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Open accessJournal ArticleDOI: 10.1136/JECH-2020-216275

Socioeconomic inequalities associated with mortality for COVID-19 in Colombia: a cohort nationwide study.

04 Mar 2021-Journal of Epidemiology and Community Health (BMJ Publishing Group Ltd)-Vol. 75, Iss: 7, pp 610-615
Abstract: Background After 8 months of the COVID-19 pandemic, Latin American countries have some of the highest rates in COVID-19 mortality. Despite being one of the most unequal regions of the world, there is a scarce report of the effect of socioeconomic conditions on COVID-19 mortality in their countries. We aimed to identify the effect of some socioeconomic inequality-related factors on COVID-19 mortality in Colombia. Methods We conducted a survival analysis in a nation-wide retrospective cohort study of confirmed cases of COVID-19 in Colombia from 2 March 2020 to 26 October 2020. We calculated the time to death or recovery for each confirmed case in the cohort. We used an extended multivariable time-dependent Cox regression model to estimate the HR by age groups, sex, ethnicity, type of health insurance, area of residence and socioeconomic strata. Results There were 1 033 218 confirmed cases and 30 565 deaths for COVID-19 in Colombia between 2 March and 26 October. The risk of dying for COVID-19 among confirmed cases was higher in males (HR 1.68 95% CI 1.64 to 1.72), in people older than 60 years (HR 296.58 95% CI 199.22 to 441.51), in indigenous people (HR 1.20 95% CI 1.08 to 1.33), in people with subsidised health insurance regime (HR 1.89 95% CI 1.83 to 1.96) and in people living in the very low socioeconomic strata (HR 1.44 95% CI 1.24 to 1.68). Conclusion Our study provides evidence of socioeconomic inequalities in COVID-19 mortality in terms of age groups, sex, ethnicity, type of health insurance regimen and socioeconomic status.

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Topics: Cohort study (55%), Cohort (54%), Retrospective cohort study (51%)
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Open accessJournal ArticleDOI: 10.1016/J.LANA.2021.100048
23 Aug 2021-
Abstract: Background Epidemiologic surveillance of COVID-19 is essential to collect and analyse data to improve public health decision making during the pandemic. There are few initiatives led by public-private alliances in Colombia and Latin America. The CoVIDA project contributed with RT-PCR tests for SARS-CoV-2 in mild or asymptomatic populations in Bogota. The present study aimed to determine the factors associated with SARS-CoV-2 infection in working adults. Methods COVID-19 intensified sentinel epidemiological surveillance study, from April 18, 2020, to March 29, 2021. The study included people aged 18 years or older without a history of COVID-19. Two main occupational groups were included: healthcare and essential services workers with high mobility in the city. Social, demographic, and health-related factors were collected via phone survey. Afterwards, the molecular test was conducted to detect SARS-CoV-2 infection. Findings From the 58,638 participants included in the study, 3,310 (5·6%) had a positive result. A positive result was associated with the age group (18-29 years) compared with participants aged 60 or older, participants living with more than three cohabitants, living with a confirmed case, having no affiliation to the health system compared to those with social health security, reporting a very low socioeconomic status compared to those with higher socioeconomic status, and having essential occupations compared to healthcare workers. Interpretation The CoVIDA study showed the importance of intensified epidemiological surveillance to identify groups with increased risk of infection. These groups should be prioritised in the screening, contact tracing, and vaccination strategies to mitigate the pandemic. Funding The CoVIDA study was funded through donors managed by the philanthropy department of Universidad de los Andes.

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Topics: Epidemiologic Surveillance (54%), Public health (54%), Social determinants of health (53%) ... show more

1 Citations


Open accessJournal ArticleDOI: 10.1007/S40615-021-01035-2
Abstract: Due to social and geographical isolation, indigenous people are more vulnerable to adverse conditions; however, there is a lack of data on the epidemics’ impact on these populations. Thus, this article’s objective was to describe the epidemiological situation of COVID-19 in indigenous communities in Brazil. This descriptive observational study was carried out in indigenous communities in the municipality of Amatura (Amazonas, Brazil). Individuals from the Alto Rio Solimoes Special Indigenous Sanitary District (DSEI) who met the Sars-Cov-2 infection case definitions during the period between January and August 2020 were included. For case notification, the definitions adopted by the Ministry of Health of Brazil and by the Special Secretariat for Indigenous Health were considered. Out of the entire population served by the Alto Rio Solimoes DSEI (n = 2890), 109 indigenous people were suspected of having been infected with Sars-Cov-R during the study period; a total of 89 cases were actually confirmed (rate: 3.08 cases/100,000 inhabitants). Most patients diagnosed with COVID-19 were female (56.2%), with a mean age of 32.4 (± 23.6) years. Predominant symptoms were fever (76.4%), dry cough (64%), and headache (60.7%). Complications occurred in 7.9% of the patients; no deaths were reported. These results enhance the observation that indigenous populations, even if relatively isolated, are exposed to COVID-19. The disease cases assessed showed a favorable evolution, which does not mean reducing the need for caring of this population.

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Topics: Indigenous (54%), Population (53%)

1 Citations


Open accessJournal ArticleDOI: 10.7759/CUREUS.14865
06 May 2021-Cureus
Abstract: Introduction Different factors are critical when assessing COVID-19 mortality, and can explain why severity differs so widely among populations. However, there is little information regarding prognostic factors and mortality in COVID-19 from Latin American countries. Objectives To determine prognostic factors in hospitalized COVID-19 patients and to evaluate the impact of tocilizumab use in patients with hyperinflammatory syndrome and severe disease defined by the National Early Warning Score 2 (NEWS2) with a value greater than or equal to seven points. Materials and methods This retrospective cohort study included hospitalized COVID-19 patients from May to July 2020. A multivariate logistic regression analysis was performed to determine independent factors associated with mortality. Results A total of 136 patients required hospital admission. In-hospital mortality was 39.7%. Mortality was observed to be potentiated by older age, LDH serum levels and the presence of type 2 diabetes mellitus. Lymphopenia and lower PaO2/FiO2 ratio were more common in these patients. Similarly, patients who died were classified more frequently with severe disease. The independent factors associated with in-hospital mortality were age greater than 65 years, type 2 diabetes mellitus, NEWS2 greater than or equal to seven points and LDH greater than 400U/L. The use of Tocilizumab alone was not related with decreased in-hospital mortality. Subgroup analysis performed in patients with hyperinflammation and severe disease showed similar results. Conclusions COVID-19 mortality in hospitalized patients was high and mainly related with older age, comorbidities, LDH and the severity of disease at hospital admission.

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Journal ArticleDOI: 10.1136/JECH-2021-216797
Abstract: Colombia and other Latin American countries traditionally had some of the largest socioeconomic inequalities in the world. However, inequalities were substantially reduced in Colombia since the beginning of the 21st century thanks to the peace agreements with the guerrillas and some economic prosperity, which resulted in poverty being reduced by more than half in just 20 years. Many people got decent jobs and housing, and their children accessed university education.1 However, as the Spanish saying goes, the joy in the house of the poor was short-lived. The COVID-19 pandemic threatens to return Colombia and other Latin American countries to the situation of 20 years ago.2 The pandemic has resulted in huge job losses and closure of small businesses, especially affecting those with manual or low-skilled jobs that must be performed in person. Many of these workers and their families have been evicted and have had to move to lower socioeconomic neighbourhoods and even …

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Topics: Latin Americans (51%)

Open accessJournal ArticleDOI: 10.1007/S40615-021-01162-W
Abstract: This study aimed to estimate the number of excess deaths among Indigenous Peoples associated with the COVID-19 pandemic in 2020 and to assess the disparities in excess mortality between Indigenous and non-Indigenous Brazilians. A time series analysis of weekly mortality data including all deaths from January 2015 to December 2020 was conducted. The number of expected deaths for 2020 was estimated using an over-dispersed Poisson model that accounts for demographic changes, temporal trends, and seasonal effects in mortality. Weekly excess deaths were calculated as the difference between the number of observed deaths and the expected deaths. Regional differences in Indigenous mortality were investigated. A significant increase in Indigenous mortality was observed from April 1 to December 31, 2020. An estimated 1149 (95% CI 1018-1281) excess deaths was found among Indigenous Brazilians in 2020, representing a 34.8% increase from the expected deaths for this population. The overall increase in non-Indigenous mortality was 18.1%. The Indigenous population living in the Brazilian Amazon area was the earliest-affected Indigenous group, with one of the highest proportional increases in mortality. Disparities in excess mortality revealed a disproportionate burden of COVID-19 among Indigenous Brazilians compared to their non-Indigenous counterparts. Findings highlight the importance of implementing an effective emergency plan that addresses the increased vulnerability of Indigenous Peoples to COVID-19.

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Topics: Indigenous (53%), Population (52%)

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Open accessJournal ArticleDOI: 10.1056/NEJMOA2001017
Na Zhu1, Dingyu Zhang, Wenling Wang1, Xingwang Li2  +15 moreInstitutions (3)
Abstract: In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.).

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Topics: Coronavirus (57%), Betacoronavirus (56%)

15,285 Citations


Open access
01 Jan 2020-
Abstract: Globally, as of 10:47am CEST, 28 May 2020, there have been 5,556,679 confirmed cases of COVID-19, including 351,866 deaths, reported to WHO

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Topics: Coronavirus (58%)

1,791 Citations


Open accessBook
30 Mar 2006-
Abstract: This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses. The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992). From the reviews: "This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered." Journal of Biopharmaceutical Statistics, 2005 "This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book" Technometrics, February 2006 "Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally." Journal of the American Statistical Association, March 2006

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Topics: Linear model (57%), Generalized linear mixed model (53%), Regression analysis (53%) ... show more

1,117 Citations


Journal ArticleDOI: 10.1016/S0140-6736(06)69895-4
23 Dec 2006-The Lancet
Abstract: Summary Background The threat of an avian influenza pandemic is causing widespread public concern and health policy response, especially in high-income countries. Our aim was to use high-quality vital registration data gathered during the 1918–20 pandemic to estimate global mortality should such a pandemic occur today. Methods We identified all countries with high-quality vital registration data for the 1918–20 pandemic and used these data to calculate excess mortality. We developed ordinary least squares regression models that related excess mortality to per-head income and absolute latitude and used these models to estimate mortality had there been an influenza pandemic in 2004. Findings Excess mortality data show that, even in 1918–20, population mortality varied over 30-fold across countries. Per-head income explained a large fraction of this variation in mortality. Extrapolation of 1918–20 mortality rates to the worldwide population of 2004 indicates that an estimated 62 million people (10th–90th percentile range 51 million–81 million) would be killed by a similar influenza pandemic; 96% (95% CI 95–98) of these deaths would occur in the developing world. If this mortality were concentrated in a single year, it would increase global mortality by 114%. Interpretation This analysis of the empirical record of the 1918–20 pandemic provides a plausible upper bound on pandemic mortality. Most deaths will occur in poor countries—ie, in societies whose scarce health resources are already stretched by existing health priorities.

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Topics: Mortality rate (56%), Pandemic (56%), Influenza A virus subtype H5N1 (54%) ... show more

534 Citations


Open accessJournal ArticleDOI: 10.1016/S0140-6736(12)61851-0
Mariachiara Di Cesare1, Young-Ho Khang2, Perviz Asaria1, Tony Blakely3  +11 moreInstitutions (11)
16 Feb 2013-The Lancet
Abstract: In most countries, people who have a low socioeconomic status and those who live in poor or marginalised communities have a higher risk of dying from non-communicable diseases (NCDs) than do more advantaged groups and communities. Smoking rates, blood pressure, and several other NCD risk factors are often higher in groups with low socioeconomic status than in those with high socioeconomic status; the social gradient also depends on the country's stage of economic development, cultural factors, and social and health policies. Social inequalities in risk factors account for more than half of inequalities in major NCDs, especially for cardiovascular diseases and lung cancer. People in low-income countries and those with low socioeconomic status also have worse access to health care for timely diagnosis and treatment of NCDs than do those in high-income countries or those with higher socioeconomic status. Reduction of NCDs in disadvantaged groups is necessary to achieve substantial decreases in the total NCD burden, making them mutually reinforcing priorities. Effective actions to reduce NCD inequalities include equitable early childhood development programmes and education; removal of barriers to secure employment in disadvantaged groups; comprehensive strategies for tobacco and alcohol control and for dietary salt reduction that target low socioeconomic status groups; universal, financially and physically accessible, high-quality primary care for delivery of preventive interventions and for early detection and treatment of NCDs; and universal insurance and other mechanisms to remove financial barriers to health care.

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Topics: Socioeconomic status (53%), Health care (52%), Social inequality (51%)

470 Citations