Associations Between Built Environment, Neighborhood Socioeconomic Status, and SARS-CoV-2 Infection Among Pregnant Women in New York City

Second Survey of County Health Departments of Kansas and COVID-19: Time for Change in Model for Pandemic Response

INTRODUCTION

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) causing COVID-19 (Coronavirus Disease 2019) continues to be widespread in Kansas. County health departments are trying to contain this pandemic.

METHODS

This second survey of Kansas county health department directors occurred from August 7 to September 7, 2020. Since the first survey in April, there have been significant increases in the number of positive cases of COVID-19 and related deaths. Thus, the aim of the study was to re-evaluate county-level containment efforts and assess shortfalls that were identified in the April 2020 survey.

RESULTS

In total, 41 out of 105 directors responded to the survey. Generally, respondents said there were increased supplies for testing, increased testing centers, shorter time to get test results, and in some cases, increased funding. However, the number of people involved in contact tracing had not increased substantially, which was one of the recommended changes for improving containment. Moreover, of those persons who were tested, only a few (18%) counties inquired if they wear masks in public. From comments reported, there was a sense of employees being overwhelmed, especially among the smaller county health departments.

CONCLUSION

As the cases of and deaths from COVID-19 are increasing in the state, especially in high density areas, the respondents to our survey indicated there was continued need for additional funding with easy access, increased staffing, especially for contact tracing, and significant help for effective messaging to improve adherence to public health directives.

Feeling Anxious amid the COVID-19 Pandemic: Psychosocial Correlates of Anxiety Symptoms among Filipina Domestic Helpers in Hong Kong

The COVID-19 pandemic negatively impacts psychological well-being (e.g., anxiety symptoms) among the general population of Hong Kong and migrant Filipina domestic helpers (FDHs). Having to live with the employers by law, FDHs' working environment might affect their well-being during COVID-19 (e.g., household crowdedness/size, insufficiency of protective equipment against COVID-19, increased workload). Research has suggested that coping resources (e.g., social support, COVID-19-related information literacy) and COVID-19-specific worries are associated with people's well-being during COVID-19. This study examined the psychosocial correlates of probable anxiety among FDHs in Hong Kong amid the COVID-19 pandemic. By purposive sampling, FDHs (n = 295) were recruited and invited to complete a cross-sectional survey. Participants' working environment (crowdedness, household size), COVID-19 job arrangements (workload, provision of protective equipment), coping resources (social support, COVID-19 information literacy), COVID-19-specific worries (contracting COVID-19, getting fired if contracting COVID-19), and anxiety symptoms were measured. Multivariate regression results showed that the insufficiency of protective equipment (OR = 1.58, 95%CI: 1.18, 2.11), increased workload (OR = 1.51, 95%CI: 1.02, 2.25), and worries about being fired if getting COVID-19 (OR = 1.32, 95%CI: 1.04, 1.68) were significantly associated with probable anxiety. This was one of the earliest studies to indicate that job arrangements and COVID-19-specific worries significantly contributed to FDHs' anxiety symptoms. Our findings shed light on the importance of addressing employment-related rights and pandemic-specific worries through interventions among FDHs in Hong Kong during pandemic situations.

Outcomes in CME/CPD - Special Collection: How to make the "pyramid" a perpetuum mobile

Continuing medical education (CME) should not be an end in itself, but as expressed in Moore's pyramid, help to improve both individual patient and ultimately community, health. However, there are numerous barriers to translation of physician competence into improvements in community health. To enhance the effect CME may achieve in improving community health the authors suggest a kick-off/keep-on continuum of medical competence, and integration of aspects of public health at all levels from planning to delivery and outcomes measurement in CME.

Investigating the Relationship between the Built Environment and Relative Risk of COVID-19 in Hong Kong

Understanding the relationship between the built environment and the risk of COVID-19 transmission is essential to respond to the pandemic. This study explores the relationship between the built environment and COVID-19 risk using the confirmed cases data collected in Hong Kong. Using the information on the residential buildings and places visited for each case from the dataset, we assess the risk of COVID-19 and explore their geographic patterns at the level of Tertiary Planning Unit (TPU) based on incidence rate (R1) and venue density (R2). We then investigate the associations between several built-environment variables (e.g., nodal accessibility and green space density) and COVID-19 risk using global Poisson regression (GPR) and geographically weighted Poisson regression (GWPR) models. The results indicate that COVID-19 risk tends to be concentrated in particular areas of Hong Kong. Using the incidence rate as an indicator to assess COVID-19 risk may underestimate the risk of COVID-19 transmission in some suburban areas. The GPR and GWPR models suggest a close and spatially heterogeneous relationship between the selected built-environment variables and the risk of COVID-19 transmission. The study provides useful insights that support policymakers in responding to the COVID-19 pandemic and future epidemics.

Socioeconomic status and well-being during COVID-19: A resource-based examination

The authors assess levels and within-person changes in psychological well-being (i.e., depressive symptoms and life satisfaction) from before to during the COVID-19 pandemic for individuals in the United States, in general and by socioeconomic status (SES). The data is from 2 surveys of 1,143 adults from RAND Corporation's nationally representative American Life Panel, the first administered between April-June, 2019 and the second during the initial peak of the pandemic in the United States in April, 2020. Depressive symptoms during the pandemic were higher than population norms before the pandemic. Depressive symptoms increased from before to during COVID-19 and life satisfaction decreased. Individuals with higher education experienced a greater increase in depressive symptoms and a greater decrease in life satisfaction from before to during COVID-19 in comparison to those with lower education. Supplemental analysis illustrates that income had a curvilinear relationship with changes in well-being, such that individuals at the highest levels of income experienced a greater decrease in life satisfaction from before to during COVID-19 than individuals with lower levels of income. We draw on conservation of resources theory and the theory of fundamental social causes to examine four key mechanisms (perceived financial resources, perceived control, interpersonal resources, and COVID-19-related knowledge/news consumption) underlying the relationship between SES and well-being during COVID-19. These resources explained changes in well-being for the sample as a whole but did not provide insight into why individuals of higher education experienced a greater decline in well-being from before to during COVID-19. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Sociodemographic Predictors of SARS-CoV-2 Infection in Obstetric Patients, Georgia, USA

We conducted a cohort study to determine sociodemographic risk factors for severe acute respiratory syndrome coronavirus 2 infection among obstetric patients in 2 urban hospitals in Atlanta, Georgia, USA. Prevalence of infection was highest among women who were Hispanic, were uninsured, or lived in high-density neighborhoods.

Health Disparities in COVID-19: Addressing the Role of Social Determinants of Health in Immune System Dysfunction to Turn the Tide

It is evident that health disparities exist during the COVID-19 pandemic, a pandemic caused by the novel coronavirus SARS-CoV-2. Underlying reasons for COVID-19 health disparities are multi-factorial. However, social determinants, including those regarding socioeconomic status, social inequalities, health behaviors, and stress, may have implications on these disparities. Exposure to one or more of these social determinants is associated with heightened inflammatory responses, particularly increases in the cytokine interleukin-6 (IL-6), as well as immune system dysfunction. Thus, an amplified effect during COVID-19 could occur, potentially resulting in vulnerable patients experiencing an intensified cytokine storm due to a hyperactive and dysfunctional immune response. Further understanding how social determinants play a mechanistic role in COVID-19 disparities could potentially help reduce health disparities overall and in future pandemics.

Severity of COVID-19 in pregnancy: A review of current evidence

Coronavirus disease 19 (COVID-19) has recently emerged as a major threat to human health. Infections range from asymptomatic to severe (increased respiratory rate, hypoxia, significant lung involvement on imaging) or critical (multi-organ failure or dysfunction or respiratory failure requiring mechanical ventilation or high-flow nasal cannula). Current evidence suggests that pregnancy women are at increased risk of severe disease, specifically the need for hospitalization, ICU admission, and mechanical ventilation, and the already complex management of infection with an emerging pathogen may be further complicated by pregnancy. The goal of this review is to provide an overview of what is known about the clinical course of COVID-19 in pregnancy, drawing on (a) experience with other coronaviruses such as SARS and MERS, (b) knowledge of immunologic and physiologic changes in pregnancy and how these might impact infection with SARS-CoV-2, and (c) the current literature reporting outcomes in pregnant women with SARS-CoV-2. We also briefly summarize considerations in management of severe COVID-19 in pregnancy.

Geospatial Analysis of Individual and Community-Level Socioeconomic Factors Impacting SARS-CoV-2 Prevalence and Outcomes

Background

The SARS-CoV-2 pandemic has disproportionately affected racial and ethnic minority communities across the United States. We sought to disentangle individual and census tract-level sociodemographic and economic factors associated with these disparities.

Methods and Findings

All adults tested for SARS-CoV-2 between February 1 and June 21, 2020 were geocoded to a census tract based on their address; hospital employees and individuals with invalid addresses were excluded. Individual (age, sex, race/ethnicity, preferred language, insurance) and census tract-level (demographics, insurance, income, education, employment, occupation, household crowding and occupancy, built home environment, and transportation) variables were analyzed using linear mixed models predicting infection, hospitalization, and death from SARS-CoV-2.Among 57,865 individuals, per capita testing rates, individual (older age, male sex, non-White race, non-English preferred language, and non-private insurance), and census tract-level (increased population density, higher household occupancy, and lower education) measures were associated with likelihood of infection. Among those infected, individual age, sex, race, language, and insurance, and census tract-level measures of lower education, more multi-family homes, and extreme household crowding were associated with increased likelihood of hospitalization, while higher per capita testing rates were associated with decreased likelihood. Only individual-level variables (older age, male sex, Medicare insurance) were associated with increased mortality among those hospitalized.

Conclusions

This study of the first wave of the SARS-CoV-2 pandemic in a major U.S. city presents the cascade of outcomes following SARS-CoV-2 infection within a large, multi-ethnic cohort. SARS-CoV-2 infection and hospitalization rates, but not death rates among those hospitalized, are related to census tract-level socioeconomic characteristics including lower educational attainment and higher household crowding and occupancy, but not neighborhood measures of race, independent of individual factors.

Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents' risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysis

OBJECTIVE

To determine the clinical manifestations, risk factors, and maternal and perinatal outcomes in pregnant and recently pregnant women with suspected or confirmed coronavirus disease 2019 (covid-19).

DESIGN

Living systematic review and meta-analysis.

DATA SOURCES

Medline, Embase, Cochrane database, WHO COVID-19 database, China National Knowledge Infrastructure (CNKI), and Wanfang databases from 1 December 2019 to 6 October 2020, along with preprint servers, social media, and reference lists.

STUDY SELECTION

Cohort studies reporting the rates, clinical manifestations (symptoms, laboratory and radiological findings), risk factors, and maternal and perinatal outcomes in pregnant and recently pregnant women with suspected or confirmed covid-19.

DATA EXTRACTION

At least two researchers independently extracted the data and assessed study quality. Random effects meta-analysis was performed, with estimates pooled as odds ratios and proportions with 95% confidence intervals. All analyses will be updated regularly.

RESULTS

192 studies were included. Overall, 10% (95% confidence interval 7% to 12%; 73 studies, 67 271 women) of pregnant and recently pregnant women attending or admitted to hospital for any reason were diagnosed as having suspected or confirmed covid-19. The most common clinical manifestations of covid-19 in pregnancy were fever (40%) and cough (41%). Compared with non-pregnant women of reproductive age, pregnant and recently pregnant women with covid-19 were less likely to have symptoms (odds ratio 0.28, 95% confidence interval 0.13 to 0.62; I2=42.9%) or report symptoms of fever (0.49, 0.38 to 0.63; I2=40.8%), dyspnoea (0.76, 0.67 to 0.85; I2=4.4%) and myalgia (0.53, 0.36 to 0.78; I2=59.4%). The odds of admission to an intensive care unit (odds ratio 2.13, 1.53 to 2.95; I2=71.2%), invasive ventilation (2.59, 2.28 to 2.94; I2=0%) and need for extra corporeal membrane oxygenation (2.02, 1.22 to 3.34; I2=0%) were higher in pregnant and recently pregnant than non-pregnant reproductive aged women. Overall, 339 pregnant women (0.02%, 59 studies, 41 664 women) with confirmed covid-19 died from any cause. Increased maternal age (odds ratio 1.83, 1.27 to 2.63; I2=43.4%), high body mass index (2.37, 1.83 to 3.07; I2=0%), any pre-existing maternal comorbidity (1.81, 1.49 to 2.20; I2=0%), chronic hypertension (2.0, 1.14 to 3.48; I2=0%), pre-existing diabetes (2.12, 1.62 to 2.78; I2=0%), and pre-eclampsia (4.21, 1.27 to 14.0; I2=0%) were associated with severe covid-19 in pregnancy. In pregnant women with covid-19, increased maternal age, high body mass index, non-white ethnicity, any pre-existing maternal comorbidity including chronic hypertension and diabetes, and pre-eclampsia were associated with serious complications such as admission to an intensive care unit, invasive ventilation and maternal death. Compared to pregnant women without covid-19, those with the disease had increased odds of maternal death (odds ratio 2.85, 1.08 to 7.52; I2=0%), of needing admission to the intensive care unit (18.58, 7.53 to 45.82; I2=0%), and of preterm birth (1.47, 1.14 to 1.91; I2=18.6%). The odds of admission to the neonatal intensive care unit (4.89, 1.87 to 12.81, I2=96.2%) were higher in babies born to mothers with covid-19 versus those without covid-19.

CONCLUSION

Pregnant and recently pregnant women with covid-19 attending or admitted to the hospitals for any reason are less likely to manifest symptoms such as fever, dyspnoea, and myalgia, and are more likely to be admitted to the intensive care unit or needing invasive ventilation than non-pregnant women of reproductive age. Pre-existing comorbidities, non-white ethnicity, chronic hypertension, pre-existing diabetes, high maternal age, and high body mass index are risk factors for severe covid-19 in pregnancy. Pregnant women with covid-19 versus without covid-19 are more likely to deliver preterm and could have an increased risk of maternal death and of being admitted to the intensive care unit. Their babies are more likely to be admitted to the neonatal unit.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020178076.

READERS' NOTE

This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 1 of the original article published on 1 September 2020 (BMJ 2020;370:m3320), and previous updates can be found as data supplements (https://www.bmj.com/content/370/bmj.m3320/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.