Burden of COVID-19 in Córdoba, A Department of Colombia: Results of Disability-Adjusted Life-Years :  Carga de COVID-19 en Córdoba, un Departamento de Colombia: Resultados de los Años de Vida Ajustados por Discapacidad

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Objectives

This study aimed to estimate the burden of acute COVID-19 in Córdoba, one of the most affected departments (states) in Colombia, through the estimation of disability-adjusted life-years (DALYs).

Methods

DALYs were estimated based on the number of cases of severe acute respiratory syndrome coronavirus 2 infection cases reported by official Colombian sources. A transition probability matrix among severity states was calculated using data obtained from a retrospective cohort that included 1736 COVID-19 confirmed subjects living in Córdoba.

Results

Córdoba had 120.23 deaths per 100 000 habitants during the study period (March 2020 to April 2021). Estimated total DALYs were 49 243 (2692 DALYs per 100 000 inhabitants), mostly attributed to fatal cases (99.7%). On average, 25 years of life were lost because of death by this infection. A relevant proportion of years of life lost because of COVID-19 (46.6%) was attributable to people < 60 years old and was greater in men. People ≥ 60 years old showed greater risk of progression to critical state than people between the age of 35 and 60 years (hazard ratio 2.5; 95% confidence interval 2.5-12.5) and younger than 35 years (9.1; 95% confidence interval 4.0-20.6).

Conclusion

In Córdoba, premature mortality because of COVID-19 was substantially represented by people < 60 years old and was greater in males. Our data may be representative of Latin American populations with great infection spread during the first year of the pandemic and contribute to novel methodological aspects and parameter estimations that may be useful to measure COVID-19 burden in other countries of the region.

Translated abstract

Objetivos

Estimar la carga de COVID-19 aguda en Córdoba, uno de los departamentos (estados) más afectados de Colombia, a través de la estimación de años de vida ajustados por discapacidad (AVISAS).

Métodos

Los AVISAS se estimaron con base en el número de casos de infección por severe acute respiratory syndrome coronavirus 2 reportados por fuentes oficiales colombianas. Se calculó una matriz de probabilidad de transición entre estados de gravedad a partir de los datos obtenidos de una cohorte retrospectiva que incluyó a 1.736 sujetos confirmados con COVID-19 residentes en Córdoba.

Resultados

Córdoba tuvo 120,23 defunciones por cada 100.000 habitantes durante el periodo de estudio (marzo de 2020 a abril de 2021). Los AVISAS totales estimados fueron 49.243 (2.692 AV por 100.000 habitantes), en su mayoría atribuidos a los casos mortales (99,7%). En promedio, se perdieron 25 años de vida debido a las muertes secundarias a esta infección. Una proporción relevante de años de vida perdidos a causa de la COVID-19 (46,6%) fue atribuible a las personas menores de 60 años y fue mayor en los hombres. Las personas ≥ 60 años presentaron un mayor riesgo de progresión a estado crítico en comparación con las personas entre 35-60 años (hazard ratio 2,5; intervalo de confianza 95% 2,5-12,5) y menores de 35 años (9,1; intervalo de confianza 95% 4,0-20,6).

Conclusión

En Córdoba, la mortalidad prematura por COVID-19 estuvo sustancialmente representada por las personas menores de 60 años y fue mayor en el sexo masculino. Nuestros datos pueden ser representativos de poblaciones latinoamericanas con gran propagación de infecciones durante el primer año de la pandemia y aportan aspectos metodológicos novedosos para la estimación de parámetros que pueden ser útiles para medir la carga de COVID-19 en otros países de la región.

Related collections

Most cited references 43

Record: found
Abstract: found
Article: found

Is Open Access

Gender Differences in Patients With COVID-19: Focus on Severity and Mortality

Jian-Min Jin, Peng Bai, Wei He … (2020)

Objective: The recent outbreak of Novel Coronavirus Disease (COVID-19) is reminiscent of the SARS outbreak in 2003. We aim to compare the severity and mortality between male and female patients with COVID-19 or SARS. Study Design and Setting: We extracted the data from: (1) a case series of 43 hospitalized patients we treated, (2) a public data set of the first 37 cases of patients who died of COVID-19 and 1,019 patients who survived in China, and (3) data of 524 patients with SARS, including 139 deaths, from Beijing in early 2003. Results: Older age and a high number of comorbidities were associated with higher severity and mortality in patients with both COVID-19 and SARS. Age was comparable between men and women in all data sets. In the case series, however, men's cases tended to be more serious than women's (P = 0.035). In the public data set, the number of men who died from COVID-19 is 2.4 times that of women (70.3 vs. 29.7%, P = 0.016). In SARS patients, the gender role in mortality was also observed. The percentage of males were higher in the deceased group than in the survived group (P = 0.015). Conclusion: While men and women have the same prevalence, men with COVID-19 are more at risk for worse outcomes and death, independent of age.

0 comments Cited 959 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21

(2022)

Background Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021. Methods All-cause mortality reports were collected for 74 countries and territories and 266 subnational locations (including 31 locations in low-income and middle-income countries) that had reported either weekly or monthly deaths from all causes during the pandemic in 2020 and 2021, and for up to 11 year previously. In addition, we obtained excess mortality data for 12 states in India. Excess mortality over time was calculated as observed mortality, after excluding data from periods affected by late registration and anomalies such as heat waves, minus expected mortality. Six models were used to estimate expected mortality; final estimates of expected mortality were based on an ensemble of these models. Ensemble weights were based on root mean squared errors derived from an out-of-sample predictive validity test. As mortality records are incomplete worldwide, we built a statistical model that predicted the excess mortality rate for locations and periods where all-cause mortality data were not available. We used least absolute shrinkage and selection operator (LASSO) regression as a variable selection mechanism and selected 15 covariates, including both covariates pertaining to the COVID-19 pandemic, such as seroprevalence, and to background population health metrics, such as the Healthcare Access and Quality Index, with direction of effects on excess mortality concordant with a meta-analysis by the US Centers for Disease Control and Prevention. With the selected best model, we ran a prediction process using 100 draws for each covariate and 100 draws of estimated coefficients and residuals, estimated from the regressions run at the draw level using draw-level input data on both excess mortality and covariates. Mean values and 95% uncertainty intervals were then generated at national, regional, and global levels. Out-of-sample predictive validity testing was done on the basis of our final model specification. Findings Although reported COVID-19 deaths between Jan 1, 2020, and Dec 31, 2021, totalled 5·94 million worldwide, we estimate that 18·2 million (95% uncertainty interval 17·1–19·6) people died worldwide because of the COVID-19 pandemic (as measured by excess mortality) over that period. The global all-age rate of excess mortality due to the COVID-19 pandemic was 120·3 deaths (113·1–129·3) per 100 000 of the population, and excess mortality rate exceeded 300 deaths per 100 000 of the population in 21 countries. The number of excess deaths due to COVID-19 was largest in the regions of south Asia, north Africa and the Middle East, and eastern Europe. At the country level, the highest numbers of cumulative excess deaths due to COVID-19 were estimated in India (4·07 million [3·71–4·36]), the USA (1·13 million [1·08–1·18]), Russia (1·07 million [1·06–1·08]), Mexico (798 000 [741 000–867 000]), Brazil (792 000 [730 000–847 000]), Indonesia (736 000 [594 000–955 000]), and Pakistan (664 000 [498 000–847 000]). Among these countries, the excess mortality rate was highest in Russia (374·6 deaths [369·7–378·4] per 100 000) and Mexico (325·1 [301·6–353·3] per 100 000), and was similar in Brazil (186·9 [172·2–199·8] per 100 000) and the USA (179·3 [170·7–187·5] per 100 000). Interpretation The full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone. Strengthening death registration systems around the world, long understood to be crucial to global public health strategy, is necessary for improved monitoring of this pandemic and future pandemics. In addition, further research is warranted to help distinguish the proportion of excess mortality that was directly caused by SARS-CoV-2 infection and the changes in causes of death as an indirect consequence of the pandemic. Funding Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom

0 comments Cited 541 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study

Michela Antonelli, Rose S Penfold, Jordi Merino … (2021)

Background COVID-19 vaccines show excellent efficacy in clinical trials and effectiveness in real-world data, but some people still become infected with SARS-CoV-2 after vaccination. This study aimed to identify risk factors for post-vaccination SARS-CoV-2 infection and describe the characteristics of post-vaccination illness. Methods This prospective, community-based, nested, case-control study used self-reported data (eg, on demographics, geographical location, health risk factors, and COVID-19 test results, symptoms, and vaccinations) from UK-based, adult (≥18 years) users of the COVID Symptom Study mobile phone app. For the risk factor analysis, cases had received a first or second dose of a COVID-19 vaccine between Dec 8, 2020, and July 4, 2021; had either a positive COVID-19 test at least 14 days after their first vaccination (but before their second; cases 1) or a positive test at least 7 days after their second vaccination (cases 2); and had no positive test before vaccination. Two control groups were selected (who also had not tested positive for SARS-CoV-2 before vaccination): users reporting a negative test at least 14 days after their first vaccination but before their second (controls 1) and users reporting a negative test at least 7 days after their second vaccination (controls 2). Controls 1 and controls 2 were matched (1:1) with cases 1 and cases 2, respectively, by the date of the post-vaccination test, health-care worker status, and sex. In the disease profile analysis, we sub-selected participants from cases 1 and cases 2 who had used the app for at least 14 consecutive days after testing positive for SARS-CoV-2 (cases 3 and cases 4, respectively). Controls 3 and controls 4 were unvaccinated participants reporting a positive SARS-CoV-2 test who had used the app for at least 14 consecutive days after the test, and were matched (1:1) with cases 3 and 4, respectively, by the date of the positive test, health-care worker status, sex, body-mass index (BMI), and age. We used univariate logistic regression models (adjusted for age, BMI, and sex) to analyse the associations between risk factors and post-vaccination infection, and the associations of individual symptoms, overall disease duration, and disease severity with vaccination status. Findings Between Dec 8, 2020, and July 4, 2021, 1 240 009 COVID Symptom Study app users reported a first vaccine dose, of whom 6030 (0·5%) subsequently tested positive for SARS-CoV-2 (cases 1), and 971 504 reported a second dose, of whom 2370 (0·2%) subsequently tested positive for SARS-CoV-2 (cases 2). In the risk factor analysis, frailty was associated with post-vaccination infection in older adults (≥60 years) after their first vaccine dose (odds ratio [OR] 1·93, 95% CI 1·50–2·48; p<0·0001), and individuals living in highly deprived areas had increased odds of post-vaccination infection following their first vaccine dose (OR 1·11, 95% CI 1·01–1·23; p=0·039). Individuals without obesity (BMI <30 kg/m 2 ) had lower odds of infection following their first vaccine dose (OR 0·84, 95% CI 0·75–0·94; p=0·0030). For the disease profile analysis, 3825 users from cases 1 were included in cases 3 and 906 users from cases 2 were included in cases 4. Vaccination (compared with no vaccination) was associated with reduced odds of hospitalisation or having more than five symptoms in the first week of illness following the first or second dose, and long-duration (≥28 days) symptoms following the second dose. Almost all symptoms were reported less frequently in infected vaccinated individuals than in infected unvaccinated individuals, and vaccinated participants were more likely to be completely asymptomatic, especially if they were 60 years or older. Interpretation To minimise SARS-CoV-2 infection, at-risk populations must be targeted in efforts to boost vaccine effectiveness and infection control measures. Our findings might support caution around relaxing physical distancing and other personal protective measures in the post-vaccination era, particularly around frail older adults and individuals living in more deprived areas, even if these individuals are vaccinated, and might have implications for strategies such as booster vaccinations. Funding ZOE, the UK Government Department of Health and Social Care, the Wellcome Trust, the UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare, the UK National Institute for Health Research, the UK Medical Research Council, the British Heart Foundation, and the Alzheimer's Society.

0 comments Cited 347 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Value Health Reg Issues

Journal ID (iso-abbrev): Value Health Reg Issues

Title: Value in Health Regional Issues

Publisher: International Society for Health Economics and Outcomes Research. Published by Elsevier Inc.

ISSN (Print): 2212-1099

ISSN (Electronic): 2212-1102

Publication date PMC-release: 28 April 2023

Publication date (Print): September 2023

Publication date (Electronic): 28 April 2023

Volume: 37

Pages: 9-17

Affiliations

[1 ]ALZAK Foundation, Cartagena, Colombia

[2 ]Grupo de Investigación en Economía de la Salud, Universidad de Cartagena, Cartagena, Colombia

[3 ]Instituto de Investigaciones Biológicas del Trópico, Universidad de Córdoba, Montería, Córdoba

[4 ]Facultad de Medicina, Universidad CES, Medellín, Colombia

[5 ]Instituto Colombiano de Medicina Tropical-Universidad CES, Medellín, Colombia

[6 ]Departamento de Ciencias de la Salud, Universidad de la Costa, Barranquilla, Colombia

[7 ]Programa de posgraduación en Epidemiología, Universidad de São Paulo, São Paulo, Brasil

Author notes

[∗ ] Correspondence: Nelson J. Alvis-Zakzuk, MSc, Departamento de Ciencias de la Salud, Universidad de la Costa, Calle 58 # 55 – 66, Barranquilla, Colombia.

Article

Publisher Item ID: S2212-1099(23)00033-X

DOI: 10.1016/j.vhri.2023.03.005

PMC ID: 10147312

SO-VID: c66a2be5-e2e5-4853-93e4-ebd6233f1ccd

License:

Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

History

Date accepted : 20 March 2023

Burden of COVID-19 in Córdoba, A Department of Colombia: Results of Disability-Adjusted Life-Years : Carga de COVID-19 en Córdoba, un Departamento de Colombia: Resultados de los Años de Vida Ajustados por Discapacidad

Read this article at

Abstract

Objectives

Methods

Results

Conclusion

Translated abstract

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 43

Gender Differences in Patients With COVID-19: Focus on Severity and Mortality

Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21

Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study

Author and article information

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 243

Most referenced authors 1,405