The effect of area deprivation on COVID-19 risk in Louisiana

Area-Level Social Vulnerability and Severe COVID-19: A Case-Control Study Using Electronic Health Records from Multiple Health Systems in the Southeastern Pennsylvania Region

Knowledge about neighborhood characteristics that predict disease burden can be used to guide equity-based public health interventions or targeted social services. We used a case-control design to examine the association between area-level social vulnerability and severe COVID-19 using electronic health records (EHR) from a regional health information hub in the greater Philadelphia region. Severe COVID-19 cases (n = 15,464 unique patients) were defined as those with an inpatient admission and a diagnosis of COVID-19 in 2020. Controls (n = 78,600; 5:1 control-case ratio) were a random sample of individuals who did not have a COVID-19 diagnosis from the same geographic area. Retrospective data on comorbidities and demographic variables were extracted from EHR and linked to area-level social vulnerability index (SVI) data using ZIP codes. Models adjusted for different sets of covariates showed incidence rate ratios (IRR) ranging from 1.15 (95% CI, 1.13-1.17) in the model adjusted for individual-level age, sex, and marital status to 1.09 (95% CI, 1.08-1.11) in the fully adjusted model, which included individual-level comorbidities and race/ethnicity. The fully adjusted model indicates that a 10% higher area-level SVI was associated with a 9% higher risk of severe COVID-19. Individuals in neighborhoods with high social vulnerability were more likely to have severe COVID-19 after accounting for comorbidities and demographic characteristics. Our findings support initiatives incorporating neighborhood-level social determinants of health when planning interventions and allocating resources to mitigate epidemic respiratory diseases, including other coronavirus or influenza viruses.

Nucleocapsid and Spike Protein-Based Anti-SARS-CoV-2 Assay Performance in the Minority and Rural Coronavirus Insights Study: Characteristics of Socioeconomically Disadvantaged Populations with Health Disparities

BACKGROUND

COVID-19 has had a devastating impact on Black, Hispanic, and other underserved, disadvantaged populations. Here anti-SARS-CoV-2 tests are characterized in disadvantaged patients to examine equivalence in US populations.

METHODS

Underserved participant adults (age > 18 years) were enrolled before the availability of SARS-CoV-2 vaccines in Federal Qualified Health Centers in California, Florida, Louisiana, Illinois, and Ohio and contributed samples to the Minority and Rural Coronavirus Insights Study (MRCIS). A subset coined the MRCIS SARS-CoV-2 Antibody Cohort of 2365 participants was tested with the Roche Anti-SARS-CoV-2 assay (Cobas e601). Five hundred ninety-five of these were also tested with the Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 IgG assay (VITROS-5600); 1770 were also tested with the Abbott ARCHITECT SARS-CoV-2 IgG assay (ARCHITECT-2000). Assay-specific cutoffs classified negative/positive results.

RESULTS

Eight point four percent (199/2365) of the MRCIS SARS-CoV-2 Antibody Cohort was SARS-CoV-2 RNA positive at enrollment. Agreement between the Ortho/Roche and the Abbott/Roche antibody testing did not vary by enrollment RNA status. The Ortho (anti-spike protein) vs Roche (anti-nucleocapsid protein) comparison agreed substantially: kappa = 0.63 (95% CI: 0.57-0.69); overall agreement, 83%. However, agreement was even better for the Abbott vs Roche assays (both anti-nucleocapsid protein tests): kappa = 0.85 (95% CI: 0.81-0.87); overall agreement, 95%. Anti-SARS-CoV-2 comparisons stratified by demographic criteria demonstrated no significant variability in agreement by sex, race/ethnicity, or age.

CONCLUSIONS

Analytical agreement is 96.4% for anti-spike-protein vs anti-nucleocapsid-protein comparisons. Physiologically, seroreversion of anti-nucleocapsid reactivity after infection occurred in the disadvantaged population similarly to general populations. No anti-SARS-CoV-2 assays included demonstrated a clinically significant difference due to the demographics of the disadvantaged MRCIS SARS-CoV-2 Antibody Cohort.

Area-level deprivation and handwashing behavior during the COVID-19 pandemic: A multilevel analysis on a nationwide survey in Korea

This study investigated the association between area deprivation level and performance of handwashing behavior during the COVID-19 pandemic in Korean adults. This study used data from the 2015 Population and Housing Census data to measure area deprivation level. The 2020 Korea Community Health Survey was used for all other variables, including hand hygiene behavior (August through November 2020). The association between area deprivation level and practice of handwashing behavior was examined using multilevel logistic regression analysis. The study population comprised 215,676 adults aged 19 years or above. Compared to the least area deprived group, the most deprived group was more likely to not wash hands after using the restroom (OR 1.43, 95% CI 1.13-1.82), after coming home (OR 1.85, 95% CI 1.43-2.39), and using soap (OR 1.55, 95% CI 1.29-1.84). The findings suggest the importance of considering area deprivation in implementing policies that promote handwashing, particularly during a pandemic.

Neighborhood Factors Associated with COVID-19 Cases in California

BACKGROUND

There is a need to assess neighborhood-level factors driving COVID-19 disparities across racial and ethnic groups.

OBJECTIVE

To use census tract-level data to investigate neighborhood-level factors contributing to racial and ethnic group-specific COVID-19 case rates in California.

DESIGN

Quasi-Poisson generalized linear models were used to identify neighborhood-level factors associated with COVID-19 cases. In separate sequential models for Hispanic, Black, and Asian, we characterized the associations between neighborhood factors on neighborhood COVID-19 cases. Subanalyses were conducted on neighborhoods with majority Hispanic, Black, and Asian residents to identify factors that might be unique to these neighborhoods. Geographically weighted regression using a quasi-Poisson model was conducted to identify regional differences.

MAIN MEASURES

All COVID-19 cases and tests reported through January 31, 2021, to the California Department of Public Health. Neighborhood-level data from census tracts were obtained from American Community Survey 5-year estimates (2015-2019), United States Census (2010), and United States Department of Housing and Urban Development.

KEY RESULTS

The neighborhood factors associated with COVID-19 case rate were racial and ethnic composition, age, limited English proficiency (LEP), income, household size, and population density. LEP had the largest influence on the positive association between proportion of Hispanic residents and COVID-19 cases (- 2.1% change). This was also true for proportion of Asian residents (- 1.8% change), but not for the proportion of Black residents (- 0.1% change). The influence of LEP was strongest in areas of the Bay Area, Los Angeles, and San Diego.

CONCLUSION

Neighborhood-level contextual drivers of COVID-19 burden differ across racial and ethnic groups.

Explaining COVID-19 related mortality disparities in American Indians and Alaska Natives

American Indian and Alaska Native (AI/AN) individuals are more likely to die with COVID-19 than other groups, but there is limited empirical evidence to explain the cause of this inequity. The objective of this study was to determine whether medical comorbidities, area socioeconomic deprivation, or access to treatment can explain the greater COVID-19 related mortality among AI/AN individuals. The design was a retrospective cohort study of harmonized electronic health record data of all inpatients with COVID-19 from 21 United States health systems from February 2020 through January 2022. The mortality of AI/AN inpatients was compared to all Non-Hispanic White (NHW) inpatients and to a matched subsample of NHW inpatients. AI/AN inpatients were more likely to die during their hospitalization (13.2% versus 7.1%; odds ratio [OR] = 1.98, 95% confidence interval [CI] = 1.48, 2.65) than their matched NHW counterparts. After adjusting for comorbidities, area social deprivation, and access to treatment, the association between ethnicity and mortality was substantially reduced (OR 1.59, 95% CI 1.15, 2.22). The significant residual relation between AI/AN versus NHW status and mortality indicate that there are other important unmeasured factors that contribute to this inequity. This will be an important direction for future research.

Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data

For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable the pattern will be in the long term. To this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500-1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 ("Omicron") and B.1.617.2 ("Delta"). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency. Despite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures.

The Social, Demographic, and Clinical Predictors of COVID-19 Severity: a Model-based Analysis of United States Veterans

PURPOSE

This study aims to identify the contributions of individual and community social determinants of health (SDOH), demographic, and clinical factors in COVID-19 disease severity through a model-based analysis.

METHODS

This national cross-sectional study focused on hospitalization among those tested for COVID-19 and use of intensive care, analyzing data on 220,848 Veterans tested between February 20, 2020 and October 20, 2021. Multiple logistic regression models were constructed using backwards elimination. The predictive value of each model was assessed with a c-statistic.

RESULTS

Those hospitalized were older, more likely to be male, of Black or Asian race, have an income less than $39,999, live in an urban residence, and have medical comorbidities. The strongest predictors for hospitalization included Gini inequality index, race, income, heart failure, chronic kidney disease (CKD), and chronic obstructive pulmonary disease (COPD). For intensive care, Asian race, rural residence, COPD, and CKD were the strongest predictors. C-statistics were c = 0.749 for hospitalization and c = 0.582 for ICU admission.

CONCLUSIONS

A combination of clinical, demographic, individual and community SDOH factors predict COVID-19 hospitalization with good predictive ability and can inform risk stratification, discharge planning, and public health interventions. Racial disparities were not explained by social or clinical factors. Intensive care models had low discriminative power and may be better explained by other characteristics.

Empirical distributions of time intervals between COVID-19 cases and more severe outcomes in Scotland

A critical factor in infectious disease control is the risk of an outbreak overwhelming local healthcare capacity. The overall demand on healthcare services will depend on disease severity, but the precise timing and size of peak demand also depends on the time interval (or clinical time delay) between initial infection, and development of severe disease. A broader distribution of intervals may draw that demand out over a longer period, but have a lower peak demand. These interval distributions are therefore important in modelling trajectories of e.g. hospital admissions, given a trajectory of incidence. Conversely, as testing rates decline, an incidence trajectory may need to be inferred through the delayed, but relatively unbiased signal of hospital admissions. Healthcare demand has been extensively modelled during the COVID-19 pandemic, where localised waves of infection have imposed severe stresses on healthcare services. While the initial acute threat posed by this disease has since subsided with immunity buildup from vaccination and prior infection, prevalence remains high and waning immunity may lead to substantial pressures for years to come. In this work, then, we present a set of interval distributions, for COVID-19 cases and subsequent severe outcomes; hospital admission, ICU admission, and death. These may be used to model more realistic scenarios of hospital admissions and occupancy, given a trajectory of infections or cases. We present a method for obtaining empirical distributions using COVID-19 outcomes data from Scotland between September 2020 and January 2022 (N = 31724 hospital admissions, N = 3514 ICU admissions, N = 8306 mortalities). We present separate distributions for individual age, sex, and deprivation of residing community. While the risk of severe disease following COVID-19 infection is substantially higher for the elderly and those residing in areas of high deprivation, the length of stay shows no strong dependence, suggesting that severe outcomes are equally severe across risk groups. As Scotland and other countries move into a phase where testing is no longer abundant, these intervals may be of use for retrospective modelling of patterns of infection, given data on severe outcomes.

Exploring barriers to SARS-CoV-2 testing uptake in underserved black communities in Louisiana

OBJECTIVE

To collect qualitative data on approaches that can potentially reduce barriers to, and create strategies for, increasing SARS-CoV-2 testing uptake in underserved Black communities in Louisiana.

METHODS

A series of eight focus groups, including 41 participants, were conducted in primarily Black communities. The Nominal Group Technique (NGT) was used to determine perceptions of COVID-19 as a disease, access to testing, and barriers limiting testing uptake.

RESULTS

Common barriers to SARS-CoV-2 testing were identified as lack of transportation, misinformation/lack of information, lack of time/long wait times, fear of the test being uncomfortable and/or testing positive, the cost of testing, and lack of computer/smartphone/internet. The most impactful approaches identified to increase testing uptake included providing testing within the local communities; testing specifically in heavily traveled areas such as supermarkets, churches, schools, and so forth; providing incentives; engaging local celebrities; and providing information to the community through health fairs, or through churches and schools. The strategies that were deemed to be the easiest to implement revolved around communication about testing, with suggested strategies involving churches, local celebrities or expert leaders, social media, text messages, public service announcements, post cards, or putting up signs in neighborhoods. Providing transportation to testing sites, providing incentives, and bringing the testing to neighborhoods and schools were also identified as easy to implement strategies.

CONCLUSIONS

Several strategies to increase testing uptake were identified in this population. These strategies need to be tested for effectiveness in real-world settings using experimental and observational study designs.

Implementation of a novel program to support colorectal cancer screening in a community health center consortium before and after the onset of COVID-19: a qualitative study of stakeholders' perspectives

BACKGROUND

In 2017, the San Francisco Cancer Initiative (SF CAN) established the Colorectal Cancer (CRC) Screening Program to provide technical assistance and financial support to improve CRC screening processes, and outcomes in a consortium of community health centers (CHCs) serving low-income communities in San Francisco. The purpose of this study was twofold: to evaluate the perceived influence of the support provided by the CRC Screening Program's Task Force on CRC screening processes and outcomes in these settings and to identify facilitators and barriers to SF CAN-supported CRC screening activities before and after the onset of the COVID-19 pandemic.

METHODS

Semi-structured key informant interviews were conducted with consortium leaders, medical directors, quality improvement team members, and clinic screening champions. Interviews were audio-recorded, professionally transcribed, and analyzed for themes. The Consolidated Framework for Implementation Research (CFIR) was used to develop the interview questions and organize the analysis.

RESULTS

Twenty-two participants were interviewed. The most commonly cited facilitators of improved screening processes included the expertise, funding, screening resources, regular follow-up, and sustained engagement with clinic leaders provided by the task force. The most salient barriers identified were patient characteristics, such as housing instability; staffing challenges, such as being understaffed and experiencing high staff turnover; and clinic-level challenges, such as lack of ability to implement and sustain formalized patient navigation strategies, and changes in clinic priorities due to the COVID-19 pandemic and other competing health care priorities.

CONCLUSIONS

Implementing CRC screening programs in a consortium of CHCs is inherently challenging. Technical assistance from the Task Force was viewed positively and helped to mitigate challenges both before and during the pandemic. Future research should explore opportunities to increase the robustness of technical assistance offered by groups such as SF CAN to support cancer screening activities in CHCs serving low-income communities.

Racial/ethnic and socioeconomic disparities in COVID-19 infections among working-age women with precancerous cervical lesion in Louisiana: analysis of more than two years of COVID-19 data

Background

Precancerous cervical lesion (PCL) is common in working-age and minority women. In Louisiana, 98% of PCL cases were diagnosed at age 18-65 with over 90% of them being human papillomavirus (HPV)-related. PCL women represent those who may be immunocompromised from the precancerous condition and thus more vulnerable to SARS-CoV-2. Most studies evaluating racial disparities for COVID-19 infection have only used data prior to vaccine availability. This study assessed disparities by race/ethnicity and socioeconomic status (SES) in COVID-19 infections among working-age PCL women for pre- and post-COVID-19 vaccine availability.

Methods

Louisiana women aged 18-65 with PCL diagnosed in 2009-2021 were linked with the Louisiana statewide COVID-19 database to identify those with positive COVID-19 test. Race/ethnicity was categorized as non-Hispanic white (NHW), non-Hispanic black (NHB), Hispanic, and others. The census tract SES quintiles were created based on American Community Survey estimates. Logistic regression was employed to assess the racial/ethnic and SES differences in COVID-19 infections.

Results

Of 14,669 eligible PCL women, 30% were tested COVID-19 positive. NHB had the highest percentage of COVID-19 infection (34.6%), followed by NHW (27.7%). The infection percentage was inversely proportional to SES, with 32.9% for women having the lowest SES and 26.8% for those with the highest SES. NHB women and those with lower SES had higher COVID-19 infection than their counterparts with an aOR of 1.37 (95% CI 1.25-1.49) and 1.21 (95% CI 1.07-1.37), respectively. In the pre-vaccine period, NHB and Hispanic women had higher odds of infection than NHW women. However, after the vaccine was implemented, the significant racial/ethnic and SES differences in COVID-19 infections still existed in PCL women residing in non-Greater New Orleans area.

Conclusions

There are substantial variations in racial/ethnic and SES disparities in COVID-19 infections among working-age women with PCL, even after vaccine implementation. It is imperative to provide public health interventions and resources to reduce this unequal burden for this vulnerable population.

Association of socio-economic deprivation with COVID-19 incidence and fatality during the first wave of the pandemic in Italy: lessons learned from a local register-based study

BACKGROUND

COVID-19 has been characterised by its global and rapid spread, with high infection, hospitalisation, and mortality rates worldwide. However, the course of the pandemic showed differences in chronology and intensity in different geographical areas and countries, probably due to a multitude of factors. Among these, socio-economic deprivation has been supposed to play a substantial role, although available evidence is not fully in agreement. Our study aimed to assess incidence and fatality rates of COVID-19 across the levels of socio-economic deprivation during the first epidemic wave (March-May 2020) in the Italian Province of Foggia, Apulia Region.

METHODS

Based on the data of the regional active surveillance platform, we performed a retrospective epidemiological study among all COVID-19 confirmed cases that occurred in the Apulian District of Foggia, Italy, from March 1st to May 5th, 2020. Geocoded addresses were linked to the individual Census Tract (CT) of residence. Effects of socio-economic condition were calculated by means of the Socio-Economic and Health-related Deprivation Index (SEHDI) on COVID-19 incidence and fatality.

RESULTS

Of the 1054 confirmed COVID-19 cases, 537 (50.9%) were men, 682 (64.7%) were 0-64 years old, and 338 (32.1%) had pre-existing comorbidities. COVID-19 incidence was higher in the less deprived areas (p < 0.05), independently on age. The level of socio-economic deprivation did not show a significant impact on the vital status, while a higher fatality was observed in male cases (p < 0.001), cases > 65 years (p < 0.001), cases having a connection with a nursing home (p < 0.05) or having at least 1 comorbidity (p < 0.001). On the other hand, a significant protection for healthcare workers was apparent (p < 0.001).

CONCLUSIONS

Our findings show that deprivation alone does not affect COVID-19 incidence and fatality burden, suggesting that the burden of disease is driven by a complexity of factors not yet fully understood. Better knowledge is needed to identify subgroups at higher risk and implement effective preventive strategies.

Did the Physical and Mental Health of Orthopaedic Patients Change After the Onset of the COVID-19 Pandemic?

BACKGROUND

The 2019 novel coronavirus (COVID-19) pandemic has been associated with poor mental health outcomes and widened health disparities in the United States. Given the inter-relationship between psychosocial factors and functional outcomes in orthopaedic surgery, it is important that we understand whether patients presenting for musculoskeletal care during the pandemic were associated with worse physical and mental health than before the pandemic's onset.

QUESTIONS/PURPOSES

(1) Did patients seen for an initial visit by an orthopaedic provider during the COVID-19 pandemic demonstrate worse physical function, pain interference, depression, and/or anxiety than patients seen before the pandemic, as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) instrument? (2) During the COVID-19 pandemic, did patients living in areas with high levels of social deprivation demonstrate worse patterns of physical function, pain interference, depression, or anxiety on initial presentation to an orthopaedic provider than patients living in areas with low levels of social deprivation, compared with prepandemic PROMIS scores?

METHODS

This was a retrospective, comparative study of new patient evaluations that occurred in the orthopaedic department at a large, urban tertiary care academic medical center. During the study period, PROMIS computer adaptive tests were routinely administered to patients at clinical visits. Between January 1, 2019, and December 31, 2019, we identified 26,989 new patients; we excluded 4% (1038 of 26,989) for being duplicates, 4% (1034 of 26,989) for having incomplete demographic data, 44% (11,925 of 26,989) for not having a nine-digit home ZIP Code recorded, and 5% (1332 of 26,989) for not completing all four PROMIS computer adaptive tests of interest. This left us with 11,660 patients in the "before COVID-19" cohort. Between January 1, 2021 and December 31, 2021, we identified 30,414 new patients; we excluded 5% (1554 of 30,414) for being duplicates, 4% (1142 of 30,414) for having incomplete demographic data, 41% (12,347 of 30,414) for not having a nine-digit home ZIP Code recorded, and 7% (2219 of 30,414) for not completing all four PROMIS computer adaptive tests of interest. This left us with 13,152 patients in the "during COVID-19" cohort. Nine-digit home ZIP Codes were used to determine patients' Area Deprivation Indexes, a neighborhood-level composite measure of social deprivation. To ensure that patients included in the study represented our overall patient population, we performed univariate analyses on available demographic and PROMIS data between patients included in the study and those excluded from the study, which revealed no differences (results not shown). In the before COVID-19 cohort, the mean age was 57 ± 16 years, 60% (7046 of 11,660) were women, 86% (10,079 of 11,660) were White non-Hispanic, and the mean national Area Deprivation Index percentile was 47 ± 25. In the during COVID-19 cohort, the mean age was 57 ± 16 years, 61% (8051 of 13,152) were women, 86% (11,333 of 13,152) were White non-Hispanic, and the mean national Area Deprivation Index percentile was 46 ± 25. The main outcome measures in this study were the PROMIS Physical Function ([PF], version 2.0), Pain Interference ([PI], version 1.1), Depression (version 1.0), and Anxiety (version 1.0). PROMIS scores follow a normal distribution with a mean t-score of 50 and a standard deviation of 10. Higher PROMIS PF scores indicate better self-reported physical capability, whereas higher PROMIS PI, Depression, and Anxiety scores indicate more difficulty managing pain, depression, and anxiety symptoms, respectively. Clinically meaningful differences in PROMIS scores between the cohorts were based on a minimum clinically important difference (MCID) threshold of 4 points. Multivariable linear regression models were created to determine whether presentation to an orthopaedic provider during the pandemic was associated with worse PROMIS scores than for patients who presented before the pandemic. Regression coefficients (ß) represent the estimated difference in PROMIS scores that would be expected for patients who presented during the pandemic compared with patients who presented before the pandemic, after adjusting for confounding variables. Regression coefficients were evaluated in the context of clinical importance and statistical significance. Regression coefficients equal to or greater than the MCID of 4 points were considered clinically important, whereas p values < 0.05 were considered statistically significant.

RESULTS

We found no clinically important differences in baseline physical and mental health PROMIS scores between new patients who presented to an orthopaedic provider before the COVID-19 pandemic and those who presented during the COVID-19 pandemic (PROMIS PF: ß -0.2 [95% confidence interval -0.43 to 0.03]; p = 0.09; PROMIS PI: ß 0.06 [95% CI -0.13 to 0.25]; p = 0.57; PROMIS Depression: ß 0.09 [95% CI -0.14 to 0.33]; p = 0.44; PROMIS Anxiety: ß 0.58 [95% CI 0.33 to 0.84]; p < 0.001). Although patients from areas with high levels of social deprivation had worse PROMIS scores than patients from areas with low levels of social deprivation, patients from areas with high levels of social deprivation demonstrated no clinically important differences in PROMIS scores when groups before and during the pandemic were compared (PROMIS PF: ß -0.23 [95% CI -0.80 to 0.33]; p = 0.42; PROMIS PI: ß 0.18 [95% CI -0.31 to 0.67]; p = 0.47; PROMIS Depression: ß 0.42 [95% CI -0.26 to 1.09]; p = 0.23; PROMIS Anxiety: ß 0.84 [95% CI 0.16 to 1.52]; p = 0.02).

CONCLUSION

Contrary to studies describing worse physical and mental health since the onset of the COVID-19 pandemic, we found no changes in the health status of orthopaedic patients on initial presentation to their provider. Although large-scale action to mitigate the effects of worsening physical or mental health of orthopaedic patients may not be needed at this time, orthopaedic providers should remain aware of the psychosocial needs of their patients and advocate on behalf of those who may benefit from intervention. Our study is limited in part to patients who had the self-agency to access specialty orthopaedic care, and therefore may underestimate the true changes in the physical or mental health status of all patients with musculoskeletal conditions. Future longitudinal studies evaluating the impact of specific COVID-19-related factors (for example, delays in medical care, social isolation, or financial loss) on orthopaedic outcomes may be helpful to prepare for future pandemics or natural disasters.

LEVEL OF EVIDENCE

Level II, prognostic study.

Place, Race, and Case: Examining Racialized Economic Segregation and COVID-19 in Louisiana

Early COVID-19 pandemic data suggested racial/ethnic minority and low-income earning people bore the greatest burden of infection. Structural racism, the reinforcement of racial and ethnic discrimination via policy, provides a framework for understanding disparities in health outcomes like COVID-19 infection. Residential racial and economic segregation is one indicator of structural racism. Little attention has been paid to the relationship of infection to relative overall concentrations of risk (i.e., segregation of the most privileged from the most disadvantaged). We used ordinary least squares and geographically weighted regression models to evaluate the relationship between racial and economic segregation, measured by the Index of Concentration at the Extremes, and COVID-19 cases in Louisiana. We found a significant global association between racial segregation and cumulative COVID-19 case rate in Louisiana and variation across the state during the study period. The northwest and central regions exhibited a strong negative relationship indicating greater risk in areas with high concentrations of Black residents. On the other hand, the southeastern part of the state exhibited more neutral or positive relationships indicating greater risk in areas with high concentrations of White residents. Our findings that the relationship between racial segregation and COVID-19 cases varied within a state further support evidence that social and political determinants, not biological, drive racial disparities. Small area measures and measures of polarization provide localized information better suited to tailoring public health policy according to the dynamics of communities at the census tract level, which may lead to better health outcomes.

The Effects of Race/Ethnicity, Age, and Area Deprivation Index (ADI) on COVID-19 Disease Early Dynamics: Washington, D.C. Case Study

The COVID-19 pandemic and its associated mitigation strategies have significant psychosocial, behavioral, socioeconomic, and health impacts, particularly in vulnerable US populations. Different factors have been identified as influencers of the transmission rate; however, the effects of area deprivation index (as a measure of social determinants of health, SDoH) as a factor on COVID-19 disease early dynamics have not been established. We determined the effects of area deprivation index (ADI) and demographic factors on COVID-19 outcomes in Washington, D.C. This retrospective study used publicly available data on COVID-19 cases and mortality of Washington, D.C., during March 31st-July 4th, 2020. The main predictors included area deprivation index (ADI), age, and race/ethnicity. The ADI of each census block groups in D.C. (n=433) were obtained from Neighborhood Atlas map. Using a machine learning-based algorithm, the outcome variables were partitioned into time intervals: time duration (Pi, days), rate of change coefficient (Ei), and time segment load (Pi×Ei) for transmission rate and mortality. Correlation analysis and multiple linear regression models were used to determine associations between predictors and outcome variables. COVID-19 early transmission rate (E1) was highly correlated with ADI (SDoH; r= 0.88, p=0.0044) of the Washington, D.C. community. We also found positive association between ADI, age (0-17 years, r=0.91, p=0.0019), and race (African American/Black, r=0.86; p=0.0068) and COVID-19 outcomes. There was high variability in early transmission across the geographic regions (i.e., wards) of Washington, D.C., and this variability was driven by race/ethnic composition and ADI. Understanding the association of COVID-19 disease early transmission and mortality dynamics and key socio-demographic risk factors such as age, race, and ADI, as a measure of social determinants, will contribute to health equity/equality and distribution of economic resources/assistance and is essential for future predictive modeling of the COVID-19 pandemic to limit morbidity and mortality.

Clinical and social determinants of health features of SARS-CoV-2 infection among Black and Caribbean Hispanic patients with heart failure: The SCAN-MP Study

Patients with heart failure (HF) often have multiple chronic conditions and are at increased risk for severe disease and mortality when infected by SARS-CoV-2, the virus that causes COVID-19. Furthermore, disparities in outcomes with COVID-19 have been associated with both racial/ethnic identity but also social determinants of health. Among older, urban-dwelling, minority patients with HF, we sought to characterize medical and non-medical factors associated with SARS-CoV-2 infection. Patients with HF living in Boston and New York City over 60 years of age participating in the Screening for Cardiac Amyloidosis with Nuclear Imaging (SCAN-MP) study between 12/1/2019 and 10/15/2021 (n = 180) were tested for nucleocapsid antibodies to SARS-CoV-2 and queried for symptomatic infection with PCR verification. Baseline testing included the Kansas City Cardiomyopathy Questionnaire (KCCQ), assessment of health literacy, biochemical, functional capacity, echocardiography, and a novel survey tool that determined living conditions, perceived risk of infection, and attitudes towards COVID-19 mitigation. The association of infection with prevalent socio-economic conditions was assessed by the area deprivation index (ADI). There were 50 overall cases of SARS-CoV-2 infection (28%) including 40 demonstrating antibodies to SARS-CoV-2 (indicative of prior infection) and 10 positive PCR tests. There was no overlap between these groups. The first documented case from New York City indicated infection prior to January 17, 2020. Among active smokers, none tested positive for prior SARS-CoV-2 infection (0 (0%) vs. 20 (15%), p = 0.004) vs. non-smokers. Cases were more likely to be taking ACE-inhibitors/ARBs compared to non-cases (78% vs 62%, p = 0.04). Over a mean follow-up of 9.6 months, there were 6 total deaths (3.3%) all unrelated to COVID-19. Death and hospitalizations (n = 84) were not associated with incident (PCR tested) or prior (antibody) SARS-CoV-2 infection. There was no difference in age, co-morbidities, living conditions, attitudes toward mitigation, health literacy, or ADI between those with and without infection. SARS-CoV-2 infection was common among older, minority patients with HF living in New York City and Boston, with evidence of infection documented in early January 2020. Health literacy and ADI were not associated with infection, and there was no increased mortality or hospitalizations among those infected with SARS-CoV-2.

Inclusion of Race and Ethnicity With Neighborhood Socioeconomic Deprivation When Assessing COVID-19 Hospitalization Risk Among California Veterans Health Administration Users

IMPORTANCE

Despite complexities of racial and ethnic residential segregation (hereinafter referred to as segregation) and neighborhood socioeconomic deprivation, public health studies, including those on COVID-19 racial and ethnic disparities, often rely on composite neighborhood indices that do not account for residential segregation.

OBJECTIVE

To examine the associations by race and ethnicity among California's Healthy Places Index (HPI), Black and Hispanic segregation, Social Vulnerability Index (SVI), and COVID-19-related hospitalization.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included veterans with positive test results for COVID-19 living in California who used Veterans Health Administration services between March 1, 2020, and October 31, 2021.

MAIN OUTCOMES AND MEASURES

Rates of COVID-19-related hospitalization among veterans with COVID-19.

RESULTS

The sample available for analysis included 19 495 veterans with COVID-19 (mean [SD] age, 57.21 [17.68] years), of whom 91.0% were men, 27.7% were Hispanic, 16.1% were non-Hispanic Black, and 45.0% were non-Hispanic White. For Black veterans, living in lower-HPI (ie, less healthy) neighborhoods was associated with higher rates of hospitalization (odds ratio [OR], 1.07 [95% CI, 1.03-1.12]), even after accounting for Black segregation (OR, 1.06 [95% CI, 1.02-1.11]). Among Hispanic veterans, living in lower-HPI neighborhoods was not associated with hospitalization with (OR, 1.04 [95% CI, 0.99-1.09]) and without (OR, 1.03 [95% CI, 1.00-1.08]) Hispanic segregation adjustment. For non-Hispanic White veterans, lower HPI was associated with more frequent hospitalization (OR, 1.03 [95% CI, 1.00-1.06]). The HPI was no longer associated with hospitalization after accounting for Black (OR, 1.02 [95% CI, 0.99-1.05]) or Hispanic (OR, 0.98 [95% CI, 0.95-1.02]) segregation. Hospitalization was higher for White (OR, 4.42 [95% CI, 1.62-12.08]) and Hispanic (OR, 2.90 [95% CI, 1.02-8.23]) veterans living in neighborhoods with greater Black segregation and for White veterans in more Hispanic-segregated neighborhoods (OR, 2.81 [95% CI, 1.96-4.03]), adjusting for HPI. Living in higher SVI (ie, more vulnerable) neighborhoods was associated with greater hospitalization for Black (OR, 1.06 [95% CI, 1.02-1.10]) and non-Hispanic White (OR, 1.04 [95% CI, 1.01-1.06]) veterans.

CONCLUSIONS AND RELEVANCE

In this cohort study of US veterans with COVID-19, HPI captured neighborhood-level risk for COVID-19-related hospitalization for Black, Hispanic, and White veterans comparably with SVI. These findings have implications for the use of HPI and other composite neighborhood deprivation indices that do not explicitly account for segregation. Understanding associations between place and health requires ensuring composite measures accurately account for multiple aspects of neighborhood deprivation and, importantly, variation by race and ethnicity.

Spatial Distribution of COVID-19 Hospitalizations and Associated Risk Factors in Health Insurance Data Using Bayesian Spatial Modelling

The onset of COVID-19 across the world has elevated interest in geographic information systems (GIS) for pandemic management. In Germany, however, most spatial analyses remain at the relatively coarse level of counties. In this study, we explored the spatial distribution of COVID-19 hospitalizations in health insurance data of the AOK Nordost health insurance. Additionally, we explored sociodemographic and pre-existing medical conditions associated with hospitalizations for COVID-19. Our results clearly show strong spatial dynamics of COVID-19 hospitalizations. The main risk factors for hospitalization were male sex, being unemployed, foreign citizenship, and living in a nursing home. The main pre-existing diseases associated with hospitalization were certain infectious and parasitic diseases, diseases of the blood and blood-forming organs, endocrine, nutritional and metabolic diseases, diseases of the nervous system, diseases of the circulatory system, diseases of the respiratory system, diseases of the genitourinary and symptoms, and signs and findings not classified elsewhere.

Association of Area Deprivation Index With Severity of COVID-19 in Pediatric Patients: A Multisite Study of Racially and Ethnically Diverse Children

Area deprivation index (ADI) is associated with the risk of severe COVID-19 in adults. However, this association has not been established in children. Information on ADI, demographics, clinical features, disease severity, and outcomes was analyzed for 3434 children with COVID-19. A multivariate logistic regression revealed that non-Hispanic Asians, extremes of weight, and higher ADI were associated with severe disease.

Influencia del índice de privación social en resultados durante la pandemia de COVID-19

Objetivo

Determinar la relación del índice de privación de la población con la utilización del sistema sanitario, la mala evolución y la mortalidad durante la pandemia de COVID-19.

Método

Estudio de cohorte retrospectivo de personas con infección por SARS-CoV-2 del 1 de marzo de 2020 al 9 de enero de 2022. Se recopilaron datos sociodemográficos, comorbilidad y tratamientos basales prescritos, otros datos basales y el índice de privación, estimado por sección censal. Se realizaron modelos multivariable de regresión logística multinivel para cada variable de resultado: fallecimiento, mala evolución (definida como fallecimiento o ingreso en la unidad de cuidados intensivos), ingreso y visitas a urgencias.

Resultados

La cohorte se compone de 371.237 personas con infección por SARS-CoV-2. En los modelos multivariable se observó un mayor riesgo de fallecimiento, de mala evolución, de ingreso hospitalario o de visita a urgencias en los quintiles de mayor privación en comparación con el quintil de menor privación. Para el riesgo de ser hospitalizado o de acudir a urgencias, en términos generales hubo diferencias entre todos los quintiles. También se observó que estas diferencias se daban en el primer y el tercer periodos de la pandemia para la mortalidad y la mala evolución, y en todos para el riesgo de ser ingresado o de acudir a urgencias.

Conclusiones

Los colectivos con mayor nivel de privación han tenido mayores tasas de mortalidad y de ingreso en comparación con los colectivos con unas tasas de privación más bajas. Es necesario realizar intervenciones que minimicen estas desigualdades.

Hospitalization and survival of solid organ transplant recipients with coronavirus disease 2019: A propensity matched cohort study

BACKGROUND

Solid organ transplant (SOT) recipients are predicted to have worse COVID-19 outcomes due to their compromised immunity. However, this association remains uncertain because published studies have had small sample sizes and variability in chronic comorbidity adjustment.

METHODS

In this retrospective cohort study conducted at a multihospital health system, we compared COVID-19 outcomes and survival up to 60 days following hospital admission in SOT recipients taking baseline immunosuppressants versus hospitalized control patients.

RESULTS

The study included 4,562 patients who were hospitalized with COVID-19 (108 SOT recipients and 4,454 controls) from 03/2020 to 08/2020. Mortality at 60 days was higher for SOT recipients (17% SOT vs 10% control; unadjusted odds ratio (OR) = 1.74, 95% confidence interval (CI) 1.04-2.91, P = 0.04). We then conducted a 1:5 propensity matched cohort analysis (100 SOT recipients; 500 controls) using age, sex, race, body mass index, hypertension, diabetes, chronic kidney disease, liver disease, admission month, and area deprivation index. Within 28 days of admission, SOT recipients had fewer hospital-free days (median; 17 SOT vs 21 control; OR = 0.64, 95%CI 0.46-0.90, P = 0.01) but had similar ICU-free days (OR = 1.20, 95%CI 0.72-2.00, P = 0.49) and ventilator-free days (OR = 0.91, 95%CI 0.53-1.57, P = 0.75). There was no statistically significant difference in 28-day mortality (9% SOT vs 12% control; OR = 0.76, 95%CI 0.36-1.57, P = 0.46) or 60-day mortality (16% SOT vs 14% control; OR = 1.15, 95%CI 0.64-2.08, P = 0.64).

CONCLUSIONS

Hospitalized SOT recipients appear to need additional days of hospital care but can achieve short-term mortality outcomes from COVID-19 that are similar to non-SOT recipients in a propensity matched cohort study.

Using the social vulnerability index to assess COVID-19 vaccine uptake in Louisiana

Using data from the Louisiana Department of Public Health, we explored the spatial relationships between the Social Vulnerability Index (SVI) and COVID-19-related vaccination and mortality rates. Publicly available COVID-19 vaccination and mortality data accrued from December 2020 to October 2021 was downloaded from the Louisiana Department of Health website and merged with the SVI data; geospatial analysis was then performed to identify the spatial association between the SVI and vaccine uptake and mortality rate. Bivariate Moran's I analysis revealed significant clustering of high SVI ranking with low COVID-19 vaccination rates (1.00, p < 0.001) and high smoothed mortality rates (0.61, p < 0.001). Regression revealed that for each 10% increase in SVI ranking, COVID-19 vaccination rates decreased by 3.02-fold (95% CI = 3.73-2.30), and mortality rates increased by a factor of 1.19 (95% CI = 0.99-1.43). SVI values are spatially linked and significantly associated with Louisiana's COVID-19-related vaccination and mortality rates. We also found that vaccination uptake was higher in whites than in blacks. These findings can help identify regions with low vaccination rates and high mortality, enabling the necessary steps to increase vaccination rates in disadvantaged neighborhoods.

Assessing Patient-Reported Financial Hardship in Patients With Cancer in Routine Clinical Care

PURPOSE

Financial hardship (FH) in cancer care is a growing challenge for patients, their caregivers, and health care providers with impact on morbidity and mortality. In this study, we report on a standardized approach to describe the prevalence and predictors for FH as part of routine clinical workflow. We also report on the association of FH with survival in our cancer patient population.

METHODS

This study includes patients who completed a FH screen at least once between 2018 and 2020. Demographics, disease state, and mortality data were extracted from the medical records. Multivariable logistic regression models were used to examine association of sociodemographic and disease variables with FH. By using propensity score weighting to account for differences in demographic and clinical factors between patients with and without FH, we then fit Cox proportional hazards models to examine the relationship between FH and survival.

RESULTS

The study cohort included 31,154 patients. FH was reported by 14% (n = 4,250) of the patients. A significantly higher likelihood of having FH (P < .001 for all) was reported by racial/ethnic minority patients; those who were unemployed/disabled, single, or divorced; patients from disadvantaged neighborhoods; and those who were self-pay or had government insurance. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Patients who endorsed FH had a lower survival (hazard ratio for mortality 1.46).

CONCLUSION

Our study identified key groups more likely to report FH in a relatively affluent population at a large cancer center and showed an adverse association between FH and survival. Further research is needed to develop clinical care pathways for patients at high risk for worse financial and clinical outcomes.

Impact of Social Deprivation on Hospitalization and Intensive Care Unit Admission among COVID-19 Patients: A Systematic Review and Meta-Analysis

Background

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged groups; however, the association between socioeconomic status and healthcare utilization among COVID-19 patients remains unclear. Therefore, a systematic review and meta-analysis was conducted to assess the association between socioeconomic status and hospitalization and intensive care unit admission among COVID-19 patients.

Methods

PubMed, Embase, and the Cochrane Register of Controlled Trials were searched for relevant literature (updated to Jun 2022). Studies that investigated the association of social deprivation with hospitalization and intensive care unit admission in COVID-19 patients were included. The primary outcomes included risk of hospitalization and intensive care unit admission, measured by odds ratio.

Results

Eleven studies covering 2,423,095 patients were included in the meta-analysis. Socially disadvantaged patients had higher odds of hospitalization in comparison to socially advantaged patients (odds ratio 1.25, 95% confidence interval: 1.14 to 1.38; P<0.01). The odds of intensive care unit admission among more deprived patients was not significantly different from that of less deprived patients (odds ratio 1.03, 95% confidence interval: 0.78 to 1.35; P=0.85). These findings were proven robust through subgroup and sensitivity analyses.

Conclusion

Socially disadvantaged populations have higher odds of hospitalization if they become infected with COVID-19. More effective medical support and interventions for these vulnerable populations are required to reduce inequity in healthcare utilization and alleviate the burden on healthcare systems.

Variation in Clinical Treatment and Outcomes by Race Among US Veterans Hospitalized With COVID-19

IMPORTANCE

Patients from racially and ethnically minoritized populations, such as Black and Hispanic patients, may be less likely to receive evidence-based COVID-19 treatments than White patients, contributing to adverse clinical outcomes.

OBJECTIVE

To determine whether clinical treatments and outcomes among patients hospitalized with COVID-19 were associated with race.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study was conducted in 130 Department of Veterans Affairs Medical Centers (VAMCs) between March 1, 2020, and February 28, 2022, with a 60-day follow-up period until May 1, 2022. Participants included veterans hospitalized with COVID-19. Data were analyzed from May 6 to June 2, 2022.

EXPOSURES

Self-reported race.

MAIN OUTCOMES AND MEASURES

Clinical care processes (eg, intensive care unit [ICU] admission; organ support measures, including invasive and noninvasive mechanical ventilation; prone position therapy, and COVID-19-specific medical treatments) were quantified. Clinical outcomes of interest included in-hospital mortality, 60-day mortality, and 30-day readmissions. Outcomes were assessed with multivariable random effects logistic regression models to estimate the association of race with outcomes not attributable to known mediators, such as socioeconomic status and age, while adjusting for potential confounding between outcomes and mediators.

RESULTS

A total of 43 222 veterans (12 135 Black veterans [28.1%]; 31 087 White veterans [71.9%]; 40 717 [94.2%] men) with a median (IQR) age of 71 (62-77) years who were hospitalized with SARS-CoV-2 infection were included. Controlling for site of treatment, Black patients were equally likely to be admitted to the ICU (4806 Black patients [39.6%] vs 13 427 White patients [43.2%]; within-center adjusted odds ratio [aOR], 0.95; 95% CI, 0.88-1.02; P = .17). Two-thirds of patients treated with supplemental oxygen or noninvasive or invasive mechanical ventilation also received systemic steroids, but Black veterans were less likely to receive steroids (within-center aOR, 0.88; 95% CI, 0.80-0.96; P = .004; between-center aOR, 0.67; 95% CI, 0.48-0.96; P = .03). Similarly, Black patients were less likely to receive remdesivir (within-center aOR, 0.89; 95% CI, 0.83-0.95; P < .001; between-center aOR, 0.68; 95% CI, 0.47-0.99; P = .02) or treatment with immunomodulatory drugs (within-center aOR, 0.77; 95% CI, 0.67-0.87; P < .001). After adjusting for patient demographic characteristics, chronic health conditions, severity of acute illness, and receipt of COVID-19-specific treatments, there was no association of Black race with hospital mortality (within-center aOR, 0.98; 95% CI, 0.86-1.10; P = .71) or 30-day readmission (within-center aOR, 0.95; 95% CI, 0.88-1.04; P = .28).

CONCLUSIONS AND RELEVANCE

These findings suggest that Black veterans hospitalized with COVID-19 were less likely to be treated with evidence-based COVID-19 treatments, including systemic steroids, remdesivir, and immunomodulatory drugs.

The Role of Community-Level Factors on Disparities in COVID-19 Infection Among American Indian/Alaska Native Veterans

OBJECTIVES

American Indian and Alaska Native (AI/AN) communities have been disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. This study examines whether neighborhood characteristics mediate AI/AN versus White-non-Hispanic Veteran COVID-19 infection disparities, and whether mediation differs based on proximity to reservations.

METHODS

Using Veteran Health Administration's (VHA) national database of VHA users evaluated for COVID-19 infection (3/1/2020-8/25/2020), we examined whether census tract neighborhood characteristics (percent households overcrowded, without complete plumbing, without kitchen plumbing, and neighborhood socioeconomic status [n-SES]) mediated racial disparities in COVID-19 infection, using inverse odds-weighted logistic models controlling for individual-level characteristics. Using moderated mediation analyses, we assessed whether neighborhood mediating effects on disparities differed for those residing in counties containing/near federally recognized tribal lands (i.e., Contract Health Service Delivery Area [CHSDA] counties) versus not.

RESULTS

The percent of households without complete plumbing, percent without kitchen plumbing, and n-SES partially mediated AI/AN-White-non-Hispanic COVID-19 infection disparities (accounting for 17-35% of disparity) to a similar extent in CHSDA and non-CHSDA counties. The percent of households without kitchen plumbing had stronger mediating effects for CHSDA than non-CHSDA residents.

CONCLUSIONS

Neighborhood-level social determinants of health may contribute to the disproportionate COVID-19 infection burden on AI/ANs; differences are exacerbated among AI/ANs living near reservations.

Impact of Socioeconomic Deprivation on the Local Spread of COVID-19 Cases Mediated by the Effect of Seasons and Restrictive Public Health Measures: A Retrospective Observational Study in Apulia Region, Italy

The aim of this study was to investigate the spatiotemporal association between socioeconomic deprivation and the incidence of COVID-19 and how this association changes through the seasons due to the existence of restrictive public health measures. A retrospective observational study was conducted among COVID-19 cases that occurred in the Apulia region from 29 February 2020 to 31 December 2021, dividing the period into four phases with different levels of restrictions. A generalized estimating equation (GEE) model was applied to test the independent effect of deprivation on the incidence of COVID-19, taking into account age, sex, and regional incidence as possible confounding effects and covariates, such as season and levels of restrictions, as possible modifying effects. The highest incidence was in areas with a very high deprivation index (DI) in winter. During total lockdown, no rate ratio between areas with different levels of DI was significant, while during soft lockdown, areas with very high DI were more at risk than all other areas. The effects of social inequalities on the incidence of COVID-19 changed in association with the seasons and restrictions on public health. Disadvantaged areas showed a higher incidence of COVID-19 in the cold seasons and in the phases of soft lockdown.

Disaggregating disparities: A case study of heterogenous COVID-19 disparities across waves, geographies, social vulnerability, and political lean in Louisiana

While the first wave of COVID-19 primarily impacted urban areas, subsequent waves were more widespread. Most analysis of Covid-19 rates examine state or metropolitan areas, ignoring potential heterogeneity within states and metro areas, over time, and between populations with differing contextual and compositional features. In this study, we compare spatial and temporal trends in Covid-19 cases and deaths in Louisiana, USA, over time and across populations and geographies (New Orleans, other urban areas, suburban, rural) and parish-level political lean. We employ publicly available longitudinal census tract and parish-level Covid-19 data reported from February 27th, 2020 to October 27th, 2021. We find that incidence and mortality rates were initially highest in New Orleans and Democratic areas and higher in other geographies and more conservative areas during subsequent waves. We also find wide relative disparities during the first wave, where increased social vulnerability was associated with increased positivity and incidence across geographies and political contexts. However, relative disparities diverged by geography and political lean and outcome across the remaining waves. This work draws attention to the differential rates of Covid-19 cases and deaths by geography, time, and population throughout the pandemic, and importance of political and geographic boundaries for rates of Covid-19.

Older Adults' Preventive Behaviors During COVID-19 Outbreak: Application of Multiple Disadvantage Model

This study explored older adults' preventive behaviors during the pandemic. A sample of 2982 community-dwelling older adults was extracted from the United States National Health and Aging Trends Study. Results showed that number of preventive behaviors was decreased with rundown neighborhood and age; but increased with Blacks, Hispanics, other ethnic minorities, income, female, number of persons in household, social cohesion, social network, family/peer support, severity of COVID-19 symptoms, and anxiety during COVID-19 outbreak. The study results imply that joint effort of government and ethnic minority advocacy groups in public health education should focus on preventive measures as well as racial disparities in health, and that rejuvenating rundown neighborhoods, promoting neighboring, providing stimulus checks and unemployment insurance, and maintaining connection with family and friends will promote preventive behaviors.

Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis

Background

Area deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.

Methods

In this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.

Results

Deprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.

Conclusions

In more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

The COVID-19 pandemic and associated increases in experiences of assault violence among black men with low socioeconomic status living in Louisiana

Background

The COVID-19 pandemic has had mental health, social, and economic implications among communities with high levels of social disadvantage; this may have impacted community violence rates. The objective of this study was to characterize overall trends in assault and social disadvantage of patients experiencing assault before and during the COVID-19 pandemic.

Methods

All trauma activations at a level one trauma center serving the entire southeast Louisiana region were included during March–August pre-COVID (2018–2019) and during COVID (2020). ICD-10 E-codes were used to identify trauma intent (assault vs. other). Assaults in this context are defined as physical injuries caused by an act of violence wherein the perpetrator was suspected or confirmed to have intended harm, injury, or death to the victim. Social disadvantage was assessed using the Area Deprivation Index (ADI). Change in the monthly rate of assault-trauma activations was assessed using negative binomial regression with adjustment for race, gender, and injury intent. The study was reviewed and approved by the Louisiana State University Health Sciences Institutional Review Board.

Results

A total of 4,233 trauma activations were included. The majority of activations occurred among men. Assaults increased from 27.5% of all activations pre-Covid to 35.6% during the pandemic. Penetrating trauma similarly increased from 29.5% to 35.7% of all activations. Negative binomial regression demonstrated that in addition to this increase in proportion of assaults relative to all activations, the monthly assault rate also increased by 20% during the pandemic. These increases were driven primarily by increased assaults among Black men. ADI rank did not change between study periods.

Conclusions

Health disparities in violence worsened during the pandemic: increased cases of assault occurred disproportionately among Black men, and assaults persisted in occurring primarily among low-ADI communities where burden had been high pre-pandemic. There is a critical need for resources and support to Black men, to mitigate violence and improve racial heath equity.

Temporal trends in within-city inequities in COVID-19 incidence rate by area-level deprivation in Madrid, Spain

Patterns of exposure and policies aiming at reducing physical contact might have changed the social distribution of COVID-19 incidence over the course of the pandemic. Thus, we studied the temporal trends in the association between area-level deprivation and COVID-19 incidence rate by Basic Health Zone (minimum administration division for health service provision) in Madrid, Spain, from March 2020 to September 2021. We found an overall association between deprivation and COVID-19 incidence. This association varied over time; areas with higher deprivation showed higher COVID-19 incidence rates from July to November 2020 and August-September 2021, while, by contrast, higher deprivation areas showed lower COVID-19 incidence rates in December 2020 and July 2021.

Neighborhood Characteristics and Racial Disparities in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Seropositivity in Pregnancy

OBJECTIVE

To quantify the extent to which neighborhood characteristics contribute to racial and ethnic disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity in pregnancy.

METHODS

This cohort study included pregnant patients who presented for childbirth at two hospitals in Philadelphia, Pennsylvania from April 13 to December 31, 2020. Seropositivity for SARS-CoV-2 was determined by measuring immunoglobulin G and immunoglobulin M antibodies by enzyme-linked immunosorbent assay in discarded maternal serum samples obtained for clinical purposes. Race and ethnicity were self-reported and abstracted from medical records. Patients' residential addresses were geocoded to obtain three Census tract variables: community deprivation, racial segregation (Index of Concentration at the Extremes), and crowding. Multivariable mixed effects logistic regression models and causal mediation analyses were used to quantify the extent to which neighborhood variables may explain racial and ethnic disparities in seropositivity.

RESULTS

Among 5,991 pregnant patients, 562 (9.4%) were seropositive for SARS-CoV-2. Higher seropositivity rates were observed among Hispanic (19.3%, 104/538) and Black (14.0%, 373/2,658) patients, compared with Asian (3.2%, 13/406) patients, White (2.7%, 57/2,133) patients, and patients of another race or ethnicity (5.9%, 15/256) (P<.001). In adjusted models, per SD increase, deprivation (adjusted odds ratio [aOR] 1.16, 95% CI 1.02-1.32) and crowding (aOR 1.15, 95% CI 1.05-1.26) were associated with seropositivity, but segregation was not (aOR 0.90, 95% CI 0.78-1.04). Mediation analyses revealed that crowded housing may explain 6.7% (95% CI 2.0-14.7%) of the Hispanic-White disparity and that neighborhood deprivation may explain 10.2% (95% CI 0.5-21.1%) of the Black-White disparity.

CONCLUSION

Neighborhood deprivation and crowding were associated with SARS-CoV-2 seropositivity in pregnancy in the prevaccination era and may partially explain high rates of SARS-CoV-2 seropositivity among Black and Hispanic patients. Investing in structural neighborhood improvements may reduce inequities in viral transmission.

Does Adding a Measure of Social Vulnerability to a Surgical Risk Calculator Improve Its Performance?

BACKGROUND

Emerging literature suggests that measures of social vulnerability should be incorporated into surgical risk calculators. The Social Vulnerability Index (SVI) is a measure designed by the CDC that encompasses 15 socioeconomic and demographic variables at the census tract level. We examined whether adding the SVI into a parsimonious surgical risk calculator would improve model performance.

STUDY DESIGN

The eight-variable Surgical Risk Preoperative Assessment System (SURPAS), developed using the entire American College of Surgeons (ACS) NSQIP database, was applied to local ACS-NSQIP data from 2012 to 2018 to predict 12 postoperative outcomes. Patient addresses were geocoded and used to estimate the SVI, which was then added to the model as a ninth predictor variable. Brier scores and c-indices were compared for the models with and without the SVI.

RESULTS

The analysis included 31,222 patients from five hospitals. Brier scores were identical for eight outcomes and improved by only one to two points in the fourth decimal place for four outcomes with addition of the SVI. Similarly, c-indices were not significantly different (p values ranged from 0.15 to 0.96). Of note, the SVI was associated with most of the eight SURPAS predictor variables, suggesting that SURPAS may already indirectly capture this important risk factor.

CONCLUSION

The eight-variable SURPAS prediction model was not significantly improved by adding the SVI, showing that this parsimonious tool functions well without including a measure of social vulnerability.

Social and Demographic Disparities in the Severity of Multisystem Inflammatory Syndrome in Children

Social constructs are known risk factors for multisystem inflammatory syndrome in children. A review of 206 patients demonstrated that children who were non-Hispanic Black, over the age of 12 years or living in a disadvantaged neighborhood associated with severe multisystem inflammatory syndrome in children (intensive care unit admission, intubation and/or vasopressor use).

Risk factors associated with COVID-19 severity among patients on maintenance haemodialysis: a retrospective multicentre cross-sectional study in the UK

OBJECTIVES

To assess the applicability of risk factors for severe COVID-19 defined in the general population for patients on haemodialysis.

SETTING

A retrospective cross-sectional study performed across thirty four haemodialysis units in midlands of the UK.

PARTICIPANTS

All 274 patients on maintenance haemodialysis who tested positive for SARS-CoV-2 on PCR testing between March and August 2020, in participating haemodialysis centres.

EXPOSURE

The utility of obesity, diabetes status, ethnicity, Charlson Comorbidity Index (CCI) and socioeconomic deprivation scores were investigated as risk factors for severe COVID-19.

MAIN OUTCOMES AND MEASURES

Severe COVID-19, defined as requiring supplemental oxygen or respiratory support, or a C reactive protein of ≥75 mg/dL (RECOVERY trial definitions), and its association with obesity, diabetes status, ethnicity, CCI, and socioeconomic deprivation.

RESULTS

63.5% (174/274 patients) developed severe disease. Socioeconomic deprivation associated with severity, being most pronounced between the most and least deprived quartiles (OR 2.81, 95% CI 1.22 to 6.47, p=0.015), after adjusting for age, sex and ethnicity. There was no association between obesity, diabetes status, ethnicity or CCI with COVID-19 severity. We found no evidence of temporal evolution of cases (p=0.209) or clustering that would impact our findings.

CONCLUSION

The incidence of severe COVID-19 is high among patients on haemodialysis; this cohort should be considered high risk. There was strong evidence of an association between socioeconomic deprivation and COVID-19 severity. Other risk factors that apply to the general population may not apply to this cohort.

Neighborhood deprivation and risk of mortality among men with prostate cancer: Findings from a long-term follow-up study

BACKGROUND

The overall survival rate of prostate cancer (PCa) has improved over the past decades. However, huge socioeconomic and racial disparities in overall and prostate cancer-specific mortality exist. The neighborhood-level factors including socioeconomic disadvantage and lack of access to care may contribute to disparities in cancer mortality. This study examines the impact of neighborhood deprivation on mortality among PCa survivors.

METHODS

North Carolina-Louisiana Prostate Cancer Project (PCaP) data were used. A total of 2113 men, 1046 AA and 1067 EA, with PCa were included in the analysis. Neighborhood deprivation was measured by the Area Deprivation Index (ADI) at the census block group level using data from the US Census Bureau. Quintiles of ADI were created. Cox proportional hazards and competing risk models with mixed effects were performed to estimate the effect of neighborhood deprivation on all-cause and PCa-specific mortality adjusted for age, race, study site, insurance status, and comorbidities.

RESULTS

Participants living in the most deprived neighborhoods had an increased risk for all-cause mortality (quintiles 4 + 5: adjusted hazard ratio [aHR] = 1.51, 95% confidence interval [CI] = 1.16-1.96) compared to those in the least deprived (quintile 1) neighborhoods. The risk of prostate cancer-specific mortality was also higher among those living in the deprived neighborhoods (quintiles 4 + 5: aHR = 1.90, 95% CI = 1.10-3.50) than those in the least deprived neighborhood.

CONCLUSIONS

The findings suggest neighborhood-level resources or health interventions are essential to improve survival among men with PCa. Additional research should focus on the mechanisms of how the neighborhood environment affects mortality.

The association between area deprivation and COVID-19 incidence: a municipality-level spatio-temporal study in Belgium, 2020–2021

Background

In Belgium, current research on socio-economic inequalities in the coronavirus disease 2019 (COVID-19) crisis has mainly focused on excess mortality and data from the first epidemiological wave. The current study adds onto this by examining the association between COVID-19 incidence and area deprivation during the first five wave and interwave periods, thus adding a temporal gradient to the analyses.

Methods

We use all confirmed COVID-19 cases between March 2020 and June 2021 in Belgium, aggregated at the municipality-level. These data were collected by the national laboratory-based COVID-19 surveillance system. A level of area deprivation was assigned to each Belgian municipality using data of three socio-economic variables: the share of unemployed persons in the active population, the share of households without a car and the share of low-educated persons. The spatio-temporal association between COVID-19 incidence and area deprivation was assessed by performing multivariate negative-binomial regression analyses and computing population attributable fractions.

Results

A significant association between COVID-19 incidence and area deprivation was found over the entire study period, with the incidence in the most deprived areas predicted to be 24% higher than in the least deprived areas. This effect was dependent on the period during the COVID-19 crisis. The largest socio-economic inequalities in COVID-19 infections could be observed during wave 2 and wave 3, with a clear disadvantage for deprived areas.

Conclusion

Our results provide new insights into spatio-temporal patterns of socio-economic inequalities in COVID-19 incidence in Belgium. They reveal the existence of inequalities and a shift of these patterns over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00856-9.

Identifying Louisiana communities at the crossroads of environmental and social vulnerability, COVID-19, and asthma

The COVID-19 pandemic has disproportionately affected the socially and environmentally vulnerable, including through indirect effects on other health conditions. Asthma is one such condition, which may be exacerbated by both prolonged adverse in-home exposures if quarantining in unhealthy homes and prolonged outdoor exposures if the ambient air quality is unhealthy or hazardous. As both are often the case in Environmental Justice (EJ) communities, here we have analyzed data at the census tract (CT) level for Louisiana to assess any correlation between social and environmental vulnerability, and health issues like COVID-19 and asthma. Higher Social Vulnerability Index (SVI), Particulate Matter less than 2.5 μm in diameter (PM2.5) and Ozone levels were associated with higher rates of cumulative COVID-19 incidence at various time points during the pandemic, as well as higher average annual asthma hospitalization rates and estimated asthma prevalence. Further, cumulative COVID-19 incidence during the first three months of the pandemic was moderately correlated with both asthma hospitalizations and estimated prevalence, suggesting similar underlying factors may be affecting both conditions. Additionally, 137 CTs were identified where social and environmental vulnerabilities co-existed, of which 75 (55%) had high estimated prevalence of asthma. These areas are likely to benefit from asthma outreach that considers both social and environmental risk factors. Fifteen out of the 137 CTs (11%) not only had higher estimated prevalence of asthma but also a high burden of COVID-19. Further research in these areas may help to elucidate any common social determinants of health that underlie both asthma and COVID-19 burdens, as well as better clarify the possible role of the environment as related to the COVID-19 burden in Louisiana.

Resilience to COVID-19: Socioeconomic Disadvantage Associated With Positive Caregiver-Youth Communication and Youth Preventative Actions

Socioeconomic disadvantage is associated with larger COVID-19 disease burdens and pandemic-related economic impacts. We utilized the longitudinal Adolescent Brain Cognitive Development Study to understand how family- and neighborhood-level socioeconomic disadvantage relate to disease burden, family communication, and preventative responses to the pandemic in over 6,000 youth-caregiver dyads. Data were collected at three timepoints (May-August 2020). Here, we show that both family- and neighborhood-level disadvantage were associated with caregivers' reports of greater family COVID-19 disease burden, less perceived exposure risk, more frequent caregiver-youth conversations about COVID-19 risk/prevention and reassurance, and greater youth preventative behaviors. Families with more socioeconomic disadvantage may be adaptively incorporating more protective strategies to reduce emotional distress and likelihood of COVID-19 infection. The results highlight the importance of caregiver-youth communication and disease-preventative practices for buffering the economic and disease burdens of COVID-19, along with policies and programs that reduce these burdens for families with socioeconomic disadvantage.

Effects of episodic future thinking on reinforcement pathology during smoking cessation treatment among individuals with substance use disorders

RATIONALE

Reinforcer pathology (RP) is a theoretical model based on two processes: delay discounting (DD) and drug demand. Given that RP has been shown to have a predictive value on smoking behaviors, several studies have explored which interventions can reduce RP. Consistent with the RP framework, episodic future thinking (EFT) has shown effects on treatment outcomes and RP processes. The vast majority of studies that assess the effects of EFT on RP consist of experimental studies, and no previous research has tested these effects in a clinical sample of smokers.

OBJECTIVES

The primary aim of this study was to assess the effects of EFT on RP throughout the course of a smoking cessation intervention in smokers with substance use disorders (SUDs).

METHODS

Participants were randomized to cognitive behavior therapy (CBT) + EFT (n = 39) or CBT + EFT + contingency management (n = 33). Cotinine, frequency of EFT practices, cigarette purchase task (CPT), and DD were evaluated in treatment sessions. Mixed-effects model repeated measures analysis was used to explore DD and CPT in-treatment changes as a function of EFT practices and cotinine levels.

RESULTS

Greater practice of the EFT component significantly reduced cigarette demand (p < .020) as well as DD (p = .003). Additionally, a greater reduction in cotinine levels coupled with greater EFT practice led to a greater decrease in cigarette demand (p < .014).

CONCLUSIONS

EFT reduced the two facets of RP in treatment-seeking smokers with SUDs.

Community versus individual risk of SARS-CoV-2 infection in two municipalities of Louisiana, USA: An assessment of Area Deprivation Index (ADI) paired with seroprevalence data over time

OBJECTIVE

Determine whether an individual is at greater risk of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection because of their community or their individual risk factors.

STUDY DESIGN AND SETTING

4,752 records from two large prevalence studies in New Orleans and Baton Rouge, Louisiana were used to assess whether zip code tabulation areas (ZCTA)-level area deprivation index (ADI) or individual factors accounted for risk of infection. Logistic regression models assessed associations of individual-level demographic and socioeconomic factors and the zip code-level ADI with SARS-CoV-2 infection.

RESULTS

In the unadjusted model, there were increased odds of infection among participants residing in high versus low ADI (both cities) and high versus mid-level ADI (Baton Rouge only) zip codes. When individual-level covariates were included, the odds of infection remained higher only among Baton Rouge participants who resided in high versus mid-level ADI ZCTAs. Several individual factors contributed to infection risk. After adjustment for ADI, race and age (Baton Rouge) and race, marital status, household size, and comorbidities (New Orleans) were significant.

CONCLUSIONS

While higher ADI was associated with higher risk of SARS-CoV-2 infection, individual-level participant characteristics accounted for a significant proportion of this association. Additionally, stage of the pandemic may affect individual risk factors for infection.

A systematic review of racial/ethnic and socioeconomic disparities in COVID-19

BACKGROUND

Preliminary evidence from the COVID-19 pandemic shows the presence of health disparities, especially in terms of morbidity and mortality. This study aimed to systematically review the evidence on the association of racial/ethnic and socioeconomic status (SES) with health outcomes and access to healthcare services during the COVID-19 pandemic.

METHODS

We retrieved published evidence from late December 2019 through March 1, 2021. The target population was the population of the countries during the COVID-19 pandemic. The exposures were defined as belonging to racial/ethnic minority groups and/or low SES. The primary outcomes of interest include (1) death from COVID-19, (2) COVID-19 incidence/infection, (3) COVID-19 hospitalization, (4) ICU admission, (5) need for mechanical ventilation, (6) confirmed diagnosis, and (7) access to testing. We systematically synthesized the findings from different studies and provided a narrative explanation of the results.

RESULTS

After removing the duplicate results and screening for relevant titles and abstracts, 77 studies were selected for full-text review. Finally, 52 studies were included in the review. The majority of the studies were from the United States (37 studies). Despite the significant incongruity among the studies, most of them showed that racial/ethnic minority groups had higher risks of COVID-19 infection and hospitalization, confirmed diagnosis, and death. Additionally, most of the studies cited factors such as low level of education, poverty, poor housing conditions, low household income, speaking in a language other than the national language in a country, and living in overcrowded households as risk factors of COVID-19 incidence/infection, death, and confirmed diagnosis. However, findings in terms of the association of lack of health insurance coverage and unemployment with the outcome measures as well as the association of requiring mechanical ventilation, ICU admission, and access to testing for COVID-19 with race/ethnicity were limited and inconsistent.

CONCLUSION

It is evident that racial/ethnic minority groups and those from low SES are more vulnerable to COVID-19; therefore, public health policymakers, practitioners, and clinicians should be aware of these inequalities and strive to narrow the gap by focusing on vulnerable populations. This systematic review also revealed a major incongruity in the definition of the racial/ethnic minority groups and SES among the studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020190105.

Community predictors of COVID-19 cases and deaths in Massachusetts: Evaluating changes over time using geospatially refined data

BACKGROUND

The COVID-19 pandemic has highlighted the need for targeted local interventions given substantial heterogeneity within cities and counties. Publicly available case data are typically aggregated to the city or county level to protect patient privacy, but more granular data are necessary to identify and act upon community-level risk factors that can change over time.

METHODS

Individual COVID-19 case and mortality data from Massachusetts were geocoded to residential addresses and aggregated into two time periods: "Phase 1" (March-June 2020) and "Phase 2" (September 2020 to February 2021). Institutional cases associated with long-term care facilities, prisons, or homeless shelters were identified using address data and modeled separately. Census tract sociodemographic and occupational predictors were drawn from the 2015-2019 American Community Survey. We used mixed-effects negative binomial regression to estimate incidence rate ratios (IRRs), accounting for town-level spatial autocorrelation.

RESULTS

Case incidence was elevated in census tracts with higher proportions of Black and Latinx residents, with larger associations in Phase 1 than Phase 2. Case incidence associated with proportion of essential workers was similarly elevated in both Phases. Mortality IRRs had differing patterns from case IRRs, decreasing less substantially between Phases for Black and Latinx populations and increasing between Phases for proportion of essential workers. Mortality models excluding institutional cases yielded stronger associations for age, race/ethnicity, and essential worker status.

CONCLUSIONS

Geocoded home address data can allow for nuanced analyses of community disease patterns, identification of high-risk subgroups, and exclusion of institutional cases to comprehensively reflect community risk.

Association Of Neighborhood Disadvantage With Racial Disparities In COVID-19 Positivity In Chicago

Racial health inequities exemplified during the COVID-19 crisis have awakened a sense of urgency among public health and policy experts to examine contributing factors. One potential factor includes the socioeconomic disadvantage of racially segregated neighborhoods. This study quantified associations of neighborhood socioeconomic disadvantage in Chicago, Illinois, as measured by the Area Deprivation Index (ADI), with racial disparities in COVID-19 positivity. A retrospective cohort included 16,684 patients tested for COVID-19 at an academic medical center and five community-based testing sites during Chicago's "first wave" (March 12, 2020-June 25, 2020). Patients living in Black majority neighborhoods had two times higher odds of COVID-19 positivity relative to those in White majority neighborhoods. The ADI accounted for 20 percent of the racial disparity; however, COVID-19 positivity remained substantially higher at every decile of the ADI in Black relative to White neighborhoods. The remaining disparities (80 percent) suggest a large, cumulative effect of other structural disadvantages in urban communities of color.

Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status: A Systematic-Review and Meta-analysis

IMPORTANCE

COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.

OBJECTIVE

To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.

DATA SOURCES

A systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.

STUDY SELECTION

Studies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.

DATA EXTRACTION AND SYNTHESIS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.

MAIN OUTCOMES AND MEASURES

The main measures were RRs, ORs, and combined prevalence values.

RESULTS

A total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).

CONCLUSIONS AND RELEVANCE

In this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.

Violent trauma as an indirect impact of the COVID-19 pandemic: A systematic review of hospital reported trauma

INTRODUCTION

The COVID-19 pandemic has exacerbated many social conditions associated with violence. The objective of this systematic review was to examine trends in hospital reported violent trauma associated with the pandemic.

METHODS

Databases were searched in using terms "trauma" or "violence" and "COVID-19," yielding 4,473 records (2,194 de-duplicated). Exclusion criteria included non-hospital based studies and studies not reporting on violent trauma. 44 studies were included in the final review.

RESULTS

Most studies reported no change in violent trauma incidence. Studies predominately assessed trends with violent trauma as a proportion of all trauma. All studies demonstrating an increase in violent trauma were located in the United States.

CONCLUSIONS

A disproportionate rise in violence has been reported within the US. However, most studies examined violent trauma as a proportion of all trauma; results may reflect relative changes from lockdowns. Future studies should examine rates of violent trauma to provide additional context.

COVID-19 Mortality At The Neighborhood Level: Racial And Ethnic Inequalities Deepened In Minnesota In 2020

Substantial racial and ethnic disparities in COVID-19 mortality have been observed at the state and national levels. However, less is known about how race and ethnicity and neighborhood-level disadvantage may intersect to contribute to both COVID-19 mortality and excess mortality during the pandemic. To assess this potential interaction of race and ethnicity with neighborhood disadvantage, we link death certificate data from Minnesota from the period 2017-20 to the Area Deprivation Index to examine hyperlocal disparities in mortality. Black, Indigenous, and people of color (BIPOC) standardized COVID-19 mortality was 459 deaths per 100,000 population in the most disadvantaged neighborhoods compared with 126 per 100,000 in the most advantaged. Total mortality increased in 2020 by 14 percent for non-Hispanic White people and 41 percent for BIPOC. Statistical decompositions show that most of this growth in racial and ethnic disparity is associated with mortality gaps between White people and communities of color within the same levels of area disadvantage, rather than with the fact that White people live in more advantaged areas. Policy interventions to reduce COVID-19 mortality must consider neighborhood context.

Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts

BACKGROUND

Associations between community-level risk factors and COVID-19 incidence have been used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020.

METHODS

Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods from March to October 2020. We examined town-level demographic variables, including population proportions by race, ethnicity, and age, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM2.5), and institutional facilities. We calculated incidence rate ratios (IRR) associated with these predictors and compared these values across the multiple time periods to assess variability in the observed associations over time.

RESULTS

Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage of Black residents (IRR = 1.12 [95%CI: 1.12-1.13]) in early spring, IRR = 1.01 [95%CI: 1.00-1.01] in early fall) and COVID-19 incidence. The association with number of long-term care facility beds per capita also decreased over time (IRR = 1.28 [95%CI: 1.26-1.31] in spring, IRR = 1.07 [95%CI: 1.05-1.09] in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidences of COVID-19 throughout the pandemic (e.g., IRR = 1.30 [95%CI: 1.27-1.33] in spring, IRR = 1.20 [95%CI: 1.17-1.22] in fall). Towns with higher proportions of Latinx residents also had sustained elevated incidence over time (IRR = 1.19 [95%CI: 1.18-1.21] in spring, IRR = 1.14 [95%CI: 1.13-1.15] in fall).

CONCLUSIONS

Town-level COVID-19 risk factors varied with time in this study. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence may have decreased across the first 8 months of the pandemic, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.

Socio-Demographic Factors Involved in a Low-Incidence Phase of SARS-CoV-2 Spread in Sicily, Italy

Background: The present study analysed SARS-CoV-2 cases observed in Sicily and investigated social determinants that could have an impact on the virus spread. Methods: SARS-CoV-2 cases observed among Sicilian residents between the 1 February 2020 and 15 October 2020 have been included in the analyses. Age, sex, date of infection detection, residency, clinical outcomes, and exposure route have been evaluated. Each case has been linked to the census section of residency and its socio-demographic data. Results: A total of 10,114 patients (202.3 cases per 100,000 residents; 95% CI = 198.4–206.2) were analysed: 45.4% were asymptomatic and 3.62% were deceased during follow-up. Asymptomatic or mild cases were more frequent among young groups. A multivariable analysis found a reduced risk of SARS-CoV-2 cases was found in census sections with higher male prevalence (adj-OR = 0.99, 95% CI = 0.99–0.99; p < 0.001) and presence of immigrants (adj-OR = 0.89, 95% CI 0.86–0.92; p < 0.001). Proportion of residents aged <15 years, residents with a university degree, residents with secondary education, extra-urban mobility, presence of home for rent, and presence of more than five homes per building were found to increase the risk of SARS-CoV-2 incidence. Conclusion: Routinely collected socio-demographic data can be predictors of SARS-CoV-2 risk infection and they may have a role in mapping high risk micro-areas for virus transmission.