Factors Associated with the Clinical Outcome of Severe Acute Respiratory Syndrome Due to COVID-19 in Brazil, 2024

Abstract

Severe acute respiratory syndrome (SARS), caused by the COVID-19 virus, continues to pose a significant public health challenge in Brazil, particularly in 2024, with high mortality rates among vulnerable groups. This study aimed to describe the sociodemographic, clinical and vaccination profiles of SARS cases due to COVID-19 in Brazil in 2024, as well as analysing factors associated with clinical outcomes such as death, admission to the intensive care unit (ICU) and the need for ventilatory support. A total of 30,529 reported cases were analysed. On average, the interval between the last vaccine dose and symptom onset was 30.31 months (SD = 6.77), while the interval between symptom onset and clinical outcome was 13.26 days (SD = 16.55), revealing significant variability. The results showed higher mortality rates among men (23.7%) than women (19.1%) (p < 0.0001). Mortality increased progressively with age, reaching 24.4% in individuals aged 60 years or older, whereas rates were below 2% in children under 10 years of age. The highest proportions of deaths were observed regionally in the Northeast (26.8%) and North (22.6%), in contrast to the Midwest (17.7%) (p < 0.0001). Men were also more likely to require ICU admission (38.1% vs. 33.6%) and ventilation (62.9% vs. 60.5%). A time interval of over 24 months since the last vaccine dose was associated with higher mortality (21.9% vs. 20.6%; p = 0.0005). These results highlight the importance of ongoing surveillance and updating the vaccination schedule, particularly for more vulnerable populations.

1. Introduction

Severe acute respiratory syndrome (SARS), caused by the COVID-19 virus, remains a significant public health challenge in Brazil. Since the beginning of the pandemic, high mortality rates have been observed, particularly among the elderly and individuals with comorbidities. These factors are well-documented risk factors for adverse disease progression [1]. In Brazil, this vulnerability is exacerbated by regional and socioeconomic inequalities, which affect access to healthcare and treatment conditions [2,3].

Vaccination against COVID-19 is the main tool for reducing the severity and mortality associated with infection. However, recent studies indicate that vaccine-induced protection diminishes over time, particularly in the face of more transmissible and partially evasive variants, such as those of the Omicron lineage [4]. Therefore, booster doses are recommended to maintain efficacy, particularly for vulnerable groups such as the elderly and immunocompromised individuals [5].

Despite Brazil’s extensive national immunization program, vaccination coverage remains uneven across regions and social strata, mirroring long-standing structural inequalities [6]. Populations in areas with restricted healthcare access and higher social vulnerability continue to experience increased incidence of severe cases and mortality, underscoring the urgent need for context-sensitive public health responses [2,7]. Moreover, the heterogeneous clinical progression of COVID-19 reflects not only biological determinants such as age and comorbidities but also social and regional inequities that influence local healthcare system capacities [3,8].

While previous studies have explored associations between demographic, clinical, and vaccine-related factors and COVID-19 outcomes in Brazil, most analyses focus on the early pandemic waves or specific subpopulations. There remains a lack of nationwide studies integrating post-vaccination data with recent epidemiological dynamics to assess how sociodemographic, regional, and immunization-related factors jointly shape disease progression in the current phase of the pandemic.

Therefore, this study aims to address this knowledge gap by analyzing the factors associated with clinical progression, intensive care unit (ICU) admission, and ventilatory support among patients with severe acute respiratory syndrome (SARS) due to COVID-19 in Brazil during 2024. By integrating clinical, vaccination, and sociodemographic data, this work contributes novel insights into the evolving epidemiology of COVID-19 in a post-vaccine context and supports evidence-based strategies to reduce health inequities.

2. Materials and Methods

The study is quantitative, descriptive and cross-sectional. Data were collected from the openDataSUS Severe Acute Respiratory Syndrome (SARS) database in Brazil. Cases of SARS due to COVID-19 that were confirmed by clinical, epidemiological, or laboratory testing in 2024 were selected (data extracted on 24 March 2025).

The Ministry of Health defines Severe Acute Respiratory Syndrome (SARS) as the occurrence of acute respiratory symptoms characterised by fever accompanied by cough or sore throat, and presenting with dyspnoea, oxygen saturation below 95% in ambient air, or signs of severity such as respiratory distress and hypotension. In children, the following additional signs are considered: nasal flaring, cyanosis, intercostal retractions, dehydration and loss of appetite [9].

In Brazil, the SARS Notification Form is used for registering and epidemiologically monitoring cases and deaths from SARS, regardless of whether the patient is hospitalised. Therefore, all patients presenting with compatible clinical symptoms are reported, including those confirmed by laboratory tests or clinical-epidemiological criteria for influenza, COVID-19, or other respiratory viruses, as well as cases of unspecified aetiology [9].

The recorded information includes patient identification data such as full name, SUS card number, gender, age, date of birth, race/colour, education level, occupation and municipality of residence [9].

Clinical and epidemiological variables are also included, such as the date of symptom onset, the presence of main signs and symptoms (fever, cough, dyspnea, respiratory distress, reduced oxygen saturation, chest pain, diarrhea, vomiting, among others), as well as information on risk factors and comorbidities, such as pregnancy, puerperium, chronic diseases (asthma, diabetes, hypertension, cardiovascular disease, neurological disease), immunosuppression, obesity, and smoking. The form also includes the patient’s vaccination status for influenza and COVID-19 [9].

With regard to hospitalization, the date of hospitalization, the place of care (ward or ICU), the need for ventilatory support (oxygen therapy, non-invasive ventilation, or orotracheal intubation), and the evolution of the case, which may be discharge, death, or continued hospitalization, are recorded. In addition, there are specific fields for laboratory results, which include the collection of clinical samples, the type of test performed (RT-PCR, rapid test, serology), as well as the identified viral agent, when confirmed (such as influenza A H1N1, influenza A H3N2, influenza B, COVID-19, or other respiratory viruses) [9].

In cases of death, the date, place, and underlying cause of death are recorded. Finally, the form also includes administrative information related to the reporting service, such as the responsible health facility, the municipality of care, and the identification of the professional who performed the test [9].

The variables used were age group, race/colour and the region in which the SARS notification due to the 2024 Brazilian outbreak of the virus occurred. Geographically, Brazil is divided into five regions: northern, north-east, mid-west, south-east and south. The North Region consists of seven states and is home to most of the Amazon Rainforest, which is renowned for its biodiversity. The Northeast region comprises nine states and is the largest in terms of the number of federal units. It is subdivided into four sub-regions (The Mid-North, Hinterland, Agreste and Forest zones) which have different levels of human development. The Midwest consists of the states of Goiás, Mato Grosso, Mato Grosso do Sul and the Federal District. It is the only region to border all the others and has no coastline. It is also home to the country’s capital, Brasília. The Southeast, comprising the states of São Paulo, Rio de Janeiro, Minas Gerais and Espírito Santo, is Brazil’s main industrial, commercial and financial hub. The South, comprising Paraná, Santa Catarina and Rio Grande do Sul, is the only region below the tropical zone. It has well-defined seasons and social indicators above the national average [10].

We applied Pearson’s chi-square test [11] to assess the associations between evolution, ventilatory support, ICU and sociodemographic profile variables. Subsequently, modified multiple Poisson regression models with robust variance [12] were fitted, with evolution, ventilatory support and ICU status serving as the dependent variables and sociodemographic profile variables as the independent variables. The models’ results presented the prevalence ratio estimates, along with their respective confidence intervals and p-values.

The general database (30,529 cases) was used for the descriptive analysis. For the statistical analysis of clinical progression 19,386 cases were examined: 19,807 UCI and 18,797 of ventilatory support. This difference was due to the analysis being restricted to cases where all the necessary variables had been filled in.

SAS statistical software, version 9.4, was used to perform the analyses and a significance level of 5% was adopted.

As the data were secondary, publicly accessible and non-restricted, and did not contain any identifying information about the participants, the study was exempt from evaluation by the Research Ethics Committee in accordance with Resolution No. 510 of 7 April 2016 of the National Health Council [13].

3. Results

On average, 23.94 months (SD = 10.39) had elapsed since the last vaccine dose was administered. This ranged from 0 to 46.58 months, with an interquartile range (IQR) of 15.87 to 32.23 months. The interval between symptom onset and clinical outcome (recovery or death) averaged 13.26 days (SD = 16.55), ranging from 0 to 396 days, with an IQR of 5 to 15 days. This demonstrates highly variable patterns of disease progression among patients. Regarding the number of vaccine doses received, the mean was 2.41 (SD = 1.80), ranging from 0 to 6, with an IQR of 0 to 4.

Of the 30,525 reported cases of severe acute respiratory syndrome (SARS) due to COVID-19 in Brazil in 2024, 51.39% were women, 59.88% were aged 60 or over, 60.20% were white and 54.10% lived in the southeast region. In addition, 66.13% of patients had comorbidities. Of the analysed comorbidities, cardiovascular disease (58.95%) and other morbidities (57.21%) were the most prevalent, followed by diabetes (40.41%), neurological conditions (18.45%), and lung diseases (15.66%). Lower proportions were observed for immunosuppression (11.15%), chronic kidney disease (11.48%), asthma (8.32%), and obesity (8.06%). The lowest frequencies were observed for liver diseases (2.61%), haematological diseases (3.64%), and Down syndrome (1.44%). A high proportion of records were missing information on some variables.

Of the cases, 78.0% evolved to recovery, while 35.01% required admission to the intensive care unit (ICU). In terms of clinical outcome, 60.4% of patients required ventilatory support. In terms of vaccination status, 46.53% of individuals had completed the primary vaccination series with a booster dose, while 26.84% had not received any doses of the vaccine. Among those vaccinated, the majority (84.98%) received their last booster dose more than two years ago (

Table 1. Sociodemographic, Clinical, Vaccination Characteristics of Reported Cases of Severe Acute Respiratory Syndrome (SARS) due to COVID-19 in Brazil, 2024 (n = 30,529).

Variable	n	%
Sex
Male	14,835	48.59
Female	15,690	51.39
Ignored	4	0.01
Age group
<1	65	0.21
1 to 4	3192	10.46
5 to 9	1972	6.46
10 to 19	1016	3.33
20 to 39	2228	7.30
40 to 59	3774	12.36
60 or more	18,282	59.88
Race/Color
Caucasian	15,813	60.20
Black	1058	4.03
Yellow	244	0.93
Brown	9066	34.51
Indigenous	88	0.33
Ignored = 4260
Region
North	1446	4.74
Northeast	3192	10.46
Midwest	3095	10.14
Southeast	16,517	54.10
South	6279	20.57
Comorbidity
Yes	20,190	66.13
No	10,339	33.87
Clinical progression
Cure	22,696	78.04
Death	5320	18.29
Death from other causes	1067	3.67
Ignored = 1446
Intensive Care Unit (ICU)
Yes	9695	35.01
No	17,995	64.99
Ignored = 2839
Ventilatory support
Yes, invasive	4081	15.22
Yes, no invasive	12,114	45.18
No	10,620	39.60
Ignored = 3714
Number of vaccine doses (COVID-19)
No doses	8203	26.89
One dose	1168	3.83
Two doses	6193	20.30
Three or more doses	14,945	48.99
Time since last vaccine dose
Up to 3 months	225	1.07
3 to 6 months	270	1.28
7 to 12 months	3541	16.82
13 to 24 months	6425	30.52
More than 24 months	10,594	50.32
Ignored = 9474

Source: Severe Acute Respiratory Syndrome Database of the Brazilian Unified Health System (SUS), 2024.

).

A total of 19,386 cases with known clinical outcomes (recovery or death) were analysed, alongside 19,807 records detailing admission to intensive care units (ICUs) and 18,797 records regarding the requirement for ventilatory support in cases of severe acute respiratory syndrome (SARS) caused by COVID-19 in Brazil in 2024.

Analysis of clinical outcomes revealed a significantly higher death rate among men (23.7%) than women (19.1%) (p < 0.0001). A progressive increase in mortality was observed with age, reaching 24.4% among individuals aged 60 years or over. By contrast, mortality rates were below 2% among children under 10 years of age. There were also regional differences, with higher proportions of deaths in the Northeast (26.8%) and North (22.6) regions (p < 0.0001) (

Table 2. Association Between Sociodemographic, Regional and Vaccination Variables and Clinical Outcomes (Evolution (n = 19,386), ICU Admission (n = 19,807), and Ventilatory Support (n = 18,797) in Cases of SARS due to COVID-19 in Brazil, 2024.

Variable	Clinical Progression				p-Value *	ICU				p-Value *	Ventilatory Support				p-Value *
	Cure		Death			No		Yes			No		Yes
	n	%	n	%		n	%	n	%		n	%	n	%
Sex					<0.0001					<0.0001					0.0008
Male	6879	76.31	2135	23.69		5736	61.95	3524	38.06		3275	37.14	5542	62.86
Female	8394	80.93	1978	19.07		7005	66.42	3542	33.58		3944	39.52	6036	60.48
Age group					<0.0001					0.0003					<0.0001
<5	356	98.61	5	1.39		232	66.29	118	33.71		129	38.97	202	61.03
5 to 9	359	98.36	6	1.64		233	66.57	117	33.43		123	37.61	204	62.39
10 to 19	372	94.66	21	5.34		274	68.16	128	31.84		175	46.05	205	53.95
20 to 39	1380	90.61	143	9.39		1040	67.80	494	32.20		797	56.05	625	43.95
40 to 59	2177	81.41	497	18.59		1672	61.27	1057	38.73		1094	42.65	1471	57.35
60 or more	10,628	75.56	3437	24.44		9290	64.33	5152	35.67		4901	35.59	8871	64.41
Region					<0.0001					<0.0001					<0.0001
North	465	77.37	136	22.63		428	68.48	197	31.52		240	41.10	344	58.90
Northeast	1163	73.19	426	26.81		1052	58.08	742	41.36		671	39.03	1048	60.97
Midwest	1571	82.25	339	17.75		1147	58.08	828	41.92		824	45.08	1004	54.92
Southeast	8905	79.04	2361	20.96		7206	64.04	4046	35.96		3888	36.78	6682	63.22
South	3169	78.83	851	21.17		2908	69.89	1253	30.11		1596	38.96	2500	61.04
Time since last vaccine dose					<0.0281					0.8419					0.5807
Up to 24 months	7725	79.43	2001	20.57		6321	64.26	3516	35.74		3597	38.60	5721	61.40
Over 24 months	7548	78.14	2112	21.86		6420	64.39	3550	35.61		3622	38.21	5857	61.79

* p-value obtained using the Chi-square test.

).

Regarding ICU admission, a higher proportion of men (38.1%) than women (33.6%) were admitted (p < 0.0001). Similarly, the need for ventilatory support was higher among men (62.9%) than women (60.5%) (p = 0.0008). The 60+ age group had the highest demand for ventilation (64.4%), followed by the 40–59 age group (57.4%) and the 10–19 age group (54.0%) (p < 0.0001) (Table 2).

A statistically significant association was found between the time since the last dose of the vaccine and clinical evolution (p = 0.0281). A lower proportion of deaths (20.6%) was observed among individuals vaccinated up to 24 months ago compared to those vaccinated more than 24 months ago (21.9%). There was no significant difference in ICU admission rates between the groups (35.7% versus 35.6%; p = 0.8419). Similarly, no statistically significant association was observed between time since the last dose and need for ventilatory support (61.4% versus 61.8%; p = 0.5807) (Table 2).

The study found that males were at a higher risk of experiencing serious clinical outcomes than females. They were more likely to die (prevalence ratio (PR): 1.24; 95% confidence interval (CI): 1.18–1.30; p < 0.0001), be admitted to intensive care (PR: 1.13; 95% CI: 1.10–1.17; p < 0.0001), and require ventilatory support (PR: 1.03; 95% CI: 1.01–1.05; p = 0.0012) (

Table 3. The association between sociodemographic and regional characteristics, and the time since the last dose of the COVID-19 vaccine, with clinical outcomes such as death, ICU admission, and the need for ventilatory support, in cases of SARS due to the virus in Brazil in 2024.

	Clinical Progression		ICU		Ventilatory Support
Independent Variables	Prevalence Ratio *	p-Value	Prevalence Ratio **	p-Value	Prevalence Ratio **	p-Value
Sex (Male)	1.24 (IC95%:1.18;1.30)	<0.0001	1.13 (IC95%:1.10;1.17)	<0.0001	1.03 (IC95%:1.01;1.05)	0.0012
Age group (<5)	reference		1.04 (IC95%:0.88;1.22)	0.6697	1.40 (IC95%:1.26;1.55)	<0.0001
Age group (5 to 9)	1.17 (IC95%:0.35;3.89)	0.7929	1.02 (IC95%:0.82;1.27)	0.8592	1.42 (IC95%:1.27;1.59)	<0.0001
Age group (10 to 19)	3.84 (IC95%:1.52;9.68)	0.0043	reference	-	1.22 (IC95%:1.10;1.35)	0.0001
Age group (20 to 39)	7.02 (IC95%:3.16;15.59)	<0.0001	1.02 (IC95%:0.90;1.15)	0.8119	reference	-
Age group (40 to 59)	13.73 (IC95%:6.23;30.28)	<0.0001	1.21 (IC95%:1.06;1.38)	0.0037	1.30 (IC95%:1.22;1.38)	<0.0001
Age group (60 or more)	18.21 (IC95%:8.30;39.91)	<0.0001	1.12 (IC95%:0.99;1.26)	0.0699	1.46 (IC95%:1.38;1.54)	<0.0001
Region (Midwest)	reference	-	1.40 (IC95%:1.32;1.48)	<0.0001	reference	-
Region (North)	1.43 (IC95%:1.21;1.69)	<0.0001	1.06 (IC95%:0.96;1.17)	0.2799	1.09 (IC95%:0.99;1.20)	0.0676
Region (Northeast)	1.56 (IC95%:1.37;1.77)	<0.0001	1.39 (IC95%:1.30;1.48)	<0.0001	1.11 (IC95%:1.05;1.18)	0.0005
Region (Southeast)	1.17 (IC95%:1.05;1.29)	0.0033	1.20 (IC95%:1.15;1.25)	<0.0001	1.14 (IC95%:1.10;1.19)	<0.0001
Region (South)	1.16 (IC95%:1.05;1.28)	0.0038	reference	-	1.10 (IC95%:1.05;1.16)	<0.0001
Time since last vaccine dose (Over 24 months)	1.08 (IC95%:1.03;1.12)	0.0005	0.99 (IC95%:0.97;1.02)	0.7056	1.03 (IC95%:1.01;1.05)	0.0015

* The probability of the outcome being ‘death’ was estimated. ** The probability of the result being ‘Yes’ was estimated.

).

There was a progressive increase in the risk of death with advanced age, with significant increases observed in the 20–39 (PR = 7.02; 95% CI: 3.16–15.59; p < 0.0001), 40–59 (PR = 13.73; 95% CI: 6.23–30.28; p < 0.0001) and ≥60 (PR = 18.21; 95% CI: 8.30–39.91; p < 0.0001) age groups, compared to children under 5 years of age. Additionally, a significant association was observed between all age groups and the need for ventilation compared to the 20–39 age group (Table 3).

In terms of geographical distribution, a higher prevalence of death was found in the North, Northeast, Southeast and South when the Central-West region was taken as a reference (PR = 1.43; 95% CI: 1.21–1.69; p < 0.0001, PR = 1.56; 95% CI: 1.37–1.77; p < 0.0001, PR = 1.17; 95% CI: 1.05–1.29; p = 0.0033 and PR = 1.16; 95% CI: 1.05–1.28; p = 0.0038, respectively). Compared to the South region, these regions also had higher ICU admission rates, particularly the Northeast (PR = 1.39; 95% CI: 1.30–1.48; p < 0.0001), the Southeast (PR = 1.40; 95% CI: 1.32–1.48; p < 0.0001) and the Midwest (PR = 1.40; 95% CI: 1.32–1.48; p < 0.0001). Regarding the need for ventilatory support, the Northeast (PR = 1.11; 95% CI: 1.05–1.18; p = 0.0005), Southeast (PR = 1.14; 95% CI: 1.10–1.19; p < 0.0001) and South (PR = 1.10; 95% CI: 1.05–1.16; p < 0.0001) stood out in comparison to the Midwest region (Table 3).

Finally, the time elapsed since the last COVID-19 vaccine dose was also found to be significantly associated with the outcome. Those who received their last dose more than 24 months ago were more likely to die (PR = 1.08; 95% CI: 1.03–1.12; p = 0.0005) or require ventilation (PR = 1.03; 95% CI: 1.01–1.05; p = 0.0015) (Table 3).

4. Discussion

Males had a higher prevalence ratio for death, the need for admission to the intensive care unit (ICU) and the need for ventilatory support. These findings are consistent with a global meta-analysis of over 3.1 million cases, which found that males were associated with a 39% increase in mortality and a nearly threefold increase in the likelihood of ICU admission [14]. Similar results were observed in a large hospital study conducted in Houston (n = 13,454), which identified an independent association between male gender and more severe hypoxaemia, greater use of mechanical ventilation, and higher in-hospital mortality [15]. The consistency of these results across different contexts suggests that this risk disparity goes beyond the particularities of healthcare systems and indicates the involvement of common biological, hormonal, and behavioural factors.

Immunological differences between the sexes help to explain this risk gradient. For example, a longitudinal study of the inflammatory response showed that men have sustained levels of inflammatory cytokines such as IL-8 and IL-18, whereas women have a stronger CD8⁺ T cell response, which is linked to better clinical outcomes [16]. In addition, genes such as TLR7, which is located on the X chromosome, can escape inactivation. This gives women increased production of type I interferon in the early stages of infection, which favours viral control. Another relevant factor is the increased expression of the TMPRSS2 enzyme, which is induced by androgens and facilitates viral entry into male pneumocytes [17].

Behavioural aspects also contribute to this greater vulnerability in men, such as lower adherence to preventive measures, such as wearing masks, practising social distancing and getting vaccinated, as pointed out by population surveys. However, it is important to note that the database used in this study lacks detailed information on hormonal markers, immunophenotypic profiles, and individual behaviours. This limits direct analysis of these mechanisms in the Brazilian population.

In addition, the renin-angiotensin axis provides an alternative explanation for the differences in outcomes between the sexes. The ACE2 gene, which is located on the X chromosome (Xp22.2), can escape inactivation. This allows different cells to express distinct alleles, forming a cellular mosaic with greater functional reserve in women [18]. Oestrogens tend to increase ACE2 expression and reduce pro-inflammatory signalling mediated by angiotensin II, whereas testosterone has the opposite effect. These data support the development of risk algorithms that categorise patients by sex and hormonal status, as well as investigating adjuvant therapies involving renin-angiotensin system modulators or ADAM17 enzyme inhibitors.

Nevertheless, the limitations of the study must be recognised, including possible underreporting of deaths, delays in updating outcomes and the absence of relevant clinical variables such as hormonal status, previous treatments and specific unrecorded comorbidities. While such limitations may affect the accuracy of the estimates, they are unlikely to reverse the direction and magnitude of the observed effects, given the consistency with international evidence.

In elderly people, several pathophysiological mechanisms increase susceptibility to severe acute respiratory syndrome (SARS), which is caused by the COVID-19 virus. One of the main factors is immunosenescence, which is characterised by reduced T lymphocyte production and a less effective immune response to new pathogens [19]. Studies show that older adults produce approximately 50% fewer type I interferons, which are key proteins in the antiviral response and favour exacerbated viral replication. Ageing is also associated with chronic inflammation, which disrupts cytokine release and exacerbates immune dysfunction [20].

Metabolically, the risk of deterioration is even greater in people with diabetes mellitus (DM), a condition that induces the overproduction of ACE2 in the pulmonary alveoli. Added to this are impaired ATP production in respiratory epithelial cells and oxidative stress caused by excess reactive oxygen species [20].

The presence of comorbidities, which are often associated with advanced age, is also noteworthy. Individuals aged 60 years or older with diabetes mellitus (DM) have an 8.1 times higher risk of severe outcomes, while high blood pressure (HBP) increases this risk by 2.5 times [21]. Furthermore, obese elderly individuals demonstrate an amplified systemic inflammatory response, with up to 40% higher viral load in adipose tissue [19].

These findings are corroborated by national studies. For example, an analysis published in Scientific Reports identified a mortality rate of 47.6% among older adults (aged 60 years or over), compared to 8.3% among young adults (aged 20–39 years) [21]. Another study, this time by PLOS One, showed an 82.98% mortality rate among elderly people undergoing invasive ventilation, highlighting the impact of age on infection severity [22].

In this context, vaccination proves to be the most effective intervention. Estimates published in The Lancet suggest that vaccination in Brazil prevented at least 16,914 hospitalisations and 58,644 deaths among the elderly between January and August 2021, representing a 35% reduction in these outcomes. Advancing the vaccination campaign by four weeks could have prevented 220,676 hospitalisations and 81,564 deaths, and by eight weeks, these figures would have increased to 272,421 and 105,532, respectively [23]. These figures emphasise the importance of prioritising the elderly in vaccination campaigns, both during emergencies and in immune booster strategies.

Regional inequalities also had a significant impact on the dynamics of the pandemic in Brazil. The North and Northeast regions, which have lower levels of public service coverage, poor hospital infrastructure and lower levels of socioeconomic development, have faced greater challenges in controlling the virus, with higher rates of hospitalisation and death [2]. An ecological study revealed that federal units with greater social inequality had significantly higher SARS mortality rates, even after adjusting for age, comorbidities, and gender. This suggests that populations in these areas are more vulnerable [24].

Poor structural conditions also contributed to the spread of the virus. Municipalities in the North and Northeast, characterised by high poverty rates, inadequate housing, and a significant proportion of vulnerable populations, such as Black, brown, and indigenous people, had greater difficulty implementing preventive measures [25]. A study in Ceará showed that neighbourhoods with higher housing density had higher mortality rates, confirming that inadequate housing hinders disease control [26].

Vaccination coverage was also significantly lower in these regions. Even with four vaccines available in October 2021, the vaccination rate was 56.8 per 100 inhabitants in the North and 74.4 in the South. According to data from the Ministry of Health [27], this inequality persisted in 2025, with vaccination coverage in the North and Northeast regions remaining below ideal.

The analysis of current vaccination coverage indicates that nearly one-third of COVID-19 cases in 2024 occurred among unvaccinated individuals. Moreover, a substantial proportion of vaccinated patients had received their last dose more than one year earlier, with an average interval of 30.3 months since vaccination. Previous evidence demonstrates that vaccine effectiveness declines markedly five months after completion of the primary series, although booster doses temporarily restore protection [28]. During the Omicron BQ.1.1 wave, for instance, elderly individuals whose last dose had been administered more than six months earlier exhibited a significantly higher risk of hospitalisation [29]. Consistent with these findings, a study from Israel involving adults aged 50 years and older reported that those who received a booster at least five months after the second BNT162b2 dose had a 90% lower risk of death compared with those who did not receive a booster [30]. Similarly, a longitudinal study conducted in Japan demonstrated that individuals with one or more vaccine doses had a reduced likelihood of requiring ventilatory support [31]. These results reinforce the present study’s findings, underscoring that the interval since the last vaccine dose significantly influences the probability of severe outcomes, including the need for ventilation.

The wide variation in the interval between symptom onset and clinical progression (ranging from 0 to 396 days) reflects differences in comorbidity profiles, access to care, and the individual immune response. Previous studies have shown that substantial delays in diagnosis, hospitalisation and death occur among Brazilian states, influenced by socioeconomic and structural inequalities [32]. This emphasises the importance of integrated epidemiological surveillance that can monitor not only case occurrence, but also progression and determining factors.

In light of this, public policies should prioritise men, the elderly, the unvaccinated, and residents of the North and Northeast regions. The national literature emphasises that these regions have historically experienced higher mortality rates due to social inequalities and limited access to healthcare [33]. Therefore, strategies to reduce the lethality of SARS due to endemic scenarios of COVID-19 infection must include expanding vaccination coverage (especially booster doses), strengthening territorial surveillance, and promoting equity in access to healthcare.

The study has some important limitations. Firstly, it is based on secondary data from a national surveillance system which is subject to underreporting, delays and incomplete information, such as vaccination status and comorbidities. The cross-sectional design only allows associations to be established, not causality. Furthermore, there were no data on clinical management and access to health services, which are factors that may influence outcomes. The variability in the time interval between the last dose and the onset of symptoms may be due to memory bias, inconsistencies in records, or regional differences in vaccine adherence. Furthermore, the findings are restricted to 2024 and may not reflect subsequent changes in viral variants, vaccination policies or the response of the health system. Nevertheless, the study provides valuable insights into the sociodemographic, clinical and vaccination profiles of COVID-19 cases in Brazil, and identifies risk factors for severity and mortality.

5. Conclusions

The ongoing presence of Severe Acute Respiratory Syndrome due to COVID-19 in Brazil, particularly among vulnerable populations, highlights the importance of strategic public health initiatives. This study found that men, elderly people, and residents of the North and Northeast regions were at a higher risk of death, revealing regional and demographic disparities in how people cope with the disease. Furthermore, the high proportion of unvaccinated individuals among the analysed cases indicates failures in vaccination coverage and adherence to booster doses. In light of these findings, policies must be reinforced to prioritise high-risk groups, increase vaccination coverage, and ensure adherence to updated schedules. Intersectoral initiatives must be implemented to reduce regional disparities and enhance epidemiological surveillance systems. Mitigating the ongoing and sustainable impacts of the disease requires the development of more equitable, evidence-based, territory-oriented responses.