ABSTRACT

Objectives.

To estimate the burden of disease of COVID-19 in the department of Nariño, Colombia, based on the disability-adjusted life years (DALYs) between March 2020 and August 2021.

Materials and methods.

The description and characterization of COVID-19 cases reported between March 2020 and August 2021 was made according to age groups, sex, ethnicity, municipalities of residence and subregions of Nariño by using information from the national surveillance system SIVIGILA. Crude and cumulative mortality rates for COVID-19 were estimated for the previously described variables. Years lost due to premature death (YLL) and years lived with disability (YLD) were calculated. Total DALYs were estimated by adding YLL + YLD. These were calculated by sex, ethnicity, age group and subregions of Nariño. Relative risks were estimated from rate ratios (RR) and 95% confidence intervals for the study variables.

Results.

The highest morbidity, mortality and DALY rates occurred between February and September 2021, in men, in those older than 70 years, in the Afro-descendant ethnic minority group and in the Central, Obando and Juanambú subregions. The burden of disease of COVID-19 in Nariño during the study period is attributed to the YLL, which explain more than 97% of it.

Conclusions.

This is one of the first studies on burden of disease at the regional level, carried out in Colombia, that employs a standardized methodology for COVID-19. This measurement would generate estimates that would allow targeting resources in an intersectoral manner, mitigating the damage to specific populations and geographic areas, especially the most vulnerable ones.

Keywords:
SARS-CoV-2; COVID-19; Burden Disease; Disability-adjusted Life Year; Coronavirus; Colombia

KEY MESSAGES

1. Motivation for the study: burden of disease studies are methodological strategies that contribute to the analysis of population health status. This is one of the first studies on COVID-19 that estimates disability-adjusted healthy life years (DALYs), adapting a methodology to a Latin American context.
2. Main findings: the burden of disease in Nariño, at the beginning of the epidemic, was mainly due to premature mortality, in men, older than 70 years, of undetermined ethnic groups and in territories previously affected by chronic non-communicable diseases.
3. Implications: the estimation of DALYs guides decision-makers in generating priorities for resource intervention and control/prevention strategies for this emerging disease based on scientific evidence.

Keywords:
SARS-CoV-2; COVID-19; Burden Disease; Disability-adjusted Life Year; Coronavirus; Colombia

INTRODUCTION

Coronaviruses behave as a zoonosis ¹1. Cyranoski D. Mystery deepens over animal source of coronavirus. Nature. 2020; 79(7797):18-9. doi: 10.1038/d41586-020-00548-w.
https://doi.org/10.1038/d41586-020-00548... affecting human health in different periods. In the last 20 years they have caused several epidemics. The first was caused by SARS (severe acute respiratory syndrome); between 2002-2003 this strain infected more than 8000 people (China, United States, Canada, among others) with a lethality rate close to 10%. The second one occurred in 2012, by MERS-CoV (Middle East Respiratory Syndrome); this epidemic affected about 857 people with a mortality rate close to 35% ²2. Feng H, Yu Deng WL. Coronavirus disease 2019: What we know?. J Med Virol. 2020; 92(7): 719-725. doi: 10.1002/jmv.25766.
https://doi.org/10.1002/jmv.25766... . The third outbreak was produced by a new strain (SARS-CoV-2), which appeared at the end of 2019 ³3. Organización Mundial de la Salud. Alocución de apertura del director general de la OMS en la rueda de prensa sobre la COVID-19 celebrada el 11 de marzo de 2020. Disponible en: https://www.who.int/es/dg/speeches/detail/who-director-general-sopening-remarks-at-the-media-briefing-on-covid-19---11-march-2020.
https://www.who.int/es/dg/speeches/detai... causing the healthcare emergency due to COVID-19, with lethality rates between 1-10% worldwide ⁴4. Río D, Malani PN. COVID-19-New Insights on a Rapidly Changing Epidemic. JAMA .2020 323(14):1339-40. Disponible en: https://jamanetwork.com/journals/jama/fullarticle/2762510.
https://jamanetwork.com/journals/jama/fu... . The high transmissibility of this virus is due to the rapid respiratory dissemination, because viral transmission can occur by symptomatic patients or asymptomatic individuals ⁵5. Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, Wallrauch C, et al. Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany. N Engl J Med. 2020; 382(10):970-1. doi: 10.1056/NEJMc2001468.
https://doi.org/10.1056/NEJMc2001468... .

Although SARS-CoV-2 is a partially preventable and treatable disease, it has been a health, economic, political, and social challenge for the world. For low- and middle-income countries, it has been the worst humanitarian and public health crisis in their history ⁶6. García PJ, Alarcón A, Bayer A, Buss P, Guerra G, Ribeiro H, et al. COVID-19 Response in Latin America. Am J Trop Med Hyg. 2020; 103(5): 1765-1772. doi: 10.4269/ajtmh.20-0765.
https://doi.org/10.4269/ajtmh.20-0765... , with considerable differences in morbidity and mortality rates among them ⁷7. Litewka SH. Latin American healthcare systems in times of pandemic. Dev World Bioeth. 2020; 20(2): 69-73. doi: 10.1111/dewb.12262.
https://doi.org/10.1111/dewb.12262... . Latin America has precarious healthcare systems unable to provide effective responses, with health budgets below 4.0% of the gross domestic product (GDP) ⁸8. Organización Panamericana de la Salud. Salud en las Américas. Financiamiento de la salud en las américas; 2017 [21 de agosto de 2021]. Disponible en: https://www.paho.org/salud-en-las-americas-2017/uh-financing-es.html.
https://www.paho.org/salud-en-las-americ... , which limits access to quality healthcare, making them susceptible to collapse. During the pandemic, governments did not allocate economic and social resources efficiently to the most affected regions, which led to worsening of economic and social inequalities ⁹9. Economic Commission for Latin America and the Caribbean (ECLAC). Report on the economic impact of coronavirus disease (COVID-19) on Latin America and the Caribbean. Santiago: Community of Latin American and Caribbean States (CELAC); 2020. Disponible en: https://repositorio.cepal.org/bitstream/handle/11362/45603/S2000312_en.pdf?sequence=1&isAllowed=y.
https://repositorio.cepal.org/bitstream/... .

There are other social determinants specific to the continent that have an impact on population health. For example, in Colombia, 37% of households do not eat three meals a day, and 43.9% of heads of household perceive that their economic status has worsened ¹⁰10. Departamento Administrativo Nacional de Estadística (DANE). Boletín Técnico Encuesta Pulso Social. Resultados Agosto de 2021; 2021. Disponible en: https://www.dane.gov.co/index.php/estadisticas-por-tema/encuesta-pulso-social.
https://www.dane.gov.co/index.php/estadi... . Colombia has the second highest unemployment rate after Haiti, where women are the most affected (39%) compared to men (18%). Likewise, labor informality and the widening of the social inequality gap in Brazil and Colombia are very high ¹¹11. Banco Mundial. Una recuperación desigual: Tomando el pulso de América Latina y el Caribe después de la pandemia. Washington D.C.: Programa de Naciones Unidas (PNUD); 2021. Disponible en: https://www.undp.org/es/latin-america/publications/una-recuperaci%C3%B3n-desigual-tomando-el-pulso-de-am%C3%A9rica-latina-y-el-caribe-despu%C3%A9s-de-la-pandemia.
https://www.undp.org/es/latin-america/pu... , but this gap also exists between regions in Colombia ¹²12. Acosta-Navas JP. Derecho Internacional Humanitario y COVID-19 en Colombia: la construcción de paz en el posacuerdo y la pospandemia. Ánfora [Internet]. 2022 Jul [cited 2022 Sep 1];29(53):141-62. Disponible en: https://search-ebscohost-com.ezproxy.javeriana.edu.co/login.aspx?direct=true&AuthType=ip&db=a9h&AN=158311228&lang=es&site=eds-live.
https://search-ebscohost-com.ezproxy.jav... . Some of the aforementioned determinants may have contributed to the fact that in mid-June 2021 the epidemiological outlook for COVID-19 in Colombia was one of the most unfavorable in the world ¹³13. World Health Organization. COVID-19 Weekly Epidemiological Update. Washington D.C.: World Health Organization; 2021 [22 june 2021] #45. Disponible en: https://apps.who.int/iris/handle/10665/342009?locale-attribute=es&.
https://apps.who.int/iris/handle/10665/3... , affecting people with comorbidities, who required specialized care ¹⁴14. Raghunath N, Tan T. The impact of social stratification on morbidity during the COVID-19 pandemic. Int J Sociol Soc Policy. 2020; 40 (9/10): 793-806. doi: 10.1108/IJSSP-07-2020-0261.
https://doi.org/10.1108/IJSSP-07-2020-02... .

In Colombia, the first case of COVID-19 was reported in March 2020. By August 2021 SARS-CoV-2 had spread throughout the country with nearly five million confirmed cases and more than 122,000 deaths. By the end of 2020, the department of Nariño recorded 88,927 confirmed cases and 3381 deaths, with a cumulative incidence of 48/1000 inhabitants and mortality of 1.8/1000 inhabitants ¹⁵15. Instituto Nacional de Salud [Internet]. Bogotá, Colombia: Gobierno de Colombia; 2021 [citado 23 de diciembre de 2021]. Disponible en: https://www.ins.gov.co/Noticias/Paginas/Coronavirus.aspx.
https://www.ins.gov.co/Noticias/Paginas/... .

In low- and middle-income countries, the evaluation of population health status has traditionally been based on mortality indicators such as general or specific mortality rates, infant mortality, maternal mortality ratio, among others; and/or morbidity indicators such as incidence or prevalence, depending on the type of event under study. Due to their limitations in the measurement of the health-disease phenomena, there is a need to develop other indicators to measure related aspects such as the quality of life of people. In this context, burden of disease studies makes it possible to identify various health problems that cause death, morbidity, and disability, since they integrate the burden produced by premature death, duration, sequelae of the disease and disability through the disability-adjusted healthy life years indicator (DALYs) ¹⁶16. Murray CJ, Lopez AD. The Global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020. 1st. ed. World Health Organization, World Bank & Harvard School of Public Health; 1996..

Colombia has several previous burden of disease studies, including those conducted by the Universidad Javeriana ¹⁷17. Escobar ML, Gallardo HM, Giraldo PG, Londoño JL, Rodríguez J. La Carga de la enfermedad en Colombia. Primera edición, Ministerio de Salud. Editorial Carrera Séptima Ltda;1994.^,1818. Peñaloza-Quintero RE, Salamanca-Balen N, Rodríguez-Hernández JM, Rodríguez-García J, Beltrán-Villegas AR. Estimación de la Carga de la Enfermedad para Colombia, 2010. Primera edición, Editorial Pontificia Universidad Javeriana; 2014. and the National Health Observatory ¹⁹19. Castillo-Rodríguez L, Díaz-Jiménez D, Castañeda-Orjuela C, De la Hoz-Restrepo F. Years of Life Lost (YLL) in Colombia 1998-2011: Overall and Avoidable Causes of Death Analysis. 2015. Plos one; 10(5): e01 2545 6. doi: 10.1371/journal.pone.0125456.
https://doi.org/10.1371/journal.pone.012... .

The department of Nariño is the only one in Colombia that has a disease burden study by subregion conducted by its health authority; in part, because it is a border region characterized by jointly possessing: contexts of armed conflict, high levels of corruption and territories with population at and below the poverty line ¹²12. Acosta-Navas JP. Derecho Internacional Humanitario y COVID-19 en Colombia: la construcción de paz en el posacuerdo y la pospandemia. Ánfora [Internet]. 2022 Jul [cited 2022 Sep 1];29(53):141-62. Disponible en: https://search-ebscohost-com.ezproxy.javeriana.edu.co/login.aspx?direct=true&AuthType=ip&db=a9h&AN=158311228&lang=es&site=eds-live.
https://search-ebscohost-com.ezproxy.jav... , which increases the risk of COVID-19 mortality; hence the relevance of studying the COVID-19 situation based on the estimation of departmental ²⁰20. Rocha-Buelvas A, Trujillo-Montalvo E, Hidalgo-Patiño C, Hidalgo-Eraso A. Carga de enfermedad en Nariño, Colombia, 2010. Colomb Med. 2014; 45 (3): 96-103. and, in this case, subregional DALYs for the department of Nariño.

In the current scenario, it is important to conduct not only national but also territorial burden of disease studies, since according to the National Administrative Department of Statistics (DANE) and the National Institute of Health of Colombia (INS), COVID-19 is currently one of the most important causes of mortality and, therefore, it is essential to identify the burden attributed to this event, in order to guide targeted actions and strategies ²¹21. Azuero F. Los datos que tenemos (y los que no tenemos) sobre la COVID en Colombia. Razón Pública [Internet]. 5 de julio 2021 [citado 21 de diciembre de 2021]. Disponible en: https://razonpublica.com/los-datos-tenemos-los-no-tenemos-la-covid-colombia/.
https://razonpublica.com/los-datos-tenem... . The aim of the study was to determine the burden of disease attributed to COVID-19 in the department of Nariño, between March 2020 and August 2021.

MATERIALS AND METHODS

This is a descriptive analytical study that uses the records of COVID-19 cases reported to the National Public Health Surveillance System (SIVIGILA), which is coordinated by the INS, as the source of information. For this study, we used the records of the department of Nariño.

Based on information from SIVIGILA, we carried out the description and characterization of COVID-19 cases reported from March 2020 to August 2021, by age grouped as follows: (0-4, 5-14, 15-29, 30-44, 45-59, 60-69, 70-79 and 80 and +); sex (men and women); ethnicity (1: Indigenous, 2: Gypsies, 3-5: Afro-descendant, 6: Other ); municipalities (all municipalities in the department of Nariño) and by the thirteen administrative sub-regions managed by the department of Nariño (Obando, Occidente, Centro, Guambuyaco, Juanambú, La Cordillera, La Sabana, Los Abades, Pacífico Sur, Piedemonte Costero, Río Mayo, Sanquianga and Telembí). a We obtained percentage descriptions for each variable. Time was divided into three semesters: March-August 2020 (A), September-February 2021 (B) and March-August 2021 (C).

Disease burden of COVID-19

Based on DANE 2020 population projections, crude incidence rates of morbidity (contagion) and cumulative mortality by COVID-19 were obtained for the previously described variables (age groups, sex, ethnicity, municipality, and departmental subregion). Statistical significance tests were applied at a level of 0.05 to identify changes in the rate ratios (RR) of DALYs by age, sex, subregion, and period, by means of Wald tests using a generalized linear model.

DALYs were disaggregated by both, years lost due to premature death (YLLD) and years lived due to disability (YLD) using some methodological references as described below. Table 1, which contains the life expectancies (LE) for both sexes, was used to calculate the YLLFs, taking as the main input the lowest mortality rates recorded for each age group in countries with more than 5 million people. The estimate was made by multiplying the LE by the volume of deaths in the same age group, municipality, region, sex, and ethnicity specific to the department of Nariño.

The equation for calculating the YLLD was as follows:

Where: Dx =1 at death at X age; Ex = standard life expectancy of each specific age of the chosen model and L = theoretical limiting age of the chosen life table.

We used the following formula for the estimation of DALYs, or years lived with disability due to COVID-19: YLD _a = D * L. Where: a = the age of onset of the disease, D = burden of the disease, which ranges between 0 and 1. If the individual is completely healthy, a D equal to 0 would be obtained; on the contrary, if the individual dies, D is equal to 1. Severe disease has a value of D close to 1; a mild clinical condition has a value of D close to zero. For this research, regarding the burden of the disease, we used the approach by Wyper et al.²²22. Wyper GMA, Assunção RMA, Colzani E, Grant I, Haagsma JA, Lagerweij G, et al. Burden of Disease Methods: A Guide to Calculate COVID-19 Disability-Adjusted Life Years. Int J Public Health. 2021; 66:619011. doi: 10.3389/ijph.2021.619011.
https://doi.org/10.3389/ijph.2021.619011... , which uses three categories: mild/moderate (0.051), severe (0.133) and critical (0.655) (Figure 1). L=duration of the disease, which, in this case, was estimated as a fraction in years, with the difference between the date of recovery and the date of symptom onset according to SIVIGILA records.

The YLLD and YLD allowed us to calculate the total DALYs by adding them together, as follows: DALYs = YLLD + YLD. Similarly, based on DANE population projections, the total DALY rates per 1000 inhabitants were estimated by sex, ethnicity, age group and subregion in the department of Nariño.

Negative binomial regression model

Finally, we estimated a generalized linear model to identify the trend in COVID-19 DALY rates for the study period. It was calculated from the number of COVID-19 DALYs, which were taken as a random variable, taking Y = Ln(R), where R represents COVID-19 DALY rates and as independent or explanatory variables, age as X1, sex as X2, time period as X3, and departmental regions as X4. Relative risks were estimated from the rate ratios (RR), together with 95% confidence intervals, for each of the categories of the study variables, based on reference groups for each of the explanatory variables.

For the estimation of the generalized linear model, we used the IBM SPSS version 23 statistical package. The assumptions of equidispersion were verified using Pearson’s deviation and chi-square statistics to establish whether the Poisson regression model was the appropriate model for the data. The goodness-of-fit statistics showed scale values indicating overdispersion, i.e., violation of this property, therefore the alternative negative binomial model was used, and the pseudoR2 statistic was estimated to establish the goodness-of-fit of the model.

Ethical considerations

For this study, the data were extracted from the records of the National Public Health Surveillance System coordinated by the INS. No modifications were made to the figures provided by the sources of information; whenever reference is made to a text, the authors are cited, while respecting copyright.

This research is classified as “without risk” according to resolution 8430 of 1993 of the Ministry of Health, in addition, this study has approval certificate No. 004 of April 23, 2020 of the Research Ethics Committee of the Vice-Rectory of Research and Social Interaction of the Universidad de Nariño.

RESULTS

We found 88,762 cases of COVID-19 infection in the department of Nariño during the period March 2020 and August 2021, with an annual rate of 3196 cases per 100,000 inhabitants. In the same period, deaths from the virus were equal to 2985 cases with an annual mortality rate of 107.5 cases per 100,000 inhabitants.

Regarding the morbidity component, Table 2 shows that the highest cumulative incidence rate (4794 per 100,000 inhabitants) occurred in periods B (1828.3) and C (2121.4). This rate increased gradually with age, the highest rate corresponding to the group aged 80 years and over (7779.8). Women had slightly higher morbidity rates (5034) than men (4556.1). The most affected ethnic minority group were Afro-descendants (4468.3). The most affected subregions were Centro (9955.3) and Juanambú (5400.6), exceeding the departmental average (4794.1). Regarding the mortality component, we observed that the highest cumulative rates occurred in periods B (56.87) and C (69.46). Mortality rates (161.2 per 100,000 population) also increased gradually, with the group aged 80 years and over being the most affected (2367.6). In contrast to morbidity, mortality in men (199.3) was higher than in women (122.9). Once again, the Afro-descendant ethnic group had a higher mortality rate (211). The subregions with the highest mortality from COVID-19 were also Centro (293.6), Obando (180.3) and Juanambú (172.8).

COVID-19 disease burden

The YLLD were 67,638.6 with an annual rate of 25.3 per thousand inhabitants during the analyzed period. YLD were 313.2 with an annual rate of 0.11 per 1000 inhabitants. DALYs were 97,950.81 with an annual rate of 24.5 per 1000 inhabitants during the evaluated period. Table 3 shows that the third time period had the highest DALYs due to COVID-19 (17.8). By age group, 190 DALYs were lost in those aged 80 years and older; 177.5 DALYs in those aged 70-79 years; 138.61 in those aged 60-69 years and 74.55 in those aged 45-59 years. Men lost 46.3 DALYs, and women lost 27 per 1000 inhabitants. The Afro-descendant ethnic minority group lost 53.2 DALYs. Finally, the subregions with the highest DALYs were Centro (64.8), Obando (42.1) and Juanambú (39.1).

Negative binomial regression model

We carried out the adjustment of the DALY rates by age in order to construct the model by using the direct method and taking the standard world population according to the World Health Organization (WHO) as reference.With this model we found that the variables age groups and subregion presented statistically significant associations (p < 0.05), and that the risk of DALYs is higher in age groups of 60 or more years than in those younger. The subregions with the highest risk were Piedemonte Costero (RR = 12.95), followed by Los Abades (RR = 2.54), which presented statistically significant differences with the reference subregion Sanquianga (p < 0.05), no statistical differences were found for the other subregions. No statistical differences were observed in the risks of DALYs by time period and sex (Table 4).

We calculated the determination coefficient, which measures the goodness of fit of the model to the data: D1 = log likelihood of the proposed model and D0 = log likelihood of the null model (only with the intercept).

Pseudo R² = (D0 - D1) / D1 = 22.7%

The variables period, age, sex, and subregion explain 22.7% of the variations in DALYs.

Likewise, the size of the effect on the variations in the DALYs due to COVID-19 was determined from the four variables evaluated in the model, with the age group variable being the variable with the greatest weight, followed by the subregion variable and with a much smaller effect by period and sex, which explain globally about 23% of the variance of the DALYs.

DISCUSSION

This is one of the first researches on COVID-19 disease burden worldwide. Although there are few studies on this subject, new results are published every day. In this research we observed that the burden of disease by COVID-19, for the department of Nariño, increased during the study period (it was significant between the first and third semester under observation), attributed to the increase in mortality, prior to the dissemination of vaccination. The most affected were men, those older than 70 years, population without ethnic affiliation, and those in subregions with a history of high incidence of chronic noncommunicable diseases.

The magnitude of the burden of disease found in this study relative to other types of flu (none pandemic) can be explained comparatively. For example, in 2022, WHO reported more than 300 million confirmed cases with more than 5 million deaths from COVID-19; whereas, for influenza, in 2022, WHO reported 1 billion cases, 3 to 5 million severe, which have resulted in 650,000 deaths. In other words, the lethality due to COVID-19, compared to other influenzas, is much higher and unprecedented as a public health problem ⁹9. Economic Commission for Latin America and the Caribbean (ECLAC). Report on the economic impact of coronavirus disease (COVID-19) on Latin America and the Caribbean. Santiago: Community of Latin American and Caribbean States (CELAC); 2020. Disponible en: https://repositorio.cepal.org/bitstream/handle/11362/45603/S2000312_en.pdf?sequence=1&isAllowed=y.
https://repositorio.cepal.org/bitstream/... .

Our results show that during the studied period (March 2020 - August 2021), the risk of morbidity due to COVID-19 in the department of Nariño increased significantly, the most affected were women, those over 45 years of age, people without ethnic affiliation, and those from the Central and Juanambú regions of the department of Nariño. The risk of death also increased during the study period, being higher in men, over 70 years of age, without ethnic affiliation; and the most affected regions were the Central and Juanambú regions. This agrees with a research carried out in Europe, which found that morbidity and lethality due to COVID-19 varies between regions, but that in countries such as Germany and Switzerland, the incidence by age and sex are higher in men aged 60 years and older ²³23. Gebhard C, Regitz-Zagrosek V, Neuhauser HK, Morgan R, Klein SL. Impact of sex and gender on COVID-19 outcomes in Europe. Biology of sex differences, 2020; 11(1), 29. doi: 10.1186/s13293-020-00304-9.
https://doi.org/10.1186/s13293-020-00304... .

It is important to note that the most populated subregions: Centro, Obando and Juanambú are the ones that occupy the first places in mortality due to COVID-19, but also according to the last study of disease burden ²⁰20. Rocha-Buelvas A, Trujillo-Montalvo E, Hidalgo-Patiño C, Hidalgo-Eraso A. Carga de enfermedad en Nariño, Colombia, 2010. Colomb Med. 2014; 45 (3): 96-103. they are the ones that occupy the first places in mortality due to chronic diseases as well. This suggests a possible syndemic effect. According to a study in counties from the United States, there is a confluence of epidemics of both COVID-19 and chronic diseases in contexts of social disadvantage, where the African-American ethnic and population is the most affected group ²⁴24. Islam N, Lacey B, Shabnam S, Erzurumluoglu AM, Dambha-Miller H, Chowell G, et al. Social inequality and the syndemic of chronic disease and COVID-19: county-level analysis in the USA. J Epidemiol Community Health. 2021; 75:496-500. doi: 10.1136/jech-2020-215626.
https://doi.org/10.1136/jech-2020-215626... . A study based on data from 185 countries reports that COVID-19 morbidity and mortality correlate with the burden of chronic diseases, due to the aging of the population and the low capacity of health services to test and provide hospital beds, in socially unequal settings ²⁵25. Barbosa TP, Costa FBP, Ramos ACV, Berra TZ, Arroyo LH, Alves YM, et al. Morbimortalidade por COVID-19 associada a condições crônicas, serviços de saúde e iniquidades: evidências de sindemia. Rev Panam Salud Publica. 2022; 46:e6. doi: 10.26633/RPSP.2022.6.
https://doi.org/10.26633/RPSP.2022.6... .

We found 97,950.8 DALYs with an annual rate of 24.5 per thousand inhabitants; and due to the recent and acute nature of the event, more than 97% of the burden (by age, sex, ethnicity, region, municipalities, among others), was contributed by the YLLD, which is explained because in the first two years of the pandemic, and prior to the introduction of vaccines ²⁶26. Reuters. COVID-19 Tracker Global. Latin America and the Caribbean. Reuters [Internet]. [Consultado 20 diciembre 2021]. Disponible en: https://graphics.reuters.com/world-coronavirus-tracker-and-maps/regions/latin-america-and-the-caribbean/.
https://graphics.reuters.com/world-coron... , the people at greatest risk of death (men and those over 70 years of age), were the most affected by this event ²⁷27. Char L. Risk factors for predicting mortality in elderly patients with COVID-19: A review of clinical data in China. Mech Ageing Dev. 2020;188: 111255. doi: 10.1016/j.mad.2020.111255.
https://doi.org/10.1016/j.mad.2020.11125... ^-2828. Cortis D. On Determining the Age Distribution of COVID-19 Pandemic: Front Public Health. 2020; 8:202. doi: 10.3389/fpubh.2020.00202.
https://doi.org/10.3389/fpubh.2020.00202... . This agrees with other studies, for example, one from the Netherlands reported that the DALY rate was 19.7 per 1000 inhabitants for age groups 85 years and older ²⁹29. McDonald SA, Lagerweij GR, de Boer P, de Melker HE, Pijnacker R, Mughini Gras L, et al. The estimated disease burden of acute COVID-19 in the Netherlands in 2020, in disability-adjusted life-years. Eur J Epidemiol.2022; 1-13. doi: 10.1007/s10654-022-00895-0.
https://doi.org/10.1007/s10654-022-00895... . Another study conducted in Ireland suggests that DALYs are significantly concentrated in populations aged 65 and over ³⁰30. Moran DP, Pires SM, Wyper G, Devleesschauwer B, Cuschieri S, Kabir Z. (2022). Estimating the Direct Disability-Adjusted Life Years Associated with SARS-CoV-2 (COVID-19) in the Republic of Ireland: The First Full Year. International journal of public health, 67, 1604699. doi: 10.3389/ijph.2022.1604699.
https://doi.org/10.3389/ijph.2022.160469... .

There are some similarities with a preliminary study on the burden of disease in the department of Córdoba (Colombia), which reports that 26.5 DALYs were lost per thousand inhabitants, and 99.9% of the burden of disease due to COVID-19 was due to YLLD; people who died from COVID-19 lost an average of 25 years of life, and 44% of the years of life lost corresponded to people under 60 years of age ³¹31. Lozano MA, De la Hoz F, Alvis R, Moyano NL, Salcedo F, Zakzuk J, et al. The COVID-19 disease burden in Córdoba, Colombia: results of disabilityadjusted life years. En: Memorias, XVII Encuentro Científico. Bogotá: Biomédica. 2021;41(Supl.3):36-14..

Similarly, a study in Germany reported that the percentage of DALYs in people under 70 years of age was 34.8% in men and 21.0% in women; people who died from COVID-19 lost an average of 9.6 years of life; those under 70 years of age who died lost an average of 25.2 years of life, more in men than in women ³²32. Rommel A, von der Lippe E, Plass D, Ziese T, Diercke M, Heiden MA, et al. The COVID-19 Disease Burden in Germany in 2020: Years of Life Lost to Death and Disease over the Course of the Pandemic. Dtsch Arztebl Int. 2020; 118(9):145-151. doi: 10.3238/arztebl.m2021.0147.
https://doi.org/10.3238/arztebl.m2021.01... . Also, a study in India found a rate loss of 10.2 DALYs per 1000 inhabitants and 14 million DALYs were reported due to the direct impact of COVID-19 in 2020 ³³33. Balbir BS, Brecht D, Mehar S, Mark L, Baljit S, Navneet K, et al. Disability-adjusted life years (DALYs) due to the direct health impact of COVID-19 in India, 2020. Sci Rep. 2022; 12: 2454. doi: 10.1038/s41598-022-06505-z.
https://doi.org/10.1038/s41598-022-06505... .

Gökler et al. ³⁴34. Gökler ME, Metintas S. Years of potential life lost and productivity costs due to COVID-19 in Turkey: one yearly evaluation. Public Health. 2022; 203:91-96. doi: 10.1016/j.puhe.2021.12.009.
https://doi.org/10.1016/j.puhe.2021.12.0... , found that there is a significant difference between the average age of death and the average age of years of life lost (YLL) in a period of 1 year of pandemic in Turkey, reporting a difference of six years in men (average age of death: 69.79 years; average age of YLL: 63.67 years) and women (72.68; 66.07, respectively), premature deaths are included in the age group of 50 to 69 years. Likewise, it will be necessary to identify what happens with symptomatic cases; for the time being, in Colombia and in various countries of the world, the occupation of intensive care units has decreased considerably ³⁵35. Ministerio de Salud y Protección Social. Colombia. Habitación de camas de UCI depende de situación epidemiológica. 01 de febrero de 2022. Boletín de Prensa No 74 de 2022. Disponible en: https://www.minsalud.gov.co/Paginas/Habilitacion-de-camas-UCI-depende-de-situacion-epidemiologica.aspx#:~:text=El%20momento%20de%20mayor%20presi%C3%B3n,de%2013.105%20camas%20UCI%20habilitadas.
https://www.minsalud.gov.co/Paginas/Habi... .

However, this event may become endemic due to vaccination ³⁶36. Idrovo AJ. Gestación y nacimiento de pandemia. Salud UIS.2021; 53: e:21014. doi: 10.18273/saluduis.53e:21014.
https://doi.org/10.18273/saluduis.53e:21... ; that is, that the number of cases reduces and/or stabilizes, where mortality decreases considerably, as has been observed in different scenarios worldwide ³⁷37. World Health Organization. Weekly epidemiological update on COVID-19 - 31 August 2022. Publications/Overview. Disponible en: https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19---31-august-2022.
https://www.who.int/publications/m/item/... and most cases are asymptomatic, mild, or moderate ³⁸38. Albavera-Hernández C, Rodríguez-Hernández JM, Piñeros-Garzón F, Montoya-Sanabria SM. The challenge of asymptomatic carriers of COVID-19: A rapid review of literature. Revista de Salud Pública. 2020. Rev Salud Pública. 22(6): 1-9. doi: 10.15446/rsap.v22n6.91181.
https://doi.org/10.15446/rsap.v22n6.9118... . Regarding the aforementioned, a study carried out among healthcare workers shows that, among those vaccinated, 52.6% presented mild COVID-19 symptoms and 10.3% moderate symptoms, without serious illness or hospitalization ³⁹39. Alshamrani MM, Farahat FM, El-Saed A, Alzunitan M, Alsaedi A, El Gammal A, et al. Post-vaccination SARS-CoV-2 infection among healthcare workers in tertiary care hospitals in Saudi Arabia: A case series, J Infect Public Health.2022; 15 (1): 10-12. doi: 10.1016/j.jiph.2021.11.015.
https://doi.org/10.1016/j.jiph.2021.11.0... .

In the future, mortality cases may occur mostly in the unvaccinated, as was the case at the end of 2021 in several European countries and in Asia ⁴⁰40. Abdul Taib NA, Baha Raja D, Teo A, Kamarulzaman A, William T, Hs AS, et al. Characterisation of COVID-19 deaths by vaccination types and status in Malaysia between February and September 2021. Lancet Reg Health West Pac. 2022; 18:100354. doi: 10.1016/j.lanwpc.2021.100354.
https://doi.org/10.1016/j.lanwpc.2021.10... , or may occur in those with known risk factors (advanced age, cardiovascular disease, metabolic and immune problems, among others) or unknown risk factors (immune or genetic) ⁴¹41. Aguilar-Jiménez W, Flórez-Álvarez L, Rincón DS, Marín-Palma D, Sánchez-Martínez A, et al. Immune characterization of a Colombian family cluster with SARS-CoV-2 infection. Biomed. 2021; 41(Suppl 2): 86-102. doi: 10.7705/biomedica.5976.
https://doi.org/10.7705/biomedica.5976... .

Our study has some limitations. We used the public database provided by the National Institute of Health which does not have clinical or sociodemographic variables different from those used in this research.The accuracy of the information provided by the source is variable and somewhat different from that presented by the official source of the National Statistics Department (this source is more accurate, but it may take 12 to 18 months to be completed due to the processes of analysis, review and source verification carried out by that entity). Overdispersion of the data forced the use of an alternative regression model to the one initially considered. Cases of persistent COVID-19 disease were not considered, a syndrome that has various forms of presentation, affecting both asymptomatic and hospitalized patients, with multiple symptoms, and requiring multidisciplinary management, which in many cases impacts quality of life. There may be an underestimation of the YDL morbidity component, due to possible underreporting and mild cases ⁴²42. López-Sampalo A, Bernal-López MR, Gómez-Huelgas R. Síndrome de COVID-19 persistente. Una revisión narrativa. Rev Clin Esp. 2022; 222(4): 241-250. doi: 10.1016/j.rce.2021.10.003.
https://doi.org/10.1016/j.rce.2021.10.00... ^,4343. Carod-Artal FJ, García-Moncó JC. Epidemiology, pathophysiology, and classification n of the neurological symptoms of post-COVID-19. Síndrome. Neurology Perspectives. 2021; 1: S5-S15. doi: 10.1016/j.neurop.2021.07.005.
https://doi.org/10.1016/j.neurop.2021.07... .

Despite the limitations, there are a number of advantages and potential benefits worth considering: this is one of the first studies at the regional level on the burden of disease in a given territory. Despite the potential source limitations, we used an official database to identify the magnitude and distribution of the problem, which is used by the national government. For the estimation of DALYs, we used microdata, i.e., contrary to what is done in other burden studies, which use aggregate information, in our study both YLLD and DALYs were estimated from the individual records of persons with morbidity or who died from this event, which is more precise. As an alternative, we used a negative binomial regression model to correct the overdispersion found in the data, which generates precise estimates of the risks adjusted for age, sex, region, and study period.

In conclusion, studies on the burden of disease due to COVID-19 during the pandemic, in regions and subregions, with the use of a standardized methodology such as that of Wyper et al²²22. Wyper GMA, Assunção RMA, Colzani E, Grant I, Haagsma JA, Lagerweij G, et al. Burden of Disease Methods: A Guide to Calculate COVID-19 Disability-Adjusted Life Years. Int J Public Health. 2021; 66:619011. doi: 10.3389/ijph.2021.619011.
https://doi.org/10.3389/ijph.2021.619011... allow the estimation of DALYs. This study generates estimates that show that the population in Nariño with high indexes of multidimensional poverty are the most affected by COVID-19, which suggests that state resources should be focused in an intersectoral way in order to mitigate the effects on these populations, by means of social protection strategies and programs, through the management of policies that protect their livelihoods and promote human capital.

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