Associated factors for COVID-19 mortality among children and adolescents in Rio de Janeiro state, 2020–2023

Abstract

Background

Children and adolescents with COVID-19 typically present milder symptoms of the infection, with fatal outcomes being rare. This study aimed to analyze the main associated factors for mortality in this population group.

Methods

A cross-sectional study was performed to analyze reported COVID-19 cases among individuals under 18 years old in Rio de Janeiro state, Brazil, from March 2021 to September 2023. Pearson’s chi-square test was used for categorical variables, and the Wilcoxon test for numerical variables. The significance level was set at 5%. Logistic regression analysis was performed to identify factors associated with COVID-19 mortality in individuals under 18.

Results

Infants under 1 year old had a higher mortality chance (OR = 4.70; 95% CI: 2.45–9.60) compared to adolescents aged 15–17 years. Non-white individuals had a lower mortality chance compared to white individuals (OR = 0.64; 95% CI: 0.41–0.99). The presence of fever (OR = 1.83; 95% CI: 1.17–2.89), dyspnea (OR = 11.83; 95% CI: 7.50-18.74), and oxygen saturation below 95% (OR = 11.97; 95% CI: 3.78–33.19) was associated with a higher mortality chance. Patients with heart disease (OR = 7.74; 95% CI: 3.89–14.58) and immunodeficiency/immunosuppression (OR = 17.16; 95% CI: 8.58–32.14) had a higher mortality chance. Infection during the predominance of variants B1_wild (OR = 3.44; CI 1.75–6.81), Gamma (OR = 3.93; CI 2.13–7.44), and Delta (OR = 2.27; CI 1.02–4.84) was associated with a higher mortality chance compared to the Omicron variant.

Conclusions

The main associated factors for death were fever, dyspnea, oxygen saturation below 95% on room air, age under one year, cardiac disease comorbidity, immunodeficiency, and infection during the predominance of B1_wild, Gamma, and Delta variants. Understanding the epidemiological profile and associated factors for mortality in this population is essential to inform effective prevention and control measures and guide optimal clinical management.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12887-026-07151-4.

Background

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that primarily affects the respiratory system in adults and children. Clinical manifestations of infection in children and adolescents are typically milder than in adults, who tend to develop more severe cases and have higher mortality rates [1–6].

Our understanding of how SARS-CoV-2 affects children and adolescents has evolved significantly as the pandemic has progressed. In this group, infection manifests heterogeneously, ranging from asymptomatic or mild cases (common cold symptoms) to lower respiratory tract infections, gastrointestinal involvement, and a wide range of other manifestations. Severe cases in children can manifest as severe acute respiratory syndrome and multisystem inflammatory syndrome in children (MIS-C) [7].

Global adult mortality rates increased sharply during the COVID-19 pandemic in 2020 and 2021, reversing the declining trends observed before the pandemic. Meanwhile, infant mortality rates decreased, albeit more slowly than in previous years [8].

In Brazil, data from the Mortality Information System (Sistema de Informação sobre Mortalidade - SIM), from 2020 to 2021, analyzed by Fiocruz’s Child Health Observatory, revealed that COVID-19 caused the death of two children under 5 years daily, with the highest mortality rates concentrated among children aged 29 days to 1 year [9].

According to Kitano et al. [10], Brazil has the highest number of pediatric COVID-19 deaths (under 19 years) worldwide among 138 countries. According to Sousa et al. [11], Rio de Janeiro ranked 19th among Brazilian states for mortality rates in individuals under 20 years of age and second within the Southeast region.

A U-shaped severity curve has been demonstrated in children diagnosed with COVID-19, with infants under 1 year of age and adolescents aged 10–14 years at higher risk of developing severe COVID-19 [7].

According to Oliveira et al. [12], COVID-19 mortality risk factors in Brazil included age (under 2 years and 12–19 years), Indigenous ethnicity, residence in the North and Northeast regions, and one or more comorbidities.

In Brazil, a country with vast territory and significant socioeconomic diversity, the relationship between COVID-19 mortality and sociodemographic variables is evident, as demonstrated by Sousa et al. [11]. Sousa et al. [11] investigated the relationship between non-communicable diseases and the risk of COVID-19 mortality in individuals under 20 years of age in Brazil. The mortality rate among those with chronic non-communicable diseases was 15.8%, compared to 5.6% in healthy children and adolescents. Except for asthma, all comorbidities increased mortality rates, particularly kidney disease (29.2%) and cardiovascular disease (26.3%).

In record time in the history of medicine, the first COVID-19 vaccine doses began to be administered worldwide in December 2020. Initially, only individuals aged 18 and older received the doses, followed by the inclusion of pediatric age groups, with approval in Brazil for children 6 months and older. In Brazil, COVID-19 vaccination was made available to adolescents aged 12 and older starting in June 2021. In Rio de Janeiro state, vaccination coverage rates were as follows: 0.96% for the third dose in children aged 6 months to 2 years; 0.11% for the third dose in children aged 3–4 years; 49.50% for the second dose in children aged 5–11 years; and 80.10% for the second dose in adolescents aged 12–17 years [13].

According to the 2022 demographic census, Rio de Janeiro is Brazil’s third most populous state, with its capital being the country’s second-largest city. Despite its relatively small territorial area, the state has a high population density of 366.97 inhabitants/km². Although it represents the country’s second-largest economy, significant income disparities exist between the state’s capital city, suburban areas, and rural regions.

The study aimed to characterize the epidemiological profile of the disease in children and adolescents under 18 years in Rio de Janeiro state from January 2020 to September 2023 and to identify associated factors for mortality in this age group, determining case fatality and mortality rates.

Methods

A cross-sectional study was conducted to assess the association between individual characteristics (age, sex, race/skin color), clinical variables (signs, symptoms, and comorbidities), and epidemiological factors (metropolitan region of residence, notification year, season, and dominant COVID-19 variant) with mortality among confirmed COVID-19 cases.

The study period (2020–2023) encompassed the pre-vaccination phase and the predominance of all SARS-CoV-2 variants that circulated in the state (Alpha, Zeta, Gamma, Delta, and Omicron), enabling assessment of the disease’s impact on this population.

COVID-19 cases in Brazil are mandatorily reported through two national notification systems: e-SUS Notifica (Ministry of Health Notification System) and SIVEP-Gripe (Influenza Epidemiological Surveillance Information System). e-SUS Notifica is a nationwide system for recording suspected and confirmed cases of COVID-19 and influenza-like illness, implemented during the pandemic to serve both public and private healthcare facilities (primary care units, medical offices, clinics, healthcare centers, and emergency units). SIVEP-Gripe records all patients admitted to public or private hospitals with influenza-like illness, dyspnea/respiratory distress, persistent chest pressure, oxygen saturation below 95% on room air, or cyanosis. All patients included in this system have documented demographic data, clinical characteristics, and place of residence. This study included patients under 18 years of age with a confirmed COVID-19 diagnosis who were reported in both the e-SUS Notifica and SIVEP-Gripe databases.

Confirmed cases of COVID-19 influenza-like illness were obtained from the Brazilian Ministry of Health’s e-SUS Notifica system. Confirmed cases of severe acute respiratory syndrome (SARS) due to COVID-19 were obtained from the Ministry of Health’s SIVEP-Gripe database. These two databases were linked using probabilistic record linkage. A consistency analysis was performed to remove duplicate entries from the resulting database. Within six months, duplicate records were defined as multiple notifications for the same case in the database.

The National Mortality Information System (Sistema de Informações sobre Mortalidade - SIM) is a nationwide epidemiological surveillance system that regularly collects mortality data. The Death Certificate (DC) is Brazil’s fundamental and essential document for mortality data collection. It is also Brazil’s death assessment reference system.

Subsequently, the database resulting from linking e-SUS Notifica with SIVEP-Gripe was again linked through probabilistic record linkage to the Ministry of Health’s SIM to identify COVID-19 deaths not recorded in either SIVEP-Gripe or e-SUS Notifica. Detailed information about record linkage is specified in the Supplementary Material.

After this final linkage, 511 all-cause deaths were identified in the SIM between January 1, 2020, and September 6, 2023, among individuals under 18 years of age in Rio de Janeiro State who had been reported as COVID-19 cases in SIVEP-Gripe and e-SUS Notifica surveillance systems. An individual analysis of these deaths was then conducted by examining the underlying cause, antecedent causes, and contributing causes documented in the Death Certificates.

Deaths were classified as follows:

1. COVID-19 deaths were those with ICD-10 codes B34.2 (“Coronavirus infection of the unspecified site”) + U07.1 (“COVID-19, virus identified through laboratory testing”) or B34.2 + U07.2 (“COVID-19, virus not identified, clinically-epidemiologically diagnosed, listed as the underlying cause of death. It is attributed to a clinical or epidemiological diagnosis of COVID-19 where laboratory confirmation is inconclusive or unavailable”); M303 (“mucocutaneous lymph node syndrome - Kawasaki”) + U10.9 (“COVID-19-associated multisystem inflammatory syndrome, unspecified”); B34.2 + U92.1 (“confirmed COVID-19 reinfection”) and B94.8 (“sequelae of other specified infectious and parasitic diseases”) + U09.9 (“post-COVID-19 condition, unspecified”), according to the Ministry of Health [14].

The World Health Organization (WHO) codes U07.1 and U07.2 serve as pandemic markers in Brazil and must always follow code B34.2 on the same line. On the Death Certificate, when a sequence of events mentions Multisystem Inflammatory Syndrome in Children (MIS-C), codes M30.3 + marker U10.9 must be entered on the same line. When COVID-19 reinfection is mentioned in the death certificate, codes B34.2 and marker U92.1 must be listed on the same line. Codes B94.8 and marker U09.9 must be listed on the same line of the medical certificate when documenting post-COVID-19 sequelae events.

• b)A suspected COVID-19 death was one where COVID-19-related codes were recorded in Part II of the Death Certificate as a significant contributing factor. In contrast, the underlying cause and antecedents were coded as unspecified respiratory or infectious diseases.
• c)A COVID-19-related death was one where the disease codes were recorded in Part II of the Death Certificate. However, a different underlying cause of death was specified, excluding unspecified respiratory or infectious diseases.
• d)COVID-19 was ruled out as the cause of death when COVID-19 codes were not recorded on the death certificate as the underlying cause, its antecedents (Part I), or as a significant contributing factor (Part II).

Of the 511 deaths identified through linkage, 282 were excluded due to other causes; COVID-19 caused 213; COVID-19 likely caused six deaths; and 10 deaths occurred during active COVID-19 infection. This study considered COVID-19-confirmed deaths (n = 213) as the outcome.

Age was stratified into the following groups: under 1 year, 1–4 years, 5–9 years, 10–14 years, and 15–17 years. Sex was classified as female, male, or not reported. Race/ethnicity was categorized as White, Black, Brown, Asian, Indigenous, or not reported. The race/skin color variable was also dichotomized into white and non-white.

Clinical variables were categorized as present, absent, or unreported, including fever, cough, sore throat, dyspnea, oxygen saturation below 95%, ageusia, anosmia, and diarrhea. The presence of a comorbidity variable, which included respiratory disease, kidney disease, heart disease, diabetes mellitus, and immunodeficiency/immunosuppression, was classified as yes, no, or not reported. Comorbidity was analyzed as a dichotomous variable (present/absent) and a three-level categorical variable (none, one, or two or more pre-existing medical conditions).

The region of residence was categorized into the following areas: Rio de Janeiro municipality, Ilha Grande Bay, Coastal Lowlands, South-Central, Middle Paraíba Valley, Metropolitan I (excluding Rio de Janeiro municipality), Metropolitan II, Northwest, North, and Mountain regions. The Rio de Janeiro municipality was separated from Metropolitan Region I due to being the most populous municipality in the area. The case notification year variable was categorized as 2020, 2021, 2022, or 2023. The season variable was categorized into four categories: summer, fall, winter, and spring. The predominant SARS-CoV-2 variant during the study period was classified as B.1 (wild type), Zeta, Gamma, Delta, and Omicron. Each dominant variant’s start and end dates were determined according to the Rio de Janeiro State Health Department bulletin by state region, thus assuming that all cases occurring within each dominant variant’s period were attributed to that variant [15].

Statistical analyses and database linkage were performed using R x64 4.0.0 through RStudio Desktop.

Bivariate descriptive analyses were conducted using contingency tables for all categorical predictor variables. Associations were assessed with Pearson’s chi-square test, and the significance level was set at 5%. Measures of association were expressed as odds ratios (ORs) with corresponding 95% confidence intervals (CIs).

Logistic regression analysis was performed to identify factors associated with COVID-19 mortality in individuals under 18 years of age. Furthermore, model goodness-of-fit was assessed using sensitivity, specificity, the area under the receiver operating characteristic curve (AUROC), and Matthews correlation coefficient (MCC).

The mortality rate was defined as the number of deaths from confirmed COVID-19 cases divided by the population, as per the 2022 Brazilian Institute of Geography and Statistics (IBGE) demographic census. The case fatality rate was defined as the number of deaths from confirmed COVID-19 cases divided by the total number of confirmed cases. The 2022 census population was used for the entire study period, as year-to-year variation in population size was minimal and did not materially affect the results.

Results

From January 2020 to September 2023, a total of 241,533 COVID-19 cases and 213 deaths were reported among children and adolescents under 18 years of age in Rio de Janeiro state. The case fatality rate was 0.09%, and the mortality rate was 5.81 per 100,000 children and adolescents under 18 years of age.

The distribution of cases over the years showed that 29,380 (12.2%) cases were registered in 2020, 75,187 (31.1%) in 2021, 128,025 (53%) in 2022, and 8,941 (3.7%) cases through September 2023.

Table 1 presents the distribution of cases by clinical, epidemiological, and demographic variables. The age distribution revealed COVID-19 cases as follows: 21,738 (9.0%) in infants under 1 year; 37,352 (15.5%) in children aged 1–4 years; 55,989 (23.2%) in those aged 5–9 years; 69,356 (28.7%) in those aged 10–14 years; and 57,098 (23.6%) in adolescents aged 15–18 years.

Table 1.

Distribution of cases according to clinical, epidemiological, and demographic variables

Characteristics	Complete casesN = 238,915	Missing casesN = 2,618	TotalN = 241,533
Anosmia
No	238,129 (99.7%)	2,614 (99.8%)	240,743 (99.7%)
Yes	786 (0.3%)	4 (0.2%)	790 (0.3%)
Ageusia
No	238,627 (99.9%)	2,618 (100.0%)	241,245 (99,9%)
Yes	288 (0.1%)	0 (0.0%)	288 (0.1%)
Diarrhea
No	232,320 (97.2%)	2,615 (99.9%)	234,935 (97.3%)
Yes	6,595 (2.8%)	3 (0.1%)	6,598 (2.7%)
Oxygen Saturation < 95%
No	238,812 (100.0%)	2,617 (100.0%)	241,429 (100.0%)
Yes	103 (0.0%)	1 (0.0%)	104 (0.0%)
Number of comorbidities
0	231,870 (97.1%)	2,312 (88.3%)	234,182 (97.0%)
1	6,739 (2.8%)	278 (10.6%)	7,017 (2.9%)
2 or more	306 (0.1%)	28 (1.1%)	334 (0.14%)
Age distribution
15-17	56,824 (23.8%)	274 (10.5%)	57.098 (23.6%)
10-14	69,002 (28.9%)	354 (13.5%)	69.356 (28.7%)
5-9	55,573 (23.3%)	416 (15.9%)	55.989 (23.2%)
1-4	36,587 (15.3%)	765 (29.2%)	37.352 (15.5%)
< 1	20,929 (8.8%)	809 (30.9%)	21.738 (9.0%)
Sex
F	125,514 (52.5%)	1,208 (46.2%)	126.722 (52.5%)
M	113,401 (47.5%)	1,409 (53.8%)	114.810 (47.5%)
Missing	-	-	1 (0.0%)
Race/skin color
White	65,907 (27.6%)	625 (23.9%)	66,532 (27.5%)
Black	10,949 (4.6%)	194 (7.4%)	11,143 (4.6%)
Asian	2,958 (1.2%)	9 (0.3%)	2,967 (1.2%)
Brown	83,152 (34.8%)	861 (32.9%)	84,013 (34.8%)
Indigenous	235 (0.1%)	3 (0.1%)	238 (0.1%)
Not information	75,714 (31.7%)	926 (35.4%)	76,640 (31.7)
Metropolitan region of residency
Center-South	7,775 (3.3%)	19 (0.7%)	7,794 (3.2%)
Rio de Janeiro municipality	116,019 (48.6%)	1,251 (47.8%)	117,270 (48.6%)
Ilha Grande Bay	3,546 (1.5%)	49 (1.9%)	3,595 (1.5%)
Coastal Lowlands	9,609 (4.0%)	125 (4.8%)	9.734 (4,0%)
Médio Paraíba	19,198 (8.0%)	110 (4.2%)	19,308 (8.0%)
Metropolitan I	20,335 (8.5%)	470 (18.0%)	20,805 (8.6%)
Metropolitan II	20,794 (8.7%)	302 (11.5%)	21,096 (8.7%)
Northwest	9,340 (3.9%)	29 (1.1%)	9,369 (3.9%)
North	11,624 (4.9%)	138 (5.3%)	11,762 (4.9%)
Mountain region	20,675 (8.7%)	125 (4.8%)	20.800 (8,6%)
Fever
No	136,273 (57.0%)	477 (22.4%)	136,750 (56.6%)
Yes	102,642 (43.0%)	1,652 (77.6%)	104,294 (43.2%)
Missing	-	-	489 (0.2%)
Cough
No	125,763 (52.6%)	495 (24.0%)	126,258 (52.3%)
Yes	113,152 (47.4%)	1,571 (76.0%)	114,723 (47.5%)
Missing	-	-	552 (0.2%)
Sore throat
No	177,631 (74.3%)	1,164 (81.1%)	178,795 (74.0%)
Yes	61,284 (25.7%)	271 (18.9%)	61,555 (25.5%)
Missing	-	-	1,183 (0.5%)
Dyspnea
No	224,852 (94.1%)	674 (35.0%)	225,526 (93.4%)
Yes	14,063 (5.9%)	1,254 (65.0%)	15,317 (6.3%)
Missing	-	-	690 (0.3%)
Respiratory disease
No	234,005 (97.9%)	2,422 (92.9%)	236,427 (97.9%)
Yes	4,910 (2.1%)	184 (7.1%)	5,094 (2.1%)
Missing	-	-	12 (0.0%)
Kidney disease
No	238,810 (100.0%)	19 (61.3%)	238,829 (98.9%)
Yes	105 (0.0%)	12 (38.7%)	117 (0.0%)
Missing	-	-	2,587 (1.1%)
Heart disease
No	237,859 (99.6%)	21 (27.3%)	237,880 (98.5%)
Yes	1,056 (0.4%)	56 (72.7%)	1,112 (0.5%)
Missing	-	-	2,541 (1.1%)
Diabetes mellitus
No	238,324 (99.8%)	20 (35.7%)	238,344 (98.7%)
Yes	591 (0.2%)	36 (64.3%)	627 (0.3%)
Missing			2,562 (1.1%)
Immunodeficiency/immunosuppression
No	238,211 (99.7%)	17 (25.8%)	238,228 (98.6%)
Yes	704 (0.3%)	49 (74.2%)	753 (0.3%)
Missing			2,552 (1.1%)
COVID-19 variants
Omicron	137,285 (57.5%)	57 (2.2%)	136,342 (56.9%)
B1_wild	20,456 (8.6%)	842 (32.2%)	21,298 (8.8%)
Zeta	18,016 (7.5%)	443 (16.9%)	18,459 (7.6%)
Gamma	32,931 (13.8%)	763 (29.1%)	33,694 (14.0%)
Delta	30,227 (12.7%)	513 (19.6%)	30,740 (12.7%)
Skin color
White	65,907 (27.6%)	625 (23.9%)	66,532 (27.5%)
Non-White	97,294 (40.7%)	1,067 (40.8%)	98,361 (40.7%)
Not information	75,714 (31.7%)	926 (35.4%)	76,640 (31.7%)
Year of registered cases
2020	28,298 (11.8%)	1,082 (41.3%)	29,380 (12.2%)
2021	73,692 (30.8%)	1,495 (57.1%)	75,187 (31.1%)
2022	127,984 (53.6%)	41 (1.6%)	128,025 (53.0%)
2023	8,941 (3.7%)	0 (0.0%)	8,941 (3.7%)
Seasonal distribution
Summer	100,729 (42.2%)	488 (18.6%)	101,217 (41.9%)
Autumn	49,843 (20.9%)	836 (31.9%)	50,679 (21.0%)
Winter	54,002 (22.6%)	749 (28.6%)	54,751 (22.7%)
Spring	34,341 (14.4%)	545 (20.8%)	34,886 (14,4%)

The sex distribution revealed that 114,810 (47.5%) cases occurred in males and 126,722 (52.5%) in females. Regarding race/skin color, 66,532 (40.3%) cases occurred in White individuals, 11,143 (6.8%) in Black individuals, 2,967 (1.8%) in Asian individuals, 84,013 (51.0%) in Brown individuals, and 238 (0.1%) in Indigenous individuals, with 76,640 cases missing this information. According to the 2022 IBGE Census, the race/skin color distribution among individuals under 18 years of age in the state of Rio de Janeiro, Brazil, was 39.8% White, 14.0% Black, 0.1% Asian, 46.1% Brown, and 0.1% Indigenous, with missing data for 77 individuals. Comparison with the distribution observed among COVID-19 cases revealed differences between the general and case populations. Given these differences and the high proportion of missing data for this variable in the study database, race/skin color was categorized as White and non-White for the analyses. The distribution by skin color showed that 66,532 (40.3%) of cases occurred among white children and adolescents, while 98,361 (59.7%) occurred among non-white individuals (Table 1).

Cough was reported in 114.723 (47.6%) cases, followed by fever in 104,294 (43.3%), sore throat in 61,555 (25.6%), dyspnea in 15,317 (6.4%), diarrhea in 6,598 (2.7%), anosmia in 790 (0.3%), ageusia in 288 (0.1%), and oxygen saturation below 95% in 104 (0.04%) cases (Table 1).

Regarding comorbidities, the respiratory disease was present in 5,094 (2.1%) cases, kidney disease in 117 (0.05%), heart disease in 1,112 (0.5%), diabetes mellitus in 627 (0.3%), and immunodeficiency/immunosuppression in 753 (0.3%) cases. A total of 234,182 (97.0%) children and adolescents had no comorbidities, while 7,017 (2.9%) had one comorbidity, and 334 (0.14%) had two or more comorbidities (Table 1).

The distribution by metropolitan region showed that 117,270 (48.6%) cases lived in Rio de Janeiro municipality, 3,595 (1.5%) in Ilha Grande Bay, 9,734 (4.0%) in the Coastal Lowlands, 7,794 (3.2%) in Center-South, 19,308 (8.0%) in Médio Paraíba, 20,805 (8.6%) in Metropolitan Region I (excluding Rio de Janeiro municipality), 21,096 (8.7%) in Metropolitan Region II, 9,369 (3.9%) in the Northwest region, 11,762 (4.9%) in the North region, and 20,800 (8.6%) in the Mountain region (Table 1).

The number of reported cases per year showed that 29,380 (12.2%) occurred in 2020, 75,187 (31.1%) in 2021, 128,025 (53%) in 2022, and 8,941 (3.7%) in 2023 (through September). The seasonal distribution of cases revealed that 101,217 (41.9%) occurred in summer, 50,679 (21.0%) in autumn, 54,751 (22.7%) in winter, and 34,866 (14.4%) in spring (Table 1).

The distribution of cases according to the predominant COVID-19 variant showed that 137,342 (56.9%) cases occurred during Omicron’s predominance, 21,298 (8.8%) during B1_wild’s predominance, 18,459 (7.6%) during Zeta’s predominance, 33,694 (14.0%) during Gamma’s predominance, and 30,740 (12.7%) during Delta’s predominance (Table 1).

The case fatality rate was 0.5% in infants under 1 year of age, 0.05% in children aged 1–4 years, 0.03% in those aged 5–9 years, 0.05% in those aged 10–14 years, and 0.06% in adolescents aged 15–17 years (Fig. 1). When the case fatality rate in infants under 1 year of age was disaggregated, we found that the rate was 0.24 for those aged 0 to 27 days (neonatal period) and 0.69 for those aged 28 to 364 days (post-neonatal period).

Fig. 1.

Case fatality rate distribution by age group

Age-specific mortality rates were 69.89 per 100,000 infants under 1 year; 2.63 per 100,000 children aged 1–4 years; 1.87 per 100,000 children aged 5–9 years; 3.52 per 100,000 children and adolescents aged 10–14 years; and 4.07 per 100,000 adolescents aged 15–17 years.

The distribution of cases fatality rate by COVID-19 showed that B1_wild variant was the most lethal (34.27 by 10,000), following Gamma variant with 14.91 by 10,000 (Fig. 2).

Fig. 2.

Case fatality rate distribution by variant

Table 2 shows the association between independent variables and death from COVID-19. Children under 1 year of age had a higher mortality chance compared to adolescents aged 15–17 years (OR = 8.63; 95% CI: 5.92–12.9). Black children and adolescents with COVID-19 had a higher mortality chance compared to White individuals (OR 1.68; 95% CI 1.08–2.54), while Brown individuals had a lower mortality chance compared to White individuals (OR 0.59; 95% CI 0.43–0.79). Oxygen saturation below 95% (OR = 84.5; CI 35.2–171), dyspnea (OR = 25.8; CI 18.7–35.8), and fever (OR = 2.56; CI 1.87–3.53) was associated with higher mortality chance, while sore throat (OR = 0.16; CI 0.07–0.32) and diarrhea (OR = 0.17; CI 0.01–0.74) were associated with a lower mortality chance. Regarding comorbidities, kidney disease (OR = 117; CI 40.7–266), immunodeficiency/immunosuppression (OR = 82.3; CI 48.8–132), heart disease (OR = 73.9; CI 46.4–114), diabetes mellitus (OR = 47.3; CI 23.8–85.0), and respiratory disease (OR = 3.86; CI 2.22–6.22) were associated with higher COVID-19 mortality. Having one comorbidity increases the mortality chance (OR = 8.22; 95% CI: 5.68–11.6) while having two or more comorbidities substantially increases the mortality chance (OR = 96.2; 95% CI: 57.9–152). The mortality chance was higher among children and adolescents living in the Northwest metropolitan region (OR = 4.41; 95% CI 1.18–28.5) and metropolitan region I (excluding Rio de Janeiro municipality) (OR = 7.69; 95% CI 2.37–47.2) compared to those living in the Center-South region.

Table 2.

Unadjusted logistic regression results between independent variables and death from COVID-19

Variables	N	OR	95% IC	p
Anosmia	238,915
No		—	—
Yes		0.00	0.00–12.9	0.976
Ageusia	238,915
No		—	—
Yes		0.00	0.00–36.1	0.978
Diarrhea	238,915
No		—	—
Yes		0.39	0.02–1.76	0.351
Oxygen saturation < 95%	238,915
No		—	—
Yes		207.0	85.3–430	< 0.001
Age group	238,915
15–17		—	—
10–14		1.03	0.48–2.24	0.940
5–9		0.77	0.31–1.81	0.547
1–4		1.04	0.41–2.50	0.939
< 1		10.70	5.85–21.0	< 0.001
Sex	238,915
F		—	—
M		1.08	0.72–1.64	0.704
Race/skin color	238,915
White		—	—
Black		2.01	1.08–3.52	0.019
Asian		0.00	0.00–0.30	0.968
Brown		0.46	0.28–0.74	0.002
Indigenous		0.00	0.00 – Inf	0.991
Not information		0.10	0.03–0.22	< 0.001
Metropolitan region of residency	238,915
Center-South		—	—
Rio de Janeiro municipality		1.88	0.40–33.5	0.536
Ilha Grande Bay		2.19	0.09–55.5	0.579
Coastal Lowlands		4.86	0.83–91.7	0.143
Médio Paraíba		3.65	0.69–67.2	0.220
Metropolitan region I		6.89	1.42–124	0.060
Metropolitan region II		2.24	0.38–42.4	0.454
Northwest		6.66	1.22–124	0.074
North		2.68	0.40–52.4	0.379
Mountain region		3.76	0.72–69.0	0.206
Fever	238,915
No		—	—
Yes		1.94	1.28–2.97	0.002
Cough	238,915
No		—	—
Yes		1.00	0.66–1.50	0.984
Sore throat	238,915
No		—	—
Yes		0.07	0.01–0.21	< 0.001
Dyspneia	238,915
No		—	—
Yes		20.5	13.5–31.1	< 0.001
Respiratory disease	238,915
No		—	—
Yes		4.60	2.05–8.92	< 0.001
Kidney disease	238,915
No		—	—
Yes		52.1	8.51–168	< 0.001
Heart disease	238,915
No		—	—
Yes		52.6	29.9–87.1	< 0.001
Diabetes mellitus	238,915
No		—	—
Yes		18.7	5.69–44.9	< 0.001
Immunodeficiency/immunosuppression	238,915
No		—	—
Yes		62.7	33.9–108	< 0.001
Number of comorbidities	238,915
None		—	—
One		11.9	6.98–19.4	< 0.001
Two or more		177	92.2–317	< 0.001
Seasonal distribution	238,915
Summer		—	—
Autumn		4.14	2.49–7.11	< 0.001
Winter		1.78	0.96–3.29	0.066
Spring		0.98	0.39–2.19	0.959
Number of reported cases per year	238,915
2023		—	—
2022		1.12	0.23–20.2	0.914
2021		5.58	1.22–98.9	0.089
2020		8.85	1.89–158	0.032
Skin color	238,915
White		—	—
Non-White		0.62	0.40–0.94	0.025
Not available		0.10	0.03–0.22	< 0.001

Having contracted COVID-19 in 2021 (OR = 12.9; CI 2.88–226) and 2022 (OR = 25.9; CI 5.78–457), compared to 2023 (through September), was associated with a higher mortality chance, as did infection during autumn (OR = 4.97; CI 3.43–7.37), winter (OR = 2.70; CI 1.78–4.13), and spring (OR = 2.35; CI 1.44–3.80), compared to summer. Infection during the predominance of variants B1_wild (OR = 23.6; CI 14.7–39.8), Zeta (OR = 10.1; CI 5.66–18.2), Gamma (OR = 11.6; CI 7.12–19.8), and Delta (OR = 8.05; CI 4.71–14.2) was associated with a higher mortality chance compared to cases during Omicron predominance.

Table 3 shows the logistic regression results for the association between independent variables and death from COVID-19. Children under 1 year of age had a higher mortality chance (OR = 4.70; 95% CI: 2.45–9.60) compared to those aged 15–17 years. Non-white children and adolescents had a lower mortality chance compared to white children (OR = 0.64; 95% CI: 0.41–0.99). Regarding symptoms, fever (OR = 1.83; 95% CI: 1.17–2.89), dyspnea (OR = 11.83; 95% CI: 7.50-18.74), and oxygen saturation below 95% (OR = 11.97; 95% CI: 3.78–33.19) were associated with a higher mortality chance. Children and adolescents presenting with a sore throat had a lower mortality chance (OR = 0.06; 95% CI: 0.01–0.19). Children and adolescents with heart disease (OR = 7.74; 95% CI: 3.89–14.58) and immunodeficiency/immunosuppression (OR = 17.16; 95% CI: 8.58–32.14) had a higher mortality chance. Infection during the predominance of B1_wild (OR = 3.44; CI 1.75–6.81), Gamma (OR = 3.93; CI 2.13–7.44), and Delta (OR = 2.27; CI 1.02–4.84) variants was associated with a higher mortality chance compared to the Omicron variant.

Table 3.

Adjusted Logistic regression results between significative variables and death from COVID-19

Variables	N	OR	95% IC	p	VIF*
Oxygen Saturation < 95%					1.1
No	238,812	—	—
Yes	103	7.58	2.40–20.92	< 0.001
Age group					1.2
15–17	56,824	—	—
10–14	69,002	1.13	0.53–2.48	0.749
5–9	55,573	0.82	0.33–1.94	0.648
1–4	36,587	0.75	0.29–1.84	0.533
< 1	20,929	5.38	2.85–10.90	< 0.001
Fever					1.0
No	136,273	—	—
Yes	102,642	1.69	1.09–2.64	0.019
Sore throat					1.0
No	177,631	—	—
Yes	61,284	0.06	0.01–0.18	< 0.001
Dyspnea					1.1
No	224,852	—	—
Yes	14,063	12.10	7.72–19.01	< 0.001
Heart disease					3.0
No	237,859	—	—
Yes	1,056	2.59	0.92–7.37	0.071
Immunodeficiency/immunossupression					2.1
No	238,211	—	—
Yes	704	5.89	2.32–15.26	< 0.001
Number of comorbidities					4.2
None	231,870	—	—
One	6,739	2.75	1.16–5.77	0.013
Two or more	306	7.49	1.97–25.50	0.002
Skin color					1.0
White	65,907	—	—
Nom-White	97,294	0.64	0.41–1.00	0.047
Not available	75,714	0.09	0.03–0.22	< 0.001
Model AUC (95% CI)		0.93	0.90–0.96

* VIF Variance Inflaction Factor

The model goodness-of-fit was 0.885 (CI95% 0.883, 0.886) for sensitivity, 0.835 (CI95% 0.743, 0.905) for specificity, the area under the receiver operating characteristic curve (AUROC), which was 0.930 (95% CI: 0.904–0.956), and 0.040 for MCC.

Discussion

The mortality burden of COVID-19 in children and adolescents was substantially lower than the overall mortality rate of 450.42 per 100,000 inhabitants in Rio de Janeiro state during the same period. However, this burden was not negligible. In our study, the mortality rate was 5.81 per 100,000 among individuals under 18 years of age. This figure is low in absolute terms, but it is still relevant from a public health perspective. Notably, deaths were concentrated in infants and in children and adolescents with underlying comorbidities. The lower mortality burden in the pediatric population should not obscure the importance of preventive strategies and timely identification of severe cases (16). COVID-19 case fatality rates (CFRs) among individuals under 18 years of age remain relatively low compared to adults, regardless of the predominant variant, with estimates ranging from 0 to 0.69% [16]. Meta-analyses and international studies confirm these findings, with Wang et al. reporting a CFR of 0.28% [17], while UNICEF estimates that only 0.4% of 4.4 million global COVID-19 deaths occurred in those under 20 years [18]. However, higher in-hospital fatality rates have been observed in Brazil, reaching 8.2% in 2020 [19] and 9.5% in early 2020 [20], contrasting with lower rates in Europe [6, 21–23] and other high-income countries. Kitano et al. [10] demonstrated markedly higher pediatric CFRs in low- and middle-income countries than in high-income countries. In Rio de Janeiro, we found a community CFR of 0.09%, higher than rates in Portugal and Germany [22, 23], but consistent with low- and middle-income contexts.

Infants under one year consistently show the highest mortality risk [1, 10, 20, 24–28]. Our data revealed a J-shaped CFR distribution, with the highest risk in infants, aligning with global evidence [12, 26, 28, 29]. Although disparities by race/skin color have been reported [12, 29], these were not statistically significant in multivariate analysis. Findings related to race/skin color should be interpreted with caution, as the high proportion of missing data for this variable may have introduced bias and limited the accurate characterization of its true distribution. Mortality was concentrated in 2020–2021, during circulation of B1_wild, Gamma, and Delta variants, with a decline following Omicron predominance, consistent with reports of reduced severity [30–35].

Comorbidities strongly increased the risk of death, particularly immunodeficiency and cardiac disease, echoing findings from meta-analyses and cohort studies [36–44]. Obesity and type 2 diabetes have also emerged as important risk factors [37–39]. Respiratory compromise at presentation—oxygen saturation < 95% and dyspnea—was associated with mortality [6, 45, 46], while sore throat appeared protective, possibly reflecting reporting bias.

This study has limitations inherent to secondary databases, including underreporting, missing data, misclassification, and reliance on caregiver-reported information. Selection bias is possible due to asymptomatic or untested cases [11]. Information and coding errors may have affected accuracy, and some deaths may have been misclassified. Socioeconomic variables were unavailable, and exposure data could not be assessed. Nonetheless, statewide coverage strengthens representativeness for the region.

Conclusions

COVID-19 in children and adolescents in Rio de Janeiro state from 2020 to September 2023 emerged as a significant infection in this population group. Although mortality rates were low, they were more substantial among children under one year of age and higher than in other countries or regions.

The main associated factors for death were fever, dyspnea, oxygen saturation below 95% on room air, age under one year, cardiac disease as a comorbidity, immunodeficiency, and infection during the predominance of B1_wild, Gamma, and Delta variants.

Understanding the epidemiological profile and associated factors for mortality in this population is essential to inform effective prevention and control measures and guide optimal clinical management.

The impact of COVID-19 on child and adolescent mortality was most significant during the pandemic’s first two years, and continued assessment of the disease’s impact is necessary, particularly regarding immunization effects and specific characteristics of future variants.

Abbreviations

e-SUS Notifica

Online tool for recording notification of suspected and confirmed cases of mild influenza-like illness due to SARS-CoV-2

SIVEP-Gripe

Sistema de Informação da Vigilância Epidemiológica da Gripe (Influenza Epidemiological Surveillance Information System)

COVID-19

Coronavirus disease - an infectious disease caused by the SARS-CoV-2 virus

OR

Odds Ratio

CI

Confidence interval

MIS-C

Multisystem Inflammatory Syndrome in Children

SIM

Mortality Information System (Sistema de Informação sobre Mortalidade)

SARS

Severe Acute Respiratory Syndrome

MCC

Matthews correlation coefficient

IBGE

Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics)

UNICEF

United Nations Children’s Fund

CEP

Comitê de Ética e Pesquisa (Research Ethics Committee)

Authors’ contributions

Esteves, L. designed the study. Esteves, L. Raymundo, CE. Medronho, RA. collected and analyzed the data. Esteves, L. Raymundo, CE. Medronho, RA. interpreted the results. Esteves, L. wrote the manuscript. Medronho RA. contributed to the refinement of the manuscript. The final manuscript has been read and approved by the authors.

Funding

This work was supported by FAPERJ (Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro).

Data availability

All data analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

Declarations

Ethics approval and consent to participate

This study complies with Resolution 466/2012, the Declaration of Helsinki and all its amendments, and Good Clinical Practice (Document of the Americas). The study was submitted to the Research Ethics Committee (Comitê de Ética e Pesquisa - CEP) of the Institute of Collective Health Studies at the Federal University of Rio de Janeiro (Certificate of Submission for Ethical Evaluation (Certificado de Apresentação de Apreciação Ética - CAAE: 66422623.5.0000.5286). The study was approved by the CEP (approval number 5,883,512).

The research databases came from secondary databases, totaling 241,533 COVID-19 cases. In this situation, there is no need to request that individuals younger than the age of 16 consent to participate with their parents or legal guardians. Therefore, we detail the procedures used in the research to ensure the confidentiality of all cases reported to the databases.

Data confidentiality: All patient identification data were deleted after the databases were linked. The database obtained was stored on a computer only accessed by the principal investigator and his team through a specific and individual password. Anonymity was guaranteed in all the provisional and definitive reports that were prepared.

Data use commitment term: The study used secondary databases, ensuring the confidentiality of information by removing personal identifiers and compliance with ethical guidelines for the data protection of participants. The data collected came from the Rio de Janeiro State Department of Health database, and a confidentiality statement of the project's principal investigator was used.

Competing interests

The authors declare no competing interests.