Poverty and survival from COVID-19 in Mexico

Socioeconomic factors and COVID-19 mortality in immune-mediated rheumatic diseases patients: regional analysis from Argentina, Mexico and Brazil

BACKGROUND

SARS-CoV-2 infection has become a major international issue, not only from a medical point of view, but also social, economic and political. Most of the available information comes from the United States, Europe, and China, where the population and the socioeconomic status are very different from Latin American countries. This study evaluates the effect of regional socioeconomic characteristics on mortality due SARS-CoV-2 infection in patients with immune-mediated rheumatic diseases (IMRD) from Argentina, Mexico and Brazil.

METHODS

Data from three national registries, SAR-COVID (Argentina), CMR-COVID (Mexico) and ReumaCoV-Brasil (Brazil), were combined. Adult IMRD patients with SARS-CoV-2 infection were recruited. National data for each province/state, including population density, number of physicians per inhabitant, income, unemployment, GINI index, Municipal Human Development Index (MHDI), stringency index, vaccination rate and most frequent viral strains per period were assessed as risk factors for mortality due to COVID-19.

RESULTS

A total of 4744 patients were included, 2534 (53.4%) from SAR-COVID, 1166 (24.6%) from CMRCOVID and 1044 (22.0%) from ReumaCoV-Brasil. Mortality due to COVID-19 was 5.4%. In the multivariable analysis, higher number of physicians per 1000 inhabitants and being infected during the vaccination period of each country were associated with lower mortality. After adjustment for socioeconomic factors, there was no association with country of residence and mortality.

CONCLUSION

These findings corroborate the complex interplay between socioeconomic factors, rheumatic disease activity, and regional disparities as determinants of death due to COVID-19 in Argentina, Brazil and Mexico. Thus, this research provides valuable insights for guiding public health policies and clinical practice in the ongoing fight against the COVID-19 pandemic.

Death from COVID-19 in contexts of social deprivation in Mexico

Introduction

Poverty is one of the macro factors that has been little studied in terms of its effect on death from COVID-19 since most studies have focused only on investigating whether the pandemic increased poverty or not. With that on mind, the present study aims to analyze how the social deprivations that comprise the measurement of municipal poverty in interaction with health comorbidities and sociodemographic characteristics, increased the probability of death from COVID-19.

Methods

The study is cross-sectional and covers daily reports on the conditions of COVID-19 in the Mexican population for almost 2 years. Using data from the National Epidemiological Surveillance System and the National Council for Evaluation of the Social Development Policy (N = 5,387,981), we employ a Generalized Linear Mixed Model (GLMM), specifically a binomial generalized linear mixed model.

Results

The findings indicate that, besides comorbidities, sociodemographic traits, and clinical aspects, living in a municipality where one or more of the social deprivations exist increases the probability of death. Specifically, in those municipalities where there is deprivation in education, social security, and food, as well as deprivation due to access to health services and deprivation in household services, the probability of death was greater.

Discussion

Living in a municipality with one or more of the social deprivations that compose poverty generated a greater probability of death. Each one of them or together, shows that poverty is a substantial factor for a pandemic like COVID-19 to worsen contagion and death, becoming a circle from which it is difficult to escape.

Extreme poverty first: An argument on the equitable distribution of the COVID-19 vaccine in Peru

Effective vaccines for COVID-19 are already available to humankind. In Peru, 86 million doses were administered to cover the demand for 33 million Peruvian people. Hence, vaccination has been prioritized in groups: health personnel, subjects with pre-existing health conditions and those over 65 years of age. However, given the social problems and the public health situation in Peru, this work defends that the priority of vaccination should be focused on the population living in extreme poverty. The method used was an ethical argumentation on the distribution of scarce antiSARS-CoV2 vaccine in Peru. This argument is based on the analysis of the Peruvian population living in extreme poverty, which presents different layers of vulnerability, and that, in the face of an eventual SARS-CoV2 infection, these would be exacerbated one after the other, through a cascade effect. This scenario would give rise to new vulnerabilities to those already existing, causing greater damage. Vaccination efforts on this key population would give them the opportunity to continue to find ways to bring food to their homes, significantly reducing the risk of contagion in their environment and mitigating the devastating effect of the local diseases to which they are already exposed. Four objections related to this argument are raised with their corresponding responses. Priority access to the vaccine would significantly reduce the humanitarian harm to people living in extreme poverty, prevailing the principles of justice and equity.

Multimorbidity and frailty are associated with poorer SARS-CoV-2-related outcomes: systematic review of population-based studies

BACKGROUND

Estimating the risks and impacts of COVID-19 for different health groups at the population level is essential for orienting public health measures. Adopting a population-based approach, we conducted a systematic review to explore: (1) the etiological role of multimorbidity and frailty in developing SARS-CoV-2 infection and COVID-19-related short-term outcomes; and (2) the prognostic role of multimorbidity and frailty in developing short- and long-term outcomes. This review presents the state of the evidence in the early years of the pandemic. It was conducted within the European Union Horizon 2020 program (No: 101018317); Prospero registration: CRD42021249444.

METHODS

PubMed, Embase, World Health Organisation COVID-19 Global literature on coronavirus disease, and PsycINFO were searched between January 2020 and 7 April 2021 for multimorbidity and 1 February 2022 for frailty. Quantitative peer-reviewed studies published in English with population-representative samples and validated multimorbidity and frailty tools were considered.

RESULTS

Overall, 9,701 records were screened by title/abstract and 267 with full text. Finally, 14 studies were retained for multimorbidity (etiological role, n = 2; prognostic, n = 13) and 5 for frailty (etiological role, n = 2; prognostic, n = 4). Only short-term outcomes, mainly mortality, were identified. An elevated likelihood of poorer outcomes was associated with an increasing number of diseases, a higher Charlson Comorbidity Index, different disease combinations, and an increasing frailty level.

DISCUSSION

Future studies, which include the effects of recent virus variants, repeated exposure and vaccination, will be useful for comparing the possible evolution of the associations observed in the earlier waves.

Spatial Survival Model for COVID-19 in México

A spatial survival analysis was performed to identify some of the factors that influence the survival of patients with COVID-19 in the states of Guerrero, México, and Chihuahua. The data that we analyzed correspond to the period from 28 February 2020 to 24 November 2021. A Cox proportional hazards frailty model and a Cox proportional hazards model were fitted. For both models, the estimation of the parameters was carried out using the Bayesian approach. According to the DIC, WAIC, and LPML criteria, the spatial model was better. The analysis showed that the spatial effect influences the survival times of patients with COVID-19. The spatial survival analysis also revealed that age, gender, and the presence of comorbidities, which vary between states, and the development of pneumonia increase the risk of death from COVID-19.

Dietary patterns, social determinants, and emotions during COVID‐19 confinement in Panama: An online survey

Aim

We aimed to evaluate health and nutrition behaviors among the Panamanian population during the confinement period corresponding to the first wave of the COVID‐19 pandemic.

Methods

We conducted a cross‐sectional study using an online survey for data collection with a total of 2475 participants over the age of 18 using an online survey. We also completed 64 face‐to‐face interviews. After data validation, 1561 surveys were included in the study. Most respondents were women (74.2%) between 18 and 49 years old. Among the respondents, 83.3% had a university education level, and 49.9% reported a monthly family income of fewer than 1000 USD. In addition, more than 50% self‐reported as overweight or obese.

Results

We identified three dietary patterns: a healthy, a non‐healthy, and a mixed dietary pattern. The respondents with healthy and nonhealthy dietary patterns reported better socioeconomic conditions than participants from the mixed dietary pattern. Individuals with mixed dietary patterns had lower incomes, less education, and higher unemployment rates. Regarding emotions, we found that women experienced more negative emotions, such as fear, worry, and anxiety, during the lockdown period.

Conclusions

Taken together, these results indicate that the mobility restriction measures imposed during the COVID‐19 pandemic could have affected dietary patterns by exacerbating existing inequalities. Directing resources toward promoting healthy nutrition strategies with the most significant positive impacts on public health is a priority, especially in critical situations such as the COVID‐19 pandemic.

Association of government effectiveness, logistics performance, IT systems and income with COVID-19 mortality

The COVID-19 pandemic has unprecedentedly shaken the public health system worldwide. It has been one of the greatest humanitarian crises faced by all countries, regardless of their economic prosperity. However, some countries have been able to minimize the deaths caused by the coronavirus even in the face of a large number of cases, while others have failed to control the death rate even in a comparatively small number of cases. This study explores possible causes of this disparity using cross-sectional data from 126 countries associated with demography, governance, income level, the extent of ICT maturity and the geographical divide. The results of this study suggest that while government effectiveness is negatively associated with the COVID-19 death rate, the logistics performance of governments is positively linked to the COVID-19 mortality rate. The ICT maturity proxied through online service delivery did not confirm its association with the COVID-19 mortality rate. This study informs that poverty and the location of countries do not necessarily influence COVID-19 deaths. Hence, it behoves governments to focus on improving government effectiveness and putting in place more effective and efficient mobility systems, healthcare supply chains and digital administration to address the global health crisis posed by the COVID-19 pandemic and mitigate its harsh effects, including mortality.

Risks of mortality and severe coronavirus disease 19 (COVID-19) outcomes in patients with or without systemic lupus erythematosus

OBJECTIVES

We compared the outcomes of patients with or without systemic lupus erythematosus (SLE) who were diagnosed with coronavirus disease 19 (COVID-19) and evaluated factors within patients with SLE associated with severe outcomes.

METHODS

This retrospective cohort study used the deidentified Optum COVID-19 electronic health record dataset to identify patients with COVID-19 from 1/1/2020 to 31/12/2020. Cases with SLE were matched with general controls at a ratio of 1:10 by age, sex, race and ethnicity and COVID-19 diagnosis date. Outcomes included 30-day mortality, mechanical ventilation, hospitalisation and intensive care unit admission. We evaluated the relationship between COVID-19-related outcomes and SLE using multivariable logistic regression. In addition, within SLE cases, we examined factors associated with COVID-19 related outcomes, including disease activity and SLE therapy.

RESULTS

We included 687 patients matched with 6870 controls. Unadjusted rates of outcomes for patients with SLE were significantly worse than for matched controls including mortality (3.6% vs 1.8%), mechanical ventilation (6% vs 2.5%) and hospitalisation (31% vs 17.7%) (all p<0.001). After multivariable adjustment, patients with SLE had increased risks of mechanical ventilation (OR 1.81, 95% CI 1.16 to 2.82) and hospitalisation (OR 1.32, 95% CI 1.05 to 1.65). Among patients with SLE, severe disease activity was associated with increased risks of mechanical ventilation (OR 5.83, 95% CI 2.60 to 13.07) and hospitalisation (OR 3.97, 95% CI 2.37 to 6.65). Use of glucocorticoids, mycophenolate and tacrolimus before COVID-19 was associated with worse outcomes.

CONCLUSION

Patients with SLE had increased risk of severe COVID-19-related outcomes compared with matched controls. Patients with severe SLE disease activity or prior use of corticosteroids experienced worse outcomes.

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.

A machine learning-driven spatio-temporal vulnerability appraisal based on socio-economic data for COVID-19 impact prevention in the U.S. counties

A mature and hybrid machine-learning model is verified by mature empirical analysis to measure county-level COVID-19 vulnerability and track the impact of the imposition of pandemic control policies in the U.S. A total of 30 county-level social, economic, and medical variables and a timeline of the imposed policies constitutes a COVID-19 database. A hybrid feature-selection model composed of four machine-learning algorithms is developed to emphasize the regional impact of community features on the case fatality rate (CFR). A COVID-19 vulnerability index (COVULin) is proposed to measure the county's vulnerability, the effects of model's parameters on mortality, and the efficiency of control policies. The results showed that the dense counties in which minority groups represent more than 45% of the population and those with poverty rates greater than 24% were the most vulnerable counties during the first and the last pandemic peaks, respectively. Highly-correlated CFR and COVULin scores indicated a close agreement between the model outcomes and COVID-19 impacts. Counties with higher poverty and uninsured rates were the most resistant to government intervention. It is anticipated that the proposed model can play an essential role in identifying vulnerable communities and help reduce damages during long-term alike disasters.

Impact of environmental and individual factors on COVID-19 mortality in children and adolescents in Mexico: An observational study

Background

During the Covid-19 pandemic, children and adolescents faced poverty, potentially dying from preventable causes, or missing out essential vaccines. The aim of this study was to assess potential environmental and individual factors associated to COVID-19 mortality in children and adolescents in Mexico.

Methods

This cross-sectional study analysed the official data of 131,001 children under 10 years of age and adolescents between 10 and 19 years of age with COVID-19 disease, in Mexico. Participants were diagnosticated between March 2020 and June 13, 2021. The environmental variables such as malnutrition, vaccination coverage and social lag index were evaluated at the state level. Multilevel models were fitted to evaluate the association between environmental and individual factors and COVID-19 mortality.

Findings

A total of 773 (0.6%) children and adolescents died due to COVID-19. Younger age (OR = 0.878, 95%CI: 0.869-0.888), diabetes (OR = 3.898, 95%CI: 2.596-5.851), immunosuppression (OR = 5.410, 95%CI: 4.088-7.158), obesity (OR = 1.876, 95%CI: 1.397-2.521), hypertension (OR = 1.906, 95%CI: 1.239-2.932), cardiovascular disease (OR = 2.288, 95%CI: 1.482-3.531), and chronic kidney disease (OR = 13.250, 95%CI: 9.066-19.350) were associated with mortality. COVID-19 mortality was directly associated with social lag index and malnutrition (OR_{very high} = 2.939, 95%CI: 1.111-7.775, and OR = 1.390, 95%CI: 1.073-1.802, respectively), and inversely associated with population density (OR = 0.374, 95%CI: 0.204-0.688). Finally, children and adolescents living in areas with a higher percentage of people with incomplete education (OR = 1.045, 95%CI: 1.011-1.081), of children of school age of 6–14 years who do not attend school (OR = 1.266, 95%CI: 1.032-1.554), and of illiterate population aged 15 and over (OR = 1.086, 95%CI: 0.999-1.179) were associated with a higher risk of COVID-19 mortality.

Interpretation

Malnutrition, social lag index and population density are key factors to understand COVID-19 mortality in children and adolescents. Also, age and pre-existing comorbidities were also associated with worse COVID-19 prognosis.

Funding

No funding was secured for this study.

Correlation between mobility in mass transport and mortality due to COVID-19: A comparison of Mexico City, New York, and Madrid from a data science perspective

In most big cities, public transports are enclosed and crowded spaces. Therefore, they are considered as one of the most important triggers of COVID-19 spread. Most of the existing research related to the mobility of people and COVID-19 spread is focused on investigating highly frequented paths by analyzing data collected from mobile devices, which mainly refer to geo-positioning records. In contrast, this paper tackles the problem by studying mass mobility. The relations between daily mobility on public transport (subway or metro) in three big cities and mortality due to COVID-19 are investigated. Data collected for these purposes come from official sources, such as the web pages of the cities’ local governments. To provide a systematic framework, we applied the IBM Foundational Methodology for Data Science to the epidemiological domain of this paper. Our analysis consists of moving averages with a moving window equal to seven days so as to avoid bias due to weekly tendencies. Among the main findings of this work are: a) New York City and Madrid show similar distribution on studied variables, which resemble a Gauss bell, in contrast to Mexico City, and b) Non-pharmaceutical interventions don’t bring immediate results, and reductions to the number of deaths due to COVID are observed after a certain number of days. This paper yields partial evidence for assessing the effectiveness of public policies in mitigating the COVID-19 pandemic.

Punt Politics as Failure of Health System Stewardship: Evidence from the COVID-19 Pandemic Response in Brazil and Mexico

We present a new concept, Punt Politics, and apply it to the COVID-19 non-pharmaceutical interventions (NPI) in two epicenters of the pandemic: Mexico and Brazil. Punt Politics refers to national leaders in federal systems deferring or deflecting responsibility for health systems decision-making to sub-national entities without evidence or coordination. The fragmentation of authority and overlapping functions in federal, decentralized political systems make them more susceptible to coordination problems than centralized, unitary systems. We apply the concept to pandemics, which require national health system stewardship, using sub-national NPI data that we developed and curated through the Observatory for the Containment of COVID-19 in the Americas to illustrate Punt Politics in Mexico and Brazil. Both countries suffer from protracted, high levels of COVID-19 mortality and inadequate pandemic responses, including little testing and disregard for scientific evidence. We illustrate how populist leadership drove Punt Politics and how partisan politics contributed to disabling an evidence-based response in Mexico and Brazil. These cases illustrate the combination of decentralization and populist leadership that is most conducive to punting responsibility. We discuss how Punt Politics reduces health system functionality, providing lessons for other countries and future pandemic responses, including vaccine rollout.

The income gradient in COVID-19 mortality and hospitalisation: An observational study with social security administrative records in Mexico

BACKGROUND

The COVID-19 pandemic revealed large structural inequalities that led to disparities in health outcomes related to socioeconomic status. So far, most of the evidence is based on aggregated data or simulations with individual data, which point to various possible mechanisms behind the association. To date, there have been no studies regarding an income gradient in COVID-19 mortality based on individual-level data and adjusting for comorbidities or access to healthcare.

METHODS

In this paper, we use linked employee-patient data for patients tested for COVID-19 at the Mexican Institute of Social Security. We estimate the association of the probability of dying with income centiles, using a probit estimation and adjusting for COVID-19 diagnosis, sociodemographic variables, and comorbidities.

FINDINGS

After controlling for all these variables, we find that persons in the lowest income decile still had a probability of dying from COVID-19 five times greater than those at the top decile.

INTERPRETATION

Our results imply that the association between income and COVID outcomes is not explained by the prevalence of comorbidities or by a lack of access to healthcare among the low-income population.

FUNDING

This study was not supported by any external funding source.

SARS-CoV-2 Brazil variants in Latin America: More serious research urgently needed on public health and vaccine protection

COVID-19 has not only created a pandemic but also affected both economically and socially in all countries. It has further created a socio-economic chaos throughout Latin America. Currently, some new SARS-CoV-2 variants are circulating in Latin America and one among the significant variant belongs to the P.1 lineage (B.1.1.28.1) that has 17 mutations. The essential modifications located in the spike glycoprotein RBD include E484K, K417T and N501Y. Along with the P.1 lineage, P.2 lineage (B.1.1.28.2) has also appeared recently. Details on all the variants are unknown, along with the Brazil variants at this time. Therefore, we call for intensive research to collect more data to understand the variants' virulence and the effects on vaccine efficacy.

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The COVID-19 pandemic has affected socially and economically the entire world, including Latin America.

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Recently, a significant variant of COVID-19 was found in Brazil, known as lineage P.1.

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Two other variants (P.2 Lineage and B.1.1.7 lineage) are currently circulating across Latin America.

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We urge the scientific community to research the new emerging variants of SARS-CoV-2 intensively.

Higher COVID-19 mortality in low-income communities in the City of Cape Town - a descriptive ecological study

Background Cape Town, a South African city with high levels of economic inequality, has gone through two COVID-19 waves. There is evidence globally that low-income communities experience higher levels of morbidity and mortality during the pandemic. Methods Age-standardized COVID-19 mortality in the eight sub-districts of Cape Town was compared by economic indicators taken from the most recent Census (unemployment rate, monthly income). Results The overall Standardized Death Rate (SDR) for COVID-19 in Cape Town was 1 640 per million, but there was wide variation across the different sub-districts. A linear relationship was seen between sub-districts with high poverty and high COVID-19 SDRs. Conclusions Low-income communities in Cape Town experienced higher levels of COVID-19 mortality. As we continue to contend with COVID-19, these communities need to be prioritized for access to quality health care.