A model of disparities: risk factors associated with COVID-19 infection

Understanding COVID-19 infection among people with intellectual and developmental disabilities using machine learning

BACKGROUND

People with intellectual and developmental disabilities (IDD) were disproportionately affected by the COVID-19 pandemic. Predicting COVID-19 infection has been difficult.

OBJECTIVE

We sought to address two research questions in this study: 1) to assess the overall utility of a machine learning model to predict COVID-19 diagnosis for people with IDD, and 2) to determine the primary predictors of COVID-19 diagnosis in a random sample of Home and Community Based Services users in one state.

METHODS

We merged three major IDD-specific datasets (National Core Indicators, Supports Intensity Scale, Medicaid HCBS expenditures) from one state to create one combined dataset for analyses that included more than 700 variables. We then built a random forest machine learning algorithm to predict COVID-19 diagnosis and to explore the top predictors of such a diagnosis, when present.

RESULTS

Our algorithm predicted COVID-19 diagnosis in a random sample of HCBS users with IDD with 62.5% accuracy. The top predictors of having a documented case of COVID-19 among our sample were higher age, having high overall, medical, or behavioral support needs, living in a lower-income neighborhood, total Medicaid expenditure, and higher body mass index.

CONCLUSIONS

Results largely followed trends in the general population, and were largely suggestive that increased contact with other people may have exposed a person with IDD to greater COVID-19 risk.

Latent classification model for censored longitudinal binary outcome

Latent classification model is a class of statistical methods for identifying unobserved class membership among the study samples using some observed data. In this study, we proposed a latent classification model that takes a censored longitudinal binary outcome variable and uses its changing pattern over time to predict individuals' latent class membership. Assuming the time-dependent outcome variables follow a continuous-time Markov chain, the proposed method has two primary goals: (1) estimate the distribution of the latent classes and predict individuals' class membership, and (2) estimate the class-specific transition rates and rate ratios. To assess the model's performance, we conducted a simulation study and verified that our algorithm produces accurate model estimates (ie, small bias) with reasonable confidence intervals (ie, achieving approximately 95% coverage probability). Furthermore, we compared our model to four other existing latent class models and demonstrated that our approach yields higher prediction accuracies for latent classes. We applied our proposed method to analyze the COVID-19 data in Houston, Texas, US collected between January first 2021 and December 31st 2021. Early reports on the COVID-19 pandemic showed that the severity of a SARS-CoV-2 infection tends to vary greatly by cases. We found that while demographic characteristics explain some of the differences in individuals' experience with COVID-19, some unaccounted-for latent variables were associated with the disease.

Long COVID awareness and receipt of medical care: a survey among populations at risk for disparities

Introduction

The COVID-19 pandemic has been characterized by disparities in disease burden and medical care provision. Whether these disparities extend to long COVID awareness and receipt of medical care is unknown. We aimed to characterize awareness of long COVID and receipt of medical care for long COVID symptoms among populations who experience disparities in the United States (US).

Methods

We conducted a cross-sectional survey among a national sample of US adults between January 26-February 5, 2023. We surveyed approximately 2,800 adults drawn from the Ipsos probability-based KnowledgePanel® who identify as White, Black, or Hispanic, with over-sampling of Black, Hispanic, and Spanish-proficient adults. Awareness of long COVID was assessed with the question, "Have you heard of long COVID? This is also referred to as post-COVID, Long-haul COVID, Post-acute COVID-19, or Chronic COVID." Respondents reporting COVID-19 symptoms lasting longer than 1 month were classified as having long COVID and asked about receipt of medical care.

Results

Of the 2,828 respondents, the mean age was 50.4 years, 52.8% were female, 40.2% identified as Hispanic, 29.8% as Black, and 26.7% as White. 18% completed the survey in Spanish. Overall, 62.5% had heard of long COVID. On multivariate analysis, long COVID awareness was lower among respondents who identified as Black (OR 0.64; 95% CI 0.51, 0.81), Hispanic and completed the survey in English (OR 0.59; 95% CI 0.46, 0.76), and Hispanic and completed the survey in Spanish (OR 0.31, 95% C.I. 0.23, 0.41), compared to White respondents (overall p < 0.001). Long COVID awareness was also associated with educational attainment, higher income, having health insurance, prior history of COVID-19 infection, and COVID-19 vaccination. Among those reporting symptoms consistent with long COVID (n = 272), 26.8% received medical care. Older age, longer symptom duration and greater symptom impact were associated with receipt of medical care for long COVID symptoms. Of those who received care, most (77.8%) rated it as less than excellent on a 5-point scale.

Discussion

This survey reveals limited awareness of long COVID and marked disparities in awareness according to race, ethnicity, and language. Targeted public health campaigns are needed to raise awareness.

Association of socio-demographic factors with clinical outcome among hospitalized patients in first and second waves of COVID-19 pandemic: Study from the developing world

Background

Recent disease resurgence in China indicates that corona virus infectious disease is still a pertinent public health problem. We stand at a juncture where we are still unsure about the initial dilemmas regarding its birth, therapies, and the emerging novel strains. Medical literature has focused on the clinical, laboratory, radiological, and therapeutic aspects of disease management. There is paucity of literature on the association between socio-demographic variables on disease severity and clinical outcome.

Materials and Methods

This retrospective observational study analyzing the socio-demographic variables was performed at a dedicated COVID care center in western Maharashtra, India. Electronic records of all individuals who were admitted to this hospital from July 29 2020, to June 14, 2021, and diagnosed COVID-19 positive by reverse transcriptase polymerase chain reaction (RT-PCR) were identified after due institutional ethical clearance. Patients admitted from July 29, 2020, to February 27, 2021, were categorized as patients presenting during the 'first wave of viral pandemic'. Those admitted from March 01, 2021, to June 14, 2021, have been included as patients admitted during 'second wave of viral pandemic'. The following outcome parameters were collected (presenting symptoms, duration of symptoms before the individual presented for diagnostic RT-PCR, total duration of symptoms, severity of disease at onset, duration of hospital stay, the final outcome (discharge/death) and Charlson's comorbidity index). The linear regression model was used to establish association between socio-demographic factors and disease severity at onset (mild/moderate/severe/critical).

Results

A total of 37033 patients were screened, and the positivity rate with RT-PCR was 16.99% (n = 6275) during the study period. Out of which 45% (n = 2824) of the patients had mild disease requiring home isolation and the remaining 55% of patients required admission. 1590 patients from the first wave and 910 from the second wave of COVID-19 were hospitalized and included in the study after exclusion. The mean age of patients in first wave was 49 years and that in second wave was 54 years with 77.6% and 70.6% males in two waves, respectively. The burden of critical cases was higher in second wave as computed to first wave (10% vs 8%). The second wave had more outreach in the rural population as compared to second one (17.8% vs 12.2%). The mean duration from the onset of symptoms to hospitalization was 03 and 04 days, respectively, in two waves. Mortality associated in two waves was 11.9% and 24%, respectively (P < 0.05). Higher Charlson's comorbidity index was associated with higher mortality, and the cumulative survival from urban area was more as compared to the rural population (log rank - 9.148, P = 0.0002).

Conclusion

The second COVID-19 wave had significantly higher case mortality. It affected elderly patients and those with rural background. The factors associated with higher mortality during COVID-19 pandemic were rural background, higher Charlson's comorbidity index and late presentation to the hospital. Ongoing vaccine campaigns, thus, should focus on rural areas and individuals with comorbidities especially in developing and least developed countries.

Melatonin: a ferroptosis inhibitor with potential therapeutic efficacy for the post-COVID-19 trajectory of accelerated brain aging and neurodegeneration

The unprecedented pandemic of COVID-19 swept millions of lives in a short period, yet its menace continues among its survivors in the form of post-COVID syndrome. An exponentially growing number of COVID-19 survivors suffer from cognitive impairment, with compelling evidence of a trajectory of accelerated aging and neurodegeneration. The novel and enigmatic nature of this yet-to-unfold pathology demands extensive research seeking answers for both the molecular underpinnings and potential therapeutic targets. Ferroptosis, an iron-dependent cell death, is a strongly proposed underlying mechanism in post-COVID-19 aging and neurodegeneration discourse. COVID-19 incites neuroinflammation, iron dysregulation, reactive oxygen species (ROS) accumulation, antioxidant system repression, renin-angiotensin system (RAS) disruption, and clock gene alteration. These events pave the way for ferroptosis, which shows its signature in COVID-19, premature aging, and neurodegenerative disorders. In the search for a treatment, melatonin shines as a promising ferroptosis inhibitor with its repeatedly reported safety and tolerability. According to various studies, melatonin has proven efficacy in attenuating the severity of certain COVID-19 manifestations, validating its reputation as an anti-viral compound. Melatonin has well-documented anti-aging properties and combating neurodegenerative-related pathologies. Melatonin can block the leading events of ferroptosis since it is an efficient anti-inflammatory, iron chelator, antioxidant, angiotensin II antagonist, and clock gene regulator. Therefore, we propose ferroptosis as the culprit behind the post-COVID-19 trajectory of aging and neurodegeneration and melatonin, a well-fitting ferroptosis inhibitor, as a potential treatment.

Disparities in COVID-19 Hospitalization at the Intersection of Race and Ethnicity and Income

BACKGROUND

Existing studies have elucidated racial and ethnic disparities in COVID-19 hospitalizations, but few have examined disparities at the intersection of race and ethnicity and income.

METHODS

We used a population-based probability survey of non-institutionalized adults in Michigan with a polymerase chain reaction-positive SARS-CoV-2 test before November 16, 2020. We categorized respondents by race and ethnicity and annual household income: low-income (< $50,000) Non-Hispanic (NH) Black, high-income (≥ $50,000) NH Black, low-income Hispanic, high-income Hispanic, low-income NH White, and high-income NH White. We used modified Poisson regression models, adjusting for sex, age group, survey mode, and sample wave, to estimate COVID-19 hospitalization prevalence ratios by race and ethnicity and income.

RESULTS

Over half of the analytic sample (n = 1593) was female (54.9%) and age 45 or older (52.5%), with 14.5% hospitalized for COVID-19. Hospitalization was most prevalent among low-income (32.9%) and high-income (31.2%) Non-Hispanic (NH) Black adults, followed by low-income NH White (15.3%), low-income Hispanic (12.9%), high-income NH White (9.6%), and high-income Hispanic adults (8.8%). In adjusted models, NH Black adults, regardless of income (low-income prevalence ratio [PR]: 1.86, 95% CI: 1.36-2.54; high-income PR: 1.57, 95% CI: 1.07-2.31), and low-income NH White adults (PR: 1.52, 95% CI: 1.12-2.07), had higher prevalence of hospitalization compared to high-income NH White adults. We observed no significant difference in the prevalence of hospitalization among Hispanic adults relative to high-income NH White adults.

CONCLUSIONS

We observed disparities in COVID-19 hospitalization at the intersection of race and ethnicity and income for NH Black adults and low-income NH White adults relative to high-income NH White adults, but not for Hispanic adults.

Association between healthy lifestyles and post-COVID-19 syndrome among college students

BACKGROUND

Post-COVID-19 syndrome still occurs in some populations. A healthy lifestyle is widely recognized as a first-line treatment to increase the body's antiviral resistance and tissue repair, but it is unclear whether a healthy lifestyle can promote or alleviate the symptoms of post-COVID-19 syndrome.

METHODS

A stratified random sampling method was used to select 498 participants from three universities in Fujian as the target of the questionnaire survey. The survey focused on students' healthy lifestyles and the symptoms of fatigue, anxiety, dyspnea, and depression that are common in post-COVID-19 syndrome.

RESULTS

Two months after developing COVID-19, some students continued to experience fatigue, anxiety, dyspnea, and depression, with fatigue being the most prominent symptom. The results of the study showed that there was a significant negative correlation (P < 0.01) between a healthy lifestyle and fatigue, anxiety, dyspnea, and depression among university students. Furthermore, when analyzing the different subdimensions of healthy lifestyles among university students, it was found that all dimensions showed varying degrees of negative correlation with fatigue, anxiety, dyspnea, and depression, except for health-related behaviors and interpersonal behaviors, which showed no relationship with fatigue (P < 0.01).

CONCLUSIONS

By improving healthy lifestyles, long-term COVID-19 symptoms can be reduced and improved and contribute positively to patient recovery, providing a viable rehabilitation option for long-term COVID-19 patients.

Racism, health and pandemic: a narrative review of the relationship between black population and COVID-19 events in 2020

This study aimed to analyze how scientific publications described and interpreted findings about the relationship between the Black population and events linked to COVID-19 in 2020. Narrative review with systematic search, in which a survey was conducted on articles published in 2020 in the Scopus, Medline/PubMed, and Web of Science databases. Initially, 665 articles were found, and after reading and applying the eligible criteria, the final number of 45 articles was reached. Epidemiological, observational studies, secondary data and developed in the United States predominated. Four groupings and respective findings emerged from the synthesis of information extracted: Main events in the Black population - high number of deaths and mortality rate; Direct relationships - poor health, housing, and work conditions; Intermediate relationships - low income and anti-Black prejudice; Comprehensive relationships - structural racism and social determinants of health. The identification of racial health disparities is an important finding about the dynamics of the pandemic among the Black population. However, multicausal explanations were limited. It is necessary to mobilize critical theoretical resources from ethnic and health studies to qualify research in order to support global actions to combat the SARS-CoV-2 epidemic in this group.

The COVID-19 pandemic and neurology: A survey on previous and continued restrictions for clinical practice, curricular training, and health economics

BACKGROUND AND PURPOSE

The COVID-19 pandemic has significantly impacted health systems worldwide. Here, we assessed the pandemic's impact on clinical service, curricular training, and financial burden from a neurological viewpoint during the enforced lockdown periods and the assumed recovery by 2023.

METHODS

An online 18-item survey was conducted by the European Academy of Neurology (EAN) NeuroCOVID-19 Task Force among the EAN community. The survey was online between February and March 2023. Questions related to general, demographic, clinical, work, education, and economic aspects.

RESULTS

We collected 430 responses from 79 countries. Most health care professionals were aged 35-44 years, with >15 years of work experience. The key findings of their observations were as follows. (i) Clinical services were cut back in all neurological subspecialties during the most restrictive COVID-19 lockdown period. The most affected neurological subspecialties were services for patients with dementia, and neuromuscular and movement disorders. The levels of reduction and the pace of recovery were distinct for acute emergencies and in- and outpatient care. Recovery was slow for sleep medicine, autonomic nervous system disorders, neurorehabilitation, and dementia care. (ii) Student and residency rotations and grand rounds were reorganized, and congresses were converted into a virtual format. Conferences are partly maintained in a hybrid format. (iii) Affordability of neurological care and medication shortage are emerging issues.

CONCLUSIONS

Recovery of neurological services up to spring 2023 has been incomplete following substantial disruption of neurological care, medical education, and health economics in the wake of the COVID-19 pandemic. The continued limitations for the delivery of neurological care threaten brain health and call for action on a global scale.

Racial and Ethnic Disparities in Excess All-Cause Mortality in the First Year of the COVID-19 Pandemic

Research on the COVID-19 pandemic in the United States has consistently found disproportionately high mortality among ethnoracial minorities, but reports differ with respect to the magnitude of mortality disparities and reach different conclusions regarding which groups were most impacted. We suggest that these variations stem from differences in the temporal scope of the mortality data used and difficulties inherent in measuring race and ethnicity. To circumvent these issues, we link Social Security Administration death records for 2010 through 2021 to decennial census and American Community Survey race and ethnicity responses. We use these linked data to estimate excess all-cause mortality for age-, sex-, race-, and ethnicity-specific subgroups and examine ethnoracial variation in excess mortality across states and over the course of the pandemic's first year. Results show that non-Hispanic American Indians and Alaska Natives experienced the highest excess mortality of any ethnoracial group in the first year of the pandemic, followed by Hispanics and non-Hispanic Blacks. Spatiotemporal and age-specific ethnoracial disparities suggest that the socioeconomic determinants driving health disparities prior to the pandemic were amplified and expressed in new ways in the pandemic's first year to disproportionately concentrate excess mortality among racial and ethnic minorities.

Covid-19 outbreak associated with demographic-meteorological factors in the arid and semi-arid region Iran: case study Gonabad city, 2020-2021

Since the (Covid-19) pandemic outbreak, questioning regarding climate and incident of Covid-19 infection rates has been debated, while there is no clear research evidence until now in Iran. This study has focused on investigating the association between Covid-19 cases and demographic -meteorological factors in arid and semi-arid zones of Iran (from March 1, 2020, to January 31, 2022) by analyzing with Via Poisson and negative binomial regression. As a result, the incidence rate of both Covid-19 hospitalization and mortality cases reached peaks in the summer followed by the autumn. Interestingly, Covid-19 hospitalization cases are associated with humidity, temperature, and wind factors seasonally and monthly, but mortality cases are just associated with wind. In conclusion, the result demonstrated that demographicand meteorological factorsare positively and negatively associated with Covid-19 cases. Therefore, identifying the environmental factors contributing to the excess Covid-19 can help to prevent future pandemic waves in Iranian arid and semi-arid zone.

Primary healthcare workers' COVID-19 infection status following implementation of adjusted epidemic prevention and control strategies: a cross-sectional study in Jiangsu, China

Introduction

In times of epidemic outbreaks, healthcare workers (HCWs) emerge as a particularly vulnerable group. This cross-sectional study endeavors to assess the COVID-19 infection rate among the primary HCWs in Jiangsu Province subsequent to the implementation of adjusted epidemic prevention and control strategies.

Methods

From January 17 to February 2, 2023, an extensive survey was conducted among primary HCWs in Jiangsu Province, employing a self-designed questionnaire. Logistic regression analysis was utilized to identify the factors associated with COVID-19 infection.

Results

The overall infection rate among primary HCWs stood at 81.05%, with a 95% confidence interval (CI) of 80.61-81.48%. Among those afflicted, cough, fatigue, and fever emerged as the three most prevalent symptoms, each with an incidence rate exceeding 80%. In the context of multivariate logistic regression, an elevated risk of COVID-19 infection was observed in correlation with female gender (adjusted odds ratio [aOR] = 1.12, 95% CI: 1.04-1.21), possessing a bachelor's degree or higher (aOR = 1.32, 95% CI: 1.23-1.41), accumulating over 10 years of work experience (aOR = 1.28, 95% CI: 1.11-1.47), holding a middle-level cadre position (aOR = 1.22, 95% CI: 1.11-1.35), assuming the role of a unit leader (aOR = 1.30, 95% CI: 1.11-1.54), and working in a fever clinic for 1 to 10 days per month (aOR = 1.42, 95% CI: 1.29-1.57). Conversely, advanced age (aOR = 0.76, 95% CI: 0.70-0.82), being underweight (aOR = 0.78, 95% CI: 0.69-0.90), current smoking (aOR = 0.64, 95% CI: 0.57-0.71), receiving 4 doses of COVID-19 vaccine (aOR = 0.49, 95% CI: 0.37-0.66), and pregnancy or perinatal status (aOR = 0.85, 95% CI: 0.72-0.99) were associated with a diminished risk of infection.

Conclusion

Following the implementation of adjusted policies, a substantial proportion of primary HCWs in Jiangsu province contracted COVID-19. Female gender and younger age emerged as risk factors for COVID-19 infection, while no discernible link was established between professions and COVID-19 susceptibility. The receipt of COVID-19 vaccines demonstrated efficacy in curtailing the infection rate, underscoring the significance of bolstering prevention knowledge and heightening self-protective awareness among primary HCWs.

Impact of sociodemographic and economic determinants of health on COVID-19 infection: incidence variation between reference periods

OBJECTIVES

The COVID-19 pandemic hit Portugal in March 2020, causing widespread disruption to various aspects of society. While extensive research has been conducted on the significance of socio-economic disparities in infection risk, this study aims to enhance our understanding of their evolving relationship over time by analysing four distinct periods in 2020.

STUDY DESIGN AND METHODS

This retrospective observational ecological study included individuals residing in the Primary Healthcare Cluster areas of Almada-Seixal and Western Lisbon and Oeiras, who tested positive for SARS-CoV-2 through a polymerase chain reaction (PCR) test between the 2nd of March and the 8th of November of 2020. Using incidence rates for each specific neighbourhood (n = 29) and period, we explored the relationship between neighbourhood-level socio-economic variables and the risk of infection using negative-binomial regression models.

RESULTS

In the analysed period, a total of 8562 confirmed COVID-19 cases were identified. Overall incidence rates for each period were sequentially 2.74, 5.03, 3.99 and 14.29 COVID-19 cases per 100,000 person-days. Housing overcrowding, illiteracy rate and place of birth were associated with increased risk of infection, while age, congregate living, and employment in the secondary sector exhibited the opposite association. No association was consistent across all time periods.

CONCLUSIONS

Our findings support the idea that the influence of socio-economic determinants of health is not immutable throughout time. In a pandemic context where information, knowledge, beliefs, and behaviours are ever-changing and evolving, a dynamic, inclusive, and adaptable approach to disease control can lead to a more equitable distribution of improved outcomes, benefiting all strata of society.

Evaluating the Added Value of Digital Contact Tracing Support Tools for Citizens: Framework Development

BACKGROUND

The COVID-19 pandemic revealed that with high infection rates, health services conducting contact tracing (CT) could become overburdened, leading to limited or incomplete CT. Digital CT support (DCTS) tools are designed to mimic traditional CT, by transferring a part of or all the tasks of CT into the hands of citizens. Besides saving time for health services, these tools may help to increase the number of contacts retrieved during the contact identification process, quantity and quality of contact details, and speed of the contact notification process. The added value of DCTS tools for CT is currently unknown.

OBJECTIVE

To help determine whether DCTS tools could improve the effectiveness of CT, this study aims to develop a framework for the comprehensive assessment of these tools.

METHODS

A framework containing evaluation topics, research questions, accompanying study designs, and methods was developed based on consultations with CT experts from municipal public health services and national public health authorities, complemented with scientific literature.

RESULTS

These efforts resulted in a framework aiming to assist with the assessment of the following aspects of CT: speed; comprehensiveness; effectiveness with regard to contact notification; positive case detection; potential workload reduction of public health professionals; demographics related to adoption and reach; and user experiences of public health professionals, index cases, and contacts.

CONCLUSIONS

This framework provides guidance for researchers and policy makers in designing their own evaluation studies, the findings of which can help determine how and the extent to which DCTS tools should be implemented as a CT strategy for future infectious disease outbreaks.

Communications for US Populations With Limited English Proficiency During Infectious Disease Outbreaks: A Scoping Review

The COVID-19 pandemic has highlighted the need for research about communicating with populations who have limited English proficiency in the United States during infectious disease outbreaks. These populations have experienced significantly worse health outcomes during emergencies, including the COVID-19 pandemic, and evidence-based risk communications are critical to protecting their health. To support improved development of emergency communications for these communities, we conducted a scoping review that examined the extent of research available, with an intent to identify which communications topics are covered in the literature and where research gaps exist. Following the JBI framework, with reporting guided by the PRISMA extension for scoping reviews, 6 electronic databases were systematically searched in October 2022. The inclusion criteria for articles selected were: data collected between 2009 and 2022, published in English, and focused on communications pertaining to emergency infectious disease outbreaks (eg, H1N1 influenza, Zika virus, COVID-19) for populations with limited English proficiency. Of 2,049 articles identified through the search, 31 met the inclusion criteria and were selected for review. We identified major limitations in the evidence base: a majority of studies were conducted only among Spanish speakers or during the COVID-19 pandemic, and most used qualitative or nonrandom samples. Most studies documented basic language barriers in communications, but there was little exploration of more nuanced barriers, such as cultural relevance or social context. Ahead of future outbreaks, more research is urgently needed to examine the information landscapes of populations with limited English proficiency, to inform the development of more effective communications strategies from public health institutions and others.

Neither Words nor Images: Health Departments' and Hospitals' Use of Twitter During COVID-19 Had Limited Racial Representation and Content on Disparities Decreased Over Time

OBJECTIVE

To determine the degree to which hospitals and state health departments used written content or visual representation on social media to draw attention to racial disparities during the COVID-19 pandemic.

STUDY DESIGN

A retrospective analysis, using Twitter content (words and images) between May-June 2020 and May-June 2021 from organizations in the 5 states with the largest documented racial disparities in COVID-19-related mortality.

MAIN OUTCOMES

All tweets and retweets (n = 6790) were coded along several lines. For May-June 2020 and May-June 2021, posts were coded as pandemic related (yes/no) and disparities related (yes/no). Open-coding methods categorized pandemic-related content into content areas, including COVID-19 education, hospital or public policy, and addressing misinformation. After self-identifying their own race/ethnicity, survey respondents (n = 100) coded pandemic-related Twitter images (n = 198) as including individuals of a similar race/ethnicity (yes/no).

RESULTS

In May-June 2020, health departments posted more pandemic-related content than hospitals (μ = 204 and 71 tweets, respectively; P = .03), including more about health disparities (μ = 14.3% and 2.11% of tweets, respectively; P = .03). Between May-June 2020 and May-June 2021, content addressing health disparities decreased for both groups (47% decrease for health departments and 69% decrease for hospitals). Black respondents were more likely to feel represented in images from health departments than in those from hospitals (44.3% and 23.7% of images, respectively; P = .05). Both hospitals and health departments were more likely to use images where White respondents felt represented (hospitals = 76.1% of images; health departments = 59.7%) than images where respondents from racial/ethnic minorities felt represented (hospitals = 19.3% of images; health departments = 21.4%) ( P ≤ .001 for hospitals; P = .004 for health departments).

CONCLUSIONS

Health education ideally comes in a variety of ways. Hospitals used social media for this purpose less than health departments, and neither group increased such content during the COVID-19 pandemic even as evidence of racial disparities grew.

Native American Community Perspectives on Oral Health Access: Understanding the Impact of Rurality

PURPOSE

Oral health disparities related to access persist for American Indian/Alaska Native (AI/AN) communities compared to the general population, especially in rural areas of the United States. The objective of this study was to better understand community perspectives of oral health, how rurality impacts access to care, and attitudes towards the implementation of dental therapists in Oklahoma, particularly among the AI/AN population.

METHODS

A descriptive, observational study design was utilized. An exploratory survey was conducted online and comprised of qualitative and quantitative data. The total frequencies and percentages were evaluated for the quantitative questions. The qualitative data was analyzed using thematic analysis. Utilizing descriptive and qualitative research methods, the focus was to describe the experiences of the respondents and their characteristics related to oral health in Oklahoma.

RESULTS

A total of 201 responses were obtained, where 65% (n = 131) identified as an enrolled member or employee of a tribe represented in Oklahoma. Key qualitative themes included community access to care, community concerns, and community motivated solutions.

CONCLUSIONS

AI/AN communities are an underserved group in healthcare. Although communities in rural areas face major barriers to oral health services, evidence-based solutions can be implemented.

Adjusting expected deaths for mortality displacement during the COVID-19 pandemic: a model based counterfactual approach at the level of individuals

BACKGROUND

Near-real time surveillance of excess mortality has been an essential tool during the COVID-19 pandemic. It remains critical for monitoring mortality as the pandemic wanes, to detect fluctuations in the death rate associated both with the longer-term impact of the pandemic (e.g. infection, containment measures and reduced service provision by the health and other systems) and the responses that followed (e.g. curtailment of containment measures, vaccination and the response of health and other systems to backlogs). Following the relaxing of social distancing regimes and reduction in the availability of testing, across many countries, it becomes critical to measure the impact of COVID-19 infection. However, prolonged periods of mortality in excess of the expected across entire populations has raised doubts over the validity of using unadjusted historic estimates of mortality to calculate the expected numbers of deaths that form the baseline for computing numbers of excess deaths because many individuals died earlier than they would otherwise have done: i.e. their mortality was displaced earlier in time to occur during the pandemic rather than when historic rates predicted. This is also often termed "harvesting" in the literature.

METHODS

We present a novel Cox-regression-based methodology using time-dependent covariates to estimate the profile of the increased risk of death across time in individuals who contracted COVID-19 among a population of hip fracture patients in England (N = 98,365). We use these hazards to simulate a distribution of survival times, in the presence of a COVID-19 positive test, and then calculate survival times based on hazard rates without a positive test and use the difference between the medians of these distributions to estimate the number of days a death has been displaced. This methodology is applied at the individual level, rather than the population level to provide a better understanding of the impact of a positive COVID-19 test on the mortality of groups with different vulnerabilities conferred by sociodemographic and health characteristics. Finally, we apply the mortality displacement estimates to adjust estimates of excess mortality using a "ball and urn" model.

RESULTS

Among the exemplar population we present an end-to-end application of our methodology to estimate the extent of mortality displacement. A greater proportion of older, male and frailer individuals were subject to significant displacement while the magnitude of displacement was higher in younger females and in individuals with lower frailty: groups who, in the absence of COVID-19, should have had a substantial life expectancy.

CONCLUSION

Our results indicate that calculating the expected number of deaths following the first wave of the pandemic in England based solely on historical trends results in an overestimate, and excess mortality will therefore be underestimated. Our findings, using this exemplar dataset are conditional on having experienced a hip fracture, which is not generalisable to the general population. Fractures that impede mobility in the weeks that follow the accident/surgery considerably shorten life expectancy and are in themselves markers of significant frailty. It is therefore important to apply these novel methods to the general population, among whom we anticipate strong patterns in mortality displacement - both in its length and prevalence - by age, sex, frailty and types of comorbidities. This counterfactual method may also be used to investigate a wider range of disruptive population health events. This has important implications for public health monitoring and the interpretation of public health data in England and globally.

Increased odds for COVID-19 infection among individuals with periodontal disease

OBJECTIVES

Periodontal disease has been linked to multiple systemic conditions, but the relationship with COVID-19 still needs to be elucidated. We hypothesized that periodontal disease may be associated with COVID-19 infection.

MATERIALS AND METHODS

This study utilized cross-sectional data to establish the strength of the association between periodontal disease and COVID-19 infection. The University of Florida Health Center's i2b2 patient's registry was used to generate patient counts through ICD-10 diagnostic codes. Univariate descriptive statistics of the patient population and logistic regression to estimate odds ratios of associations between periodontal disease and COVID-19 infection were used for analysis.

RESULTS

Patients with periodontal disease were 4.4 times more likely to be positively diagnosed with COVID-19 than patients without PD. Associations remained similar and robust (P value < 0.0001) after adjustment for age (OR = 4.34; 95% CI, 3.68-5.09), gender (OR = 4.46; 95% CI, 3.79-5.23), and smoking status (OR = 4.77; 95% CI, 4.04-5.59). Associations were smaller but remained robust (P value < 0.0001) after adjusting for race (OR = 2.83; 95% CI, 2.40-3.32), obesity (OR = 2.53; 95% CI, 2.14-2.98), diabetes (OR = 3.32; 95% CI, 2.81-3.90), and cardiovascular disease (OR = 2.68; 95% CI, 2.27-3.14).

CONCLUSIONS

Periodontal disease is significantly associated with increased odds for COVID-19 infection.

CLINICAL RELEVANCE

With the caveat of a cross-sectional study design, these results suggest that periodontal disease may increase the odds for COVID-19 infection.

Assessment of hospitalisation costs and their determinants among Covid-19 patients in South Central Ethiopia

BACKGROUND

The coronavirus disease 2019 (Covid-19) pandemic is a global public health problem. The Covid-19 pandemic has had a substantial impact on the economy of developing countries, including Ethiopia.This study aimed to determine the hospitalisation costs of Covid-19 and the factors associated with the high cost of hospitalisation in South Central Ethiopia.

METHODS

A retrospective cost analysis of Covid-19 patients hospitalised between July 2020 and July 2021 at Bokoji Hospital Covid-19 Treatment Centre was conducted using both the micro-costing and top-down approaches from the health system perspective. This analysis used cost data obtained from administrative reports, the financial reports of the treatment centre, procurement invoices and the Covid-19 standard treatment guidelines. The Student's t-test, Mann-Whitney U test or Kruskal-Wallis test was employed to test the difference between sociodemographic and clinical factors when appropriate.To identify the determinants of cost drivers in the study population, a generalised linear model with gamma distribution and log link with a stepwise algorithm were used.

RESULTS

A total of 692 Covid-19 patients were included in the costing analysis. In this study, the mean cost of Covid-19-infected patients with no symptoms was US$1,073.86, with mild symptoms US$1,100.74, with moderate symptoms US$1,394.74 and in severe-critically ill condition US$1,708.05.The overall mean cost was US$1,382.50(95% CI: 1,360.60-1,404.40) per treated episode.The highest mean cost was observed for personnel, accounting for 64.0% of the overall cost. Older age, pre-existing diseases, advanced disease severity at admission, admission to the intensive care unit, prolonged stay on treatment and intranasal oxygen support were strongly associated with higher costs.

CONCLUSIONS

This study found that the clinical management of Covid-19 patients incurred significant expenses to the health system. Factors such as older age, disease severity, presence of comorbidities, use of inhalation oxygen therapy and prolonged hospital stay were associated with higher hospitalisation costs.Therefore, the government should give priority to the elderly and those with comorbidities in the provision of vaccination to reduce the financial burden on health facilities and health systems in terms of resource utilisation.

Supplemental Nutrition Assistance Program Education reductions during COVID-19 may have exacerbated health inequities

OBJECTIVE

Describe, and assess disparities in, the changes in Supplemental Nutrition Assistance Program Education (SNAP-Ed) that occurred the year before vs. the year when COVID-19 restrictions were implemented.

DESIGN

Observational study comparing reach, intensity, and dose of California Local Health Department (LHD) SNAP-Ed interventions in Federal Fiscal years 2019 and 2020 (FFY19, FFY20).

ANALYSIS

Student t-tests determined significance of differences in the number of Direct Education (DE) programs, Policy, Systems and Environmental change (PSE) sites, people reached, and intervention intensity and dose between FFY19 and FFY20 using data reported online by LHDs. Linear regression assessed associations between census tract-level characteristics (urbanicity; percentages of population with income <185% of federal poverty level, under 18 years of age, and belonging to various racial/ethnic groups; and California Healthy Places Index) and changes in number of DE programs, PSE sites, people reached, and intervention dose between FFY19 and FFY20.

RESULTS

From FFY19 to FFY20, the number of DE programs, PSE sites, people reached, and census tract-level intervention intensity and dose decreased. Higher census tract poverty, higher proportions of Black and Latino residents, and less healthy neighborhood conditions were associated with greater decreases in some intervention characteristics including PSE sites, PSE reach, DE programs, and DE dose.

CONCLUSIONS AND IMPLICATIONS

These reductions in LHD SNAP-Ed interventions indicate reduced access to education and environments that support healthy eating and obesity prevention during a time when this support was especially needed to reduce risk of COVID-19 infection and complications. Disproportionately reduced access, may have worsened health disparities in already-disadvantaged communities. Assuring maintenance of SNAP-Ed interventions, especially in disadvantaged communities, should be a priority during public health emergencies.

Psychosocial predictors of COVID-19 infection in UK biobank (N = 104 201)

BACKGROUND

Since the outbreak of COVID-19, data on its psychosocial predictors are limited. We therefore aimed to explore psychosocial predictors of COVID-19 infection at the UK Biobank (UKB).

METHODS

This was a prospective cohort study conducted among UKB participants.

RESULTS

The sample size was N = 104 201, out of which 14 852 (14.3%) had a positive COVID-19 test. The whole sample analysis showed significant interactions between sex and several predictor variables. Among females, absence of college/university degree [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.45-1.66] and socioeconomic deprivation (OR 1.16 95% CI 1.11-1.21) were associated with higher odds of COVID-19 infection, while history of psychiatric consultation (OR 0.85 95% CI 0.77-0.94) with lower odds. Among males, absence of college/university degree (OR 1.56, 95% CI 1.45-1.68) and socioeconomic deprivation (OR 1.12, 95% CI 1.07-1.16) were associated with higher odds, while loneliness (OR 0.87, 95% CI 0.78-0.97), irritability (OR 0.91, 95% CI 0.83-0.99) and history of psychiatric consultation (OR 0.85, 95% CI 0.75-0.97) were associated with lower odds.

CONCLUSION

Sociodemographic factors predicted the odds of COVID-19 infection equally among male and female participants, while psychological factors had differential impacts.

Neutralization against SARS-CoV-2 Delta/Omicron variants and B cell response after inactivated vaccination among COVID-19 convalescents

Emerging SARS-CoV-2 variants have made COVID-19 convalescents susceptible to re-infection and have raised concern about the efficacy of inactivated vaccination in neutralization against emerging variants and antigen-specific B cell response. To this end, a study on a long-term cohort of 208 participants who have recovered from COVID-19 was conducted, and the participants were followed up at 3.3 (Visit 1), 9.2 (Visit 2), and 18.5 (Visit 3) months after SARS-CoV-2 infection. They were classified into three groups (no-vaccination (n = 54), one-dose (n = 62), and two-dose (n = 92) groups) on the basis of the administration of inactivated vaccination. The neutralizing antibody (NAb) titers against the wild-type virus continued to decrease in the no-vaccination group, but they rose significantly in the one-dose and two-dose groups, with the highest NAb titers being observed in the two-dose group at Visit 3. The NAb titers against the Delta variant for the no-vaccination, one-dose, and two-dose groups decreased by 3.3, 1.9, and 2.3 folds relative to the wild-type virus, respectively, and those against the Omicron variant decreased by 7.0, 4.0, and 3.8 folds, respectively. Similarly, the responses of SARS-CoV-2 RBD-specific B cells and memory B cells were boosted by the second vaccine dose. Results showed that the convalescents benefited from the administration of the inactivated vaccine (one or two doses), which enhanced neutralization against highly mutated SARS-CoV-2 variants and memory B cell responses. Two doses of inactivated vaccine among COVID-19 convalescents are therefore recommended for the prevention of the COVID-19 pandemic, and vaccination guidelines and policies need to be updated.

Clinical Characteristics of Hospitalized Patients With COVID-19: A Retrospective Cohort Study in Pakistan

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe upper respiratory tract infections known as COVID-19. This single-center study aimed to investigate the demographics, comorbidities, symptoms, and disease severity of COVID-19 patients in Pakistan.

METHODS

A retrospective descriptive study was conducted at the Pakistan Kidney and Liver Institute and Research Center from April 2020 to August 2020. A total of 430 PCR-positive COVID-19 patients were categorized into symptomatic and asymptomatic groups. The symptomatic group was further classified into severe and non-severe subgroups. Patients' demographics, comorbid conditions, presenting symptoms, laboratory parameters, and clinical outcomes were assessed in these two subgroups. Statistical tests were applied to determine significant differences.

RESULTS

A total of 430 patients with COVID-19 presented in our center, of whom 334 (78%) were symptomatic and included in the study. Severe disease was observed in 83 (24.8%) symptomatic patients, with a male predominance (75.9%) and higher mean age (61.7 ± 13.2). Travel to high-risk destinations (p < 0.002) and close contact with COVID-19 patients (p < 0.001) were significant risk factors. Major comorbid conditions included diabetes mellitus (30.5%) and hypertension (39.8%). Frequent symptoms included fever (71.8%), cough (68.8%), dyspnea (53.8%), and myalgias (35.9%). Higher C-reactive protein (median = 12.76 vs. 1.45, p = 0.001), ferritin (median = 996.70 vs. 628, p = 0.004), and D-dimers (median = 1121 vs. 439.50, p = 0.009) were noted in severe vs non-severe disease. Lymphopenia was more prevalent in severe vs. non-severe disease (83.1% vs. 14.3% p-value = 0.033). More deaths (28.9%) and ICU admissions (53%) with a prolonged hospital stay (median = 25 days, IQR = 16.0-31.0) were noted in the severe group.

CONCLUSION

This retrospective study provides insights into the clinical characteristics and outcomes of COVID-19 patients. Age, male gender, comorbidities, and specific symptoms were associated with disease severity. Inflammatory markers, including D-dimers, ferritin, and CRP, were elevated in severe cases. These findings contribute to a better understanding of COVID-19 and may aid in clinical management and decision-making for patients affected by the disease.

Intersectional Stigma as a Fundamental Cause of Health Disparities: A case study of how drug use stigma intersecting with racism and xenophobia creates health inequities for Black and Hispanic persons who use drugs over time

Recent evidence points to racial and ethnic disparities in drug-related deaths and health conditions. Informed by stigma, intersectionality, intersectional stigma, and fundamental cause theories, we aimed to explore whether intersectional stigma was a fundamental cause of health. We document key events and policies over time and find that when progress is made new mechanisms emerge that negatively affect health outcomes for Black and Hispanic persons. We then focus on intersectional stigma targeting Black and Hispanic persons who use drugs. We document that when a person, or group of people, occupy multiple stigmatized identities the processes of stigmatization and scapegoating are particularly persistent and pernicious since people and groups can be stigmatized and scapegoated on varying intersections. We propose that an intersectional stigma framework allows for a better understanding of observed patterns over time, thereby providing a better guide for policies and interventions designed to reduce disparities. As a framework, intersectional stigma aims to recognize that when different sources of stigma collide, a new set of circumstances is created for those who reside in the intersection. We conclude that intersectional stigma is a fundamental cause of health inequities and provide policy recommendations aimed at dismantling intersectional stigma processes and mitigating the effects of intersectional stigmas to ultimately promote better health outcomes for Black and Hispanic persons who use drugs.

Risk factors for SARS-CoV-2 infection during the early stages of the COVID-19 pandemic: a systematic literature review

Introduction

Identifying SARS-CoV-2 infection risk factors allows targeted public health and social measures (PHSM). As new, more transmissible variants of concern (VoC) emerge, vaccination rates increase and PHSM are eased, it is important to understand any potential change to infection risk factors. The aim of this systematic literature review is to describe the risk factors for SARS-CoV-2 infection by VoC.

Methods

A literature search was performed in MEDLINE, PubMed and Embase databases on 5 May 2022. Eligibility included: observational studies published in English after 1 January 2020; any age group; the outcome of SARS-CoV-2 infection; and any potential risk factors investigated in the study. Results were synthesized into a narrative summary with respect to measures of association, by VoC. ROBINS-E tool was utilized for risk of bias assessment.

Results

Of 6,197 studies retrieved, 43 studies were included after screening. Common risk factors included older age, minority ethnic group, low socioeconomic status, male gender, increased household size, occupation/lower income level, inability to work from home, public transport use, and lower education level. Most studies were undertaken when the ancestral strain was predominant. Many studies had some selection bias due to testing criteria and limited laboratory capacity.

Conclusion

Understanding who is at risk enables the development of strategies that target priority groups at each of the different stages of a pandemic and helps inform vaccination strategies and other interventions which may also inform public health responses to future respiratory infection outbreaks. While it was not possible to determine changes to infection risk by recent VoC in this review, the risk factors identified will add to the overall understanding of the groups who are at greatest risk of infection in the early stages of a respiratory virus outbreak.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022330706, PROSPERO [CRD42022330706].

SARS-CoV-2 Infection in Cities from the Southern Region of Bahia State, Brazil: Analysis of Variables Associated in Both Individual and Community Level

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), challenged public health systems worldwide. Individuals in low-income countries/regions are still at individual and community risk concerning inequality, sanitation, and economic conditions. Besides, during the pandemic, the transmission in municipalities and communities in the countryside and less developed regions kept viral spread and required structured and strengthened clinical and laboratory surveillance. Here, we present an observational, analytic, cross-sectional study conducted using secondary data from the Laboratório de Farmacogenômica e Epidemiologia Molecular (LAFEM)-Universidade Estadual de Santa Cruz (UESC), to evaluate individual and community factors associated to SARS-CoV-2 infection in outpatients from different cities from Southern Region of Bahia State, in Brazil. The data were collected between June 2021 and May 2022. The SARS-CoV-2 positivity by RT-qPCR was correlated with low socio-economic indicators, including the Human development index (HDI_c) and Average worker salary (AWSc). Besides, in general, females were less likely to test positive for SARS-CoV-2 (OR = 0.752; CI 95% 0.663-0.853; p < 0.0001), while brown individuals had more positivity for infection (p < 0.0001). In addition, those who had clinical symptoms were more likely to test positive for SARS-CoV-2 (OR = 6.000; CI 95% 4.932-7.299; p < 0.0001). Although dry cough, headache, and fever were the most frequent, loss of taste (OR = 5.574; CI 95% 4.334-7.186) and loss of smell (OR = 6.327; CI 95% 4.899-8.144) presented higher odds ratio to be positive to SARS-CoV-2 by RT-qPCR. Nonetheless, the distribution of these characteristics was not homogenous among the different cities, especially for age and gender. The dynamic of SARS-CoV-2 positivity differed between cities and the total population and reinforces the hypothesis that control strategies for prevention needed to be developed based on both individual and community risk levels to mitigate harm to individuals and the health system.

Age-based spatial disparities of COVID-19 incidence rates in the United States counties

COVID-19 incidence disparities have been documented in the literature, but the different driving factors among age groups have yet to be explicitly explained. This study proposes a community-based COVID-19 spatial disparity model, considering different levels of geographic units (individual and community), various contextual variables, multiple COVID-19 outcomes, and different geographic contextual elements. The model assumes the existence of age nonstationarity effects on health determinants, suggesting that health effects of contextual variables vary among place and age groups. Based on this conceptual model and theory, the study selected 62 county-level variables for 1,748 U.S. counties during the pandemic, and created an Adjustable COVID-19 Potential Exposure Index (ACOVIDPEI) using principal component analysis (PCA). The validation was done with 71,521,009 COVID-19 patients in the U.S. from January 2020 through June 2022, with high incidence rates shifting from the Midwest, South Carolina, North Carolina, Arizona, and Tennessee to the West and East coasts. This study corroborates the age nonstationarity effect of health determinants on COVID-19 exposures. These results empirically identify the geographic disparities of COVID-19 incidence rates among age groups and provide the evidentiary guide for targeting pandemic recovery, mitigation, and preparedness in communities.

Early COVID-19 Attitudes and Behaviors and Their Associations With Later Infection: A Local Perspective From One U.S. City

BACKGROUND

At the onset of the pandemic, there was poor public awareness and inaction in response to COVID-19; it is less known whether this translated to subsequent infections.

OBJECTIVES

To explore whether adults who perceived COVID-19 as less of a threat and who were not taking early actions were more likely to become infected over the following year.

RESEARCH DESIGN

Survey data from the ongoing (COVID-19 & Chronic Conditions (C3) anonymized for review) cohort study.

PARTICIPANTS

Six hundred forty-two adults with a mean age of 63 and ≥1 chronic condition.

MEASURES

Self-reported attitudes and behaviors regarding COVID-19 were assessed from March 13 to April 3, 2020, and COVID-19 infection status was captured between May 2020 and January 2021. Bivariate and multivariable analyses examined associations between early perceptions and behaviors with later infection.

RESULTS

Approximately 7% reported infection with COVID-19 (N = 46). Adults who perceived the threat of COVID-19 less seriously at the initial outbreak were more likely to test positive over the following year [odds ratio (OR): 0.81, CI: 0.70-0.94; P = 0.006]. Those who were less likely to believe their actions would affect whether they would become infected were more likely to test positive (OR: 0.87, CI: 0.77-0.99; P = 0.03), as were adults who reported not changing their routines (OR: 0.45; CI: 0.24-0.85; P = 0.01).

CONCLUSIONS

Adults with delayed responses in acknowledging the threat of COVID-19 and in changing behaviors were more likely to contract the virus. This investigation provides insight into the consequences of inadequate public understanding and response to COVID-19, and it highlights the importance of promoting early awareness among high-risk groups during public health crises.

Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study

INTRODUCTION

Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures.

METHODS

A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%.

RESULTS

According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10-2.13) and employed adults (aOR = 2.06, 95% CI 1.42-3.00), and was more frequent among adults with a higher education (aOR_secondary = 1.93, 95% CI 1.20-3.13; aOR_tertiary = 3.19, 95% CI 1.81-5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17-9.45) and employed (aOR = 4.58, 95% CI 1.38-15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56-22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09-4.15; aOR71+y = 14.52, 95% CI 7.33-28.77). Higher than primary education (aOR_secondary = 1.69, 95% CI 1.08-2.63; aOR_tertiary = 4.36, 95% CI 2.46-7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75-3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44-0.83).

CONCLUSIONS

The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates.

Clinical Disease Characteristics and Treatment Trajectories Associated with Mortality among COVID-19 Patients in Punjab, Pakistan

BACKGROUND

Data on Pakistani COVID-19 patient mortality predictors is limited. It is essential to comprehend the relationship between disease characteristics, medications used, and mortality for better patient outcomes.

METHODS

The medical records of confirmed cases in the Lahore and Sargodha districts were examined using a two-stage cluster sampling from March 2021 to March 2022. Demographics, signs and symptoms, laboratory findings, and pharmacological medications as mortality indicators were noted and analyzed.

RESULTS

A total of 288 deaths occurred out of the 1000 cases. Death rates were higher for males and people over 40. Most of those who were mechanically ventilated perished (OR: 124.2). Dyspnea, fever, and cough were common symptoms, with a significant association amid SpO2 < 95% (OR: 3.2), RR > 20 breaths/min (OR: 2.5), and mortality. Patients with renal (OR: 2.3) or liver failure (OR: 1.5) were at risk. Raised C-reactive protein (OR: 2.9) and D-dimer levels were the indicators of mortality (OR: 1.6). The most prescribed drugs were antibiotics, (77.9%), corticosteroids (54.8%), anticoagulants (34%), tocilizumab (20.3%), and ivermectin (9.2%).

CONCLUSIONS

Older males having breathing difficulties or signs of organ failure with raised C-reactive protein or D-dimer levels had high mortality. Antivirals, corticosteroids, tocilizumab, and ivermectin had better outcomes; antivirals were associated with lower mortality risk.

A Literature Review of the Effects of Air Pollution on COVID-19 Health Outcomes Worldwide: Statistical Challenges and Data Visualization

Several peer-reviewed papers and reviews have examined the relationship between exposure to air pollution and COVID-19 spread and severity. However, many of the existing reviews on this topic do not extensively present the statistical challenges associated with this field, do not provide comprehensive guidelines for future researchers, and review only the results of a relatively small number of papers. We reviewed 139 papers, 127 of which reported a statistically significant positive association between air pollution and adverse COVID-19 health outcomes. Here, we summarize the evidence, describe the statistical challenges, and make recommendations for future research. To summarize the 139 papers with data from geographical locations around the world, we also present anopen-source data visualization tool that summarizes these studies and allows the research community to contribute evidence as new research papers are published.

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

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

Pandemic justice: fairness, social inequality and COVID-19 healthcare priority-setting

A comprehensive understanding of the ethics of the COVID-19 pandemic priorities must be sensitive to the influence of social inequality. We distinguish between ex-ante and ex-post relevance of social inequality for COVID-19 disadvantage. Ex-ante relevance refers to the distribution of risks of exposure. Ex-post relevance refers to the effect of inequality on how patients respond to infection. In the case of COVID-19, both ex-ante and ex-post effects suggest a distribution which is sensitive to the prevalence social inequality. On this basis, we provide a generic fairness argument for the claim that welfare states ought to favour a healthcare priority scheme that gives particular weight to protecting the socially disadvantaged.

The Impact of COVID-19 on Education Experiences of High School Students in Semi-Rural Georgia

BACKGROUND

This study examines the consequences of COVID-19 pandemic on academic and career concerns of high school students; relationship between attendance and grades with educational concerns; and association between student perception of the pandemic and decision to attend school virtually or in-person.

METHODS

Diverse students in grades 9-12 from two public high schools in semi-rural Georgia (n = 666) completed a survey shortly after school closures. Survey results were linked to academic and demographic data. Analyses were examined for differences by demographic and education measures.

RESULTS

Overall, 60% expressed academic worry and reported obstacles to virtual learning. Hispanic students expressed more worry and less confidence while black students reported less worry than peers. Females indicated more worry than males. Grade 12 students reported greater academic and career worry than younger students. Students eligible for free and reduced lunch expressed more worry and obstacles than peers. Non-honors and low-attendance students reported more worry about grades and graduation than their counterparts.

CONCLUSIONS

Results can inform targeted multi-level interventions to reduce the pandemic's effects on learning and ensure healthy trajectories for development across demographics. Stakeholders must take proactive measures to recover from academic loss to ensure our youth's healthy development.

Communication inequalities and health disparities among vulnerable groups during the COVID-19 pandemic - a scoping review of qualitative and quantitative evidence

BACKGROUND

The COVID-19 pandemic has exacerbated health disparities in vulnerable groups (e.g., increased infection, hospitalization, and mortality rates in people with lower income, lower education, or ethnic minorities). Communication inequalities can act as mediating factors in this relationship. Understanding this link is vital to prevent communication inequalities and health disparities in public health crises. This study aims to map and summarize the current literature on communication inequalities linked with health disparities (CIHD) in vulnerable groups during the COVID-19 pandemic and to identify research gaps.

METHODS

A scoping review of quantitative and qualitative evidence was conducted. The literature search followed the guidelines of PRISMA extension for scoping reviews and was performed on PubMed and PsycInfo. Findings were summarized using a conceptual framework based on the Structural Influence Model by Viswanath et al. RESULTS: The search yielded 92 studies, mainly assessing low education as a social determinant and knowledge as an indicator for communication inequalities. CIHD in vulnerable groups were identified in 45 studies. The association of low education with insufficient knowledge and inadequate preventive behavior was the most frequently observed. Other studies only found part of the link: communication inequalities (n = 25) or health disparities (n = 5). In 17 studies, neither inequalities nor disparities were found.

CONCLUSIONS

This review supports the findings of studies on past public health crises. Public health institutions should specifically target their communication to people with low education to reduce communication inequalities. More research about CIHD is needed on groups with migrant status, financial hardship, not speaking the language in the country of residence, sexual minorities, and living in deprived neighborhoods. Future research should also assess communication input factors to derive specific communication strategies for public health institutions to overcome CIHD in public health crises.

Psychology Meets Biology in COVID-19: What We Know and Why It Matters for Public Health

Psychosocial factors are related to immune, viral, and vaccination outcomes. Yet, this knowledge has been poorly represented in public health initiatives during the COVID-19 pandemic. This review provides an overview of biopsychosocial links relevant to COVID-19 outcomes by describing seminal evidence about these associations known prepandemic as well as contemporary research conducted during the pandemic. This focuses on the negative impact of the pandemic on psychosocial health and how this in turn has likely consequences for critically relevant viral and vaccination outcomes. We end by looking forward, highlighting the potential of psychosocial interventions that could be leveraged to support all people in navigating a postpandemic world and how a biopsychosocial approach to health could be incorporated into public health responses to future pandemics.

Temporal and spatial trends in suicide-related visits before and during the COVID-19 pandemic in the US, 2018-2021

BACKGROUND

COVID-19 disproportionately impacted mental health in disadvantaged populations and areas. However, disparities in long-term changes in suicide-related visits across the US are unclear. This retrospective study aims to characterize temporal and spatial changes in suicide-related visits in healthcare settings from 2018 to 2021 in the U.S.

METHODS

We use electronic health records for 21,860,370 patients from Healthjump through the COVID-19 Research Database Consortium. Healthjump harmonizes EHR data from over 55 national databases across the US. Suicide ideation and suicide attempts between January 1, 2018 and December 12, 2021 were identified by the diagnosis codes in 6 periods in 2021 compared with the same periods in 2018-2020.

RESULTS

There was 30,019 suicidal ideation, and 7392 suicide attempt visits from January 2018 to November 2021. 15-20-year-olds were the most represented age group at 6302 suicide ideation visits (21.0 % of suicide ideation visits) and 1326 suicide attempt visits (17.9 % of suicide attempt visits), followed by suicide-related visits among 60+ years old. Compared with pre-pandemic periods, youth aged 15-20, females, White, non-Hispanic, and English speakers had increased suicide-related visits, especially suicidal ideation (P < 0.05). Suicide attempts with non-medical substances increased to 28.0 % in the first 6 months of the pandemic in 2020, compared with the prior year (21.5 %). COVID-19 patients had increased suicidal ideation in 2020.

LIMITATIONS

The EHR data is not nationally representative.

CONCLUSIONS

This study found significant and disproportionate increases in suicide related visits over the COVID-19 stages. To prevent the next storms of suicides, future interventions shall accommodate needs among vulnerable groups during and after periods of crisis.

Dementia and COVID-19 among Older African American Adults: A Scoping Review of Healthcare Access and Resources

African American/Black communities comprise 12.2% of the U.S. population, with a COVID-19 infection rate of more than 18% and marginal access to healthcare services. This scoping review synthesizes the emerging evidence on healthcare accessibility among older African American adult communities with dementia and COVID-19, as well as the resource requirements for this population during the pandemic. Searches of different databases for empirical studies and other sources on dementia and COVID-19 among older African American adults yielded 13 studies that met the following inclusion criteria: (a) focus on dementia and COVID-19, (b) sampled older African American adults, (c) investigated healthcare accessibility and resources, and (d) published between 2019 and 2022. Following the initial selection of the studies, eight were selected for relevance based on the Population, Concept, and Context (PCC) inclusion and exclusion criteria. Thematic analysis indicated that older African Americans with dementia and COVID-19 experienced longer delays in accessing timely healthcare, including transportation, intensive care units (ICUs), and mechanical ventilation. They also had reduced healthcare resources associated with a lack of health insurance, low financial resources, and an increased length of hospital stay, which further aggravated the negative effects of comorbid dementia and COVID-19 infections. Evidence showed that racial and age disparities affected older African American adults with dementia and COVID-19, resulting in lower healthcare access and marginal resources. This is consistent with historical and systemic inequities in meeting the healthcare needs of people of color in the United States, which was compounded for older African Americans during the COVID-19 pandemic.

Pathogen exposure misclassification can bias association signals in GWAS of infectious diseases when using population-based common control subjects

Genome-wide association studies (GWASs) have been performed to identify host genetic factors for a range of phenotypes, including for infectious diseases. The use of population-based common control subjects from biobanks and extensive consortia is a valuable resource to increase sample sizes in the identification of associated loci with minimal additional expense. Non-differential misclassification of the outcome has been reported when the control subjects are not well characterized, which often attenuates the true effect size. However, for infectious diseases the comparison of affected subjects to population-based common control subjects regardless of pathogen exposure can also result in selection bias. Through simulated comparisons of pathogen-exposed cases and population-based common control subjects, we demonstrate that not accounting for pathogen exposure can result in biased effect estimates and spurious genome-wide significant signals. Further, the observed association can be distorted depending upon strength of the association between a locus and pathogen exposure and the prevalence of pathogen exposure. We also used a real data example from the hepatitis C virus (HCV) genetic consortium comparing HCV spontaneous clearance to persistent infection with both well-characterized control subjects and population-based common control subjects from the UK Biobank. We find biased effect estimates for known HCV clearance-associated loci and potentially spurious HCV clearance associations. These findings suggest that the choice of control subjects is especially important for infectious diseases or outcomes that are conditional upon environmental exposures.

Mobility support for disadvantaged and disabled travelers during pandemic or similar situations

The COVID-19 lockdown has reduced public transportation service to the disadvantaged and disabled people who urgently need adequate mobility to obtain essential suppliers. This paper aims to improve the life quality of people with disabilities and elderly people by addressing social exclusion, accessibility, and mobility issues. Demand responsive transport services are frequently offered in the context of door-to-door transportation of the elderly and persons with disabilities. We study and compare two frameworks. We apply both Sample average approximation (SAA) and Rolling Horizon (RH) to optimize a car sharing system for the total cost, including initiation cost and operation cost after fleet size is determined. The model is implemented with given geographic conditions and other local information to be tailored for specific applications for local communities. Given that no historical data is available, random sample data is generated to simulate expected demands. We consider three types of probability distributions for daily demand data, and the results generated using three different distributions are being examined and compared. The research shows that the demand data following a normal distribution results in the minimum total cost. Additionally, we study the impact of several factors on total cost, including demand fulfillment rates and operation hours. Our results suggest that the impact of fulfillment rate on fleet size is exponential after a threshold under all three types of daily demand data, and extended operation hours can significantly reduce the total cost. Finally, the paper provides applicable frameworks for city planners, NPOs, and policymakers to better allocate limited resources to implement the carsharing system when little to no historical travel information is available for low-density population areas. It is anticipated that the outcome from this research would benefit disadvantaged and disabled travelers during COVID-19 or similar difficult situations in the future.

Health behaviors and the risk of COVID-19 incidence: A Bayesian hierarchical spatial analysis

OBJECTIVES

Effective infection control measures, based on a sound understanding of geographical community-specific health behavioral characteristics, should be implemented from the early stage of disease transmission. However, few studies have explored health behaviors as a possible contributor to COVID-19 infection in the spatial context. We investigated health behaviors as potential factors of COVID-19 incidence in the early phase of transmission in the spatial context.

METHODS

We extracted COVID-19 cumulative case data as of February 25, 2021-one day prior to nationwide COVID-19 vaccination commencement-regarding health behaviors and covariates, including health condition and socio-economic factors, at the municipal level from publicly available datasets. The spatial autocorrelation of incidence was analyzed using Global Moran's I statistics. The associations between health behaviors and COVID-19 incidence were examined using Besag-York-Mollie models to deal with spatial autocorrelation of residuals.

RESULTS

The COVID-19 incidence had positive spatial autocorrelation across South Korea (I = 0.584, p = 0.001). The results suggest that individuals vaccinated against influenza in the preceding year had a negative association with COVID-19 incidence (relative risk=0.913, 95 % Credible Interval=0.838-0.997), even after adjusting for covariates.

CONCLUSIONS

Our ecological study suggests an association between COVID-19 infection and health behaviors, especially influenza vaccination, in the early stage of COVID-19 transmission at the municipal level.

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R² of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO₂, PM₁₀, and O₃); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

Development of Innovative Vitamin D Enrichment Designs for Two Typical Italian Fresh Cheeses: Burrata and Giuncata

The aim of this research was to develop innovative cheeses fortified with vitamin D3 (VD3). Formulation studies and analyses of textural properties and chemicals were carried out for these developments. Two traditional Italian varieties of cheese (giuncata and burrata) were studied. For giuncata, the fortification of milk for cheese production provided a VD₃ retention level of 43.9 ± 0.6% in the food matrix. For burrata, the VD₃ ingredient was incorporated into the creamy inner part after mixing, maintaining the textural quality of the product (adhesiveness 4.3 ± 0.4 J × 10^-3; firmness 0.7 ± 0.0 N; and cohesiveness 0.8 ± 0.2). The optimized enrichment designs allowed to obtain homogenous contents of VD₃ during the production of giuncata (0.48 ± 0.01 µg/g) and burrata cheeses (0.32 ± 0.02 µg/g). Moreover, analyses revealed the high stability of VD₃ during the storage of the two fortified cheese types (2 weeks, 4 °C). These fortification designs could be implemented at an industrial scale to obtain new cheese types enriched in VD₃ and thus contribute to the reduction in VD deficiency prevalence.

Influence of socioeconomic inequality on the distribution of COVID-19 hospitalizations and deaths in Brazilian municipalities, 2020: an ecological study

OBJECTIVE

to analyze the influence of socioeconomic inequality on COVID-19 distribution in larger Brazilian municipalities, controlling for effect of hospital infrastructure, comorbidities and other variables.

METHODS

this was an ecological study of COVID-19 hospitalizations and deaths in 2020; outcome data were obtained from the Ministry of Health; incidence ratios were estimated using a generalized linear model.

RESULTS

we identified 291,073 hospitalizations and 139,953 deaths; we found higher mortality rates in municipalities with a higher proportion of non-White people (95%CI 1.01;1.16) and with more households with more than two people per room (95%CI 1.01;1.13); presence of sewerage systems was protective for both outcomes (hospitalizations: 95%CI 0.87;0.99 - deaths: 95%CI 0.90;0.99), while a higher proportion of the population in subnormal housing clusters was a risk factor (hospitalizations: 95%CI 1.01;1.16 - deaths: 95%CI 1.09;1.21), with this variable interacting with the proportion of people receiving Emergency Aid (hospitalizations: 95%CI 0.88;1.00 - deaths: 95%CI 0.89;0.98).

CONCLUSION

socioeconomic conditions affected illness and death due to COVID-19 in Brazil.

The Effect of Language on Access to Timely COVID-19 Vaccination of Solid Abdominal Organ Transplant Recipients

In dynamic healthcare environments including the COVID-19 pandemic, it is paramount to communicate health recommendations expediently and clearly. Research has shown social determinants of health affect the impact of COVID-19 on abdominal transplant recipients, but there has been less research on the effect of language proficiency. This is a cohort study of time to first COVID-19 vaccination among abdominal organ transplant recipients in an academic medical center in Boston, MA between 18 December 2020, and 15 February 2021. Cox proportional hazards analysis of time to vaccination by preferred language were adjusted for race, age group, insurance, and transplanted organ. Among 3001 patients, 53% were vaccinated during the study period. Language preference other than English was independently associated with delay to vaccination (0.64, p = 0.001), on adjusted analysis. In addition, Black, Hispanic and other race patients were less likely to be vaccinated than white patients (0.58, 0.67, 0.68 vs. reference, all p < 0.03). Language preference other than English is an independent barrier to solid abdominal organ transplant recipients' access to timely COVID-19 vaccination. Equity in care should be improved by providing targeted services to minority language speakers.

Evaluating resilience in response to COVID-19 pandemic stressors among veteran mental health outpatients

There is a public health need to understand mental health vulnerabilities to COVID-19 pandemic-related stressors and promote resilience among high-risk populations with preexisting psychiatric conditions. Recent cross-sectional studies suggest increases in mental health distress (e.g., depression and anxiety) during the pandemic. The present study expands upon these emerging findings using longitudinal latent modeling and hierarchical linear regressions. Consistent with the developmental psychopathology literature on resilience, we distinguished between promotive or risk (i.e., main effect), and protective or vulnerability (i.e., moderation) effects on mental health during the pandemic. At a large medical center, 398 veterans receiving outpatient mental health care provided prepandemic (Time 1) and during pandemic (Time 2) assessments of mental and physical health-related distress. Additional Time 2 questionnaires assessed pandemic-related stressors and positive behavioral adaptations in the summer of 2020. As expected, total stressor scores predicted longitudinal worsening of self-reported mental (β = -.205) and physical health (β = -.217). Positive behavioral adaptations enacted during the pandemic moderated and protected against stressor effects on mental health (β = .160). In addition, the presence of substance use disorders moderated and conferred vulnerability to stressor effects on physical health (β = -.158). Thus, higher COVID-19 pandemic stressor exposure may have exacerbated mental and physical health distress among veterans with common forms of psychopathology. Nevertheless, behavioral activation, purposeful maintenance of social connections, and focused treatment for substance misuse may be important intervention targets for reducing the longitudinal impact of pandemic stressors and enhancing resilience among people with mental illness. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Love in the Time of COVID-19: The Social Dimensions of Intimate Life under Lockdown

Although popular media across the United States reported that the coronavirus disease 2019 COVID pandemic incited dramatic transformations in personal relationships, identities, and practices, little sociological research examines these developments. What exists elaborates the "how" and "how much" of sex, the frequency of sexual conduct, and changes in the patterning of sexual behavior. In this study of the intimate trajectories of 46 young adults, conducted during the height of U.S. quarantine restrictions in 2020 and early 2021, the authors explore the "whys" of sex. They find that the exogenous force of the pandemic profoundly altered individual relationship trajectories, prompted sexual introspection projects, shifted understandings of sexual risk, and promoted new modes of intimacy. These findings suggest that pandemic life reached deep into subjective self-understandings and ways of relating to others. They also reveal the benefits of foregrounding cultural meanings over behaviors, changes in thoughts over actions, and social processes over individual outcomes.

Race and ethnicity: Risk factors for fungal infections?

Racial and ethnic identities, largely understood as social rather than biologic constructs, may impact risk for acquiring infectious diseases, including fungal infections. Risk factors may include genetic and immunologic differences such as aberrations in host immune response, host polymorphisms, and epigenomic factors stemming from environmental exposures and underlying social determinants of health. In addition, certain racial and ethnic groups may be predisposed to diseases that increase risk for fungal infections, as well as disparities in healthcare access and health insurance. In this review, we analyzed racial and ethnic identities as risk factors for acquiring fungal infections, as well as race and ethnicity as they relate to risk for severe disease from fungal infections. Risk factors for invasive mold infections such as aspergillosis largely appear related to environmental differences and underlying social determinants of health, although immunologic aberrations and genetic polymorphisms may contribute in some circumstances. Although black and African American individuals appear to be at high risk for superficial and invasive Candida infections and cryptococcosis, the reasons for this are unclear and may be related to underling social determinants of health, disparities in access to healthcare, and other socioeconomic disparities. Risk factors for all the endemic fungi are likely largely related to underlying social determinants of health, socioeconomic, and health disparities, although immunologic mechanisms likely play a role as well, particularly in disseminated coccidioidomycosis.