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Journal of Human Growth and Development

versão impressa ISSN 0104-1282versão On-line ISSN 2175-3598

J. Hum. Growth Dev. vol.33 no.3 Santo André set./dec. 2023  Epub 20-Jan-2025

https://doi.org/10.36311/jhgd.v33.15287 

ORIGINAL ARTICLE

Analysis of incidence, mortality and lethality by COVID-19 in the States of Pará and Rio Grande do Sul, Brazil: epidemiological aspects of evolution 2020-2022

Célia Guarnieri da Silvaa  b 
http://orcid.org/0000-0003-0006-2159

Blanca Elena Guerrero Daboina  b 
http://orcid.org/0000-0002-7618-2109

Carlos Bandeira de Mello Monteirob  c 
http://orcid.org/0000-0002-2661-775X

aPrograma de Pós-Graduação em Ciências da Saúde, Centro Universitário FMABC - Santo André, São Paulo, Brasil;

bLaboratório de Delineamento de Estudo e Escrita Científica, Centro Universitário FMABC - Santo André, São Paulo, Brasil;

cEscola de Artes, Ciências e Humanidades da Universidade de São Paulo (EACH-USP), Departamento de Pós-Graduação em Ciências da Reabilitação – São Paulo, São Paulo, Brasil.


Authors summary

Why was this study done?

When evaluating the COVID-19 scenario in the states of Pará and Rio Grande do Sul and its combat measures such as variants and vaccination in the period from 2020 to 2022. It is important to recognize that socioeconomic disparities between the north and south of the country differentiate the context. It is necessary to identify the factors that influenced the epidemiological indicators of COVID-19 and understand the pandemic situation in the different Brazilian states, in order to facilitate the formulation of strategies to control the disease. Analyzing the Infection Rate, Mortality and Fatality Rate in the States of Pará and Rio Grande do Sul and Observing the Trends of These Indicators During the Period from 2020 to 2022.

What did the researchers do and find?

When comparing the lethality between the states of Para and Rio Grande do Sul, it was noted that during the period analyzed, the total rate remained higher in the state of Pará, highlighting the months of April/2020, May/2020 and March/2021. Incidence rates showed increasing trends during 2020. In 2021, the incidence was decreasing in both states.

What do these findings mean?

The vaccination program has had a beneficial effect on the trajectory of the pandemic. Throughout the period examined, there was stability in the incidence of cases in both States, which suggests the importance of maintaining continuous surveillance over the number of cases and the health of different age groups and groups.

Key words: COVID-19; SARS-CoV-2; incidence; mortality; lethality; trends

Abstract

Introduction

COVID-19 unfolded differently in Pará and Rio Grande do Sul, Brazil, owing to distinct socioeconomic contexts. From 2020 to 2022, both states implemented diverse measures against the virus SARS-CoV-2, including vaccination and variant monitoring, tailored to their specific challenges. Understanding regional impacts on COVID-19 indicators is crucial for designing effective control strategies.

Objective

to analyze the incidence, mortality, and lethality of COVID-19 in Pará and Rio Grande do Sul and the trends of these indicators from 2020 to 2022.

Methods

ecological study with time series from public and official data available in the Health Secretariat of Pará and Rio Grande do Sul, including all cases and deaths by COVID-19 from February 2020 to December 2022. Lethality, mortality, and incidence rates were calculated. Prais-Winsten regression analysis was used, and trends were classified as stationary, increasing, or decreasing. Significant differences were considered when the p-value is <0.05.

Results

when examining the lethality rates between the states of Para and Rio Grande do Sul, an observable trend emerged during the analyzed period. It became evident that the total lethality rate consistently remained higher in Para. Noteworthy peaks in lethality were mainly observed during the months of April 2020, May 2020, and March 2021. The incidence rates showed increasing trends during 2020, both in Pará with a daily percentage change (DPC) of 1.69% (p <0.05) and in Rio Grande do Sul with a DPC of 1.70% (p<0.05). In 2021, the incidence was decreasing (p <0.05) in both states, with a DPC of 0.60% in Pará and 0.64% in Rio Grande do Sul and continued this trend in Pará in 2022 (DPC of -0.50% p <0.05), becoming stationary in Rio Grande do Sul, with a non-significant p-value (p> 0.05).

Conclusion

the positive impact of the vaccination program is reflected in the evolution of the pandemic. During the study period Rio Grande do Sul and Para exhibited a stationary incidence trend, emphasizing the need for continued monitoring of cases and morbidity across various age and demographic groups.

Key words: COVID-19; SARS-CoV-2; incidence; mortality; lethality; trends

Highlights

Pará had higher fatality rates, but lower mortality rates compared to Rio Grande do Sul in 2020. Rio Grande do Sul has consistently presented higher incidence rates compared to Pará, with the difference increasing in 2021 and 2022. Mortality rates showed an increasing trend in Rio Grande do Sul in 2020 but remained stable in Pará. Both states saw decreasing trends in 2021 and 2022. Fatality rates showed decreasing trends in the first two years and remained stable in 2022 in Pará, while in RS they remained constant throughout the entire period analyzed.

Key words: COVID-19; SARS-CoV-2; incidence; mortality; lethality; trends

Resumo

Introdução

panorama da progressão da pandemia de COVID-19 nos Estados do Pará e Rio Grande do Sul, Brasil e as ações de combate ao vírus SARS-CoV-2 as variantes e vacinação, no período de 2020 a 2022. O contexto de vulnerabilidade socioeconômica da região Norte é diferente da região Sul. É fundamental identificar os elementos que impactam a evolução dos indicadores epidemiológicos da COVID-19 e entender a situação da pandemia nos diferentes Estados do país, para facilitar a busca de estratégias de controle da doença.

Objetivo

analisar a incidência, mortalidade e letalidade nos estados do Pará e Rio Grande do Sul e as tendências destes indicadores no período de 2020 a 2022.

Método

estudo ecológico com série temporal, a partir de dados públicos e oficiais disponíveis na Secretaria de Saúde dos Estados do Pará e do Rio Grande do Sul, incluindo todos os casos e óbitos por COVID-19 que ocorreram durante fevereiro de 2020 a dezembro de 2022. As taxas de letalidade, mortalidade e incidência foram calculadas. Utilizou-se a análise de regressão do Prais-Winsten, as tendências foram classificadas como estacionárias, crescentes ou decrescentes. Diferenças significativas foram consideradas quando p <0,05.

Resultados

ao comparar a letalidade entre os Estados do Para e o Rio Grande do Sul, notou-se que durante o período analisado, a taxa total manteve-se maior no estado do Pará, sendo destacado os meses de abril/2020, maio/2020 e março/2021. As taxas de incidência apresentaram tendências crescentes durante o ano de 2020, tanto no Pará com VPD de 1,69% (p <0,05) quanto no RS com VPD de 1,70% (p <0,05). Em 2021 a incidência foi decrescente (p <0,05) nos dois estados, com uma taxa de redução diária de 0,60% no Pará e 0,64% no RS; e continuou nesta tendência no Pará em 2022 (VPD de -0,50% p <0,05), ficando estacionária no RS, com valor de p não significativo (p> 0,05).

Conclusão

o impacto positivo do programa de vacinação reflete-se na evolução da pandemia. Para todo o período analisado a incidência apresenta tendência estacionária para ambos Estados, indicando que o número de casos e a morbidade entre as diferentes faixas etárias e grupos devem continuar sendo monitorado.

Palavras-Chave: COVID-19; SARs-CoV-2; incidência; mortalidade; letalidade; tendência

INTRODUCTION

In Brazil, existing evidence primarily concentrates on individual states1-6 or compares states within specific geographic regions7. However, there’s a gap in research that directly compares states from different geographical areas. To address this and comprehensively monitor the evolving landscape of the COVID-19 pandemic in Brazil, along with the associated response measures, the COVID-19 Brazil/Ireland Observatory was established. This initiative is led by the Study Design and Scientific Writing Laboratory at the FMABC University Center. COVID-19 is identified as a metabolic disorder caused by the SARS-CoV-2 virus and is associated with severe acute respiratory syndrome (SARS). Predominant symptoms include fever (≥ 37.8°C), cough, myalgia, fatigue, headache, dyspnea, upper respiratory, and gastrointestinal manifestations. The Ministry of Health designates flu syndrome as the most prevalent presentation, potentially progressing to pneumonia and SARS, characterized by respiratory distress and oxygen saturation levels falling below 95%. Elevated levels of angiotensin-converting enzyme 2 (ACE2), particularly in individuals with underlying health conditions, are correlated with respiratory symptoms8-10.

The SARS-CoV-2 virus was initially identified in the central region of China, specifically in the city of Wuhan, in December 2019. Demonstrating high transmissibility, it profoundly affected global health and the economy. Responding swiftly to the escalating situation, the World Health Organization (WHO) declared it a pandemic. In light of the increasing global cases, the WHO issued health recommendations, urging countries to adopt containment strategies and protective measures. These measures encompassed social distancing, quarantine protocols, the closure of educational institutions such as schools and universities, and the implementation of remote work policies11-12.

This virus is highly contagious, and one of the main transmission routes includes direct contact with airborne droplets released during conversation, coughing, and sneezing from infected people. However, recent research suggests that the virus also can spread by air via aerosols13.

According to data from the World Health Organization (WHO) on Coronavirus - COVID-19, as of March 5, 2023, there have been 759,408,703 confirmed cases of COVID-19 globally, with 6,866,434 documented deaths attributed to the disease14. In February 2020, Brazil reported its initial confirmed case of COVID-19. Despite three years of sustained efforts to combat the pandemic, Brazil currently holds the unfortunate distinction of having the highest number of COVID-19 deaths globally, second only to the United States of America15. Given the elevated rate of spread, incidence, and mortality associated with COVID-19, managers of the Unified Health System (SUS) and their teams must formulate effective strategies for dealing with the situation. Developing comprehensive risk management plans at the national, state, municipal, and local levels is crucial. Understanding regional factors that influence the contagion and spread of the virus is essential in this endeavor. Additionally, employing time series studies is instrumental in analyzing the evolving patterns and behavior curves of the pandemic16. Hence, the objective of this study is to analyze the incidence, mortality, and lethality rates of COVID-19 in the States of Pará and Rio Grande do Sul and the trends of these key indicators over the period from 2020 to 2022.

METHODS

It is a Population-based ecological study with time series analysis. Time series are necessary to make valid inferences from the data, accounting for the correlation between repeated observations over time17.

The analysis of indicators for each State followed the protocol by Elmulsharaf and Siqueira (2021)18 with official secondary data from government public disclosure. The database was extracted from the electronic pages made available by the Ministry of Health19 of the States of Pará and Rio Grande do Sul. All cases confirmed by laboratory, clinical, clinical-epidemiological, or/and clinical-imaging diagnosis of COVID-19 from February 2020 to December 2022 were included. The disease was classified according to the International Classification of Diseases, 10th edition (ICD-10), as “U07.1 COVID-19 – identified virus” or “U07.2 COVID-19, unidentified virus”20. Cases without information on the date of notification or death were excluded.

Cases were classified based on the date of notification and fatal cases according to the date of death.

Characterization of the study site

Pará and Rio Grande do Sul, situated in distinct geographical regions, possess unique territorial attributes. Figure 1 depicts the map illustrating the geographic positioning of each state, and table 1 outlines the key sociodemographic features specific to each region.

Source: Own authorship – IBGE21.

Figure 1 : Map of Brazil by regions 

Table 1 : Sociodemographic characteristics of Brazil and the States of Pará and Rio Grande do Sul according to the last Census carried out in Brazil in 2010 

Sociodemographic characteristics Description
BRASIL PARÁ RIO GRANDE DO SUL
Region North Soulth
Number of municipalities 5.570 144 497
capital Brasília Belém Porto Alegre
Territorial Extension (2021) - KM2 8.510.345,54 1.245.870,70 281.707,15
Population (Last Census 2010) - People 190.755.799 7.581.051 10.693.929
Estimated population (2021) 213.317.639 8.777.124 11.466.630
Demographic Density (Last Census, 2010) - Inhabitants/km2 22,43 6,07 37,96
Per capita home monthly monthly income R$ 1.625,00 R$ 1.061,00 R$ 2.087,00
Human Development Index (HDI) (Last Census, 2010) 0,699 0,646 0,746
Basic Health Units of the Unique Health System - SUS (2009)* 63.184 2.300 3.868
establishments Ambulatory SUS* 52.394 2.019 3.066
SUS Dialysis* 923 16 81
SUS Emergency* 5.553 210 327
SUS Internment* 5.415 218 324
SUS ICU/CTI* 1.099 25 71
Number of beds for hospitalization in health facilities (2009)* 431.996 13.720 31.055
beds Public* 152.892 5.830 4440
Private* 279.104 7.890 26615

Source: Brazilian Institute of Geography and Statistics (IBGE, 2021)21. Note 1: 2010 Census; SUS=Unified Health System.

Statistical analysis of data

The number of COVID-19 cases and deaths were described by absolute (n) and relative frequency (%).

The incidence rate (number of cases per 100.000 inhabitants), mortality (number of deaths per 100.000 inhabitants), and lethality (%) were calculated for each State as described in the formulas (1), (2), and (3):

Incidence = number inhabitants number of cases ×100.000 (1)
Mortality = number of deaths number inhabitants ×100.000 (2)
Lethality = number of deaths number of cases ×100 (3)

The study considered the Population Projection of the Federation Units from 2000 to 2060 to determine the number of inhabitants. Specifically, population estimates for 2020, 2021, and 2022 were utilized. This approach ensures a comprehensive understanding of the impact of the pandemic on these regions relative to their demographic dynamics during the specified timeframe22.

Prais-Winsten regression was applied to examine indicator trends, and the daily percentage change (DPC) was determined to classify trends as increasing, decreasing, or stationary. Stationary trends were considered when p>0.05.

We followed the methodological guidelines proposed by Antunes and Cardoso (2015)23 for the construction of time series, considering a significance level of 95%, according to the equations below (1), (2), and (3):

VPD =(10β1)×100% (1)
( IC95%) =(10β_max1)×100% (2)
( IC95%) =(10β_min1)×100% (3)

Where β is the linear regression slope, the indices ul mean the upper limit, and ll is the lower limit of the confidence level.

Statistical analyses were performed using STATA 14.0 software (College Station, TX, USA 2013).

Legal and ethical aspects

The data obtained from the information systems maintained by the State Health Department are official, enabling their use as a feasible tool for analyzing the epidemiological indicators of COVID-19. As this is public and widely accessible data without patient identification, the Scientific Research Ethics Committee does not need to assess this research, respecting the institutional precepts of resolution 466/12.

RESULTS

In the State of Pará, from January 2020 until December 2022, a total of 860,013 cases and 21,504 deaths were recorded through the Ministry of Health’s Coronavirus Panel.

The first cases confirmed by COVID-19 in March 2020 correspond to <0.001% of the total cases throughout the analyzed period. As for deaths, the first records appeared in April of the same year, corresponding to a relative frequency of 0.96% of deaths. In 2020, the state of Pará reported a total of 29,352.9 confirmed cases and 718.3 deaths due to COVID-19. Notably, the months with the highest confirmed cases were June (7.586%), July (5.985%), and August (5.217%). Regarding deaths, the standout months were May (12.625%), June (9.286%), and July (3.757%).

Moving to 2021, the number of cases and deaths in Pará amounted to 27,618.08 and 1,038, respectively. March, April, and May were significant months for both confirmed cases and deaths, representing 6.148%, 6.283%, and 5.238% of the total cases, and 20.414%, 11.881%, and 7.082% of the total deaths during the specified period.

In 2022, the number of COVID-19 cases in Pará was 19,588.92, with 155.41 deaths. January emerged as a notable month, contributing to 2.577% of the total cases, followed by February with 8.277% and July with 3.278%. Regarding deaths, the months of January, February, and March were significant, representing relative frequencies of deaths equivalent to 1.181%, 2.120%, and 1.362%, respectively.

Table 3 shows the monthly distribution of cases and deaths confirmed by COVID-19 in Pará and Rio Grande do Sul over time (2020 to 2022).

Table 3 : Monthly distribution of cases and deaths confirmed by COVID-19 in the States of Pará and Rio Grande do Sul, Brazil, from January 2020 to December 2022 

Year Month Confirmed Cases Confirmed Deaths
absolut frequency (n) relative frequency (%) absolut frequency (n) relative frequency (%)
PARÁ
2020 January 0 0 0 0
February 0 0 0 0
March 21 0,002 0 0
April 2.844 0,330 208 0,960
May 35.085 4,079 2.715 12,625
June 65.245 7,586 1.997 9,286
July 51.479 5,985 808 3,757
August 44.871 5,217 418 1,943
September 30.893 3,592 427 1,985
October 22.470 2,612 165 0,767
November 17.629 2,049 172 0,799
December 22.992 2,673 273 1,269
Total 2020 293.529 34,125 7.183 33,391
2021 January 35.260 4,099 448 2,083
February 35.337 4,108 955 4,441
March 52.880 6,148 4.390 20,410
April 54.036 6,283 2.555 11,880
May 45.055 5,238 1.523 7,082
June 36.323 4,223 965 4,487
July 19.519 2,269 579 2,692
August 11.341 1,318 405 1,883
September 7.521 0,874 205 0,953
October 7.097 0,825 87 0,404
November 10.281 1,195 155 0,720
December 16.767 1,949 189 0,878
Total 2021 331.417 38,529 12.456 57,913
2022 January 22.165 2,577 254 1,181
February 71.187 8,277 456 2,120
March 34.651 4,029 293 1,362
April 11.629 1,352 175 0,813
May 9.113 1,059 106 0,492
June 8.173 0,950 90 0,418
July 28.194 3,278 80 0,372
August 21.015 2,443 192 0,892
September 7.986 0,928 117 0,544
October 4.854 0,564 35 0,162
November 7.046 0,819 35 0,162
December 9.054 1,052 32 0,148
Total 2022 235.067 27,328 1.865 8,666
Total triennium 860.013 100,00 21.504 100,00
RIO GRANDE DO SUL
2020 January 0 0 0 0
February 33 0,001 0 0
March 1.264 0,043 4 0,009
April 3.607 0,123 60 0,144
May 10.175 0,347 182 0,437
June 25.581 0,873 440 1,057
July 57.060 1,948 1.391 3,344
August 62.303 2,127 1.606 3,861
September 48.290 1,649 1.282 3,082
October 57.298 1,956 1.000 2,404
November 121.909 4,163 1.167 2,805
December 123.048 4,202 2.111 5,075
Total 2020 510.568 17,432 9.243 22,218
2021 January 93.303 3,186 1.776 4,269
February 189.941 6,487 2.048 4,923
March 200.621 6,852 8.445 20,303
April 96.858 3,308 4.534 10,900
May 136.372 4,657 2.964 7,126
June 104.827 3,580 2.895 6,960
July 46.802 1,598 1.697 4,079
August 31.093 1,061 796 1,913
September 26.665 0,910 616 1,480
October 31.607 1,079 664 1,596
November 18.519 0,632 595 1,430
December 19.411 0,662 257 0,617
Total 2021 996.019 34,012 27.287 65,593
2022 January 559.912 19,123 678 1,630
February 237.036 8,095 1.431 3,440
March 52.772 1,802 606 1,456
April 36.897 1,260 196 0,471
May 115.364 3,940 293 0,704
June 94.756 3,236 482 1,158
July 87.758 2,997 425 1,021
August 47.428 1,619 356 0,855
September 9.543 0,325 180 0,432
October 3.776 0,128 59 0,141
November 39.493 1,348 72 0,173
December 136.587 4,665 286 0,687
Total 2022 1.421.322 48,538 5.064 12,168
Total triennium 2.927.909 100,00 41.594 100,00

The first confirmed cases of COVID-19 in Rio Grande do Sul were registered in February 2020, corresponding to 0.001% of the total cases throughout the period analyzed, with the first death registered in March, representing 0.009 % of the total number of deaths about the period analyzed.

In 2020, the number of cases and deaths confirmed by COVID-19 was 42,547.33 and 770.25, respectively. The months with the highest number of cases were October (1,956%), November (4,163%) and December (4,202%). Regarding deaths, the months that stood out were July (3.344%), August (3.861%) and December (5.075%).

In 2021, the number of cases and deaths confirmed by COVID-19 was 83,001.58 and 2,273.91, respectively. February, March and May stand out for cases, being 6.487%, 6.852%, and 4.657%, respectively, concerning the total period. However, for deaths, the months with the highest number of records were March (20.303%), April (10.900%) and May (7.126%).

In 2022, until July, the number of cases and deaths confirmed by COVID-19 was 118,443.5 and 422, respectively. January represents 19.123% of the total cases, followed by February, 8.095%, and December, 4.665%. Regarding the deaths, the months with the highest number were January, February, and March, with the relative frequencies equivalent to 1.630%, 3.440%, and 1.456, respectively.

For both States, table 4 shows the mortality, lethality, and incidence rates of COVID-19.

Table 4 Monthly distribution of mortality, lethality and incidence rates of COVID-19 in the States of Pará and Rio Grande do Sul, Brazil, from January 2020 to July 2022 

Year Month PARÁ RIO GRANDE DO SUL
Mortality Incedence Letality Mortality Incedence Letality
2020 January 0 0 0 0 0 0
February 0 0 0 0 0,289 0
March 0 0,37 0 0,035 11,071 0,316
April 2,410 32,959 7,313 0,525 31,593 1,663
May 31,464 406,598 7,738 1,594 89,122 1,788
June 23,143 756,121 3,06 3,853 224,062 1,72
July 9,363 596,588 1,569 12,183 499,785 2,437
August 4,844 520,008 0,931 14,066 545,708 2,577
September 4,948 358,017 1,382 11,228 422,9696 2,654
October 1,97 260,403 0,734 8,758 501,87 1,745
November 1,993 204,301 0,975 10,221 1067,795 0,957
December 3,163 266,453 1,187 18,49 1077,771 1,715
Total 2020 83,301 3401,823 2,447 80,958 4472,039 1,81
2021 January 5,143 410,614 1,27 15,52 815,388 1,903
February 11,56 414,506 2,702 17,897 1659,922 1,078
March 21,066 607,092 8,301 73,802 1753,256 4,209
April 29,332 620,364 4,728 39,623 846,456 4,681
May 17,484 517,257 3,38 25,902 1191,775 2,173
June 11,078 417,008 2,656 25,299 916,098 2,761
July 6,647 224,089 2,966 14,83 409,009 3,625
August 4,649 130,201 3,571 6,956 271,726 2,56
September 2,353 86,345 2,725 5,383 233,029 2,31
October 0,998 81,477 1,225 5,802 276,218 2,1
November 1,779 118,031 1,507 5,199 161,84 3,212
December 2,169 192,494 1,127 2,245 169,635 1,323
Total 2021 114,266 3819,484 3,758 238,465 8704,355 2,739
2022 January 2,889 258 1,145 5,913 4883,363 0,121
February 5,188 809,943 0,64 12,48 2067,348 0,603
March 3,333 394,248 0,845 5,285 460,259 1,148
April 1,991 132,311 1,504 1,709 321,803 0,531
May 1,206 103,684 1,163 2,555 1006,165 0,253
June 1,023 92,989 1,101 4,203 826,429 0,508
July 0,91 320,782 0,283 3,706 765,39 0,484
August 2,184 239,102 0,913 3,104 413,65 0,75
September 1,331 90,862 1,465 1,569 83,23 1,886
October 0,386 55,227 0,721 0,514 32,932 1,562
November 0,398 80,167 0,496 0,627 344,444 0,182
December 0,364 103,013 0,353 2,494 1191,265 0,209
Total 2022 21,208 2680,333 0,793 44,166 12 396,289 0,356
Total triennium 218,775 9901,641 2,5 363,59 25 572,683 1,42

When comparing lethality between Para and Rio Grande do Sul, it was noted that during the period analyzed, the total rate remained higher in Pará, with April/2020 being highlighted (7.313% - 1.663 %), May/2020 (7.738% - 1.788%) and March/2021 (8.301% - 4.209%).

When comparing incidences, Rio Grande do Sul stands out compared to Pará, presenting the highest rates. In 2022, it was the highest incidence rate for COVID-19 in Rio Grande do Sul, with a total of 12,396.289/100,000 inhabitants, compared to a rate of 2,680.333/100,000 inhabitants in Pará. In 2020, the rate was higher by 1.31 times, and in 2021, the rate was 2.27 times higher.

Although lethality in Pará was higher throughout the period, mortality was higher in Pará than in Rio Grande do Sul only in 2020, reaching a rate of 83.301/100,000 inhabitants against 80.859/100,000 inhabitants. For 2021 and 2022, Rio Grande do Sul recorded a mortality rate of 2.08 and 2.09 times higher than Pará, respectively.

The trends in mortality, lethality, and incidence rates of COVID-19 in Pará and Rio Grande do Sul are shown in Table 5.

Table 5 : Estimates of Prais-Winsten regression and daily percentage variation (DPV) of mortality, lethality and incidence rates of COVID-19 in the States of Pará and Rio Grande do Sul, Brazil, from January 2020 to December 2022 

Rate/year Pará Rio grande do sul
Linear regression Linear regression
β P VPD 95%CI Trend β P VPD 95% CI Trend
Mortality
2020 to 2022 -0.0011841 <0.001 -0.30 -0.33: -0.21 Descending 0.0002123 0.630 0.05 -0.15: 0.25 Stationary
2020 -0.0013088 0.217 -0.30 -0.78: 0.18 Stationary 0.007 <0.001 1.16 1.31: 2.02 Growing
2021 -0.003438 <0.001 -0.80 -0.99: -0.59 Descending -0.003 <0.001 -0.76 -1.02: -0.50 Descending
2022 -0.002467 <0.001 -0.60 -0.70: -0.43 Descending -0.002 <0.001 -0.61 -0.82: -0.40 Descending
Lethality
2020 to 2022 -0.000641 <0.001 -0.20 -0.19: -0.11 Descending -0.0006 <0.001 -0.14 -0.20: -0.08 Descending
2020 -0.003552 <0.001 -0.80 -1.05: -0.58 Descending -0.0002 0.305 -0.06 -0.16: 0.05 Stationary
2021 -0.000695 0.022 -0.20 -0.30: -0.02 Descending -0.0002 0.473 -0.07 -0.24: 0.11 Stationary
2022 -0.000531 0.156 -0.10 -0.29: 0.05 Stationary 0.001 0.107 0.25 -0.05: 0.56 Stationary
Incidence
2020 to 2022 -0.000203 0.200 -0.10 -0.12: 0.02 Stationary 0.0009 0.122 0.22 -0.06: 0.51 Stationary
2020 0.007291 <0.001 1.69 0.82: 2.58 Growing 0.007 <0.001 1.70 1.31: 2.09 Growing
2021 -0.002774 <0.001 -0.60 -0.64: -0.83 Descending -0.002 <0.001 -0.64 -0.85: -0.43 Descending
2022 -0.002247 <0.001 -0.50 -0.52: -0.73 Descending -0.002 0.295 -0.46 -1.32: 0.41 Stationary

Mortality rates in 2020 showed an increasing trend in Rio Grande do Sul and remained stationary in Pará. In 2021 and 2022, the trends were decreasing for both states.

Lethality rates showed decreasing trends for 2020 and 2021 and remained stationary in 2022 in Pará; however, in Rio Grande do Sul, they remained stationary throughout the analyzed period (2020 to 2022).

Incidence rates showed increasing trends during 2020, both in Pará with a DPC of 1.69% (p <0.05) and 1.70% (p <0.05) in Rio Grande do Sul. In 2021, the incidence decreased (p <0.05) in both states, with a DPC of 0.60% in Pará and 0.64% in Rio Grande do Sul; and continued this trend in Pará in 2022 (DPC of -0.50% p <0.05), remaining stationary in Rio Grande do Sul, with a non-significant p-value (p> 0.05).

DISCUSSION

The distinct socioeconomic vulnerabilities in the North and South regions of Brazil underscore the need to identify factors influencing the evolution of COVID-19 epidemiological indicators. Understanding the unique pandemic situations in different states is crucial for devising effective disease control strategies. In this study, we delve into the analysis of COVID-19 incidence, mortality, and lethality in Pará and Rio Grande do Sul, examining trends from 2020 to 2022.

Throughout this period, both states confronted critical episodes. In Pará, a significant surge occurred between May and June 2020, marked by 5,520 deaths and 161,595 new cases of COVID-19. Meanwhile, in Rio Grande do Sul, another notable period unfolded between November and December, witnessing 3,278 deaths and 244,947 new cases. These episodes serve as pivotal points for understanding the dynamics and challenges faced by each state in managing the impact of the pandemic. The second critical period unfolded between March and May 2021 in Pará, witnessing a nearly doubling of both deaths and COVID-19 cases compared to the most critical period of the previous year. This significant surge played a decisive role in overwhelming the health system25, as previously analyzed concerning the capacity of hospital infrastructure to cope with the pandemic and the effectiveness of government actions in combating the pandemic26.

While scrutinizing the evolution of COVID-19 epidemiological indicators throughout 2020, 2021, and 2022 in Pará and Rio Grande do Sul, notable differences and distinctive aspects emerge. Each year unfolds a unique scenario, emphasizing the dynamic and evolving nature of the pandemic in these regions. In 2020, the peak number of COVID-19 cases in Pará was recorded in June (65,245), while in Rio Grande do Sul, it occurred in December (123,048). Despite the higher absolute numbers in Rio Grande do Sul, the incidence rate in Pará for the same period was 3,401.82 per 100,000 population, which was lower than that in Rio Grande do Sul, which reached 4,472.03 per 100,000. It’s noteworthy that both states reported incidence rates higher than the national average for this period, which stood at 3,129 per 100,000 population. This information underscores the variations in the spread of COVID-19 between these states during 2020.

In 2020, the incidence in Pará was still lower than the North region’s average (4,262.4/100,000 inhabitants). Notably, Roraima in the North region reported the highest incidence in the country, reaching 10,678 cases per 100,000 inhabitants. The seven states in the North region collectively accounted for 11.9% of the country’s total COVID-19 cases. Among these, the municipalities with the highest number of new cases were Manaus/AM (2,026), Belém/PA (1,686), and Boa Vista/RR (1,328). In July 2020, Pará held the fourth position with one of the highest COVID-19 case counts nationally. The findings from Lélis da Silva F. et al., (2021)27 highlight that the most significantly affected states in the North were Pará and Amazonas. According to the study, one week after the notification of the first case of COVID-19 in Pará, 0.82% of municipalities reported cases. This figure increased to 5.56% in the second week and substantially rose to 15.3% in the third week. Seven weeks after the initial case, 81.8% of municipalities had reported cases of COVID-19. The highest case numbers were concentrated in the capital’s metropolitan region, specifically in and around Belém.

Contrastingly, the incidence of COVID-19 in Rio Grande do Sul exceeded that of the South region (3,471.7/100,000), with Santa Catarina registering the highest incidence rate at 5,493.6 cases per 100,000 inhabitants. According to the Ministry of Health’s epidemiological bulletin (2020), by the end of the year, Rio Grande do Sul ranked as the third federative unit with the highest number of COVID-19 cases after São Paulo and Santa Catarina. Notably, there was an increase in the number of cases in Rio Grande do Sul (+26%), Santa Catarina (+16%), and Paraná (+11%), collectively representing 15.8% of total COVID-19 cases in Brazil. The municipalities with the highest frequency of new cases were Porto Alegre/Rio Grande do Sul (4,179), Joinville/SC (3,540), and Florianópolis/SC (2,627).

In terms of deaths, in 2020, Pará reported its highest number in May (2,715), while Rio Grande do Sul peaked in December (2,111). The mortality rate in Pará was 83.30 deaths per 100,000 inhabitants, and in Rio Grande do Sul, it was 80.95 deaths per 100,000 inhabitants. Notably, both states had lower mortality rates than the national average of 84 deaths per 100,000 inhabitants. Furthermore, Pará exhibited a lower mortality rate than the North region, with 92 deaths per 100,000 inhabitants. On May 6, the government of Pará declared a lockdown in the capital and in municipalities close to the metropolitan region to reduce human trafficking and try to control the spread of the pandemic27.

In contrast, Rio Grande do Sul had the highest mortality rate in the Brazilian South region. The municipalities with the highest number of deaths from COVID-19 were Porto Alegre, Curitiba, and Blumenau28.

The values of the number of cases and deaths impacted the trend behavior of the analyzed indicators; thus, it is observed that at the end of 2020, the incidence trend was increasing in both Pará and Rio Grande do Sul. Mortality was stationary in Pará and increasing in Rio Grande do Sul, with decreasing lethality in Pará and stationary in Rio Grande do Sul.

The evolution of epidemiological indicators in 2021 in Rio Grande do Sul was marked by an aggressive second wave of the pandemic, the implementation and progress of the vaccination program against COVID-19 conducted by the Unified Health System (Sistema Único de Saúde - SUS), and at the end of December the arrival of the Omicron variant.

The quarter formed by March, April, and May 2021 recorded the highest volume of cases and deaths in Pará and Rio Grande do Sul of the entire period analyzed (table 2). These numbers coincide with national data; in fact, on March 23, 3,251 deaths were recorded in one day in Rio Grande do Sul. One month later, on April 8, Brazil sadly registered a new record in the number of fatalities, recording 4,249 deaths from COVID-19 in 24 hours in Rio Grande do Sul, according to data from CONASS (2021)29.

Table 2 : projection of the population of Brazil and Federation Units by sex and age for the period 2010-2060 (2018 edition) 

Federation Region/Unit 2020 2021 2022
North Region 18.672.591 18.906.962 19.133.894
For 8.690.745 8.777.124 8.861.974
South Region 30.192.315 30.402.587 30.606.047
Rio Grande do Sul 11.422.973 11.466.630 11.507.906

Source: IBGE/Research Directorate. Population Coordination and Social Indicators. Management of Studies and Analysis of Demographic Dynamics (DATASUS, 2023)21,22.

In the subsequent months, from June to November 2021, both Pará and Rio Grande do Sul experienced a decline in cases and deaths from COVID-19. This reduction can be attributed to the consistent implementation of non-pharmacological measures and the successful coverage of the vaccination program in these states. The combination of ongoing public health measures and widespread vaccination played a crucial role in mitigating the impact of the virus during this period.

However, mortality and incidence in 2021 were higher in Rio Grande do Sul than in Pará. The higher incidence rates of COVID-19 in Rio Grande do Sul compared to Pará in 2021 and 2022 were divergent from other studies. The highest incidence rates of COVID-19 occurred in Brazil’s North and Northeast regions, where areas with lower human development converge7.

Pará initiated its vaccination program on January 19, 2021. By September 24 of the same year, it had achieved a vaccination rate of 46.04% for the first dose and 29% for the second or single dose. In contrast, by December 2021, Rio Grande do Sul had a higher vaccination coverage, with 70.3% of the population receiving two doses and 80.9% receiving at least the first vaccine against COVID-1928. These vaccination figures underscore the progress made in immunization efforts in both states, contributing to the observed decline in COVID-19 cases and deaths during the mentioned period. At the national level, by December 2021, Brazil had reached 80% of its target population fully vaccinated30.

The national immunization strategy against COVID-19 was implemented in stages, following the prioritized order of groups defined by the PNI (National Immunization Program)31. The strategy aimed to prioritize individuals at the highest risk of developing severe forms of the disease and facing an increased risk of death. This included specific groups such as health professionals, older adults, institutionalized older people, individuals with comorbidities like hypertension and diabetes mellitus, and those with a high degree of social and economic vulnerability, such as indigenous people, quilombolas, riverside communities, and the population deprived of liberty32. This phased and targeted approach aimed to efficiently and equitably distribute the available vaccines, considering the varying degrees of vulnerability and risk across different population segments.

Mass vaccination against COVID-19 has proven to be an effective weapon in combating the pandemic. The WHO supported more countries to have access to vaccines to prevent people from becoming more seriously ill and, therefore, save more lives.

The increase in COVID-19 cases and deaths observed in both Pará and Rio Grande do Sul in December 2021, continuing into January and February 2022, aligns with the emergence of the Omicron variant. This variant, first identified in South Africa and Botswana in November, was classified as a variant of concern by the World Health Organization33. The designation was due to its numerous mutations34, making it more transmissible than the original strain of the virus. The rise in cases and deaths during this period underscores the challenges posed by the Omicron variant and its potential impact on the trajectory of the COVID-19 pandemic.

Furthermore, at the end of 2021, coinciding with the year-end holiday period, the population felt more confident due to the protection of vaccines, and there was a relaxation in the maintenance of non-pharmacological measures against COVID-19, which favored the spread of the virus in all regions of the country35. The results of this study reflect the reality of other regions of Brazil during January and February 2022. Pará totaled 93,352 cases of COVID-19, and R io Grande do Sul registered 796,948, the highest values of the entire period analyzed. This situation impacted the incidence rates, which were also the highest in the three years analyzed.

The influence of the extensive vaccination program is evident in the December 2022 trends, where mortality decreased in both Pará and Rio Grande do Sul. Despite the significant increase in cases attributed to the Omicron variant, the lethality trend remained stable in both states. The incidence decreased in Pará and remained steady in Rio Grande do Sul for 2022. However, considering the entire period, the incidence shows a consistent trend in both states, indicating the importance of ongoing monitoring of cases and morbidity across various age groups.

In both states, the spread of the virus and the high number of cases and deaths throughout the analyzed period compromised the structure of the public and private health systems due to the exponential increase in primary health services and the need for more complex services that require hospitalization and invasive mechanical ventilation27.

Despite the relevance of these epidemiological data for understanding the evolution of the disease for possible planning following statistics, some factors such as the rapid spread of the virus, the reduced number of tests carried out, especially at the beginning of the pandemic, the asymptomatic cases that often, go unnoticed by the health system, among other conditions, making it difficult to estimate the actual number of cases, generating considerable underreporting throughout the country36.

The evolution of the pandemic is influenced by several factors, where the context of vulnerability is considered a determining factor in the incidence and mortality of COVID-19. In this scenario, it is essential to mention the presence of indigenous groups in each region. According to the last Census carried out by IBGE21, Rio Grande do Sul had a population of approximately 32,989 indigenous people, and Pará had approximately 60,000 people of indigenous origin. These communities are significantly more vulnerable to epidemics because they live in remote locations, with precarious socioeconomic and health conditions, they live in remote places, with a lack of human resources in the health area, and communication limitations due to the native language. Living in collective houses and sharing utensils favors the spread of the virus. It is stated that the indigenous population affected by COVID-19 is underreported37.

The total number of cases and victims and the corresponding incidence, mortality, and lethality caused by the coronavirus during 2020, 2021, and 2022 in Pará and Rio Grande do Sul show three possible pandemic waves. The first occurred between March and November 2020, marked by high circulation of the virus38. The second, from February to July 2021, marked the emergence of several variants, and the third, from December 2021 to December 2022, was characterized by the presence of the Omicron variant. From January 2020 to May 2021, changes in the frequency of dominant lineages were recorded in Brazil, according to data from the Fiocruz Genomic Network. At the beginning of the epidemic, it was mainly driven by the B.1.1.28 and B.1.1.33 lineages, which were the most prevalent until October 202039. After this period, there was an increase in the circulation of two variants of national origin, P.1 and P.2, originating from the B.1.1.28 lineage. Regarding the notification of variants of concern and interest in public health, four variants classified as VOC and two (Zeta and Lambda) of the seven variants classified as VOI by the WHO were registered in Brazil40.

Since the beginning of the pandemic, replacements of variants have been observed, which remained throughout the period analyzed37,41.

Therefore, it is a priority to monitor the behavior of different variants to adjust control measures. According to the Pan American Health Organization40, the best way to contain the spread of the virus, regardless of the variant, is to maintain infection quarantine, patient isolation, physical distancing, use of masks, and vaccination.

This study presents some limitations in the spatial analysis arising from the methodology of ecological studies and secondary database analysis, such as delays in notifications, changes in the household that can cause distortions in the number of cases and deaths per city or municipality, and underreporting cases of the disease.

Furthermore, the results presented are partial data as the pandemic continues to be studied. The number of cases found may be higher, considering the limitations of mass testing for detecting COVID-19.

CONCLUSION

The spread of the virus and the high number of cases and deaths throughout the analyzed period compromised the structure of the health system due to the exponential increase in primary health services.

The positive impact of the vaccination program is reflected in the evolution of the pandemic and the stationary trend in incidence for both States.

REFERENCES

1. Guarnieri CS, Sousa LVA, Paiva LS, Morais TC, Ribeiro MAL, Ribeiro MR, Monteiro CBM. COVID-19 mortality and lethality in the State of Pará, legal Amazon, Brazil. J Hum Growth Dev. 2021; 31(3): 398- 404. DOI: 10.36311/jhgd.v31.12605 [ Links ]

2. Lima DL, Morais TC, Daboin BG, Cavalcanti MPE, Mesaroch A, Silva HMR, Silva CG, Monteiro CBM, Abreu LC. Epidemiological perspective of the evolution of the COVID-19 pandemic in Amapá State, Northern Brazil. J Hum Growth Dev. 2021; 31(3): 414-424. DOI: 10.36311/jhgd.v31.126100 [ Links ]

3. Martire Junior L, Morais TC, Eichemberg JO, Pereira JEG, Cavalcanti MPE, Pereira GAV, Silva HMR, Jacintho LC, Abreu LC. Lethality and mortality of COVID-19 in an important industrial center in Latin America, region of Grande ABC, São Paulo. J Hum Growth Dev. 2021; 31(3): 436-446. DOI: 10.36311/jhgd.v31.12612 [ Links ]

4. Cesar AEM, Daboin BEG, Morais TC, Portugal I, Echeimberg JO, Rodrigues LMR, Jacintho LC, Raimundo RD, Elmusharaf K, Siqueira CE. Analysis of COVID-19 mortality and case-fatality in a low-income region: an ecological time-series study in Tocantins, Brazilian Amazon. J Hum Growth Dev. 2021; 31(3): 496-506. DOI: 10.36311/jhgd.v31.12744 [ Links ]

5. Trivilato RA, Morais TC, Daboin BEG, Cavalcanti MPE, Jacintho LC, Raimundo RD, Echeimberg JO, Elmusharaf K, Siqueira CE, Figueiredo JL. Mortality and case fatality rates of COVID-19 in the State of Goiás, Brazil. J Hum Growth Dev. 2021; 31(3): 521-532. DOI: 10.36311/jhgd.v31.12781 [ Links ]

6. Daboin BEG, Bezerra IMP, Morais TC, Portugal I. Echeimberg JDO, Cesar AEM, Cavalcanti MPE, Jacintho LC, Raimundo RD, Elmusharaf K.; et al. Deciphering Multifactorial Correlations of COVID-19 Incidence and Mortality in the Brazilian Amazon Basin. Int. J. Environ. Res. Public Health 2022, 19, 1153. DOI: https://doi.org/10.3390/ijerph19031153Links ]

7. Castro RR et al. (2021). Spatial dynamics of the COVID-19 pandemic in Brazil. Epidemiology and infection, 149, e60. DOI: https://doi. org/10.1017/S0950268821000479Links ]

8. Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Centro de Operações de Emergências em Saúde Pública. Doença pelo coronavírus 2019: ampliação da vigilância, medidas não farmacológicas e descentralização do diagnóstico laboratorial. Bol Epidemiol [Internet]. 2020. [ Links ]

9. Salian VS, Wright JA et al. Transmissão COVID-19, tratamento atual e estratégias terapêuticas futuras. Mol Pharm. 2021; 18 (3): 754-771. DOI: 10.1021/acs.molpharmaceut.0c00608 [ Links ]

10. Brandão AS et al. COVID-19 e complicações neurológicas: uma pequena revisão sistemática. Revista Neurociências, v. 29, p. 1-16, 2021. [ Links ]

11. Souza BAB, Tritany ÉF. COVID-19: importância das novas tecnologias para a prática de atividades físicas como estratégia de saúde pública. Cadernos de Saúde Pública [online]. v. 36, n. 5. Disponível em: https://doi.org/10.1590/0102-311X00054420Links ]

12. World Health Organization. WHO announces COVID-19 outbreak a pandemic. 2023. [ Links ]

13. Muralidar S, Ambi SV, Sekaran S, Krishnan UM. The emergence of COVID-19 as a global pandemic: Understanding the epidemiology, immune response and potential therapeutic targets of SARS-CoV-2. Biochimie. 2020 Dec; 179:85-100. DOI: 10.1016/j.biochi.2020.09.018. Epub 2020 September 22. [ Links ]

14. WHO Coronavirus (COVID-19) Dashboard. Disponível em: https://covid19.who.int Acesso em: 9 fev. 2022. [ Links ]

15. Abreu LC, Raimundo RD, Pérez-Riera AR, Bezerra IMP, Tristan-Cheever E, Atrash HK. Three urgent needs in the battle against COVID-19: specific medications, information and acceptance of pandemic. J Hum Growth Dev. 2021; 31(3): 371-375. DOI: 10.36311/jhgd.v31.12794 [ Links ]

16. Leitão FNC, Ferreira CRT, de Abreu KL, de Deus MBB, Junior HM, Morais MJD. Effects of the social isolation generated by Covid-19 on the quality of life of the population in Rio Branco - Acre and Santo André - São Paulo, Brazil. J Hum Growth Dev. 2021; 31(3): 405-413. DOI: 10.36311/jhgd.v31.12609 [ Links ]

17. Zeger SL, Irizarry R, Peng RD. On time series analysis of public health and biomedical data. [ Links ]

18. Abreu LC et al. A time-series ecological study protocol to analyze trends of incidence, mortality, lethality of COVID-19 in Brazil. Journal of Human Growth and Development, v. 31, n. 3, p. 491-495, dez. 2021. DOI: 10.36311/jhgd.v31.12667 [ Links ]

19. Ministério da Saúde - Link: https://covid.saude.gov.br/Links ]

20. World Health Organization. (‎2020)‎. Laboratory testing strategy recommendations for COVID-19: interim guidance, March 21 2020. World Health Organization. License: CC BY-NC-SA 3.0 IGO Disponível em: Acesso em 27 de março de 2020 [ Links ]

21. IBGE. Instituto Brasileiro de Geografia e Estatística. 2023 - Disponível em: https://www.ibge.gov.br/cidades-e-estados/Links ]

22. DATASUS. Ministério da Saúde. 2023. Disponível em: http://tabnet.datasus.gov.br/cgi/deftohtm. exe?ibge/cnv/projpopuf.defLinks ]

23. Antunes, José Leopoldo Ferreira; CARDOSO, Maria Regina Alves. Uso da análise de séries temporais em estudos epidemiológicos. Epidemiologia e Serviços de Saúde, v. 24, p. 565-576, 2015. [ Links ]

24. Painel Coronavírus em 12 de janeiro de 2023, disponível em:< https://covid.saude.gov.br/> [ Links ]

25. Cardoso P, Seabra V, Bastos I, Porto Costa E. (2020). A IMPORTÂNCIA DA ANÁLISE ESPACIAL PARA TOMADA DE DECISÃO: UM OLHAR SOBRE A PANDEMIA DE COVID-19. Revista Tamoios, 16(1). DOI: https://doi.org/10.12957/tamoios.2020.50440Links ]

26. Mariano B, Torres M, Almeida D, Ferraz D et al. "Brazilian states in the context of COVID-19 pandemic: an index proposition using Network Data Envelopment Analysis," in IEEE Latin America Transactions, vol. 19, no. 6, pp. 917-924, June 2021, DOI: 10.1109/TLA.2021.9451236. [ Links ]

27. Lélis SF, Dias Pita J, Gomes MDA et al. Intraregional propagation of Covid-19 cases in Pará, Brazil: assessment of isolation regime to lockdown. Epidemiol Infect. 2021 February 16;149:e72. DOI: 10.1017/S095026882100039X. Erratum in: Epidemiol Infect. 2021 Apr 22; 149: e93. [ Links ]

28. BOLETIM EPIDEMIOLÓGICO ESPECIAL - Secretaria de Vigilância em Saúde - Ministério da Saúde. Disponível em: https://www.gov.br/saude/pt-br/centrais-de-conteudo/publicacoes/boletins/ epidemiologicos/covid-19/2020/boletim_epidemiologico_covid_40-1.pdfLinks ]

29. Conselho Nacional de Secretários de Saúde (CONASS). 2021. Disponível em: https://www.conasems.org.br/wp-content/uploads/2021/04/Covid-19_guia_orientador_4ed.pdfLinks ]

30. INSTITUTO BUTANTAN- Portal Butantan- Retrospectiva 2021. Disponível em: https://butantan.gov.br/ noticias/retrospectiva-2021-segundo-ano-da-pandemia-e-marcado-pelo-avanco-da-vacinacao-contra- covid-19-no-brasilLinks ]

31. MINISTÉRIO DA SAÚDE. Boletim Epidemiológico No 99 - Boletim COE Coronavírus - português (Brasil). [ Links ]

32. ANVISA- Saúde e Vigilância Sanitária. Disponível em: https://www.gov.br/anvisa/pt-br/assuntos/noticias-anvisa/2020/fique-por-dentro-do-mapa-das-vacinas-em-teste-no-brasil. Acesso em 01/02/2023 [ Links ]

33. ONU. Nações Unidas. OMS: É prematuro declarar vitória contra Covid-19. ONU News. Perspectiva Global Reportagens Humanas. Disponível em: https://news.un.org/pt/story/2022/02/1778362. Acesso em: 9 fev. 2022. [ Links ]

34. Campos SG, et al. SARS-CoV-2 epidemic in Brazil: how variants displacement have driven distinct epidemic waves Genomic monitoring unveils a high prevalence of SARIO GRANDE DO SUL-CoV-2 Omicron variant in vaccine breakthrough cases. MedRxiv. 2022. DOI: 10.1101/2022.02.16.22271059 [ Links ]

35. Lamarca AP. et al. The Omicron Lineages BA.1 and BA.2 (Betacoronavirus SARS-CoV-2) Have Repeatedly Entered Brazil through a Single Dispersal Hub. Viruses 2023, 15, 888. DOI: https://doi. org/10.3390/v15040888Links ]

36. Veloso JCS et al. A PANDEMIA DA COVID-19 NO BRASIL: INVESTIGAÇÃO DA SUBNOTIFICAÇÃO DE CASOS. In: Congresso Internacional em Saúde. 2021. [ Links ]

37. Santos RV, Pontes AL and Coimbra CEA Jr (2020) Um "fato social total": COVID-19 e povos indígenas no Brasil. Cadernos de Saúde Pública [Internet] 36(10), e00268220. DOI: https://doi.org/10.1590/0102- 311X00268220Links ]

38. Giovanetti, M et al. (2022). Genomic epidemiology of the SARS-CoV-2 epidemic in Brazil. Nature Microbiology, 7(9), 1490-1500. DOI: https://doi.org/10.1038/s41564-022-01191-zLinks ]

39. Candido DS et al. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science (80-) [Internet]. 2020 Sep 4; 369(6508): 1255-60. Disponível em: https://www.sciencemag.org/lookup/doi/10.1126/ science.abd2161Links ]

40. OPAS. Organizacion Panamericana de la salud. 2021. Disponível em: https://www.paho.org/pt/noticias/4- 8-2021-diretora-da-opas-pede-que-paises-priorizem-comunidades-indigenas-nas-respostasLinks ]

41. Junior LC., et al. (2022). SARS-CoV-2 epidemic in Brazil: How the displacement of variants has driven distinct epidemic waves. Virus Research, 315, 198785. DOI: https://doi.org/10.1016/j. virusres.2022.198785Links ]

Received: May 2023; Accepted: August 2023; Published: December 2023

Corresponding author celiaguarnieris@gmail.com

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