Disparities in COVID-19 Incidence, Hospitalizations, and Testing, by Area-Level Deprivation - Utah, March 3-July 9, 2020

Pandemic Readiness: Disparities Among New York City Residents Living in the Epicenter of the COVID-19 Outbreak

BACKGROUND

Queens County was identified as the epicenter of the coronavirus disease 2019 (COVID-19) outbreak in United States, representing a significant proportion of racial and ethnic minorities. As the pandemic surged and new variants emerged, one factor that has not been explored is the level of pandemic readiness (preparedness) in urban communities.

METHODS

This was a cross-sectional study using a survey to assess pandemic readiness among residents in Queens County, New York, which was disseminated online by means of elected officials. The survey included basic demographics, health status, essential supplies (such as food, water, and prescription medication), social support, spatial capacity, and access to COVID-19 health information.

RESULTS

A total of 306 participants completed the survey (59% response rate). Eighty-two percent of participants were not pandemic ready with only 11.4% at beginner-level and 7% advanced-level readiness. Beginner- and advanced-level readiness was more common among participants with college experience. Regarding employment, 85% of participants who were employed were not ready for the pandemic, compared with 68% of those who were not employed. More strikingly, over 60% of participants learned something new by completing the survey.

CONCLUSIONS

This study adds to the existing literature on pandemic preparedness and highlights the need for greater outreach and education among racial and ethnic minorities.

Deprivation, essential and non-essential activities and SARS-CoV-2 infection following the lifting of national public health restrictions in England and Wales

Background

Individuals living in deprived areas in England and Wales undertook essential activities more frequently and experienced higher rates of SARS-CoV-2 infection than less deprived communities during periods of restrictions aimed at controlling the Alpha (B.1.1.7) variant. We aimed to understand whether these deprivation-related differences changed once restrictions were lifted.

Methods

Among 11,231 adult Virus Watch Community Cohort Study participants multivariable logistic regressions were used to estimate the relationships between deprivation and self-reported activities and deprivation and infection (self-reported lateral flow or PCR tests and linkage to National Testing data and Second Generation Surveillance System (SGSS)) between August - December 2021, following the lifting of national public health restrictions.

Results

Those living in areas of greatest deprivation were more likely to undertake essential activities (leaving home for work (aOR 1.56 (1.33 - 1.83)), using public transport (aOR 1.33 (1.13 - 1.57)) but less likely to undertake non-essential activities (indoor hospitality (aOR 0.82 (0.70 - 0.96)), outdoor hospitality (aOR 0.56 (0.48 - 0.66)), indoor leisure (aOR 0.63 (0.54 - 0.74)), outdoor leisure (aOR 0.64 (0.46 - 0.88)), or visit a hairdresser (aOR 0.72 (0.61 - 0.85))). No statistical association was observed between deprivation and infection (P=0.5745), with those living in areas of greatest deprivation no more likely to become infected with SARS-CoV-2 (aOR 1.25 (0.87 - 1.79).

Conclusion

The lack of association between deprivation and infection is likely due to the increased engagement in non-essential activities among the least deprived balancing the increased work-related exposure among the most deprived. The differences in activities highlight stark disparities in an individuals' ability to choose how to limit infection exposure.

Race, Healthcare, and Health Disparities: A Critical Review and Recommendations for Advancing Health Equity

An overwhelming body of evidence points to an inextricable link between race and health disparities in the United States. Although race is best understood as a social construct, its role in health outcomes has historically been attributed to increasingly debunked theories of underlying biological and genetic differences across races. Recently, growing calls for health equity and social justice have raised awareness of the impact of implicit bias and structural racism on social determinants of health, healthcare quality, and ultimately, health outcomes. This more nuanced recognition of the role of race in health disparities has, in turn, facilitated introspective racial disparities research, root cause analyses, and changes in practice within the medical community. Examining the complex interplay between race, social determinants of health, and health outcomes allows systems of health to create mechanisms for checks and balances that mitigate unfair and avoidable health inequalities. As one of the specialties most intertwined with social medicine, emergency medicine (EM) is ideally positioned to address racism in medicine, develop health equity metrics, monitor disparities in clinical performance data, identify research gaps, implement processes and policies to eliminate racial health inequities, and promote anti-racist ideals as advocates for structural change. In this critical review our aim was to (a) provide a synopsis of racial disparities across a broad scope of clinical pathology interests addressed in emergency departments-communicable diseases, non-communicable conditions, and injuries-and (b) through a race-conscious analysis, develop EM practice recommendations for advancing a culture of equity with the potential for measurable impact on healthcare quality and health outcomes.

Patient-facing job role is associated with SARS-CoV-2 positivity among healthcare workers in long term care facilities in Minnesota, August-December, 2020

OBJECTIVE

Healthcare workers (HCWs) in long-term care facilities (LTCFs) are disproportionately affected by severe acute respiratory coronavirus virus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). To characterize factors associated with SARS-CoV-2 positivity among LTCF HCWs, we performed a retrospective cohort study among HCWs in 32 LTCFs in the Minneapolis-St Paul region.

METHODS

We analyzed the outcome of SARS-CoV-2 polymerase chain reaction (PCR) positivity among LTCF HCWs during weeks 34-52 of 2020. LTCF and HCW-level characteristics, including facility size, facility risk score for resident-HCW contact, and resident-facing job role, were modeled in univariable and multivariable generalized linear regressions to determine their association with SARS-CoV-2 positivity.

RESULTS

Between weeks 34 and 52, 440 (20.7%) of 2,130 unique HCWs tested positive for SARS-CoV-2 at least once. In the univariable model, non-resident-facing HCWs had lower odds of infection (odds ratio [OR], 0.50; 95% confidence interval [CI], 0.36-0.70). In the multivariable model, the odds remained lower for non-resident-facing HCW (OR, 0.50; 95% CI, 0.36-0.71), and those in medium- versus low-risk facilities experienced higher odds of testing positive for SARS-CoV-2 (OR, 1.47; 95% CI, 1.08-2.02).

CONCLUSIONS

Our findings suggest that COVID-19 cases are related to contact between HCW and residents in LTCFs. This association should be considered when formulating infection prevention and control policies to mitigate the spread of SARS-CoV-2 in LTCFs.

COVID-19 Vaccination Actual Uptake and Potential Inequalities Due to Socio-Demographic Characteristics: A Population-Based Study in the Umbria Region, Italy

Socio-demographic factors are responsible for health inequalities also in vaccination. The aim of this study was to evaluate their role at the population level through a population-based study performed on the whole population entitled to receive COVID-19 vaccines in the Umbria Region, Italy, and registered to the Regional Healthcare Service as of 28 February 2021. Socio-demographic characteristics and vaccination status in terms of uptake of at least one dose of any available vaccine, completion of the primary vaccination cycle and uptake of the booster doses as of 28 February 2022 were collected from the Umbria regional database. The percentage of eligible population who did not initiate the COVID-19 vaccination, complete the full vaccination cycle and get the booster dose was 11.8%, 1.2% and 21.5%, respectively. A younger age, being a non-Italian citizen, and not holding an exemption for chronic disease/disability and a GP/FP were associated with all the endpoints. Females, as compared to males, were more likely to not initiate the vaccination but less likely to not receive the booster dose. On the contrary, the findings did not show a significant association between the deprivation index and the vaccine uptake. The findings, beyond confirming current knowledge at the population level, provide new inputs for better tailoring vaccination campaigns.

Reversed urban-rural gradient in COVID-19 seroprevalence and related factors in a nationally representative survey, Poland, 29 March to 14 May 2021

BackgroundWe anticipated that people in rural areas and small towns with lower population density, lower connectivity and jobs less dependent on social interaction will be less exposed to COVID-19. Still, other variables correlated with socioeconomic inequalities may have a greater impact on transmission.AimWe investigated how COVID-19 affected rural and urban communities in Poland, focussing on the most exposed groups and disparities in SARS-CoV-2 transmission.MethodsA random digit dial sample of Polish adults stratified by region and age was drawn from 29 March to 14 May 2021. Serum samples were tested for anti-S1 and anti-N IgG antibodies, and positive results in both assays were considered indicative of past infection. Seroprevalence estimates were weighted to account for non-response. Adjusted odds ratios (AORs) were calculated using multivariable logistic regression.ResultsThere was serological evidence of infection in 32.2% (95% CI: 30.2-34.4) of adults in rural areas/small towns (< 50,000 population) and 26.6% (95% CI: 24.9-28.3) in larger cities. Regional SARS-CoV-2 seroprevalence ranged from 23.4% (95% CI: 18.3-29.5) to 41.0% (95% CI: 33.5-49.0) and was moderately positively correlated (R = 0.588; p = 0.017; n = 16) with the proportion of respondents living in rural areas or small cities. Upon multivariable adjustment, both men (AOR = 1.60; 95% CI: 1.09-2.35) and women (AOR = 2.26; 95% CI: 1.58-3.21) from these areas were more likely to be seropositive than residents of larger cities.ConclusionsWe found an inverse urban-rural gradient of SARS-CoV-2 infections during early stages of the COVID-19 pandemic in Poland and suggest that vulnerabilities of populations living in rural areas need to be addressed.

Socio-ecological barriers to access COVID-19 vaccination among Burmese irregular migrant workers in Thailand

Thailand is a migration hub in ASEAN (Association of Southeast Asian Nations), with more than 3.9 million migrant workers, accounting for 10% of the country's workforce. The government of Thailand has moved from a pandemic to an endemic state of living with the SAR-CoV2 virus as a new normal since over half of the population has been vaccinated. There is, however, an estimated 1.3 million irregular migrant workers in Thailand who are not covered by Social Security Schemes (SSS) and are likely to have not been vaccinated. This study examines the socio-ecological barriers to accessing vaccination among Burmese irregular migrant workers in Thailand. Qualitative and quantitative data were collected from NGO (Non-Government Organizations) workers and Burmese irregular migrants through an online survey and in-depth interviews. The study reported that over 90% of Burmese irregular migrants were unvaccinated. The main reasons for the low vaccination rate include exclusion from the vaccine distribution program, high cost of the vaccine, perceived low quality of vaccine, language barriers, lack of vaccine information, private and public discrimination against migrants, fear of being detained and deported, and difficulties in finding time and transportation to go to vaccination centres. The Thai government should employ culturally competent interpreters to disseminate vaccine information and potential side effects to encourage vaccinations in order to prevent further casualties and curb the global health crisis. Moreover, it is imperative that the Thai government provide free vaccines to all immigrants regardless of their status and amnesty from deportation and detention during the vaccination period.

The neighborhood built environment and COVID-19 hospitalizations

Research on the associations between the built environment and COVID-19 outcomes has mostly focused on incidence and mortality. Also, few studies on the built environment and COVID-19 have controlled for individual-level characteristics across large samples. In this study, we examine whether neighborhood built environment characteristics are associated with hospitalization in a cohort of 18,042 individuals who tested positive for SARS-CoV-2 between May and December 2020 in the Denver metropolitan area, USA. We use Poisson models with robust standard errors that control for spatial dependence and several individual-level demographic characteristics and comorbidity conditions. In multivariate models, we find that among individuals with SARS-CoV-2 infection, those living in multi-family housing units and/or in places with higher particulate matter (PM2.5) have a higher incident rate ratio (IRR) of hospitalization. We also find that higher walkability, higher bikeability, and lower public transit access are linked to a lower IRR of hospitalization. In multivariate models, we did not find associations between green space measures and the IRR of hospitalization. Results for non-Hispanic white and Latinx individuals highlight substantial differences: higher PM2.5 levels have stronger positive associations with the IRR of hospitalization for Latinx individuals, and density and overcrowding show stronger associations for non-Hispanic white individuals. Our results show that the neighborhood built environment might pose an independent risk for COVID-19 hospitalization. Our results may inform public health and urban planning initiatives to lower the risk of hospitalization linked to COVID-19 and other respiratory pathogens.

Association between distance to community health care facilities and COVID-19-related mortality across U.S. counties in the COVID-19-vaccine era

OBJECTIVE

COVID-19 has caused tremendous damage to U.S. public health, but COVID vaccines can effectively reduce the risk of COVID-19 infections and related mortality. Our study aimed to quantify the association between proximity to a community healthcare facility and COVID-19 related mortality after COVID vaccines became publicly available and explore how this association varied across racial and ethnic groups.

RESULTS

Residents living farther from a facility had higher COVID-19-related mortality across U.S. counties. This increased mortality incidence associated with longer distances was particularly pronounced in counties with higher proportions of Black and Hispanic populations.

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.

A spatial and contextual exposome-wide association study and polyexposomic score of COVID-19 hospitalization

Environmental exposures have been linked to COVID-19 severity. Previous studies examined very few environmental factors, and often only separately without considering the totality of the environment, or the exposome. In addition, existing risk prediction models of severe COVID-19 predominantly rely on demographic and clinical factors. To address these gaps, we conducted a spatial and contextual exposome-wide association study (ExWAS) and developed polyexposomic scores (PES) of COVID-19 hospitalization leveraging rich information from individuals' spatial and contextual exposome. Individual-level electronic health records of 50 368 patients aged 18 years and older with a positive SARS-CoV-2 PCR/Antigen lab test or a COVID-19 diagnosis between March 2020 and October 2021 were obtained from the OneFlorida+ Clinical Research Network. A total of 194 spatial and contextual exposome factors from 10 data sources were spatiotemporally linked to each patient based on geocoded residential histories. We used a standard two-phase procedure in the ExWAS and developed and validated PES using gradient boosting decision trees models. Four exposome measures significantly associated with COVID-19 hospitalization were identified, including 2-chloroacetophenone, low food access, neighborhood deprivation, and reduced access to fitness centers. The initial prediction model in all patients without considering exposome factors had a testing-area under the curve (AUC) of 0.778. Incorporation of exposome data increased the testing-AUC to 0.787. Similar findings were observed in subgroup analyses focusing on populations without comorbidities and aged 18-24 years old. This spatial and contextual exposome study of COVID-19 hospitalization confirmed previously reported risk factor but also generated novel predictors that warrant more focused evaluation.

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.

Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States

BACKGROUND

COVID-19 is an important public health concern due to its high morbidity, mortality and socioeconomic impact. Its burden varies by geographic location affecting some communities more than others. Identifying these disparities is important for guiding health planning and service provision. Therefore, this study investigated geographical disparities and temporal changes of the percentage of positive COVID-19 tests and COVID-19 incidence risk in North Dakota.

METHODS

COVID-19 retrospective data on total number of tests and confirmed cases reported in North Dakota from March 2020 to September 2021 were obtained from the North Dakota COVID-19 Dashboard and Department of Health, respectively. Monthly incidence risks of the disease were calculated and reported as number of cases per 100,000 persons. To adjust for geographic autocorrelation and the small number problem, Spatial Empirical Bayesian (SEB) smoothing was performed using queen spatial weights. Identification of high-risk geographic clusters of percentages of positive tests and COVID-19 incidence risks were accomplished using Tango's flexible spatial scan statistic. ArcGIS was used to display and visiualize the geographic distribution of percentages of positive tests, COVID-19 incidence risks, and high-risk clusters.

RESULTS

County-level percentages of positive tests and SEB incidence risks varied by geographic location ranging from 0.11% to 13.67% and 122 to 16,443 cases per 100,000 persons, respectively. Clusters of high percentages of positive tests were consistently detected in the western part of the state. High incidence risks were identified in the central and south-western parts of the state, where significant high-risk spatial clusters were reported. Additionally, two peaks (August 2020-December 2020 and August 2021-September 2021) and two non-peak periods of COVID-19 incidence risk (March 2020-July 2020 and January 2021-July 2021) were observed.

CONCLUSION

Geographic disparities in COVID incidence risks exist in North Dakota with high-risk clusters being identified in the rural central and southwest parts of the state. These findings are useful for guiding intervention strategies by identifying high risk communities so that resources for disease control can be better allocated to communities in need based on empirical evidence. Future studies will investigate predictors of the identified disparities so as to guide planning, disease control and health policy.

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.

Mortality among inpatients with bipolar disorders and COVID-19: a propensity score matching analysis in a national French cohort study

BACKGROUND

It remains unknown whether coronavirus disease 2019 (COVID-19) patients with bipolar disorders (BDs) are at an increased risk of mortality. We aimed to establish whether health outcomes and care differed between patients infected with COVID-19 with BD and patients without a diagnosis of severe mental illness.

METHODS

We conducted a population-based cohort study of all patients with identified COVID-19 and respiratory symptoms who were hospitalized in France between February and June 2020. The outcomes were in-hospital mortality and intensive care unit (ICU) admission. We used propensity score matching to control for confounding factors.

RESULTS

In total, 50 407 patients were included, of whom 480 were patients with BD. Patients with BD were 2 years older, more frequently women and had more comorbidities than controls without a diagnosis of severe mental illness. Patients with BD had an increased in-hospital mortality rate (26.6% v. 21.9%; p = 0.034) and similar ICU admission rate (27.9% v. 28.4%, p = 0.799), as confirmed by propensity analysis [odds ratio, 95% confidence interval (OR, 95% CI) for mortality: 1.30 (1.16-1.45), p < 0.0001]. Significant interactions between BD and age and between BD and social deprivation were found, highlighting that the most important inequalities in mortality were observed in the youngest [OR, 95% CI 2.28 (1.18-4.41), p = 0.0015] and most deprived patients with BD [OR, 95% CI 1.60 (1.33-1.92), p < 0.001].

CONCLUSIONS

COVID-19 patients with BD were at an increased risk of mortality, which was exacerbated in the youngest and most deprived patients with BD. Patients with BD should thus be targeted as a high-risk population for severe forms of COVID-19, requiring enhanced preventive and disease management strategies.

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.

SARS-CoV-2 spread and area economic disadvantage in the italian three-tier restrictions: a multilevel approach

BACKGROUND

To face the second wave of COVID-19, Italy implemented a tiered restriction system with different limitation levels (yellow = medium; orange = medium-high, red = high) at the beginning of November 2020. The restrictions systematically reduced the transmission of SARS-CoV-2 with increasing strength for increasing tier. However, it is unknown whether the effect of limitations was equal between provinces with different socioeconomic levels. Therefore, we investigated the association between the province's socioeconomic level and SARS-CoV-2 infection daily reproduction number in each restriction level.

METHODS

We measured the province's socioeconomic level as the percentage of individuals whose 2019 total yearly income was lower than 10,000€, using the measure as a proxy of economic disadvantage. We estimated the daily reproduction number (Rt) at the province level using the SARS-CoV-2 daily incidence data from November 2020 to May 2021. We then used multilevel linear regression models with random intercepts stratified by restriction level to estimate the association between economic disadvantage and Rt. We also adjusted the analyses for potential confounders of the association between the province's economic disadvantage and the Rt: the percentage of people with 0-5 years, the quartiles of population density, and the geographical repartition.

RESULTS

Overall, we found increasing Rt in yellow (+ 0.004 p < 0.01, from Rt = 0.99 to 1.08 in three weeks) and containing effects for the orange (-0.005 p < 0.01, from Rt = 1.03 to 0.93) and the red tier (-0.014 p < 0.01, from Rt = 1.05 to 0.76). More economically disadvantaged provinces had higher Rt levels in every tier, although non-significantly in the yellow level (yellow = 0.001 p = 0.19; orange = 0.002 p = 0.02; red = 0.004 p < 0.01). The results showed that the association between economic disadvantage and Rt differed by level of restriction. The number of days into the restriction and the economic disadvantage had statistically significant interactions in every adjusted model. Compared to better off, more economically disadvantaged provinces had slower increasing trends in yellow and steeper Rt reductions in orange, but they showed slower Rt reductions in the highest tier.

CONCLUSION

Lower tiers were more effective in more economically disadvantaged provinces, while the highest restriction level had milder effects. These results underline the importance of accounting for socioeconomic level when implementing public health measures.

Spatiotemporal evolution of COVID-19 in Portugal's Mainland with self-organizing maps

BACKGROUND

Self-Organizing Maps (SOM) are an unsupervised learning clustering and dimensionality reduction algorithm capable of mapping an initial complex high-dimensional data set into a low-dimensional domain, such as a two-dimensional grid of neurons. In the reduced space, the original complex patterns and their interactions can be better visualized, interpreted and understood.

METHODS

We use SOM to simultaneously couple the spatial and temporal domains of the COVID-19 evolution in the 278 municipalities of mainland Portugal during the first year of the pandemic. Temporal 14-days cumulative incidence time series along with socio-economic and demographic indicators per municipality were analyzed with SOM to identify regions of the country with similar behavior and infer the possible common origins of the incidence evolution.

RESULTS

The results show how neighbor municipalities tend to share a similar behavior of the disease, revealing the strong spatiotemporal relationship of the COVID-19 spreading beyond the administrative borders of each municipality. Additionally, we demonstrate how local socio-economic and demographic characteristics evolved as determinants of COVID-19 transmission, during the 1st wave school density per municipality was more relevant, where during 2nd wave jobs in the secondary sector and the deprivation score were more relevant.

CONCLUSIONS

The results show that SOM can be an effective tool to analysing the spatiotemporal behavior of COVID-19 and synthetize the history of the disease in mainland Portugal during the period in analysis. While SOM have been applied to diverse scientific fields, the application of SOM to study the spatiotemporal evolution of COVID-19 is still limited. This work illustrates how SOM can be used to describe the spatiotemporal behavior of epidemic events. While the example shown herein uses 14-days cumulative incidence curves, the same analysis can be performed using other relevant data such as mortality data, vaccination rates or even infection rates of other disease of infectious nature.

Geographic disparities in COVID-19 testing and outcomes in Florida

BACKGROUND

Understanding geographic disparities in Coronavirus Disease 2019 (COVID-19) testing and outcomes at the local level during the early stages of the pandemic can guide policies, inform allocation of control and prevention resources, and provide valuable baseline data to evaluate the effectiveness of interventions for mitigating health, economic and social impacts. Therefore, the objective of this study was to identify geographic disparities in COVID-19 testing, incidence, hospitalizations, and deaths during the first five months of the pandemic in Florida.  METHODS: Florida county-level COVID-19 data for the time period March-July 2020 were used to compute various COVID-19 metrics including testing rates, positivity rates, incidence risks, percent of hospitalized cases, hospitalization risks, case-fatality rates, and mortality risks. High or low risk clusters were identified using either Kulldorff's circular spatial scan statistics or Tango's flexible spatial scan statistics and their locations were visually displayed using QGIS.

RESULTS

Visual examination of spatial patterns showed high estimates of all COVID-19 metrics for Southern Florida. Similar to the spatial patterns, high-risk clusters for testing and positivity rates and all COVID-19 outcomes (i.e. hospitalizations and deaths) were concentrated in Southern Florida. The distributions of these metrics in the other parts of Florida were more heterogeneous. For instance, testing rates for parts of Northwest Florida were well below the state median (11,697 tests/100,000 persons) but they were above the state median for North Central Florida. The incidence risks for Northwest Florida were equal to or above the state median incidence risk (878 cases/100,000 persons), but the converse was true for parts of North Central Florida. Consequently, a cluster of high testing rates was identified in North Central Florida, while a cluster of low testing rate and 1-3 clusters of high incidence risks, percent of hospitalized cases, hospitalization risks, and case fatality rates were identified in Northwest Florida. Central Florida had low-rate clusters of testing and positivity rates but it had a high-risk cluster of percent of hospitalized cases.

CONCLUSIONS

Substantial disparities in the spatial distribution of COVID-19 outcomes and testing and positivity rates exist in Florida, with Southern Florida counties generally having higher testing and positivity rates and more severe outcomes (i.e. hospitalizations and deaths) compared to Northern Florida. These findings provide valuable baseline data that is useful for assessing the effectiveness of preventive interventions, such as vaccinations, in various geographic locations in the state. Future studies will need to assess changes in spatial patterns over time at lower geographical scales and determinants of any identified patterns.

Economic Migrants and Clinical Course of SARS-CoV-2 Infection: A Follow-Up Study

Objective: To analyze whether social deprivation and economic migrant (EM) status influence the risk of being hospitalized with COVID-19. Methods: This was a retrospective follow-up study including all patients older than 18 years attending the Daroca Health Center in Madrid, Spain, diagnosed with COVID-19 during September 2020. Data on EM status and other sociodemographic, lifestyle and comorbidities that could affect the clinical course of the infection were obtained from electronic medical records. Results: Of the 796 patients positive for COVID-19, 44 (5.53%) were hospitalized. No significant differences were observed between those who were hospitalized and those who were not in the mean of social deprivation index or socioeconomic status, but EM status was associated with the risk of being hospitalized (p = 0.028). Logistic regression models showed that years of age (OR = 1.07; 95% CI: 1.04-1.10), EM status (OR = 5.72; 95% CI: 2.56-12.63) and hypertension (OR = 2.22; 95% CI: 1.01-4.85) were the only predictors of hospitalization. Conclusion: Our data support that EM status, rather than economic deprivation, is the socioeconomic factor associated with the probability of hospital admission for COVID-19 in Madrid, Spain.

Community vulnerability to the COVID-19 pandemic: A narrative synthesis from an ecological perspective

Background

We aimed to conduct a narrative synthesis of components and indicators of community vulnerability to a pandemic and discuss their interrelationships from an ecological perspective.

Methods

We searched from PubMed, Embase, Web of Science, PsycINFO, and Scopus (updated to November 2021) for studies focusing on community vulnerability to a pandemic caused by novel respiratory viruses on a geographic unit basis . Studies that reported the associations of community vulnerability levels with at least one disease morbidity or mortality outcome were included.

Results

Forty-one studies were included. All were about the COVID-19 pandemic. Suitable temperature and humidity environments, advanced social and human development (including high population density and human mobility, connectivity, and occupations), and settings that intensified physical interactions are important indicators of vulnerability to viral exposure. However, the eventual pandemic health impacts are predominant in communities that faced environmental pollution, higher proportions of socioeconomically deprived people, health deprivation, higher proportions of poor-condition households, limited access to preventive health care and urban infrastructure, uneven social and human development, and racism. More stringent social distancing policies were associated with lower COVID-19 morbidity and mortality only in the early pandemic phases. Prolonged social distancing policies can disproportionately burden the socially disadvantaged and racially/ethnically marginalized groups.

Conclusions

Community vulnerability to a pandemic is foremost the vulnerability of the ecological systems shaped by complex interactions between the human and environmental systems.

Registration

PROSPERO (CRD42021266186).

COVID-19 Vaccination in Migrants and Refugees: Lessons Learnt and Good Practices

The COVID-19 pandemic has exacerbated inequalities between low- and high-income countries. Within the latter, a greater impact is seen in the poorest and most vulnerable people, including refugees, asylum seekers, and migrants. They all may experience poor access to quality healthcare or have suboptimal health-seeking behavior, distrust of governments, or fear of detention and deportation if seeking healthcare. Some refugees and migrants may face multiple barriers to vaccination and access to health systems that are relevant to the administration of COVID-19 vaccines, despite the growing inclusion of these populations in public health policies. Several good practices have emerged to ensure the inclusion of these populations in vaccination and healthcare for COVID-19 globally. However, inequalities persist between high-income and low-/middle-income populations. The inequalities in COVID-19 vaccination reflect the already existing ones in common health services worldwide. Further efforts are necessary to reduce such disparities, to protect the vulnerable, and, by extension, the general population. The initiatives organized, both at global and local levels, to support vaccination campaigns represent a notable example of how complex multilevel structures, such as health systems, as well as limited resource health services, can successfully face, even during a health emergency, the challenges related to global health issues.

'I Doubt Myself and Am Losing Everything I Have since COVID Came'-A Case Study of Mental Health and Coping Strategies among Undocumented Myanmar Migrant Workers in Thailand

Migrant populations have always been vulnerable to a high burden of social exclusion, mental disorders, physical illnesses, and economic crises. The current COVID-19 pandemic has further created a frantic plight among them, particularly for undocumented migrant workers in the global south. We have conducted a mixed method study among the undocumented Myanmar migrant workers (UMMWs) in Thailand to explore how the COVID-19 disruption has impacted their mental health and what coping strategies they have adopted. Following the onset of COVID-19 and the recent coup d'état in Myanmar, our current study is the first attempt to understand the mental health status and predicament of this neglected migrant group. A total of 398 UMMWs were included in the online survey, of which 23 participated in qualitative interviews. The major mental health issues reported by the study participants were depression, generalized anxiety disorder, frustration, stress, and panic disorders, while loss of employment, worries about the pandemic, social stigma, lack of access to healthcare, lockdown, and fear of detention were the predominant contributing factors. In response, we identified two key coping mechanisms: coping at a personal level (listening to music, playing online game, praying, and self-motivation) and coping at a social level (chatting with family and friends and visiting religious institutions). These findings point to the importance of policy and intervention programs aimed at upholding mental health at such humanitarian conditions. Sustainable institutional mental health care support and social integration for the migrant workers, irrespective of their legal status, should be ensured.

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.

Missing science: A scoping study of COVID-19 epidemiological data in the United States

Systematic approaches to epidemiologic data collection are critical for informing pandemic responses, providing information for the targeting and timing of mitigations, for judging the efficacy and efficiency of alternative response strategies, and for conducting real-world impact assessments. Here, we report on a scoping study to assess the completeness of epidemiological data available for COVID-19 pandemic management in the United States, enumerating authoritative US government estimates of parameters of infectious transmission, infection severity, and disease burden and characterizing the extent and scope of US public health affiliated epidemiological investigations published through November 2021. While we found authoritative estimates for most expected transmission and disease severity parameters, some were lacking, and others had significant uncertainties. Moreover, most transmission parameters were not validated domestically or re-assessed over the course of the pandemic. Publicly available disease surveillance measures did grow appreciably in scope and resolution over time; however, their resolution with regards to specific populations and exposure settings remained limited. We identified 283 published epidemiological reports authored by investigators affiliated with U.S. governmental public health entities. Most reported on descriptive studies. Published analytic studies did not appear to fully respond to knowledge gaps or to provide systematic evidence to support, evaluate or tailor community mitigation strategies. The existence of epidemiological data gaps 18 months after the declaration of the COVID-19 pandemic underscores the need for more timely standardization of data collection practices and for anticipatory research priorities and protocols for emerging infectious disease epidemics.

Access, socioeconomic environment, and death from COVID-19 in Nebraska

Our study assesses whether factors related to healthcare access in the first year of the pandemic affect mortality and length of stay (LOS). Our cohort study examined hospitalized patients at Nebraska Medicine between April and October 2020 who were tested for SARS-CoV-2 and had a charted sepsis related diagnostic code. Multivariate logistic was used to analyze the odds of mortality and linear regression was used to calculate the parameter estimates of LOS associated with COVID-19 status, age, gender, race/ethnicity, median household income, admission month, and residential distance from definitive care. Among 475 admissions, the odds of mortality is greater among those with older age (OR: 1.04, 95% CI: 1.02-1.07) and residence in an area with low median household income (OR: 2.11, 95% CI: 0.52-8.57), however, the relationship between mortality and wealth was not statistically significant. Those with non-COVID-19 sepsis had longer LOS (Parameter Estimate: -5.11, adjusted 95% CI: -7.92 to -2.30). Distance from definitive care had trends toward worse outcomes (Parameter Estimate: 0.164, adjusted 95% CI: -1.39 to 1.97). Physical and social aspects of access to care are linked to poorer COVID-19 outcomes. Non-COVID-19 healthcare outcomes may be negatively impacted in the pandemic. Strategies to advance patient-centered outcomes in vulnerable populations should account for varied aspects (socioeconomic, residential setting, rural populations, racial, and ethnic factors). Indirect impacts of the pandemic on non-COVID-19 health outcomes require further study.

Understanding COVID-19 Risk in Patients With Immune-Mediated Inflammatory Diseases: A Population-Based Analysis of SARS-CoV-2 Testing

OBJECTIVE

To investigate the incidence of and factors associated with SARS-CoV-2 testing and infection in immune-mediated inflammatory disease (IMID) patients versus matched non-IMID comparators from the general population.

METHODS

We conducted a population-based, matched cohort study among adult residents from Ontario, Canada, from January 2020 to December 2020. We created cohorts for the following IMIDs: rheumatoid arthritis (RA), psoriasis, psoriatic arthritis, ankylosing spondylitis, systemic autoimmune rheumatic diseases, multiple sclerosis (MS), iritis, inflammatory bowel disease (IBD), polymyalgia rheumatica, and vasculitis. Each patient was matched with 5 patients without IMIDs based on sociodemographic factors. We estimated the incidence of SARS-CoV-2 testing and infection in IMID patients and non-IMID patients. Multivariable logistic regressions assessed odds of SARS-CoV-2 infection.

RESULTS

We studied 493,499 patients with IMIDs and 2,466,946 patients without IMIDs. Patients with IMIDs were more likely to have at least 1 SARS-CoV-2 test versus patients without IMIDs (27.4% versus 22.7%), but the proportion testing positive for SARS-CoV-2 was identical (0.9% in both groups). Overall, IMID patients had 20% higher odds of being tested for SARS-CoV-2 (odds ratio 1.20 [95% confidence interval 1.19-1.21]). The odds of SARS-CoV-2 infection varied across IMID groups but was not significantly elevated for most IMID groups compared with non-IMID comparators. The odds of SARS-CoV-2 infection was lower in IBD and MS and marginally higher in RA and iritis.

CONCLUSION

Patients across all IMIDs were more likely to be tested for SARS-CoV-2 versus those without IMIDs. The risk of SARS-CoV-2 infection varied across disease subgroups.

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.

County-Level Social Vulnerability is Associated With In-Hospital Death and Major Adverse Cardiovascular Events in Patients Hospitalized With COVID-19: An Analysis of the American Heart Association COVID-19 Cardiovascular Disease Registry

BACKGROUND

The COVID-19 pandemic has disproportionately affected low-income and racial/ethnic minority populations in the United States. However, it is unknown whether hospitalized patients with COVID-19 from socially vulnerable communities experience higher rates of death and/or major adverse cardiovascular events (MACEs). Thus, we evaluated the association between county-level social vulnerability and in-hospital mortality and MACE in a national cohort of hospitalized COVID-19 patients.

METHODS

Our study population included patients with COVID-19 in the American Heart Association COVID-19 Cardiovascular Disease Registry across 107 US hospitals between January 14, 2020 to November 30, 2020. The Social Vulnerability Index (SVI), a composite measure of community vulnerability developed by Centers for Disease Control and Prevention, was used to classify the county-level social vulnerability of patients' place of residence. We fit a hierarchical logistic regression model with hospital-level random intercepts to evaluate the association of SVI with in-hospital mortality and MACE.

RESULTS

Among 16 939 hospitalized COVID-19 patients in the registry, 5065 (29.9%) resided in the most vulnerable communities (highest national quartile of SVI). Compared with those in the lowest quartile of SVI, patients in the highest quartile were younger (age 60.2 versus 62.3 years) and more likely to be Black adults (36.7% versus 12.2%) and Medicaid-insured (31.1% versus 23.0%). After adjustment for demographics (age, sex, race/ethnicity) and insurance status, the highest quartile of SVI (compared with the lowest) was associated with higher likelihood of in-hospital mortality (OR, 1.25 [1.03-1.53]; P=0.03) and MACE (OR, 1.26 [95% CI, 1.05-1.50]; P=0.01). These findings were not attenuated after accounting for clinical comorbidities and acuity of illness on admission.

CONCLUSIONS

Patients hospitalized with COVID-19 residing in more socially vulnerable communities experienced higher rates of in-hospital mortality and MACE, independent of race, ethnicity, and several clinical factors. Clinical and health system strategies are needed to improve health outcomes for socially vulnerable patients.

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.

Spatial Risk Factors for Pillar 1 COVID-19 Excess Cases and Mortality in Rural Eastern England, UK

Understanding is still developing about spatial risk factors for COVID-19 infection or mortality. This is a secondary analysis of patient records in a confined area of eastern England, covering persons who tested positive for SARS-CoV-2 through end May 2020, including dates of death and residence area. We obtained residence area data on air quality, deprivation levels, care home bed capacity, age distribution, rurality, access to employment centers, and population density. We considered these covariates as risk factors for excess cases and excess deaths in the 28 days after confirmation of positive Covid status relative to the overall case load and death recorded for the study area as a whole. We used the conditional autoregressive Besag-York-Mollie model to investigate the spatial dependency of cases and deaths allowing for a Poisson error structure. Structural equation models were applied to clarify relationships between predictors and outcomes. Excess case counts or excess deaths were both predicted by the percentage of population age 65 years, care home bed capacity and less rurality: older population and more urban areas saw excess cases. Greater deprivation did not correlate with excess case counts but was significantly linked to higher mortality rates after infection. Neither excess cases nor excess deaths were predicted by population density, travel time to local employment centers, or air quality indicators. Only 66% of mortality was explained by locally high case counts. Higher deprivation clearly linked to higher COVID-19 mortality separate from wider community prevalence and other spatial risk factors.

Spatial Risk Factors for Pillar 1 COVID-19 Excess Cases and Mortality in Rural Eastern England, UK

Understanding is still developing about spatial risk factors for COVID-19 infection or mortality. This is a secondary analysis of patient records in a confined area of eastern England, covering persons who tested positive for SARS-CoV-2 through end May 2020, including dates of death and residence area. We obtained residence area data on air quality, deprivation levels, care home bed capacity, age distribution, rurality, access to employment centers, and population density. We considered these covariates as risk factors for excess cases and excess deaths in the 28 days after confirmation of positive Covid status relative to the overall case load and death recorded for the study area as a whole. We used the conditional autoregressive Besag-York-Mollie model to investigate the spatial dependency of cases and deaths allowing for a Poisson error structure. Structural equation models were applied to clarify relationships between predictors and outcomes. Excess case counts or excess deaths were both predicted by the percentage of population age 65 years, care home bed capacity and less rurality: older population and more urban areas saw excess cases. Greater deprivation did not correlate with excess case counts but was significantly linked to higher mortality rates after infection. Neither excess cases nor excess deaths were predicted by population density, travel time to local employment centers, or air quality indicators. Only 66% of mortality was explained by locally high case counts. Higher deprivation clearly linked to higher COVID-19 mortality separate from wider community prevalence and other spatial risk factors.

Health disparities and COVID-19: A retrospective study examining individual and community factors causing disproportionate COVID-19 outcomes in Cook County, Illinois

Early data from the COVID-19 pandemic suggests that the disease has had a disproportionate impact on communities of color with higher infection and mortality rates within those communities. This study used demographic data from the 2018 US census estimates, mortality data from the Cook County Medical Examiner’s office, and testing results from the Illinois Department of Public Health to perform bivariate and multivariate regression analyses to explore the role race plays in COVID-19 outcomes at the individual and community levels. We used the ZCTA Social Deprivation Index (SDI), a measure of ZCTA area level deprivation based on seven demographic characteristics to quantify the socio-economic variation in health outcomes and levels of disadvantage across ZCTAs. Principal findings showed that: 1) while Black individuals make up 22% of Cook County’s population, they account for 28% of the county’s COVID-19 related deaths; 2) the average age of death from COVID-19 is seven years younger for Non-White compared with White decedents; 3) residents of Minority ZCTA areas were 1.02 times as likely to test positive for COVID-19, (Incidence Rate Ratio (IRR) 1.02, [95% CI 0.95, 1.10]); 1.77 times as likely to die (IRR 1.77, [95% CI 1.17, 2.66]); and were 1.15 times as likely to be tested (IRR 1.15, [95% CI 0.99, 1.33]). There are notable differences in COVID-19 related outcomes between racial and ethnic groups at individual and community levels. This study illustrates the health disparities and underlying systemic inequalities experienced by communities of color.

Racial/ethnic and neighborhood disparities in metals exposure during pregnancy in the Northeastern United States

Despite the unequal burden of environmental exposures borne by racially minoritized communities, these groups are often underrepresented in public health research. Here, we examined racial/ethnic disparities in exposure to metals among a multi-ethnic sample of pregnant women. The sample included women enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) pregnancy cohort (N = 382). Urinary metal concentrations (arsenic [As], barium [Ba], cadmium [Cd], cesium [Cs], chromium [Cr], lead [Pb], antimony [Sb]) were measured during mid-pregnancy and information on individual- and neighborhood-level characteristics was ascertained during an in-person interview and from publicly available databases, respectively. Linear regression was used to examine individual and neighborhood characteristics in relation to metal concentrations. Black/Black-Hispanic women had Cd, Cr, Pb, and Sb levels that were 142.0%, 10.9%, 35.0%, and 32.1% higher than White, non-Hispanic women, respectively. Likewise, White-Hispanic women had corresponding levels that were 141.5%, 108.2%, 59.9%, and 38.3% higher. These same metals were also higher among women residing in areas with higher crime, higher diversity, lower educational attainment, lower household income, and higher poverty. Significant disparities in exposure to metals exist and may be driven by neighborhood-level factors. Exposure to metals for pregnant women can be especially harmful. Understanding exposure inequalities and identifying factors that increase risk can help inform targeted public health interventions.

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.

[Health literacy and health crisis: the example of COVID-19]

Implementation and enforcement of COVID-19 control measures are essential to limit the spread of the virus. Unfortunately, these actions are very difficult, if not impossible, for part of the population, mainly present in the socio-economically disadvantaged categories. This difficulty is linked, on the one hand, to the lack of health literacy, which is found to be insufficient among almost a third of the European population, and on the other hand, to their increased exposure to the virus. Difficulty in reading and acquiring health measures therefore leads to a challenge for institutions, a socio-economic gap and impacts on future generations. There is therefore no choice than to invest massively in education and health promotion in the long term to minimize the impact of crises and thus limit the increase in inequalities.

Investigating the association between mass transit adoption and COVID-19 infections in US metropolitan areas

Urbanization introduces the threat of increased epidemic disease transmission resulting from crowding on mass transit. The coronavirus disease 2019 (COVID-19) pandemic, which has directly led to over 600,000 deaths in the US as of July 2021, triggered mass social distancing policies to be enacted as a key deterrent of widespread infections. Social distancing can be challenging in confined spaces required for transportation such as mass transit systems. Little is published regarding the degree to which mass transit system adoption effects impacted the rise of the COVID-19 pandemic in urban centers. Taking an ecological approach where areal data are the unit of observation, this national-scale study aims to measure the association between the adoption of mass transit and COVID-19 spread through confirmed cases in US metropolitan areas. National survey-based transit adoption measures are entered in negative binomial regression models to evaluate differences between areas. The model results demonstrate that mass transit adoption in US metropolitan areas was associated with the magnitude of outbreaks. Higher incidence of COVID-19 early in the pandemic was associated with survey results conveying higher transit use. Increasing weekly bus transit usage in metropolitan statistical areas by one scaled unit was associated with a 1.38 [95% CI: (1.25, 1.90)] times increase in incidence rate of COVID-19; a one scaled unit increase in weekly train transit usage was associated with an increase in incidence rate of 1.54 [95% CI: (1.42, 2.07)] times. These conclusions should inform early action practices in urban centers with busy transit systems in the event of future infectious disease outbreaks. Deeper understanding of these observed associations may also benefit modeling efforts by allowing researchers to include mathematical adjustments or better explain caveats to results when communicating with decision makers and the public in the crucial early stages of an epidemic.

The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France: a population-based analysis

BACKGROUND

Data on health inequalities related to the dynamic of SARS-CoV-2 infection in France are scarce. The aim of this study was to analyse the association between an area-based deprivation indicator and SARS-CoV-2 incidence, positivity, and testing rates between May 2020 and April 2021.

METHODS

We analysed data reported to the Système d'Information de Dépistage Populationnel surveillance system between May 14, 2020 and April 29, 2021, which records the results of all SARS-CoV-2 tests in France. Residential addresses of tested individuals were geocoded to retrieve the associated aggregated units for the statistical information (IRIS) scale, corresponding to an area comprising 2000 inhabitants relatively homogenous in terms of socioeconomic characteristics. A social deprivation score was assigned to each area using the European Deprivation Index (EDI). We fitted negative binomial generalised additive models to model the age-standardised and sex-standardised ratios for SARS-CoV-2 incidence, positivity rates, and testing rates, and to estimate incidence rate ratios (IRRs) and 95% CIs of their association with EDI quintiles, using the first quintile (least deprived) as the reference category, adjusted for week, population density, and region.

FINDINGS

Analyses were based on 70 990 478 SARS-CoV-2 tests, of which 5 000 972 were positive. SARS-CoV-2 incidence was higher in the most deprived areas than the least deprived areas (IRR 1·148 [95% CI 1·138-1·158]) and positivity rates were also higher (IRR 1·283 [1·273-1·294]), whereas testing rates were lower in the most deprived areas than the least deprived areas (IRR 0·905 [0·904-0·907]). SARS-CoV-2 incidence and positivity rates remained higher in the most deprived areas than the least deprived areas during the second and third national lockdowns, and variation in testing rate was observed according to population density.

INTERPRETATION

Our results highlight a positive social gradient between deprivation and the risk of testing positive for SARS-CoV-2, with the highest risk among individuals living in the most deprived areas and a negative social gradient for testing rate. These findings might reflect structural barriers to health-care access in France and lower capacity of deprived populations to benefit from protective measures.

FUNDING

None.

Educational Inequalities in COVID-19 Vaccination: A Cross-Sectional Study of the Adult Population in the Lazio Region, Italy

Several studies reported socioeconomic inequalities during the COVID-19 pandemic. We aimed at investigating educational inequalities in COVID-19 vaccination on 22 December 2021. We used the cohort of all residents in the Lazio Region, Central Italy, established at the beginning of the pandemic to investigate the effects of COVID-19. The Lazio Region has 5.5 million residents, mostly distributed in the Metropolitan Area of Rome (4.3 million inhabitants). We selected those aged 35 years or more who were alive and still residents on 22 December 2021. The cohort included data on sociodemographic, health characteristics, COVID-19 vaccination (none, partial, or complete), and SARS-CoV-2 infection. We used adjusted logistic regression models to analyze the association between level of education and no vaccination. We investigated 3,186,728 subjects (54% women). By the end of 2021, 88.1% of the population was fully vaccinated, and 10.3% were not vaccinated. There were strong socioeconomic inequalities in not getting vaccinated: compared with those with a university degree, residents with a high school degree had an odds ratio (OR) of 1.29 (95% confidence interval, CI, 1.27–1.30), and subjects with a junior high or primary school attainment had an OR = 1.41 (95% CI: 1.40–1.43). Since a comprehensive vaccination against COVID-19 could help reduce socioeconomic inequalities raised with the pandemic, further efforts in reaching the low socioeconomic strata of the population are crucial.

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.

Incidence of SARS-CoV-2 Infection and Related Mortality by Education Level during Three Phases of the 2020 Pandemic: A Population-Based Cohort Study in Rome

Evidence on social determinants of health on the risk of SARS-CoV-2 infection and adverse outcomes is still limited. Therefore, this work investigates educational disparities in the incidence of infection and mortality within 30 days of the onset of infection during 2020 in Rome, with particular attention to changes in socioeconomic inequalities over time. A cohort of 1,538,231 residents in Rome on 1 January 2020, aged 35+, followed from 1 March to 31 December 2020, were considered. Cumulative incidence and mortality rates by education were estimated. Multivariable log-binomial and Cox regression models were used to investigate educational disparities in the incidence of SARS-CoV-2 infection and mortality during the entire study period and in three phases of the pandemic. During 2020, there were 47,736 incident cases and 2281 deaths. The association between education and the incidence of infection changed over time. Till May 2020, low- and medium-educated individuals had a lower risk of infection than that of the highly educated. However, there was no evidence of an association between education and the incidence of SARS-CoV-2 infection during the summer. Lastly, low-educated adults had a 25% higher risk of infection from September to December than that of the highly educated. Similarly, there was substantial evidence of educational inequalities in mortality within 30 days of the onset of infection in the last term of 2020. In Rome, social inequalities in COVID-19 appeared in the last term of 2020, and they strengthen the need for monitoring inequalities emerging from this pandemic.

Social Determinants of Disease: HIV and COVID-19 Experiences

PURPOSE OF REVIEW

The differential impact of the COVID-19 and HIV pandemics on marginalized communities has renewed calls for more robust and deeper investigation into structural and social causes of health inequities contributing to these infections, including underlying factors related to systematic racism. Using the Social Determinants of Health (SDOH) framework, we analyzed parallel and divergent factors associated with COVID-19 and HIV/AIDS and the prevalence of disparate disease in diverse communities. We utilized PRISMA guidelines to identify relevant literature (N = 210 articles) that resulted in a review of 125 articles included in our synthesis.

RECENT FINDINGS

With racial health inequities as a core contributor to disease vulnerability, we also identified other factors such as economic stability, social and community support, the neighborhood and built environment, healthcare access and quality, and education access and quality as important socioecological considerations toward achieving health equity. Our review identifies structural and systematic factors that drive HIV and COVID-19 transmission. Our review highlights the importance of not solely focusing on biomedical interventions as solutions to ending HIV and COVID-19, but rather call for building a more just public health and social service safety net that meets the needs of people at the intersection of multiple vulnerabilities.

Prevalence and risk characteristics of COVID-19 in outpatients: A cross-sectional study of New York-area clinics

Outpatients can be at heightened risk of COVID-19 due to interaction between existing non-communicable diseases in outpatients and infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study measured the magnitude of COVID-19 prevalence and explored related risk characteristics among adult outpatients visiting medicine clinics within a New York state-based tertiary hospital system. Data were compiled from 63,476 adult patients visiting outpatient medicine clinics within a New York-area hospital system between March 1, 2020, and August 28, 2020. The outcome was a clinical diagnosis of COVID-19. Crude and adjusted prevalence ratios (PR) of a COVID-19 were analyzed using univariable and multivariable Poisson regression with robust standard errors. The prevalence of COVID-19 was higher among these outpatients (3.0%) than in the total population in New York State (2.2%) as of August 28, 2020. Multivariable analysis revealed adjusted prevalence ratios significantly greater than one for male sex (PR=1.10), age 40 to 64 compared to <40 (PR=1.19), and racial/ethnic minorities in comparison to White patients (Hispanic: PR=2.76; Black: PR=1.89; and Asian/others: PR=1.56). Nonetheless, factors including the advanced age of ≥65 compared to <40 (PR=0.69) and current smoking compared to non-smoking (PR=0.60) were related to significantly lower prevalence. Therefore, the prevalence of COVID-19 in outpatients was higher than that of the general population. The findings also enabled hypothesis generation that routine clinical measures comprising sex, age, race/ethnicity, and smoking were candidate risk characteristics of COVID-19 in outpatients to be further verified by designs capable of assessing temporal association.

Experiences and impacts of COVID-19 among Pacific Islanders in Los Angeles County

Objective:

To explore and document the experiences and impacts of COVID-19 among Pacific Islander (PI) adults living in Los Angeles County.

Methods:

Study participants completed a brief online demographic questionnaire followed by a 45- to 60-min semi-structured one-on-one interview conducted via Zoom. Participants were asked about two main areas: (1) reasons for high rates of COVID-19 cases among the PI community and its impacts on their community and (2) the impacts of COVID-19 on them as individuals.

Results:

A total of 14 PI adults, a majority of whom were females (76%) with an average age of 39.2 years took part in the study. Participants cited underlying medical conditions, overrepresentation in the essential workforce, multigeneration households, and the collectivistic culture of PIs as possible reasons for high rates of COVID-19 cases in their communities. Impacts of the pandemic included loss of jobs, loss of family and friends, and poor mental health which have been exacerbated by the pandemic.

Conclusion:

This study documents the perspectives of PIs on why rates of COVID-19 are high in their community, their experiences with COVID-19 testing, and the impacts that the pandemic has had on themselves and their community. Findings from this study will assist public health professionals and health care providers in refining services and programs for the PI community.

The Association Between Neighborhood Social Vulnerability and COVID-19 Testing, Positivity, and Incidence in Alabama and Louisiana

Racial/ethnic and socioeconomic disparities in COVID-19 burden have been widely reported. Using data from the state health departments of Alabama and Louisiana aggregated to residential Census tracts, we assessed the relationship between social vulnerability and COVID-19 testing rates, test positivity, and incidence. Data were cumulative for the period of February 27, 2020 to October 7, 2020. We estimated the association of the 2018 Social Vulnerability Index (SVI) overall score and theme scores with COVID-19 tests, test positivity, and cases using multivariable negative binomial regressions. We adjusted for rurality with 2010 Rural-Urban Commuting Area codes. Regional effects were modeled as fixed effects of counties/parishes and state health department regions. The analytical sample included 1160 Alabama and 1105 Louisiana Census tracts. In both states, overall social vulnerability and vulnerability themes were significantly associated with increased COVID-19 case rates (RR 1.57, 95% CI 1.45-1.70 for Alabama; RR 1.36, 95% CI 1.26-1.46 for Louisiana). There was increased COVID-19 testing with higher overall vulnerability in Louisiana (RR 1.26, 95% CI 1.14-1.38), but not in Alabama (RR 0.95, 95% CI 0.89-1.02). Consequently, test positivity in Alabama was significantly associated with social vulnerability (RR 1.66, 95% CI 1.57-1.75), whereas no such relationship was observed in Louisiana (RR 1.05, 95% CI 0.98-1.12). Social vulnerability is a risk factor for COVID-19 infection, particularly among racial/ethnic minorities and those in disadvantaged housing conditions without transportation. Increased testing targeted to vulnerable communities may contribute to reduction in test positivity and overall COVID-19 disparities.

Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7-April 20, 2020

PURPOSE

Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order.

METHODS

Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7-April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI).

RESULTS

Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders.

CONCLUSIONS

Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.

Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic

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Our study uses 50 US states’ public health surveillance datasets to measure COVID-19 outcomes relationships with populational, social, air travel related and environmental factors.

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Found associations are used to predict expected numbers of cases, hospitalizations and deaths due to COVID-19 early in the epidemic.

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The COVID-19 associated factors enplanements, population density, race, humidity and sun exposure predicted COVID-19 outcomes with reasonable accuracy in approximately 50% of states.

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This study models can help public health identify communities at higher risk for rapid growth of cases, hospitalizations and deaths in a future respiratory-disease epidemic like COVID-19.

By 21 October 2020, the coronavirus disease (COVID-19) epidemic in the United States (US) had infected 8.3 million people, resulting in 61,364 laboratory-confirmed hospitalizations and 222,157 deaths. Currently, policymakers are trying to better understand this epidemic, especially the human-to-human transmissibility of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in relation to social, populational, air travel related and environmental exposure factors. Our study used 50 US states’ public health surveillance datasets (January 1-April 1, 2020) to measure associations of confirmed COVID-19 cases, hospitalizations and deaths with these variables. Using the resulting associations and multivariate regression (Negative Binomial and Poisson), predicted cases, hospitalizations and deaths were generated for each US state early in the epidemic. Factors associated with a significantly increased risk of COVID-19 disease, hospitalization and death included: population density, enplanement, Black race and increased sun exposure; in addition, COVID-19 disease and hospitalization were also associated with morning humidity. Although predictions of the number of cases, hospitalizations and deaths due to COVID-19 were not accurate for every state, those states with a combination of large number of enplanements, high population density, high proportion of Black residents, high humidity or low sun exposure may expect more rapid than expected growth in the number of COVID-19 events early in the epidemic.