analyzed from December 2021 to February 2022. Exposures: Exposures were (1) period when women gave birth, either before the pandemic (January 2018 to February 2020) or during the pandemic (March 2020 to June 2021) and (2) Black-White residential segregation (isolation index), categorizing US Census tracts in a county as low (<40%), medium (40%-59%), and high (≥60%). Main Outcomes and Measures: SMM was identified using International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes developed by the US Centers for Disease Control and Prevention. Multilevel logistic regressions with an interrupted approach were used, adjusting for maternal-level and facility-level factors, accounting for residential county-level random effects. Results: Of 166 791 women, 95 098 (57.0%) lived in low-segregated counties (mean [SD] age, 28.1 [5.7] years; 5126 [5.4%] Hispanic; 20 523 [21.6%] non-Hispanic Black; 62 690 [65.9%] White), and 23 521 (14.1%) women (mean [SD] age, 28.1 [5.8] years; 782 [3.3%] Hispanic; 12 880 [54.8%] non-Hispanic Black; 7988 [34.0%] White) lived in high-segregated areas. Prepandemic SMM rates were decreasing, followed by monthly increasing trends after March 2020. On average, living in high-segregated communities was associated with higher odds of SMM (adjusted odds ratio [aOR], 1.61; 95% CI, 1.06-2.34). Black women regardless of residential segregation had higher odds of SMM than White women (aOR, 1.47; 95% CI, 1.11-1.96 for low-segregation; 2.12; 95% CI, 1.38-3.26 for high-segregation). Hispanic women living in low-segregated communities had lower odds of SMM (aOR, 0.48; 95% CI, 0.25-0.90) but those living in high-segregated communities had nearly twice the odds of SMM (aOR, 1.91; 95% CI, 1.07-4.17) as their White counterparts. Conclusions and Relevance: Living in high-segregated Black communities in South Carolina was associated with racial and ethnic SMM disparities. During the COVID-19 pandemic, Black vs White disparities persisted with no signs of widening gaps, whereas Hispanic vs White disparities were exacerbated. Policy reforms on reducing residential segregation or combating the corresponding structural racism are warranted to help improve maternal health.

Curating a knowledge base for individuals with coinfection of HIV and SARS-CoV-2: a study protocol of EHR-based data mining and clinical implementation.

INTRODUCTION: Despite a higher risk of severe COVID-19 disease in individuals with HIV, the interactions between SARS-CoV-2 and HIV infections remain unclear. To delineate these interactions, multicentre Electronic Health Records (EHR) hold existing promise to provide full-spectrum and longitudinal clinical data, demographics and sociobehavioural data at individual level. Presently, a comprehensive EHR-based cohort for the HIV/SARS-CoV-2 coinfection has not been established; EHR integration and data mining methods tailored for studying the coinfection are urgently needed yet remain underdeveloped. METHODS AND ANALYSIS: The overarching goal of this exploratory/developmental study is to establish an EHR-based cohort for individuals with HIV/SARS-CoV-2 coinfection and perform large-scale EHR-based data mining to examine the interactions between HIV and SARS-CoV-2 infections and systematically identify and validate factors contributing to the severe clinical course of the coinfection. We will use a nationwide EHR database in the USA, namely, National COVID Cohort Collaborative (N3C). Ultimately, collected clinical evidence will be implemented and used to pilot test a clinical decision support prototype to assist providers in screening and referral of at-risk patients in real-world clinics. ETHICS AND DISSEMINATION: The study was approved by the institutional review boards at the University of South Carolina (Pro00121828) as non-human subject study. Study findings will be presented at academic conferences and published in peer-reviewed journals. This study will disseminate urgently needed clinical evidence for guiding clinical practice for individuals with the coinfection at Prisma Health, a healthcare system in collaboration.

COVID-19 vaccine effectiveness among people living with and without HIV in South Carolina, USA: protocol of a population-based cohort study.

INTRODUCTION: Despite the effectiveness of COVID-19 vaccines in preventing severe COVID-19 outcomes, a small percentage of fully vaccinated persons will develop symptomatic or asymptomatic infections with SARS-CoV-2, which is referred to as 'breakthrough COVID-19'. People living with HIV (PLWH) appear to have an elevated risk of severe COVID-19 outcomes, yet the effectiveness of the COVID-19 vaccine in this population remains unclear due to the limited research efforts in this population in the real world. This study aims to characterise and compare the breakthrough COVID-19 (eg, prevalence and disease severity) between PLWH and non-PLWH and then examine whether HIV markers play a role in COVID-19 vaccine effectiveness within the PLWH population. METHODS AND ANALYSIS: This cohort study will merge electronic health records data from multiple data sources in South Carolina (SC), including the 'HIV Cohort' (n=12 203) identified from the statewide Enhanced HIV/AIDS Reporting System, 'Vaccine Cohort' from the Statewide Immunisation Online Network which provides patient-level immunisation records (n=~1.71 million), and 'COVID-19 Cohort' which includes healthcare encounters and COVID-19 diagnosis information for all individuals who were tested for COVID-19 (n=~3.41 million). The PLWH will be matched with a comparison group of non-PLWH by the propensity score matching method. To distinguish the role of immunity level in affecting the vaccine effectiveness, we will conduct subgroup analyses to compare the outcome of virally controlled and immunosuppressed PLWH with non-PLWH. Conditional logistic regression and generalised linear models will be employed to analyse the relationship between HIV status and protection durability by adjusting for potential confounders. ETHICS AND DISSEMINATION: The study was approved by the Institutional Review Board at the University of South Carolina (Pro00117583) as a Non-Human Subject study. The study's findings will be published in peer-reviewed journals and disseminated at national and international conferences and through social media.

How Different Pre-existing Mental Disorders and Their Co-occurrence Affects COVID-19 Clinical Outcomes? A Real-World Data Study in the Southern United States

Background Although a psychiatric history might be an independent risk factor for COVID-19 infection and mortality, no studies have systematically investigated how different clusters of pre-existing mental disorders may affect COVID-19 clinical outcomes or showed how the coexistence of mental disorder clusters is related to COVID-19 clinical outcomes. Methods Using a retrospective cohort study design, a total of 476,775 adult patients with lab-confirmed and probable COVID-19 between March 06, 2020 and April 14, 2021 in South Carolina, United States were included in the current study. The electronic health record data of COVID-19 patients were linked to all payer-based claims data through the SC Revenue and Fiscal Affairs Office. Pre-existing mental disorder diagnoses from Jan 2, 2019 to Jan 14, 2021 were extracted from the patients' healthcare utilization data via ICD-10 codes. Results There is an elevated risk of COVID-19-related hospitalization and death among participants with pre-existing mental disorders adjusting for key socio-demographic and comorbidity covariates. Co-occurrence of any two clusters was positively associated with COVID-19-related hospitalization and death. The odds ratio of being hospitalized was 1.26 (95% CI: 1.151, 1.383) for patients with internalizing and externalizing disorders, 1.65 (95% CI: 1.298, 2.092) for internalizing and thought disorders, 1.76 (95% CI: 1.217, 2.542) for externalizing and thought disorders, and 1.64 (95% CI: 1.274, 2.118) for three clusters of mental disorders. Conclusions Pre-existing internalizing disorders and thought disorders are positively related to COVID-19 hospitalization and death. Co-occurrence of any two clusters of mental disorders have elevated risk of COVID-19-related hospitalization and death compared to those with a single cluster.

Listening to Voices from African American Communities in the Southern States about COVID-19 Vaccine Information and Communication: A Qualitative Study.

The high uptake of COVID-19 vaccines is one of the most promising measures to control the pandemic. However, some African American (AA) communities exhibit vaccination hesitancy due to mis- or disinformation. It is important to understand the challenges in accessing reliable COVID-19 vaccine information and to develop feasible health communication interventions based on voices from AA communities. We conducted 2 focus group discussions (FGDs) among 18 community stakeholders recruited from 3 counties in South Carolina on 8 October and 29 October 2021. The FGDs were conducted online via Zoom meetings. The FGD data were managed and thematically analyzed using NVivo 12. Participants worked primarily in colleges, churches, and health agencies. We found that the challenges of accessing reliable vaccine information in AA communities primarily included structural barriers, information barriers, and a lack of trust. Community stakeholders recommended recruiting trusted messengers, using social events to reach target populations, and conducting health communication campaigns through open dialogue among stakeholders. Health communication interventions directed at COVID-19 vaccine uptake should be grounded in ongoing community engagement, trust-building activities, and transparent communication about vaccine development. Tailoring health communication interventions to different groups may help reduce misinformation spread and thus promote vaccination in AA communities in the southern states.

Multilevel determinants of racial/ethnic disparities in severe maternal morbidity and mortality in the context of the COVID-19 pandemic in the USA: protocol for a concurrent triangulation, mixed-methods study.

INTRODUCTION: The COVID-19 pandemic has affected communities of colour the hardest. Non-Hispanic black and Hispanic pregnant women appear to have disproportionate SARS-CoV-2 infection and death rates. METHODS AND ANALYSIS: We will use the socioecological framework and employ a concurrent triangulation, mixed-methods study design to achieve three specific aims: (1) examine the impacts of the COVID-19 pandemic on racial/ethnic disparities in severe maternal morbidity and mortality (SMMM); (2) explore how social contexts (eg, racial/ethnic residential segregation) have contributed to the widening of racial/ethnic disparities in SMMM during the pandemic and identify distinct mediating pathways through maternity care and mental health; and (3) determine the role of social contextual factors on racial/ethnic disparities in pregnancy-related morbidities using machine learning algorithms. We will leverage an existing South Carolina COVID-19 Cohort by creating a pregnancy cohort that links COVID-19 testing data, electronic health records (EHRs), vital records data, healthcare utilisation data and billing data for all births in South Carolina (SC) between 2018 and 2021 (>200 000 births). We will also conduct similar analyses using EHR data from the National COVID-19 Cohort Collaborative including >270 000 women who had a childbirth between 2018 and 2021 in the USA. We will use a convergent parallel design which includes a quantitative analysis of data from the 2018-2021 SC Pregnancy Risk Assessment and Monitoring System (unweighted n>2000) and in-depth interviews of 40 postpartum women and 10 maternal care providers to identify distinct mediating pathways. ETHICS AND DISSEMINATION: The study was approved by institutional review boards at the University of SC (Pro00115169) and the SC Department of Health and Environmental Control (DHEC IRB.21-030). Informed consent will be provided by the participants in the in-depth interviews. Study findings will be disseminated with key stakeholders including patients, presented at academic conferences and published in peer-reviewed journals.

Examining Social Determinants of Health During a Pandemic: Clinical Application of Z Codes Before and During COVID-19.

Recognition of the impact of social determinants of health (SDoH) on healthcare outcomes, healthcare service utilization, and population health has prompted a global shift in focus to patient social needs and lived experiences in assessment and treatment. The International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) provides a list of non-billable "Z codes" specific to SDoH for use in electronic health records. Using population-level analysis, this study aims to examine clinical application of Z codes in South Carolina before and during the COVID-19 pandemic. The study population consists of South Carolina residents who had a healthcare visit and had their COVID-19 test result reported to the state's Department of Health and Environmental Control before January 14, 2021. Of the 1,190,531 individuals in the overall sample, Z codes were used only for 14,665 (1.23%) of the patients, including 2,536 (0.97%) COVID-positive patients and 12,129 (1.30%) COVID-negative patients. Compared with hospitals that did not use Z codes, those that did were significantly more likely to have higher bed capacity (p = 0.017) and to be teaching hospitals (p = 0.03), although this was significant only among COVID-19 positive individuals. Those at inpatient visits were most likely to receive Z codes (OR: 5.26; 95% CI: 5.14, 5.38; p < 0.0001) compared to those at outpatient visits (OR: 0.07; 95%CI: 0.06, 0.07; p < 0.0001). There was a slight increase of Z code use from 2019 to 2020 (OR: 1.33, 95% CI: 1.30, 1.36; p < 0.0001), which was still significant when stratified by facility type across time. As one of the first studies to examine Z code use among a large patient population, findings clearly indicate underutilization by providers. Additional study is needed to understand the potentially long-lasting health effects related to SDoH among underserved populations.

Patient's Perspective on the Impact of COVID-19 on Cancer Treatment in Nigeria.

PURPOSE: Because of the global COVID-19 pandemic, health care organizations introduced guidelines for modifications to health and cancer medical care delivery to mitigate transmission and ensure quality health outcomes. To examine the extent and impact of these modifications on oncology service disruptions in Nigeria, we surveyed oncology patients across selected public and private cancer treatment centers. MATERIALS AND METHODS: Participating in the study were 15 tertiary cancer treatment centers across 12 Nigerian states. We recruited adult patients with cancer (18+ years) on active treatment to complete a self-administered survey on cancer care during COVID-19. We conducted descriptive and multivariate data analysis using Stata 16.1. RESULTS: Respondents were (n = 1,072), female (65.7%), ages 18-49 years (50.3%), and married (80.7%). The top two cancers were breast and prostate. Overall, 17.3% of respondents reported disruptions to cancer care, and more than half (51.0%) reported difficulties accessing care. Changes in chemotherapy regimens or route of administration were reported in 8.4% of respondents. Odds for any disruption were highest for older patients, western states, patients with prostate cancer, and patients with two or more flu symptoms. Odds for radiotherapy cancellation were highest for older patients, those with prostate cancer, and those with medium service perception. CONCLUSION: This study investigated COVID-19-influenced cancer treatment disruptions in Nigeria. Patients with cancer experienced significant disruptions to cancer care. Vulnerable patients are most likely to be negatively affected. Policies and strategies aimed at minimizing service disruptions while maintaining cancer patients' safety should be a priority for all health care institutions in the COVID-19 era.

Associations between HIV infection and clinical spectrum of COVID-19: a population level analysis based on US National COVID Cohort Collaborative (N3C) data.

BACKGROUND: Evidence of whether people living with HIV are at elevated risk of adverse COVID-19 outcomes is inconclusive. We aimed to investigate this association using the population-based National COVID Cohort Collaborative (N3C) data in the USA. METHODS: We included all adult (aged ≥18 years) COVID-19 cases with any health-care encounter from 54 clinical sites in the USA, with data being deposited into the N3C. The outcomes were COVID-19 disease severity, hospitalisation, and mortality. Encounters in the same health-care system beginning on or after January 1, 2018, were also included to provide information about pre-existing health conditions (eg, comorbidities). Logistic regression models were employed to estimate the association of HIV infection and HIV markers (CD4 cell count, viral load) with hospitalisation, mortality, and clinical severity of COVID-19 (multinomial). The models were initially adjusted for demographic characteristics, then subsequently adjusted for smoking, obesity, and a broad range of comorbidities. Interaction terms were added to assess moderation effects by demographic characteristics. FINDINGS: In the harmonised N3C data release set from Jan 1, 2020, to May 8, 2021, there were 1 436 622 adult COVID-19 cases, of these, 13 170 individuals had HIV infection. A total of 26 130 COVID-19 related deaths occurred, with 445 among people with HIV. After adjusting for all the covariates, people with HIV had higher odds of COVID-19 death (adjusted odds ratio 1·29, 95% CI 1·16-1·44) and hospitalisation (1·20, 1·15-1·26), but lower odds of mild or moderate COVID-19 (0·61, 0·59-0·64) than people without HIV. Interaction terms revealed that the elevated odds were higher among older age groups, male, Black, African American, Hispanic, or Latinx adults. A lower CD4 cell count (<200 cells per µL) was associated with all the adverse COVID-19 outcomes, while viral suppression was only associated with reduced hospitalisation. INTERPRETATION: Given the COVID-19 pandemic's exacerbating effects on health inequities, public health and clinical communities must strengthen services and support to prevent aggravated COVID-19 outcomes among people with HIV, particularly for those with pronounced immunodeficiency. FUNDING: National Center for Advancing Translational Sciences, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA.