Socio-Demographic Health Determinants Are Associated with Poor Prognosis in Spanish Patients Hospitalized with COVID-19

Association between socioeconomic status and hospitalisation requirement in older patients attended at the emergency department: A retrospective cohort study

INTRODUCTION AND OBJECTIVE

A low socioeconomic status (SES) has been associated with poor health results. The present study aimed to investigate if SES of older patients attending the emergency department is associated with the use of healthcare resources and outcomes.

PATIENTS AND METHODS

Observational, retrospective study including consecutive patients 65 years or older admitted to the emergency department. Variables at baseline, index episode, and follow-up were recorded. SES was measured using an indirect theoretical index and patients were categorised into two groups according to whether they lived in a neighbourhood with a low or high SES. Primary outcomes included hospitalisation after the emergency department visit and prolonged hospitalisation (>7 days) at index episode. Secondary outcomes included emergency department re-consultant and hospital admission in the following 3 months after the index episode, and all-cause mortality after long-term follow-up. Logistic regression and cumulative hazards regression models were used to investigate associations between SES and outcomes.

RESULTS

The cohort included 553 patients (80 years [73-85], 50.5% female, 55.9% with low SES). After the emergency department visit, 234 patients (42.3%) required hospital admission. A low SES was inversely associated with hospitalisation with an adjusted odds ratio=0.654 (95% CI 0.441-0.970). Among hospitalised patients, a low SES was associated with prolonged hospitalisation (adjusted odds ratio=2.739; 95% CI 1.470-5.104). Follow-up outcomes, including all-cause mortality, were not associated with SES.

CONCLUSIONS

Older patients living in more deprived urban areas were hospitalised less often after emergency department care, but hospital stays were longer. Understanding the effect of social determinants in healthcare use is mandatory to tailor resources to patient needs.

Inequalities in health outcomes of SARS-CoV-2 infection by migration status in Barcelona, Spain

Background

Migrants are a vulnerable population at risk of worse health outcomes due to legal status, language barriers, and socioeconomic and cultural factors. Considering the conflicting literature on the subject, it is important to further explore the extent and nature of these inequalities.

Objective

The aim of this study is to compare health outcomes associated with SARS-CoV-2 infection between Spanish native and migrant population living in Barcelona.

Methods

Observational retrospective cohort study including all adult cases of SARS-CoV-2 infection who visited a tertiary hospital in Barcelona between the 1st March 2020 and the 31st March 2022. We established the following five health outcomes: the presence of symptomatology, hospitalisation, intensive care unit admission, use of mechanical ventilation, and in-hospital 30-day mortality (IHM). Using Spanish natives as a reference, Odds Ratios (OR) with 95% confidence interval (95%CI) were calculated for migrants by multivariate logistic regression and adjusted by sociodemographic and clinical factors.

Results

Of 11,589 patients (46.8% females), 3,914 were born outside of Spain, although 34.8% of them had legal citizenship. Most migrants were born in the Americas Region (20.3%), followed by other countries in Europe (17.2%). Migrants were younger than natives (median 43 [IQR 33-55] years vs. 65 [49-78] years) and had a higher socioeconomic privation index, less comorbidities, and fewer vaccine doses. Adjusted models showed migrants were more likely to report SARS-CoV-2 symptomatology with an adjusted OR of 1.36 (95%CI 1.20-1.54), and more likely to be hospitalised (OR 1.11 [IC95% 1.00-1.23], p < 0.05), but less likely to experience IHM (OR 0.67 [IC95% 0.47-0.93], p < 0.05).

Conclusion

Characteristics of migrant and native population differ greatly, which could be translated into different needs and health priorities. Native population had higher odds of IHM, but migrants were more likely to present to care symptomatic and to be hospitalised. This could suggest disparities in healthcare access for migrant population. More research on health disparities beyond SARS-CoV-2 in migrant populations is necessary to identify gaps in healthcare access and health literacy.

Alterations in the immune system persist after one year of convalescence in severe COVID-19 patients

Introduction

Severe COVID-19 originates a myriad of alterations in the immune system during active disease, especially in the T and NK cell compartments, but several studies in the last year have unveiled some alterations that persist in convalescence. Although most of the studies follow the participants for a short recovery time, studies following patients up to three or six months still find alterations. We aimed at evaluating changes in the NK, T and B cell compartments after severe COVID-19 in participants with a median recovery time of eleven months.

Methods

Eighteen convalescent of severe COVID-19 (CSC), 14 convalescent of mild COVID-19 (CMC) and nine controls were recruited. NKG2A, NKG2C, NKG2D and the activating receptor NKp44 were evaluated in NK^bright, NK^dim and NKT subpopulations. In addition, CD3 and CD19 were measured and a basic biochemistry with IL-6 levels was obtained.

Results

CSC participants showed lower NK^bright/NK^dim ratio, higher NKp44 expression in NK^bright subpopulations, higher levels of serum IL-6, lower levels of NKG2A⁺ T lymphocytes and a trend to a lower expression of CD19 in B lymphocytes compared to controls. CMC participants showed no significant alterations in the immune system compared to controls.

Conclusions

These results are concordant with previous studies, which find alterations in CSC weeks or months after resolution of the symptoms, and point to the possibility of these alterations lasting one year or more after COVID-19 resolution.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases

The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%-32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%-16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%-145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.

What Makes Urban Communities More Resilient to COVID-19? A Systematic Review of Current Evidence

It has been more than two years since the outbreak of the COVID-19 epidemic at the end of 2019. Many scholars have introduced the "resilience" concept into COVID-19 prevention and control to make up for the deficiencies in traditional community governance. This study analyzed the progress in research on social resilience, which is an important component of community resilience, focusing on the current literature on the impact of social resilience on COVID-19, and proposed a generalized dimension to integrated previous relevant literature. Then, VOSviewer was used to visualize and analyze the current progress of research on social resilience. The PRISMA method was used to collate studies on social resilience to the pandemic. The result showed that many current policies are effective in controlling COVID-19, but some key factors, such as vulnerable groups, social assistance, and socioeconomics, affect proper social functioning. Some scholars have proposed effective solutions to improve social resilience, such as establishing an assessment framework, identifying priority inoculation groups, and improving access to technology and cultural communication. Social resilience to COVID-19 can be enhanced by both external interventions and internal regulation. Social resilience requires these two aspects to be coordinated to strengthen community and urban pandemic resilience.

Impacto de los determinantes sociales de la salud sobre la tasa de contagios por COVID-19

Objetivo Analizar el impacto entre los determinantes sociales en salud en México y la tasa de contagios por COVID-19. Método Estudio ecológico cuantitativo a nivel nacional y municipal. Las principales variables fueron tasa de contagios por COVID-19, población total no hablante de español, ingreso per cápita, pobreza e índice de desarrollo humano (IDH). La tasa media nacional de contagios fue de 2 880/100 000 habitantes. Se aplicó la prueba T-test y, para determinar la fuerza de asociación entre la tasa de contagios y las variables, se aplicó la prueba de correlación de Pearson. Resultados Las entidades con menos tasa de población no hablante de español tuvo la menor tasa de contagios por COVID-19. El análisis de correlación mostró que los estados con tasas de contagio por COVID-19 por arriba de la media nacional tienen mejores condiciones de desarrollo. Discusión En nuestros resultados se revela una correlación negativa entre las tasas contagios por COVID-19 y la variable pertenecer a población indígena. Es necesario analizar desde la perspectiva de las comunidades las necesidades para afrontar escenarios de pandemia.

Ethnicity and Clinical Outcomes in Patients Hospitalized for COVID-19 in Spain: Results from the Multicenter SEMI-COVID-19 Registry

(1) Background: This work aims to analyze clinical outcomes according to ethnic groups in patients hospitalized for COVID-19 in Spain. (2) Methods: This nationwide, retrospective, multicenter, observational study analyzed hospitalized patients with confirmed COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry) from 1 March 2020 to 31 December 2021. Clinical outcomes were assessed according to ethnicity (Latin Americans, Sub-Saharan Africans, Asians, North Africans, Europeans). The outcomes were in-hospital mortality (IHM), intensive care unit (ICU) admission, and the use of invasive mechanical ventilation (IMV). Associations between ethnic groups and clinical outcomes adjusted for patient characteristics and baseline Charlson Comorbidity Index values and wave were evaluated using logistic regression. (3) Results: Of 23,953 patients (median age 69.5 years, 42.9% women), 7.0% were Latin American, 1.2% were North African, 0.5% were Asian, 0.5% were Sub-Saharan African, and 89.7% were European. Ethnic minority patients were significantly younger than European patients (median (IQR) age 49.1 (40.5−58.9) to 57.1 (44.1−67.1) vs. 71.5 (59.5−81.4) years, p < 0.001). The unadjusted IHM was higher in European (21.6%) versus North African (11.4%), Asian (10.9%), Latin American (7.1%), and Sub-Saharan African (3.2%) patients. After further adjustment, the IHM was lower in Sub-Saharan African (OR 0.28 (0.10−0.79), p = 0.017) versus European patients, while ICU admission rates were higher in Latin American and North African versus European patients (OR (95%CI) 1.37 (1.17−1.60), p < 0.001) and (OR (95%CI) 1.74 (1.26−2.41), p < 0.001). Moreover, Latin American patients were 39% more likely than European patients to use IMV (OR (95%CI) 1.43 (1.21−1.71), p < 0.001). (4) Conclusion: The adjusted IHM was similar in all groups except for Sub-Saharan Africans, who had lower IHM. Latin American patients were admitted to the ICU and required IMV more often.

Age Dependent Epidemic Modeling of COVID-19 Outbreak in Kuwait, France, and Cameroon

Revisiting the classical model by Ross and Kermack-McKendrick, the Susceptible−Infectious−Recovered (SIR) model used to formalize the COVID-19 epidemic, requires improvements which will be the subject of this article. The heterogeneity in the age of the populations concerned leads to considering models in age groups with specific susceptibilities, which makes the prediction problem more difficult. Basically, there are three age groups of interest which are, respectively, 0−19 years, 20−64 years, and >64 years, but in this article, we only consider two (20−64 years and >64 years) age groups because the group 0−19 years is widely seen as being less infected by the virus since this age group had a low infection rate throughout the pandemic era of this study, especially the countries under consideration. In this article, we proposed a new mathematical age-dependent (Susceptible−Infectious−Goneanewsusceptible−Recovered (SIGR)) model for the COVID-19 outbreak and performed some mathematical analyses by showing the positivity, boundedness, stability, existence, and uniqueness of the solution. We performed numerical simulations of the model with parameters from Kuwait, France, and Cameroon. We discuss the role of these different parameters used in the model; namely, vaccination on the epidemic dynamics. We open a new perspective of improving an age-dependent model and its application to observed data and parameters.