The social determinants of health and pandemic H1N1 2009 influenza severity

Association of Socioeconomic Status and Reasons for Companion Animal Relinquishment

It is important to understand the reasons for companion animal relinquishment to help reduce the financial and ethical problems arising from too many dogs and cats in shelters. This study investigates the socioeconomic factors and reasons behind companion animal relinquishment in Australia, utilizing data from five animal shelters, over a five-year period (Financial Year 2018/19 to 2022/23). Descriptive statistics reveal that the median Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD) decile of companion animal guardians who relinquished their companion animal was decile 4 out of 10, indicating that they live in areas of lower-than-average socioeconomic status. Cats accounted for 59.4% and dogs for 40.6% of all relinquishments, with more relinquishments from lower socioeconomic deciles (1-5) (cats: 62.6%, dogs: 65.8%). The median age of relinquished cats was 5 months and dogs 16 months, with human factor-related issues (e.g., Housing, Financial Constraints, Human Healthcare) cited in 86% of cases. Descriptive analysis for the five financial years shows a declining trend in numbers of relinquishments, with housing issues (31.2%) identified as the primary reason, followed by ownership decisions (16.2%), financial constraints (11.2%), and human health issues (10.4%). Comparing the reasons for relinquishment between lower (decile 1-5) and higher (decile 6-10) socioeconomic status demonstrated that financial difficulties were a more common reason in lower vs. higher socioeconomic groups, while human health and family-related issues are more common in higher vs. lower socioeconomic groups. These findings highlight the critical role of socioeconomic factors in understanding why people relinquish their companion animals, which can inform targeted interventions to support companion animal welfare across different socioeconomic backgrounds.

Use of Population Weighted Density Index for Coronavirus Spread in the United States

Background: Understanding how population density affected the transmission of COVID-19 is vitally important, since crowded cities were the epicenters for the disease. Since human contact was the main cause of the spread, population-weighted densities have been shown to be a better measure than conventional densities, since the variation in density across subareas matters more than the density in the total area. Objectives: This study investigates the impact of population-weighted density and other demographics on the rate of COVID-19 spread in the United States. Methods: The study considers population-weighted density and many other demographics. The population-weighted density index is the weighted average of density across the tracts, where tracts are weighted by population. Multivariate analysis has been used to determine the elasticity of the spread. Results: Using U.S. county-level data, we calculated the elasticity of COVID-19 spread with respect to population-weighted density to be 0.085 after controlling for other factors. In addition to the density, the proportion of people over 65 years of age, the number of total healthcare workers, and average temperature in each county positively contributed to the case numbers, while education level and income per capita had a negative effect. Discussion: For the spread, understanding the population characteristics and dynamics is as important as understanding the infectious disease itself. This will help policy makers to utilize and reallocate the resources more effectively. If the spread is successfully contained early, there will be less stress placed upon the healthcare system, resulting in better healthcare access for those who are sick. Conclusions: Our analysis suggests that population-weighted density can be a useful tool to control and manage outbreaks, especially within the early stage of the spread. We presented the early dynamics of the spread and recommended a policy measure on how to transfer healthcare workers from low-spread-risk areas to high-spread-risk areas to utilize resources better.

A Study Examining the Impact of County-Level Demographic, Socioeconomic, and Political Affiliation Characteristics on COVID-19 Vaccination Patterns in Indiana

The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R2 values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.

Impact of the COVID-19 pandemic on perceived access and quality of care in German people with parkinsonism

Due to the heterogeneous clinical presentation, people with Parkinsonism (PwP) develop individual healthcare needs as their disease progresses. However, because of limited health resources during the COVID-19 pandemic, many patients were put at risk of inadequate care. All this occurred in the context of inequitable healthcare provision within societies, especially for such vulnerable populations. This study aimed to investigate factors influencing satisfaction and unmet need for healthcare among PwP during the COVID-19 pandemic in Germany. Analyses relied on an anonymous online survey with a 49-item questionnaire. We aimed at describing access to health services before and during the early stages of the pandemic. To this end, a generalized linear model was used to derive significant predictors and a stepwise regression to subsummarize the main factors of perceived inadequate care. In total, 551 questionnaires showed that satisfaction with Parkinsonism-related care decreased significantly during the pandemic (p < 0.001). In particular, factors such as lower educational level, lower perceived expertise of healthcare providers, less confidence in remote care, difficulties in obtaining healthcare, and restricted access to care before the pandemic but also lower densities of neurologists at residence and less ability to overcome barriers were indicative of higher odds to perceive unmet needs (p < 0.05). The results unveil obstacles contributing to reduced access to healthcare during the COVID-19 pandemic for PwP. These findings enable considerations for improved provision of healthcare services to PwP.

Exploratory Study of Determinants of the Spread of COVID-19 before Shelter-in-Place Orders

This study explores the impact of relevant characteristics of counties and their relationship with increases in COVID-19 cases before shelter-in-place (SIP) orders in the U.S. The recent emergence of COVID-19 occurs when there is little understanding of the related factors affecting the growth and spread of the disease. These relationships are examined through an analysis of 672 counties before SIP orders were issued. Areas that experienced the most significant transmission of disease are identified, and their characteristics are analyzed. A meaningful relationship was found between the increase of COVID-19 cases and several factors. Average commute time and the proportion of commuters using transit had a positive relationship. Along with other socio-economic factors, such as median house value and proportion of the Black population, several transportation-related factors had a significant association with the transmission of the disease. The decrease rate of total vehicle miles traveled (VMT) before and after SIP orders also had a solid and positive relationship with the expansion of the disease. The findings suggest that planners and transportation service providers must integrate evolving public health considerations into transportation services which affect the increase in the transmission of infectious diseases.

The Impact of the Social Determinants of Human Health on Companion Animal Welfare

The social determinants of health (SDH) focus on the social, physical and economic factors that impact human health. Studies have revealed that animal guardians face a range of challenges in attaining positive welfare outcomes for their companion animals, which can be influenced by socioeconomic and environmental factors. Despite this, there is a lack of research specifically exploring the relationship between SDH and animal welfare outcomes. Given that the SDH impact on humans, which in turn directly impacts on their companion animal, it is important to adapt an SDH framework for companion animal welfare by characterising the impact of the SDH on companion animal guardians in their attempts to care for their animals and, by extension, the associated welfare outcomes. This paper explores how these human health determinants may impact animal welfare and the possible challenges that may arise for the guardian when attempting to meet their companion animal's welfare needs. By integrating the SDH with other key frameworks, including the five domains model of animal welfare, through multidisciplinary collaboration, this framework can be used to inform future programs aiming to improve animal welfare.

Health disparities in past influenza pandemics: A scoping review of the literature

Objective

The COVID-19 pandemic has exacerbated existing health disparities. To provide a historical perspective on health disparities for pandemic acute respiratory viruses, we conducted a scoping review of the public health literature of health disparities in influenza outcomes during the 1918, 1957, 1968, and 2009 influenza pandemics.

Methods

We searched for articles examining socioeconomic or racial/ethnic disparities in any population, examining any influenza-related outcome (e.g., incidence, hospitalizations, mortality), during the 1918, 1957, 1968, and 2009 influenza pandemics. We conducted a structured search of English-written articles in PubMed supplemented by a snowball of articles meeting inclusion criteria.

Results

A total of 29 articles met inclusion criteria, all but one focusing exclusively on the 1918 or 2009 pandemics. Individuals of low socioeconomic status, or living in low socioeconomic status areas, experienced higher incidence, hospitalizations, and mortality in the 1918 and 2009 pandemics. There were conflicting results regarding racial/ethnic disparities during the 1918 pandemic, with differences in magnitude and direction by outcome, potentially due to issues in data quality by race/ethnicity. Racial/ethnic minorities had generally higher incidence, mortality, and hospitalization rates in the 1957 and 2009 pandemics.

Conclusion

Individuals of low socioeconomic status and racial/ethnic minorities have historically experienced worse influenza outcomes during pandemics. These historical patterns can inform current research to understand disparities in the ongoing COVID-19 pandemic and future pandemics.

Inequality, public health, and COVID-19: an analysis of the Spanish case by municipalities

The main objective of this work is to analyze whether inequality in income distribution has an effect on COVID-19 incidence and mortality rates during the first wave of the pandemic, and how the public health system mitigates these effects. To this end, the case of 819 Spanish municipalities is used, and a linear cross-sectional model is estimated. The results obtained allow us to conclude that a higher level of income inequality generates a higher rate of infections but not deaths, highlighting the importance of the Spanish National Health Service, which does not distinguish by income level. Likewise, early detection of infection measured by the number of primary care centers per 100,000 inhabitants, access to health care for the treatment of the most severe cases, unemployment as a proxy for job insecurity, climatic conditions, and population density are also important factors that determine how COVID-19 affects the population.

Geographical variations and district-level factors associated with COVID-19 mortality in Indonesia: a nationwide ecological study

BACKGROUND

Ensuring health equity, especially for vulnerable populations in less developed settings with poor health system is essential for the current and future global health threats. This study examined geographical variations of COVID-19 mortality and its association with population health characteristics, health care capacity in responding pandemic, and socio-economic characteristics across 514 districts in Indonesia.

METHODS

This nationwide ecological study included aggregated data of COVID-19 cases and deaths from all 514 districts in Indonesia, recorded in the National COVID-19 Task Force database, during the first two years of the epidemic, from 1 March 2020 to 27 February 2022. The dependent variable was district-level COVID-19 mortality rate per 100,000 populations. The independent variables include district-level COVID-19 incidence rate, population health, health care capacity, and socio-demographics data from government official sources. We used multivariable ordinal logistic regression to examine factors associated with higher mortality rate.

RESULTS

Of total 5,539,333 reported COVID-19 cases, 148,034 (2.7%) died, and 5,391,299 (97.4%) were recovered. The district-level mortality rate ranged from 0 to 284 deaths per 100,000 populations. The top five districts with the highest mortality rate were Balikpapan (284 deaths per 100,000 populations), Semarang (263), Madiun (254), Magelang (250), and Yogyakarta (247). A higher COVID-19 incidence (coefficient 1.64, 95% CI 1.22 to 1.75), a higher proportion of ≥ 60 years old population (coefficient 0.26, 95% CI 0.06 to 0.46), a higher prevalence of diabetes mellitus (coefficient 0.60, 95% CI 0.37 to 0.84), a lower prevalence of obesity (coefficient -0.32, 95% CI -0.56 to -0.08), a lower number of nurses per population (coefficient -0.27, 95% CI -0.50 to -0.04), a higher number of midwives per population (coefficient 0.32, 95% CI 0.13 to 0.50), and a higher expenditure (coefficient 0.34, 95% CI 0.10 to 0.57) was associated with a higher COVID-19 mortality rate.

CONCLUSION

COVID-19 mortality rate in Indonesia was highly heterogeneous and associated with higher COVID-19 incidence, different prevalence of pre-existing comorbidity, healthcare capacity in responding the pandemic, and socio-economic characteristics. This study revealed the need of controlling both COVID-19 and those known comorbidities, health capacity strengthening, and better resource allocation to ensure optimal health outcomes for vulnerable population.

Incorporating social determinants of health into the mathematical modeling of HIV/AIDS

Currently, it is estimated that 37.6 million people are living with the HIV/AIDS virus worldwide, placing HIV/AIDS among the ten leading causes of death, mostly among low- and lower-middle-income countries. Despite the effective intervention in the prevention and treatment, this reduction did not occur equally among populations, subpopulations and geographic regions. This difference in the occurrence of the disease is associated with the social determinants of health (SDH), which could affect the transmission and maintenance of HIV. With the recognition of the importance of SDH in HIV transmission, the development of mathematical models that incorporate these determinants could increase the accuracy and robustness of the modeling. This article aims to propose a theoretical and conceptual way of including SDH in the mathematical modeling of HIV/AIDS. The theoretical mathematical model with the Social Determinants of Health has been developed in stages. For the selection of SDH that were incorporated into the model, a narrative literature review was conducted. Secondly, we proposed an extended model in which the population (N) is divided into Susceptible (S), HIV-positive (I), Individual with AIDS (A) and individual under treatment (T). Each SDH had a different approach to embedding in the model. We performed a calibration and validation of the model. A total of 31 SDH were obtained in the review, divided into four groups: Individual Factors, Socioeconomic Factors, Social Participation, and Health Services. In the end, four determinants were selected for incorporation into the model: Education, Poverty, Use of Drugs and Alcohol abuse, and Condoms Use. the section "Numerical simulation" to simulate the influence of the poverty rate on the AIDS incidence and mortality rates. We used a Brazilian dataset of new AIDS cases and deaths, which is publicly available. We calibrated the model using a multiobjective genetic algorithm for the years 2003 to 2019. To forecast from 2020 to 2035, we assumed two lines of poverty rate representing (i) a scenario of increasing and (ii) a scenario of decreasing. To avoid overfitting, we fixed some parameters and estimated the remaining. The equations presented with the chosen SDH exemplify some approaches that we can adopt when thinking about modeling social effects on the occurrence of HIV. The model was able to capture the influence of the employment/poverty on the HIV/AIDS incidence and mortality rates, evidencing the importance of SDOH in the occurrence of diseases. The recognition of the importance of including the SDH in the modeling and studies on HIV/AIDS is evident, due to its complexity and multicausality. Models that do not take into account in their structure, will probably miss a great part of the real trends, especially in periods, as the current on, of economic crisis and strong socioeconomic changes.

Knowledge, Attitude and Practice towards the COVID-19 Pandemic: A Cross-Sectional Survey Study among the General Public in the Kingdom of Saudi Arabia

Background: The novel coronavirus disease 2019 (COVID-19) is an infectious disease that has been spreading worldwide in an unprecedented manner. The knowledge, attitude and practices of the general population play a vital role in prevention of COVID-19. Objectives: The present study aimed to assess the COVID-19-related knowledge, attitudes and practices of the general public of Sakaka, Saudi Arabia, to identify which populations show low levels of knowledge, attitudes and practices towards COVID-19, making them highly likely to remain vulnerable during the pandemic. Methodology: For this study, a nineteen-item closed-ended questionnaire was hand delivered to the general public, including patients and other hospital attendees attending the Outpatient Department of the College of Dentistry, Jouf University, Saudi Arabia. The research questions focused on the demographic information, knowledge, attitude and practices related to COVID-19. Data analysis is presented through tables and descriptive methods. Results: A total of 722 participants took part in the survey questionnaire. The majority of the respondents belonged to the age group of 28–37 years (n = 320; 44.3%), with female participants (n = 419; 58.0%) outnumbering the male participants (n = 303; 42.0%). Most of the respondents had good knowledge, attitudes and practices towards COVID-19. Patients aged 28–37 years (p = 0.000) with a master’s degree (p = 0.011) and government employees (p = 0.000) had significantly better knowledge than their counterparts. Significantly optimistic attitudes were noticed in participants aged 28–37 years (p = 0.000) with a master’s degree (p = 0.000), the married (p = 0.047) and government employees (p = 0.000). Government employees (p = 0.014) had significantly better practices. Conclusions: Overall, the participants of this study had good COVID-19-related knowledge, attitudes and practices. These findings would be useful in motivating the general population to follow the precautionary measures that will aid in prevention of COVID-19. Furthermore, the findings may help policymakers identify the target populations, especially the less educated and older adults, for COVID-19 prevention and health education.

Explaining the deprivation gap in COVID-19 mortality rates: A decomposition analysis of geographical inequalities in England

One of the most consistent and worrying features of the COVID-19 pandemic globally has been the disproportionate burden of the epidemic in the most deprived areas. Most of the literature so far though has focused on estimating the extent of these inequalities. There has been much less attention paid to exploring the main pathways underpinning them. In this study, we employ the syndemic pandemic theoretical framework and apply novel decomposition methods to investigate the proportion of the COVID-19 mortality gap by area-level deprivation in England during the first wave of the pandemic (January to July 2020) was accounted for by pre-existing inequalities in the compositional and contextual characteristics of place. We use a decomposition approach to explicitly quantify the independent contribution of four inequalities pathways (vulnerability, susceptibility, exposure and transmission) in explaining the more severe COVID-19 outcomes in the most deprived local authorities compared to the rest. We find that inequalities in transmission (73%) and in vulnerability (49%) factors explained the highest proportion of mortality by deprivation. Our results suggest that public health agencies need to develop short- and long-term strategies to alleviate these underlying inequalities in order to alleviate the more severe impacts on the most vulnerable communities.

Health-related and socio-economic burden of the COVID-19 pandemic in Vienna

Previous pandemics have rarely affected everyone equally and, so far, the COVID-19 pandemic is no exception. Emerging evidence has shown that incidence rate, hospitalisation rate, and mortality due to COVID-19 are higher among people in lower socio-economic position (SEP). In addition, first investigations indicate that not everyone is equally affected by this pandemic's collateral public health damage. Using a stratified random sample of 1,004 participants living in Vienna, a Central European city with approximately 1.9 million inhabitants, this study analysed the distribution of 10 adverse health-related and socio-economic outcomes attributable to the COVID-19 pandemic across socio-economic strata. To this end, we estimated differences in the incidence rate of these outcomes by SEP and each of its indicators using zero-inflated Poisson and logistic regression models, adjusted for age and gender. Data were collected during first lockdown measures between 27 April and 17 May 2020. Differences in the incidence rate between the two lowest and two highest SEP groups were clearly visible. Participants in the lowest SEP category had a 32.96% higher incidence rate (IRR = 1.333 [95% CI: 1.079-1.639]), and participants in the second lowest SEP category had a 44.69% higher incidence rate (IRR = 1.447 [95% CI: 1.190-1.760]) compared with participants in the highest SEP category. In sum, 6 out of 10 adverse COVID-19-related outcomes were, to a greater or lesser extent, disproportionately experienced by Viennese residents in lower SEP. Inequalities were most visible between income groups and for the outcomes job loss, worsening of the financial situation, and worse mental health. These results strengthen and extend the current evidence on the unequally distributed burden of the COVID-19 pandemic. In light of effect heterogeneity across SEP indicators, we encourage future investigators to pay increased attention to their operationalisation of SEP. Such awareness will help to correctly identify those in most urgent need of supportive polices.

Lower class people suffered more (but perceived fewer risk disadvantages) during the COVID-19 pandemic

Does COVID-19 affect people of all classes equally? In the current research, we focus on the social issue of risk inequality during the early stages of the COVID-19 pandemic. Using a nationwide survey conducted in China (N = 1,137), we predicted and found that compared to higher-class individuals, lower-class participants reported a stronger decline in self-rated health as well as economic well-being due to the COVID-19 outbreak. At the same time, we examined participants' beliefs regarding the distribution of risks. The results demonstrated that although lower-class individuals were facing higher risks, they expressed lesser belief in such a risk inequality than their higher-class counterparts. This tendency was partly mediated by their stronger endorsement of system-justifying beliefs. The findings provide novel evidence of the misperception of risk inequality among the disadvantaged in the context of COVID-19. Implications for science and policy are discussed.

Pandemic inequity in a megacity: a multilevel analysis of individual, community and healthcare vulnerability risks for COVID-19 mortality in Jakarta, Indonesia

INTRODUCTION

Worldwide, the 33 recognised megacities comprise approximately 7% of the global population, yet account for 20% COVID-19 deaths. The specific inequities and other factors within megacities that affect vulnerability to COVID-19 mortality remain poorly defined. We assessed individual, community-level and healthcare factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning 2 March 2020 to 31 August 2021.

METHODS

This retrospective cohort included residents of Jakarta, Indonesia, with PCR-confirmed COVID-19. We extracted demographic, clinical, outcome (recovered or died), vaccine coverage data and disease prevalence from Jakarta Health Office surveillance records, and collected subdistrict level sociodemographics data from various official sources. We used multilevel logistic regression to examine individual, community and subdistrict-level healthcare factors and their associations with COVID-19 mortality.

RESULTS

Of 705 503 cases with a definitive outcome by 31 August 2021, 694 706 (98.5%) recovered and 10 797 (1.5%) died. The median age was 36 years (IQR 24-50), 13.2% (93 459) were <18 years and 51.6% were female. The subdistrict level accounted for 1.5% of variance in mortality (p<0.0001). Mortality ranged from 0.9 to 1.8% by subdistrict. Individual-level factors associated with death were older age, male sex, comorbidities and age <5 years during the first wave (adjusted OR (aOR)) 1.56, 95% CI 1.04 to 2.35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1.35, 95% CI 1.17 to 1.55; reference: wealthiest quarter) and high population density (aOR for the highest density 1.34, 95% CI 1.14 to 2.58; reference: the lowest). Healthcare factor associated with death was low vaccine coverage (aOR for the lowest coverage 1.25, 95% CI 1.13 to 1.38; reference: the highest).

CONCLUSION

In addition to individual risk factors, living in areas with high poverty and density, and low healthcare performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.

Influence of socioeconomic status on functional recovery after ARDS caused by SARS-CoV-2: a multicentre, observational study

INTRODUCTION

Prognosis of patients with COVID-19 depends on the severity of the pulmonary affection. The most severe cases may progress to acute respiratory distress syndrome (ARDS), which is associated with a risk of long-term repercussions on respiratory function and neuromuscular outcomes. The functional repercussions of severe forms of COVID-19 may have a major impact on quality of life, and impair the ability to return to work or exercise. Social inequalities in healthcare may influence prognosis, with socially vulnerable individuals more likely to develop severe forms of disease. We describe here the protocol for a prospective, multicentre study that aims to investigate the influence of social vulnerability on functional recovery in patients who were hospitalised in intensive care for ARDS caused by COVID-19. This study will also include an embedded qualitative study that aims to describe facilitators and barriers to compliance with rehabilitation, describe patients' health practices and identify social representations of health, disease and care.

METHODS AND ANALYSIS

The "Functional Recovery From Acute Respiratory Distress Syndrome (ARDS) Due to COVID-19: Influence of Socio-Economic Status" (RECOVIDS) study is a mixed-methods, observational, multicentre cohort study performed during the routine follow-up of post-intensive care unit (ICU) functional recovery after ARDS. All patients admitted to a participating ICU for PCR-proven SARS-CoV-2 infection and who underwent chest CT scan at the initial phase AND who received respiratory support (mechanical or not) or high-flow nasal oxygen, AND had ARDS diagnosed by the Berlin criteria will be eligible. The primary outcome is the presence of lung sequelae at 6 months after ICU discharge, defined either by alterations on pulmonary function tests, oxygen desaturation during a standardised 6 min walk test or fibrosis-like pulmonary findings on chest CT. Patients will be considered to be socially disadvantaged if they have an "Evaluation de la Précarité et des Inégalités de santé dans les Centres d'Examen de Santé" (EPICES) score ≥30.17 at inclusion.

ETHICS AND DISSEMINATION

The study protocol and the informed consent form were approved by an independent ethics committee (Comité de Protection des Personnes Sud Méditerranée II) on 10 July 2020 (2020-A02014-35). All patients will provide informed consent before participation. Findings will be published in peer-reviewed journals and presented at national and international congresses.

TRIAL REGISTRATION NUMBER

NCT04556513.

Citizenship Matters: Non-Citizen COVID-19 Mortality Disparities in New York and Los Angeles

U.S. non-citizen residents are burdened by inequitable access to socioeconomic resources, potentially placing them at heightened risk of COVID-19-related disparities. However, COVID-19 impacts on non-citizens are not well understood. Accordingly, the current study investigated COVID-19 mortality disparities within New York (NYC) and Los Angeles (LAC) to test our hypothesis that areas with large proportions of non-citizens will have disproportionately high COVID-19 mortality rates. We examined ecological associations between March 2020–January 2021 COVID-19 mortality rates (per 100,000 residents) and percent non-citizens (using ZIP Code Tabulation Areas (ZCTA) for NYC and City/Community units of analysis for LAC) while controlling for sociodemographic factors. Multiple linear regression analyses revealed significant positive associations between the percentage of non-citizen residents and COVID-19 mortality rates in NYC (95% CI 0.309, 5.181) and LAC (95% CI 0.498, 8.720). Despite NYC and LAC policies intended to provide sanctuary and improve healthcare access for non-citizen residents, communities with larger proportions of non-citizens appear to endure higher COVID-19 mortality rates. The challenges that non-citizens endure—e.g., inequitable access to public benefits—may discourage help-seeking behaviors. Thus, improved health surveillance, public health messaging, and sanctuary policies will be essential for reducing COVID-19 mortality disparities in communities with large shares of non-citizens.

Striving for Health Equity: The Importance of Social Determinants of Health and Ethical Considerations in Pandemic Preparedness Planning

Since the WHO's "Influenza Pandemic Preparedness Plan" in 1999, pandemic preparedness plans at the international and national level have been constantly adapted with the common goal to respond early to outbreaks, identify risks, and outline promising interventions for pandemic containment. Two years into the COVID-19 pandemic, public health experts have started to reflect on the extent to which previous preparations have been helpful as well as on the gaps in pandemic preparedness planning. In the present commentary, we advocate for the inclusion of social and ethical factors in future pandemic planning-factors that have been insufficiently considered so far, although social determinants of infection risk and infectious disease severity contribute to aggravated social inequalities in health.

Spatiotemporal analysis of urban road congestion during and post COVID-19 pandemic in Shanghai, China

Coronavirus Disease 2019 (COVID-19) has become one of the most serious global health crises in decades and tremendously influence the human mobility. Many residents changed their travel behavior during and after the pandemic, especially for a certain percentage of public transport users who chose to drive their owned vehicles. Thus, urban roadway congestion has been getting worse, and the spatiotemporal congestion patterns has changed significantly. Understanding spatiotemporal heterogeneity of urban roadway congestion during and post the pandemic is essential for mobility management. In this study, an analytical framework was proposed to investigate the spatiotemporal heterogeneity of urban roadway congestion in Shanghai, China. First, the matrix of average speed in each traffic analysis zones (TAZs) was calculated to extract spatiotemporal heterogeneity variation features. Second, the heterogenous component of each TAZ was extracted from the overall traffic characteristics using robust principal component analysis (RPCA). Third, clustering analysis was employed to explain the spatiotemporal distribution of heterogeneous traffic characteristics. Finally, fluctuation features of these characteristics were analyzed by iterated cumulative sums of squares (ICSS). The case study results suggested that the urban road traffic state evolution was complicated and varied significantly in different zones and periods during the long-term pandemic. Compared with suburban areas, traffic conditions in city central areas are more susceptible to the pandemic and other events. In some areas, the heterogeneous component shows opposite characteristics on working days and holidays with others. The key time nodes of state change for different areas have commonness and individuality. The proposed analytical framework and empirical results contribute to the policy decision-making of urban road transportation system during and post the COVID-19 pandemic.

Using GPS-enabled mobile phones to evaluate the associations between human mobility changes and the onset of influenza illness

Due to the challenges in data collection, there are few studies examining how individuals' routine mobility patterns change when they experience influenza-like symptoms (ILS). In the present study, we aimed to assess the association between changes in routine mobility and ILS using mobile phone-based GPS traces and self-reported surveys from 1,155 participants over the 2016-2017 influenza season. We used a set of mobility metrics to capture individuals' routine mobility patterns and matched their weekly ILS survey responses. For a statistical analysis, we used a time-stratified case-crossover analysis and conducted a stratified analysis to examine if such associations are moderated by demographic and socioeconomic factors, such as age, gender, occupational status, neighborhood poverty and education levels, and work type. We found that statistically significant associations existed between reduced routine mobility patterns and the experience of ILS. Results also indicated that the association between reduced mobility and ILS was significant only for female and for participants with high socioeconomic status. Our findings offered an improved understanding of ILS-associated mobility changes at the individual level and suggest the potential of individual mobility data for influenza surveillance.

Introducing the Disease Outbreak Resilience Index (DORI) Using the Demographic and Health Surveys Data from sub-Saharan Africa

Although most studies on disease emergencies underscore the need for household readiness for shocks associated with disease outbreaks, no study to date has provided a holistic measure for profiling households based on their readiness toward disease outbreaks. This paper introduces a novel Disease Outbreak Resilience Index (DORI) using a multidimensional approach that draws on the Alkire-Foster methodology. DORI measures disease outbreak resilience in four dimensions: (a) water and hygiene, (b) physical distancing, (c) energy and communication, and (d) economic security and resilience. The paper details the development of DORI and its use by presenting findings from ten countries in sub-Saharan Africa using data from the Demographic and Health Surveys (DHS) program. In addition to serving as a resilience index, we illustrate how DORI can be used to produce a disease outbreak vulnerability index (DOVI). As a versatile index, the indicators under each dimension can be tailored to meet country- and region-specific contexts based on indicators appropriate to each context.

A proposta de convenção internacional sobre a resposta às pandemias: em defesa de um tratado de direitos humanos para o campo da saúde global

Em novembro de 2021, a Organização Mundial da Saúde (OMS) deu início à negociação de uma convenção, acordo ou outro instrumento internacional sobre a resposta às pandemias. Neste ensaio, defendemos e justificamos a tese de que o novo pacto deve ser um tratado de direitos humanos, como condição indispensável para a prevenção de novas pandemias e eficiência da resposta global quando elas ocorrem. Após o breve resgate da origem das negociações, apresentamos os principais conteúdos normativos que correspondem a um enfoque de direitos humanos: a instituição da regra de indissociabilidade entre medidas quarentenárias e de proteção social; e a regulamentação do acesso a tecnologias farmacêuticas. A seguir, em seção dedicada ao tema da efetividade do futuro tratado, classificamos as propostas existentes em ajustes tecnocráticos, como alterações no procedimento de declaração de emergências; mecanismos de transparência e controle, a exemplo da adoção de um mecanismo de Revisão Periódica Universal (RPU), similar ao do Conselho de Direitos Humanos das Nações Unidas, para monitorar obrigações dos Estados relacionadas à saúde; poderes coercitivos que seriam outorgados à OMS ou outra agência, tais como inspeções nos territórios nacionais realizadas por cientistas independentes; e mecanismos de coordenação política, como a criação de um Conselho Global de Ameaças à Saúde. Concluímos que há risco de adoção de um sistema mais eficiente de vigilância para alertar o mundo desenvolvido sobre ameaças oriundas de países em desenvolvimento, em lugar de um tratado capaz de contribuir para evitar que populações mais vulneráveis continuem sendo devastadas por pandemias cada vez mais frequentes.

Assessment of COVID-19 Preventive Practice and Associated Factors Among Educators in Vietnam

Background

Educators play a critical role in offering knowledge that is vital to preventing the spread of the COVID-19 in educational settings. This study aims to assess the proportion of preventive practices towards COVID-19 and associated factors among educators in Vietnam.

Methods

A cross-sectional study was conducted on educators at the University of Medicine and Pharmacy at Ho Chi Minh City (UMP) using a self-administered questionnaire between June and August 2020. Online surveys and a multivariable logistic regression analysis were used to determine factors associated with practices. Adjusted odds ratio (AOR) and 95% confidence interval (95% CI) were performed using Stata 14.

Results

A total of 779 eligible participants were approached, most of them under 50 years (84.1%), around three-fifth were female (61.0%) and lecturers (61.1%), with only 38.1% of them working at hospitals. Overall, the majority of participants had good preventive practices towards COVID-19 (88.6%). Factors identified as being associated with good practices included participants who are lecturers (AOR 1.8, 95% CI: 1.05–2.97), attending training courses related to COVID-19 (AOR 1.7, 95% CI: 1.05–2.87), working at hospitals (AOR 2.5, 95% CI: 1.28–4.76) and having a higher level of knowledge and attitude relating to COVID-19 (AOR 2.8, 95% CI: 1.52–5.17; AOR 2.8, 95% CI: 1.70–4.48, respectively) (all p < 0.05).

Conclusion

These findings revealed that most educators reported a good level of preventive practices towards COVID-19. However, lower levels of practices still exist towards COVID-19 among participants who were administrative staff and have less access to training courses related to COVID-19, who reported that they did not work at the hospital and had a lower level of knowledge and attitude related to COVID-19. Because of the important role of educators in the education system, this study is expected to help education and health authorities implement suitable interventions to fill the gaps in practices between educators.

Social determinants of the disproportionately higher rates of COVID-19 infection among African Caribbean and Black (ACB) population: A systematic review protocol

The challenges of identifying and eliminating racial disparities regarding the exposure, transmission, prevention, and treatment of communicable diseases within the healthcare system have been a mounting concern since the COVID-19 pandemic began. The African, Caribbean, and Black (ACB) populations in Canada represent a fast-expanding and underprivileged community, which have been previously found to have higher susceptibility to communicable diseases and lower sensitivity to intervention measures. Currently, there is insufficient evidence to adequately identify racial patterns in the prevalence and healthcare utilization among the ACB population within the context of the ongoing pandemic. Our proposed study will explore the association between the social determinants of health (SDH) and COVID-19 health outcomes in ACB populations in high-income countries (UK, US, Australia, Canada). We will explore the current evidence through a systematic review of COVID-19 pandemic literature covering the period between December 2019 and October 2020. The objectives include investigating the effect of SDH on the ACB populations’ risk to COVID-19 health outcomes, including COVID-19 infection incidence, severity of disease, hospitalization, mortality and barriers to the treatment and management of COVID-19 for Black people in Canada. In addition, this project aims to investigate the effect of COVID-19 on ACB communities in Ontario by examining the challenges that front-line healthcare workers and administrators have during this pandemic as it pertains to service provisions to ACB communities. A systematic review of original and review studies will be conducted based on the publications on eleven databases (MEDLINE, Web of Science, Cochrane Library, CINAHL, NHS EDD, Global Health, PsychInfo, PubMed, Scopus, Proquest, and Taylor and Francis Online Journals) Primary outcomes will include the rate of COVID-19 infection. The systematic review will include a meta-analysis of available quantitative data, as well as a narrative synthesis of qualitative studies. This systematic review will be among the first to report racial disparities in COVID-19 infection among the ACB population in Canada. Through synthesizing population data regarding the risk factors on various levels, the findings from this systematic review will provide recommendations for future research and evidence for clinical practitioners and social workers. Overall, a better understanding of the nature and consequences of racial disparities during the pandemic will provide policy directions for effective interventions and resilience-building in the post-pandemic era.

Exploring the nexus between social vulnerability, built environment, and the prevalence of COVID-19: A case study of Chicago

COVID-19 has significantly and unevenly impacted the United States, disproportionately affecting socially vulnerable communities. While epidemiologists and public health officials have suggested social distancing and shelter-in-place orders to halt the spread of this virus, the ability to comply with these guidelines is dependent on neighborhood, household, and individual characteristics related to social vulnerability. We use structural equation modeling and multiple data sources, including anonymized mobile phone location data from SafeGraph, to examine the effects of different social vulnerability and built environment factors on COVID-19 prevalence over two overlapping time periods (March to May and March to November of 2020). We use Chicago, Illinois as a case study and find that zip codes with low educational attainment consistently experienced higher case rates over both periods. Though population density was not significantly related to the prevalence in any period, movement of people made a significant contribution only during the longer time period. This finding highlights the significance of analyzing different timeframes for understanding social vulnerability. Our results suggest social vulnerability played an influential role in COVID-19 prevalence, highlighting the needs to address socioeconomic barriers to pandemic recovery and future pandemic response.

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.

Global assessment of the impacts of COVID-19 on food security

In this paper we present the first global assessments of COVID-19's impacts on food systems and their actors, focusing specifically on the food security and nutritional status of those affected in low and middle-income countries. The assessment covers 62 countries and is based on the analysis of 337 documents published in English, French, Spanish and Portuguese. The review confirms the magnitude and the severity of an unprecedented crisis that has spread worldwide and has spared only a few. The analysis shows that the dimension of food security that has been most affected is accessibility, with reasonably solid evidence suggesting that both financial and physical access to food have been disrupted. In contrast, there is no clear evidence that the availability of food has been affected. Overall, data suggests that food systems resisted and adapted to the disruption of the pandemic. This resilience came, however, at great costs, with the majority of the systems' actors having to cope with severe disruptions in their activities. In contrast, grocery stores and supermarkets made billions of dollars in profits in 2020.

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.

Variations in Early-Stage Responses to Pandemics: Survey Evidence from the COVID-19 Pandemic in Japan

During the initial phase of pandemics, swift behavioral responses by individuals, such as social distancing, can temper the speed and magnitude of further infections. However, individual choices in this period are often made in the absence of reliable knowledge and coordinated policy interventions, producing variation in protective behaviors that cannot be easily deduced from that in later periods. Using unique monthly panel survey data, we examine variations in the association between changes in infections and risky behavior, particularly the frequencies of face-to-face conversations and dining out, between January to March 2020. We find that the increase in confirmed cases is negatively associated with the likelihood of these behaviors. However, high school graduates are less responsive than university graduates. We provide evidence that this can be attributed to their lower perception of infection risk, while we cannot fully rule out the roles of income opportunity costs. These results point to the benefits of interventions incorporating nudges to raise individuals' risk perceptions during the initial phase of pandemics. We also discuss the potential efficacy of such interventions in later periods of pandemics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41885-021-00103-5.

Social inequalities and dynamics of the early COVID-19 epidemic: a prospective cohort study in France

OBJECTIVE

Although social inequalities in COVID-19 mortality by race, gender and socioeconomic status are well documented, less is known about social disparities in infection rates and their shift over time. We aim to study the evolution of social disparities in infection at the early stage of the epidemic in France with regard to the policies implemented.

DESIGN

Random population-based prospective cohort.

SETTING

From May to June 2020 in France.

PARTICIPANTS

Adults included in the Epidémiologie et Conditions de Vie cohort (n=77 588).

MAIN OUTCOME MEASURES

Self-reported anosmia and/or ageusia in three categories: no symptom, during the first epidemic peak (in March 2020) or thereafter (during lockdown).

RESULTS

In all, 2052 participants (1.53%) reported anosmia/ageusia. The social distribution of exposure factors (density of place of residence, overcrowded housing and working outside the home) was described. Multinomial regressions were used to identify changes in social variables (gender, class and race) associated with symptoms of anosmia/ageusia. Women were more likely to report symptoms during the peak and after. Racialised minorities accumulated more exposure risk factors than the mainstream population and were at higher risk of anosmia/ageusia during the peak and after. By contrast, senior executive professionals were the least exposed to the virus with the lower rate of working outside the home during lockdown. They were more affected than lower social classes at the peak of the epidemic, but this effect disappeared after the peak.

CONCLUSION

The shift in the social profile of the epidemic was related to a shift in exposure factors under the implementation of a stringent stay-at-home order. Our study shows the importance to consider in a dynamic way the gender, socioeconomic and race direct and indirect effects of the COVID-19 pandemic, notably to implement policies that do not widen health inequalities.

Population Vulnerability to the SARS-CoV-2 Virus Infection. A County-Level Geographical-Methodological Approach in Romania

The assessment and identification of risk/vulnerable groups and risk factors are vital elements that can help quantify the pandemic potential of the SARS-CoV-2 virus in order to plan prevention and treatment measures. The aim of the study is to identify a methodological approach of population vulnerability to the SARS-CoV-2 virus infection. The study identifies reliable data sources and sets up a unitary database with statistical variables, quantitative and qualitative indicators with potential for being updated and improved. The analysis takes into account a number of variables/indicators (e.g., elderly persons, population without physician care, number of people suffering from cardiovascular diseases, number of people suffering from respiratory diseases, dwellings not connected to the public water supply network, no. of medical staff, number of COVID-19 hospitals, PCR testing laboratories, number of vaccinated persons) grouped into the key vulnerability components: exposure, sensitivity, coping capacity and adaptive capacity. They allowed the computation of the final Index of Population Vulnerability to the SARS-CoV-2 virus infection and the mapping of different dimensions of vulnerability. The study was performed using the statistical data available at NUTS3/County level provided by different institutions (e.g., the Ministry of Health, the National Institute of Public Health, the Strategic Communication Group, and the National Institute of Statistics). The mapping of the different degrees of vulnerability could solve a problem of visibility for possible areas with vulnerable population, but also a problem of communication between different institutional health and administrative levels, as well as between all of them and the local communities and/or professionals.

The Relationship Between COVID-19 Infection Rates and Social Determinants of Health in Broward and Miami-Dade Counties, Florida

Objective

To determine the relationship between per capita income and COVID-19 cases in Broward and Miami-Dade Counties of Florida, USA. 

Background

Low socioeconomic status predisposes individuals to worse health outcomes. For example, during the 2003 SARS-CoV pandemic and the 2009 H1N1 influenza pandemic disadvantaged individuals were more likely to become infected. More recently, a study found that deaths due to COVID-19 were associated with disadvantaged areas across the United States. South Florida, in particular Broward and Miami-Dade Counties, has experienced a significant burden of coronavirus cases. Investigating the association of income on coronavirus cases in Broward and Miami-Dade Counties may aid in identifying and treating those individuals at increased risk. 

Methods

This retrospective cross-sectional study used data gathered by the Florida Department of Health and 2018 U.S. Census. COVID-19 cases from March 2 - November 1, 2020 were tallied by ZIP code in Florida’s Broward and Miami-Dade Counties and scaled per housing unit. An exhaustive regression analysis using County “Miami-Dade” or “Broward,” sex, race, ethnicity, median age, and estimated per capita income was performed for each combination of independent variables in MATLAB (MathWorks, Natick, USA). Regression models were evaluated using both adjusted R-squared and the Akaike Information Criterion, along with the number of significant predictors. The most optimal model with the highest number of significant predictors was selected.

Results

Among all other variables, sex, race, and ethnicity as the variables that best predicted COVID-19 cases per housing unit within a certain ZIP code. The adjusted R-squared of this optimal model was 0.5062, indicating that within each ZIP code in Broward and Miami-Dade Counties 50.62% of the variance in COVID-19 cases per housing unit can be explained by these variables. A significant relationship was found between the number of COVID-19 cases and individuals who were Black or African American (p < 0.001), individuals who were Hispanic or Latino (p < 0.001), and male to female ratio (p = 0.016). Per capita income, age, and county were not statistically significant predictors in any model tested.

Conclusions

Racial and gender disparities may be more significant contributors to COVID-19 cases than per capita income in housing units. Based on the results of this study, investigators may consider applying this model to similar variables in order to inform the management and prevention of cases in the present and future pandemics.

The association between socioeconomic status and pandemic influenza: Systematic review and meta-analysis

BACKGROUND

The objective of this study is to document whether and to what extent there is an association between socioeconomic status (SES) and disease outcomes in the last five influenza pandemics.

METHODS/PRINCIPLE FINDINGS

The review included studies published in English, Danish, Norwegian and Swedish. Records were identified through systematic literature searches in six databases. We summarized results narratively and through meta-analytic strategies. Only studies for the 1918 and 2009 pandemics were identified. Of 14 studies on the 2009 pandemic including data on both medical and social risk factors, after controlling for medical risk factors 8 demonstrated independent impact of SES. In the random effect analysis of 46 estimates from 35 studies we found a pooled mean odds ratio of 1.4 (95% CI: 1.2-1.7, p < 0.001), comparing the lowest to the highest SES, but with substantial effect heterogeneity across studies,-reflecting differences in outcome measures and definitions of case and control samples. Analyses by pandemic period (1918 or 2009) and by level of SES measure (individual or ecological) indicated no differences along these dimensions. Studies using healthy controls tended to document that low SES was associated with worse influenza outcome, and studies using infected controls find low SES associated with more severe outcomes. A few studies compared severe outcomes (ICU or death) to hospital admissions but these did not find significant SES associations in any direction. Studies with more unusual comparisons (e.g., pandemic vs seasonal influenza, seasonal influenza vs other patient groups) reported no or negative non-significant associations.

CONCLUSIONS/SIGNIFICANCE

We found that SES was significantly associated with pandemic influenza outcomes with people of lower SES having the highest disease burden in both 1918 and 2009. To prepare for future pandemics, we must consider social vulnerability. The protocol for this study has been registered in PROSPERO (ref. no 87922) and has been published Mamelund et al. (2019).

Changes in characteristics and case-severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves-England, 2009-2010

BACKGROUND

During 2009-2010, pandemic influenza A (H1N1) pdm09 virus (pH1N1) infections in England occurred in two epidemic waves. Reasons for a reported increase in case-severity during the second wave are unclear.

METHODS

We analysed hospital-based surveillance for patients with pH1N1 infections in England during 2009-2010 and linked national data sets to estimate ethnicity, socio-economic status and death within 28 days of admission. We used multivariable logistic regression to assess whether changes in demographic, clinical and management characteristics of patients could explain an increase in ICU admission or death, and accounted for missing values using multiple imputation.

RESULTS

During the first wave, 54/960 (6%) hospitalised patients required intensive care and 21/960 (2%) died; during the second wave 143/1420 (10%) required intensive care and 55/1420 (4%) died. In a multivariable model, during the second wave patients were less likely to be from an ethnic minority (OR 0.33, 95% CI 0.26-0.42), have an elevated deprivation score (OR 0.75, 95% CI 0.68-0.83), have known comorbidity (OR 0.78, 95% CI 0.63-0.97) or receive antiviral therapy ≤2 days before onset (OR 0.72, 95% CI 0.56-0.92). Increased case-severity during the second wave was not explained by changes in demographic, clinical or management characteristics.

CONCLUSIONS

Monitoring changes in patient characteristics could help target interventions during multiple waves of COVID-19 or a future influenza pandemic. To understand and respond to changes in case-severity, surveillance is needed that includes additional factors such as admission thresholds and seasonal coinfections.

Ethnic and social inequalities in COVID-19 outcomes in Scotland: protocol for early pandemic evaluation and enhanced surveillance of COVID-19 (EAVE II)

INTRODUCTION

Evidence from previous pandemics, and the current COVID-19 pandemic, has found that risk of infection/severity of disease is disproportionately higher for ethnic minority groups, and those in lower socioeconomic positions. It is imperative that interventions to prevent the spread of COVID-19 are targeted towards high-risk populations. We will investigate the associations between social characteristics (such as ethnicity, occupation and socioeconomic position) and COVID-19 outcomes and the extent to which characteristics/risk factors might explain observed relationships in Scotland.The primary objective of this study is to describe the epidemiology of COVID-19 by social factors. Secondary objectives are to (1) examine receipt of treatment and prevention of COVID-19 by social factors; (2) quantify ethnic/social differences in adverse COVID-19 outcomes; (3) explore potential mediators of relationships between social factors and SARS-CoV-2 infection/COVID-19 prognosis; (4) examine whether occupational COVID-19 differences differ by other social factors and (5) assess quality of ethnicity coding within National Health Service datasets.

METHODS AND ANALYSIS

We will use a national cohort comprising the adult population of Scotland who completed the 2011 Census and were living in Scotland on 31 March 2020 (~4.3 million people). Census data will be linked to the Early Assessment of Vaccine and Anti-Viral Effectiveness II cohort consisting of primary/secondary care, laboratory data and death records. Sensitivity/specificity and positive/negative predictive values will be used to assess coding quality of ethnicity. Descriptive statistics will be used to examine differences in treatment and prevention of COVID-19. Poisson/Cox regression analyses and mediation techniques will examine ethnic and social differences, and drivers of inequalities in COVID-19. Effect modification (on additive and multiplicative scales) between key variables (such as ethnicity and occupation) will be assessed.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the National Research Ethics Committee, South East Scotland 02. We will present findings of this study at international conferences, in peer-reviewed journals and to policy-makers.

Identifying Patterns of Turnover Intention Among Alabama Frontline Nurses in Hospital Settings During the COVID-19 Pandemic

Introduction

Current research about frontline nurse stress and turnover intention lacks context related to rural communities’ plight in providing organizational resources during the current COVID-19 pandemic. These implications have been particularly underexamined in the United States, whose regional differences may influence how frontline nurses perceive the access and utility of organizational resources. This study investigates if anxiety and stress while working during the current COVID-19 pandemic contribute to frontline nurses’ desire to leave their current position in Alabama hospital settings.

Material and Methods

A cross-sectional survey was developed and distributed as a Qualtrics survey to frontline nurses using social media and professional contacts. A total of 111 frontline nurse respondents within May 19–June 12, 2020 were included in this study.

Results

A significant correlation was found between gender (p= 0.002), marital status (p= 0.000) and seniority (p= 0.049) on turnover intention. A nurse’s perceived anxiety and stress related to their patients’ acuity (r= 0.257, p= 0.004), their personal health as a risk factor (r= 0.507, p= 0.000), their patient assignments (r= 0.239, p= 0.01), their personal protective equipment (r= 0.412, p= 0.000), and their psychological support (r= 0.316, p= 0.001) correspond to higher turnover intention among nurses working with patients infected with COVID-19.

Conclusion

Perceived resource loss in task autonomy, PPE, and psychosocial support increased turnover intention among frontline nurses in Alabama. Research is needed to understand how intrinsic motivations and social support influence individual nurse staff’s perceptions of resource loss and job demands. Further, more research is necessary to examine the implications of rurality and place in discussing turnover intention and organizational resources across multiple health systems.

Did the Timing of State Mandated Lockdown Affect the Spread of COVID-19 Infection? A County-level Ecological Study in the United States

Objectives:

Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States.

Methods:

A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R² value from the multiple regression were chosen.

Results:

The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment.

Conclusions:

The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.

Cumulative Impacts and COVID-19: Implications for Low-Income, Minoritized, and Health-Compromised Communities in King County, WA

Few studies have assessed how the intersection of social determinants of health and environmental hazards contributes to racial disparities in COVID-19. The aim of our study was to compare COVID-19 disparities in testing and positivity to cumulative environmental health impacts, and to assess how unique social and environmental determinants of health relate to COVID-19 positivity in Seattle, King County, WA, at the census tract level. Publicly available data (n = 397 census tracts) were obtained from Public Health–Seattle & King County, 2018 ACS 5-year estimates, and the Washington Tracking Network. COVID-19 testing and positive case rates as of July 12, 2020, were mapped and compared to Washington State Environmental Health Disparities (EHD) Map cumulative impact rankings. We calculated odds ratios from a series of univariable and multivariable logistic regression analyses using cumulative impact rankings, and community-level socioeconomic, health, and environmental factors as predictors and having ≥ 10% or < 10% census tract positivity as the binary outcome variable. We found a remarkable overlap between Washington EHD cumulative impact rankings and COVID-19 positivity in King County. Census tracts with ≥ 10 % COVID-19 positivity had significantly lower COVID-19 testing rates and higher proportions of people of color and faced a combination of low socioeconomic status–related outcomes, poor community health outcomes, and significantly higher concentrations of fine particulate matter (PM_2.5). King County communities experiencing high rates of COVID-19 face a disproportionate cumulative burden of environmental and social inequities. Cumulative environmental health impacts should therefore systematically be considered when assessing for risk of exposure to and health complications resulting from COVID-19.

COVID-19 Is Connected with Lower Health Literacy in Rural Areas

The relationship between social determinants of health (SDoH) and health outcomes is established and extends to a higher risk of contracting COVID-19. Given the factors included in SDoH, such as education level, race, rurality, and socioeconomic status are interconnected, it is unclear how individual SDoH factors may uniquely impact risk. Lower socioeconomic status often occurs in concert with lower educational attainment, for example. Because literacy provides access to information needed to avoid infection and content can be made more accessible, it is essential to determine to what extent health literacy contributes to successful containment of a pandemic. By incorporating this information into clinical data, we have isolated literacy and geographic location as SDoH factors uniquely related to the risk of COVID-19 infection. For patients with comorbidities linked to higher illness severity, residents of rural areas associated with lower health literacy at the zip code level had a greater likelihood of positive COVID-19 results unrelated to their economic status.

Residential racial segregation and social distancing in the United States during COVID-19

BACKGROUND

Our objective is to examine whether residential racial segregation may be constraining capacities for social distancing thus leaving African Americans potentially more exposed to contracting COVID-19. We hypothesized that residential racial segregation constrains African Americans' spatial mobility when the whole population is locked down but increases their need for moving under reopening orders.

METHODS

We employ a Black/White dissimilarity index as our independent variable and county-level mobility ratios as our dependent variable. Using generalized estimating equations for longitudinal data, we analyzed the effects of Black/White segregation on population mobility by counties across the United States from March 8 to August 7, 2020 under two different COVID-19 related policy conditions: lockdown and reopening.

FINDINGS

While higher county-wide levels of segregation were significantly associated with decreased mobility under lockdown and stay-at-home orders, we found that this relationship between segregation and mobility dissipated under reopening orders.

INTERPRETATIONS

Investigating the effects of health policy without considering differing effects due to structural racism will likely ignore complexities that may create unintended consequences of health policy. Our conclusions suggest African Americans may face structural limitations to effective social distancing as evidenced by higher rates of mobility after reopening policies go into effect.

Examining the impact of socioeconomic variables on COVID-19 death rates at the state level

This study uses a step-wise regression model to identify the socioeconomic variables most significant in explaining COVID-19 death rates on a state-level basis. The regression tests cover the 1/1/2020 to 12/1/2020 period as well as the first and second halves of 2020. This study also uses the Oxford stringency index to measure more precisely the efficacy of governmental mandates at the state level. The results in this study rigorously showed that while the density variables were the most significant explanatory variables during the first half of the year, their significance fell during the second half. Use of the Oxford stringency index revealed that more stringent mandates led to significant reductions in COVID-19 death rates, especially during the second half of the year. The study’s findings also reveal that a higher poverty rate in a state is significantly associated with higher COVID-19 death rates during all three periods tested.

Social determinants of COVID-19 incidence and outcomes: A rapid review

Early reports indicate that the social determinants of health are implicated in COVID-19 incidence and outcomes. To inform the ongoing response to the pandemic, we conducted a rapid review of peer-reviewed studies to examine the social determinants of COVID-19. We searched Ovid MEDLINE, Embase, PsycINFO, CINAHL and Cochrane Central Register of Controlled Trials from December 1, 2019 to April 27, 2020. We also searched the bibliographies of included studies, COVID-19 evidence repositories and living evidence maps, and consulted with expert colleagues internationally. We included studies identified through these supplementary sources up to June 25, 2020. We included English-language peer-reviewed quantitative studies that used primary data to describe the social determinants of COVID-19 incidence, clinical presentation, health service use and outcomes in adults with a confirmed or presumptive diagnosis of COVID-19. Two reviewers extracted data and conducted quality assessment, confirmed by a third reviewer. Forty-two studies met inclusion criteria. The strongest evidence was from three large observational studies that found associations between race or ethnicity and socioeconomic deprivation and increased likelihood of COVID-19 incidence and subsequent hospitalization. Limited evidence was available on other key determinants, including occupation, educational attainment, housing status and food security. Assessing associations between sociodemographic factors and COVID-19 was limited by small samples, descriptive study designs, and the timeframe of our search. Systematic reviews of literature published subsequently are required to fully understand the magnitude of any effects and predictive utility of sociodemographic factors related to COVID-19 incidence and outcomes. PROSPERO: CRD4202017813.

Social determinants of health and coronavirus disease 2019 in pregnancy

Background

The social and physical environments in which people live affect the emergence, prevalence, and severity of both infectious and noninfectious diseases. There are limited data on how such social determinants of health, including neighborhood socioeconomic conditions, affect the risk of severe acute respiratory syndrome coronavirus 2 infection and severity of coronavirus disease 2019 during pregnancy.

Objective

Our objective was to determine how social determinants of health are associated with severe acute respiratory syndrome coronavirus 2 infection and the severity of coronavirus disease 2019 illness in hospitalized pregnant patients in New York during the global coronavirus disease 2019 pandemic.

Study Design

This cross-sectional study evaluated all pregnant patients who delivered and had polymerase chain reaction testing for severe acute respiratory syndrome coronavirus 2 between March 15, 2020, and June 15, 2020, at 7 hospitals within Northwell Health, the largest academic health system in New York. During the study period, universal severe acute respiratory syndrome coronavirus 2 testing protocols were implemented at all sites. Polymerase chain reaction testing was performed using nasopharyngeal swabs. Patients were excluded if the following variables were not available: polymerase chain reaction results, race, ethnicity, or zone improvement plan (ZIP) code of residence. Clinical data were obtained from the enterprise electronic health record system. For each patient, ZIP code was used as a proxy for neighborhood. Socioeconomic characteristics were determined by linking to ZIP code data from the United States Census Bureau's American Community Survey and the Internal Revenue Service's Statistics of Income Division. Specific variables of interest included mean persons per household, median household income, percent unemployment, and percent with less than high school education. Medical records were manually reviewed for all subjects with positive polymerase chain reaction test results to correctly identify symptomatic patients and then classify those subjects using the National Institutes of Health severity of illness categories. Classification was based on the highest severity of illness throughout gestation and not necessarily at the time of presentation for delivery.

Results

A total of 4873 patients were included in the study. The polymerase chain reaction test positivity rate was 11% (n=544). Among this group, 359 patients (66%) were asymptomatic or presymptomatic, 115 (21%) had mild or moderate coronavirus disease 2019, and 70 (13%) had severe or critical coronavirus disease 2019. On multiple logistic regression modeling, pregnant patients who had a positive test result for severe acute respiratory syndrome coronavirus 2 were more likely to be younger or of higher parity, belong to minoritized racial and ethnic groups, have public health insurance, have limited English proficiency, and reside in low-income neighborhoods with less educational attainment. On ordinal logit regression modeling, obesity, income and education were associated with coronavirus disease 2019 severity.

Conclusion

Social and physical determinants of health play a role in determining the risk of infection. The severity of coronavirus disease 2019 illness was not associated with race or ethnicity but was associated with maternal obesity and neighborhood level characteristics such as educational attainment and household income.

Negative Association Between Mediterranean Diet Adherence and COVID-19 Cases and Related Deaths in Spain and 23 OECD Countries: An Ecological Study

In December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-Cov2) emerged in Wuhan, China, sparking the Coronavirus disease 2019 (COVID-19) pandemic. The high prevalence of nutrition-related COVID-19 risk factors including obesity, type 2 diabetes, and hypertension, suggests that healthy dietary approaches may mitigate COVID-19 related outcomes and possibly SARS-CoV-2 infection. Based on the fundamental role of nutrition in immune function and the well-documented association between Mediterranean diet consumption and risk reduction for chronic diseases that are comorbidities in COVID-19 patients, we hypothesized that there would be a relationship between Mediterranean diet adherence and COVID-19 cases and related deaths. In this perspective, we examined the association between regional adherence to a Mediterranean diet and COVID-19 cases and deaths using an ecological study design. We observed that Mediterranean diet adherence was negatively associated with both COVID-19 cases and related deaths across 17 regions in Spain and that the relationship remained when adjusted for factors of well-being. We also observed a negative association between Mediterranean diet adherence and COVID-19 related deaths across 23 countries when adjusted for factors of well-being and physical inactivity. The anti-inflammatory properties of the Mediterranean diet - likely due to the polyphenol content of the diet - may be a biological basis to explain our findings. However, there are confounding factors unrelated to dietary factors driving COVID-19 cases and related deaths across the regions in Spain and the 23 countries examined in our analysis. Our findings will need to be confirmed and further explored in cohort studies.

[Higher risk of COVID-19 hospitalization for unemployed: an analysis of health insurance data from 1.28 million insured individuals in Germany]

BACKGROUND AND OBJECTIVE

Unemployment is related to poverty and is a risk factor for poor health. The present study investigates if unemployment increases the risk of COVID-19 hospitalization for men and women of working age in Germany.

METHODS

The study uses the health insurance data from AOK Rhineland/Hamburg (from 1 January 2020 until 18 June 2020) of 1,288,745 persons aged between 18 and 65. Four employment situations are distinguished: (1) regular employment, (2) low-wage employment with social support, (3) unemployment with receipt of unemployment benefit 1, and (4) long-term unemployment with receipt of unemployment benefit 2. COVID-19 hospitalizations are measured on the basis of the ICD codes U07.1 and U07.2 reported by the hospitals. Multiple logistic regression models are calculated (adjusted for age and sex).

RESULTS

During the observation period, 1521 persons had hospitalization with COVID-19 as primary or secondary diagnosis. Overall, this corresponds to a rate of 118 cases per 100,000 insured persons. Rates varied by employment situation. Compared with regularly employed persons, the odds ratio for a hospitalization was 1.94 (CI 95%: 1.74-2.15) for long-term unemployment, 1.29 (0.86-1.94) for unemployed, and 1.33 (0.98-1.82) for low-wage employment.

CONCLUSION

The results are in line with earlier studies from the USA and Great Britain reporting socioeconomic inequalities in COVID-19 hospitalization risk. This provides the first empirical support that socioeconomic inequalities in the severity of COVID-19 also exists in Germany.

Health inequities in influenza transmission and surveillance

The lower an individual's socioeconomic position, the higher their risk of poor health in low-, middle-, and high-income settings alike. As health inequities grow, it is imperative that we develop an empirically-driven mechanistic understanding of the determinants of health disparities, and capture disease burden in at-risk populations to prevent exacerbation of disparities. Past work has been limited in data or scope and has thus fallen short of generalizable insights. Here, we integrate empirical data from observational studies and large-scale healthcare data with models to characterize the dynamics and spatial heterogeneity of health disparities in an infectious disease case study: influenza. We find that variation in social and healthcare-based determinants exacerbates influenza epidemics, and that low socioeconomic status (SES) individuals disproportionately bear the burden of infection. We also identify geographical hotspots of influenza burden in low SES populations, much of which is overlooked in traditional influenza surveillance, and find that these differences are most predicted by variation in susceptibility and access to sickness absenteeism. Our results highlight that the effect of overlapping factors is synergistic and that reducing this intersectionality can significantly reduce inequities. Additionally, health disparities are expressed geographically, and targeting public health efforts spatially may be an efficient use of resources to abate inequities. The association between health and socioeconomic prosperity has a long history in the epidemiological literature; addressing health inequities in respiratory-transmitted infectious disease burden is an important step towards social justice in public health, and ignoring them promises to pose a serious threat.

One welfare impacts of COVID-19 - A summary of key highlights within the one welfare framework

One Welfare describes the interconnection between animal welfare, human wellbeing and their physical and social environment. The SARS-CoV-2 virus is the cause of COVID-19 and emerged as a human pathogen in 2019 although is thought to have a zoonotic source. The original wildlife reservoir and any potential intermediate hosts have not yet been identified. The combination of the virus zoonotic condition together with the impacts of disease control measures has exposed clear interconnections between animals, people and their environment from both a health and a welfare perspective. The One Welfare Framework comprises five sections that can help understand the different One Welfare levels on which the COVID-19 pandemic has impacted the world. This paper uses the One Welfare Framework to provide an overview of examples, within each of the five sections, where evidence is and/or can be made available to document COVID-19 impacts on One Welfare. The paper identifies a number of areas where further research and evidence gathering is required to better understand the different One Welfare impacts. Based on evidence summarised in this paper the author recommends that those responsible for managing the COVID-19 impacts and for planning the future recovery phase of the pandemic should consider adopting a holistic approach, including both health and welfare, by adopting & One Health, One Welfare & policies.

Knowledge, attitudes, and practices (KAP) toward COVID-19: a cross-sectional study in South Korea

BACKGROUND

The public must routinely practice precautionary behaviors to control the spread of COVID-19, as no vaccines and antiviral treatments are currently available. This paper examines the public's knowledge, attitudes, and practices (KAP) related to COVID-19 and their relationships and identified the pandemic's vulnerable populations to provide recommendations for behavioral interventions and policies.

METHODS

Data collection took place over 3 days (June 26-29) via an online survey 5 months after the Korea Centers for Disease Control and Prevention (KCDC) confirmed the first COVID case in South Korea; 970 subjects were included in the statistical data analysis.

RESULTS

Knowledge directly affected both attitudes (e.g., perceived risk and efficacy belief) and practices (e.g., personal hygiene practices and social distancing). Among the influencing factors of COVID-19 preventive behaviors, efficacy belief was the most influential and significant practice factor. It mediated the relationship between knowledge and all three preventive behaviors (wearing facial masks, practicing hand hygiene, and avoiding crowded places). The level of knowledge varied by sociodemographic characteristics. Females (β = 0.06, p <  0.05) and individuals with higher levels of education (β = 0.06, p <  0.05) demonstrated higher levels of knowledge.

CONCLUSION

To increase precautionary behaviors among the public, health officials and policymakers must promote knowledge and efficacy belief. Future interventions and policies should also be developed in a 'person-centered' approach, targeting vulnerable subgroups, embracing them, and closing the gap of KAP toward COVID-19.

Human activity pattern implications for modeling SARS-CoV-2 transmission

BACKGROUND AND OBJECTIVES

SARS-CoV-2 emerged in December 2019 and rapidly spread into a global pandemic. Designing optimal community responses (social distancing, vaccination) is dependent on the stage of the disease progression, discovery of asymptomatic individuals, changes in virulence of the pathogen, and current levels of herd immunity. Community strategies may have severe and undesirable social and economic side effects. Modeling is the only available scientific approach to develop effective strategies that can minimize these unwanted side effects while retaining the effectiveness of the interventions.

METHODS

We extended the agent-based model, SpatioTemporal Human Activity Model (STHAM), for simulating SARS-CoV-2 transmission dynamics.

RESULTS

Here we present preliminary STHAM simulation results that reproduce the overall trends observed in the Wasatch Front (Utah, United States of America) for the general population. The results presented here clearly indicate that human activity patterns are important in predicting the rate of infection for different demographic groups in the population.

CONCLUSIONS

Future work in pandemic simulations should use empirical human activity data for agent-based techniques.