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\begin{document}

\title{Impact of Variants, Epidemiological Trends, and Comorbidities on
Hospitalization Rates of Unvaccinated Children in Brazil: A
Retrospective Study (2020-2022)}



\author[1]{DANIELLE DIAS CONTE}%
\author[1]{Rai Watanabe Silva}%
\author[1]{Ana  Cunha Chaves}%
\author[1]{Felipe Lei}%
\author[2]{Ana Perosa}%
\author[3]{Gabriela  Barbosa}%
\author[4]{Nancy Cristina Bellei}%
\affil[1]{Universidade Federal de Sao Paulo}%
\affil[2]{Sao Paulo Federal University}%
\affil[3]{Universidade Federal de São Paulo}%
\affil[4]{ Federal University of São Paulo}%


\vspace{-1em}



  
  \date{May 18, 2024}


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\selectlanguage{english}
\begin{abstract}
This retrospective study aimed to investigate the impact of the
emergence of new variants and the epidemiological scenario on
hospitalization rates of unvaccinated children (0-12 years) in Brazil.
The study included 1,614 children admitted to a hospital between March
2020 and December 2022, with only 101 (6.3\%) of them testing positive
for COVID-19 via RT-PCR. The frequency of COVID-19 cases increased from
7.5\% in 2020 to 9.3\% in 2022 with the emergence of the Omicron
variant. Children over five years old with comorbidities accounted for
the majority of cases (69\% {[}70/101{]}). Sickle cell anemia was the
most frequent comorbidity (20\%), and flu disease (36\% {[}36/101{]})
and decompensation of underlying disease (33\% {[}33/101{]}) were the
main reasons for hospitalization. Co-infection was detected in 11\% of
cases, with RSV being the most common viral pathogen (71\%). Hospital
readmission occurred in 26\% of cases, with a higher frequency in
children over five years old. The death rate was 2.2\%, with
comorbidities such as cystic fibrosis and congenital heart disease as
risk factors. These findings emphasize the need to prioritize
vaccination with monovalent Omicron XBB for high-risk groups, including
children over five years old with comorbidities, to mitigate the impact
of new variants and reduce severe disease outcomes.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Since the beginning of the pandemic, epidemiologic data have shown that
hospitalization of children and adolescents associated with the severe
acute respiratory syndrome (SARS) due to COVID -19 has not significantly
impacted this population. They differ from the elderly and adult
population with comorbidities, which are specially more susceptible to
severe disease progression and complications. (1)

In children, several factors contributed to milder infection, which
reduces the number of the significant receptor angiotensin-converting
enzyme 2 (ACE2) on the cell surface, resulting in less availability of
the receptor, and the presence of other respiratory viruses competing
simultaneously and limiting replication of different viruses. In
neonates and infants, maternal antibodies provide protective immunity
against disease (2,3).

In Brazil, the incidence of SARS associated with COVID -19 totaled
20.846 cases and 856 deaths in the age group between 0 and 19 years by
epidemiological week 51 of 2022 (3). In this context, it can also be
observed that children were not initially affected by SARS-CoV-2 as much
as in the 2009 pandemic caused by H1N1. (4)

It should be noted that the government took several preventive measures
to reduce transmission rates in the early stages of the pandemic and
after the initial outbreak in Brazil. This dramatically impacted the
child population, as schools were closed and classes moved to remote
locations, as well as the introduction of social distancing (lockdown),
the use of masks, increased availability of Covid-19 testing, and the
establishment of field hospitals.

However, after two years of the pandemic, the return of social
activities, and the emergence of new variants, among other factors such
as mass vaccination of the adult population and the characterization of
a new variant of concern called \selectlanguage{ngerman}Ômicron in late 2021, there has been an
increase in confirmed cases of hospitalized children associated with
this new variant and its subtype.

\textbf{Methodology}

In this retrospective study, 1614 hospitalizations of children aged up
to 12 years at Hospital São Paulo (HSP) were tested for COVID -19 using
the polymerase chain reaction method (RT-PCR) from March 2020 to
December 2022. Hospitalization data were collected regarding the main
reason for hospitalization, underlying medical conditions, indicators of
severe disease (length of hospitalization, ICU stay and death), viral
load (Ct value), cases of hospital readmission within 6 months, and
variant wave.

Coinfection with other respiratory viruses during this period was
detected by molecular testing (RT-PCR) for human metapneumovirus (hMPV),
human respiratory tract infection (hRSV), influenza A (FLU -A) and B
(FLU -B), adenovirus (HAdV), and human rhinovirus (HRV). Simple logistic
regression models (for categorical and numerical variables), linear
regression and Pearson's chi-square (numerical variables) were used for
statistical analysis.

To evaluate the frequency of this infection in this population, we
categorized the age of patients in the following ranges: \textless{} 1
year, 1 -\textbar{} 2 years, 2 -\textbar{} 5 years and \textgreater{}
five years.

\textbf{Results}

The study reports the results of a COVID-19 test in 1614 hospitalized
children, the age range of the children ranged from 0 to 12 years, Me=
3.97; Md= 3; SD +/- 3.97 and IQR (1 - 8) years with a confirmation rate
of 6.3\% (101/1614). Men accounted for 59\% of the cases of infection.
There was no correlation between sex and positive cases of this
population. (Table 1)

Group of 1 -\textbar{} 2 years of age had the lowest frequency of cases
of COVID-19 infection among age groups, demonstrating statistical
significance among these ages. Children aged under one year were 2.54
times more likely to be infected, 2 -l 5 years of age with 2.44 times
more and those older than five years were 2.88 times more likely to be
infected by this disease. Age showed a significant difference (p 0.044;
OR = 1.10; CI 95\% (1.00-1.10)) children over one year of age are 10\%
more likely to become infected with COVID-19 each year more than life.
(Table 1)

There was no statistically significant association between COVID-19
infection and the following causes, comorbidities, hospitalization, ILI
syndrome, ICU and high viral (CT value). (Table 2)

Table 1: Characteristics of the study population\selectlanguage{english}
\begin{longtable}[]{@{}llllllllll@{}}
\toprule
\textbf{Characteristic} & \textbf{Overall (\%)} & \textbf{Overall (\%)}
& \textbf{SARS-CoV-2 test result} & \textbf{SARS-CoV-2 test result} &
\textbf{SARS-CoV-2 test result} & \textbf{SARS-CoV-2 test result} &
\textbf{Odds Ratio (IC)} & \textbf{Odds Ratio (IC)} &
\textbf{p-valuer}\tabularnewline
\midrule
\endhead
& & & \textbf{Negative (\%)} & \textbf{Negative (\%)} & \textbf{Positive
(\%)} & \textbf{Positive (\%)} & & &\tabularnewline
& \textbf{n~=~1.614} & \textbf{n~=~1.614} & \textbf{n~=~1.513 (93.7)} &
\textbf{n~=~1.513 (93.7)} & \textbf{n~=~101 (6.3)} & \textbf{n~=~101
(6.3)} & & &\tabularnewline
\textbf{Sex} & \textbf{Sex} & \textbf{Sex} & \textbf{Sex} & \textbf{Sex}
& \textbf{Sex} & \textbf{Sex} & \textbf{Sex} & \textbf{Sex} &
\textbf{Sex}\tabularnewline
Male & 892 (55.2) & 892 (55.2) & 832 (54.9) & 832 (54.9) & 60 (59.4) &
60 (59.4) & & &\tabularnewline
\textbf{Age (years)} & median 3 (IQR =1-8) & median 3 (IQR =1-8) &
median 3 (IQR =1-8) & median 3 (IQR =1-8) & Median 6 (IQR 1-10) & Median
6 (IQR 1-10) & 1.10 (1.00 -- 1.10) & 1.10 (1.00 -- 1.10) & 0.044
\textsuperscript{a}\tabularnewline
\textbf{Age-group (years)} & \textbf{Age-group (years)} &
\textbf{Age-group (years)} & \textbf{Age-group (years)} &
\textbf{Age-group (years)} & \textbf{Age-group (years)} &
\textbf{Age-group (years)} & & &\tabularnewline
\textless{} 1 years & 378 (23.4) & 378 (23.4) & 352 (93.1) & 352 (93.1)
& 26 (6.8) & 26 (6.8) & 2.54 (1.20 -- 5.35) & 2.54 (1.20 -- 5.35) &
0.014\tabularnewline
1 -\textbar{} 2 years & 354 (21.9) & 354 (21.9) & 344 (97.1) & 344
(97.1) & 10 (2.8) & 10 (2.8) & REF\textsuperscript{B} &
REF\textsuperscript{B} & REF\textsuperscript{B}\tabularnewline
2 -\textbar{} 5 years & 286 (17.7) & 286 (17.7) & 267 (93.3) & 267
(93.3) & 19 (6.6) & 19 (6.6) & 2.44 (1.12 -- 5.35) & 2.44 (1.12 -- 5.35)
& 0.025\tabularnewline
\textgreater{} 5 years & 596 (36.9) & 596 (36.9) & 550 (92.2) & 550
(92.2) & 46 (7.7) & 46 (7.7) & 2.88 (1.43 -- 5.78) & 2.88 (1.43 -- 5.78)
& 0.003\tabularnewline
\textbf{Distribution per years} & \textbf{Distribution per years} &
\textbf{Distribution per years} & \textbf{Distribution per years} &
\textbf{Distribution per years} & \textbf{Distribution per years} &
\textbf{Distribution per years} & & &\tabularnewline
\textbf{2020} & \textbf{307 (19.0)} & \textbf{307 (19.0)} & \textbf{284
(92.5)} & \textbf{284 (92.5)} & \textbf{23 (7.5)} & \textbf{23 (7.5)} &
2.2 (1.24 - 3.90) & 2.2 (1.24 - 3.90) & 0.007\tabularnewline
\textless{} 1 years & 65 & 65 & 61 & 61 & 4 (6.5) & 4 (6.5) & &
&\tabularnewline
1 -\textbar{} 2 years & 75 & 75 & 73 & 73 & 2 (2.66) & 2 (2.66) & &
&\tabularnewline
2 -\textbar{} 5 years & 59 & 59 & 54 & 54 & 5 (9.47) & 5 (9.47) & &
&\tabularnewline
\textgreater{}5 years & 108 & 108 & 96 & 96 & 12 (11.11) & 12 (11.11) &
& &\tabularnewline
\textbf{2021} & \textbf{762 (47.2)} & \textbf{762 (47.2)} & \textbf{735
(96.4)} & \textbf{735 (96.4)} & \textbf{27 (3.5)} & \textbf{27 (3.5)} &
REF & REF & -\tabularnewline
\textless{} 1 years & 213 & 213 & 208 & 208 & 5 (2.34) & 5 (2.34) & &
&\tabularnewline
1 -\textbar{} 2 years & 160 & 160 & 159 & 159 & 1 (0.62) & 1 (0.62) & &
&\tabularnewline
2 -\textbar{} 5 years & 118 & 118 & 113 & 113 & 5 (4.23) & 5 (4.23) & &
&\tabularnewline
\textgreater{}5 years & 271 & 271 & 255 & 255 & 16 (5.9) & 16 (5.9) & &
&\tabularnewline
\textbf{2022} & \textbf{545 (33.7)} & \textbf{545 (33.7)} & \textbf{494
(90.6)} & \textbf{494 (90.6)} & \textbf{51 (9.3)} & \textbf{51 (9.3)} &
2.81 (1.73 - 4.54) & 2.81 (1.73 - 4.54) & \textless{}001\tabularnewline
\textless{} 1 years & 100 & 100 & 83 & 83 & 17 (17) & 17 (17) & &
&\tabularnewline
1 -\textbar{} 2 years & 109 & 109 & 102 & 102 & 7 (6.42) & 7 (6.42) & &
&\tabularnewline
2 -\textbar{} 5 years & 119 & 119 & 110 & 110 & 9 (7.56) & 9 (7.56) & &
&\tabularnewline
\textgreater{}5 years & 217 & 217 & 199 & 199 & 18 (8.29) & 18 (8.29) &
& &\tabularnewline
\bottomrule
\end{longtable}

Estimated odds ratio and p-valuer using simple logistic regression model
(age -years) \textsuperscript{a} and binominal logistic regression
(age-group and population of Years) \textsuperscript{b.}~Ref.,
reference.

The main reason for hospitalization was flu disease (IL) with 36\%
(36/101), decompensation of the underlying disease 33\% (33/101) and
other causes not related to risk factors for COVID-19 was 32\% (32/101).
(Table 2)

69\% (70/101) of patients had underlying comorbidities as a risk factor
for COVID -19, and the most common comorbidities were sickling cell
anemia (20\%), heart disease (12\%), asthma (9.7\%), and diabetes
(9.7\%).\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
Table 2. Characteristics of positive cases & Table 2. Characteristics of
positive cases & & & &\tabularnewline
\midrule
\endhead
\textbf{Overall (\%)} & \textbf{Overall (\%)} & \textbf{Overall (\%)} &
\textbf{Overall (\%)} & \textbf{Overall (\%)} & TOTAL
(\%)\tabularnewline
& \textbf{\textless{} 1 years} & \textbf{1 -\textbar{} 2 years} &
\textbf{2 -\textbar{} 5 years} & \textbf{\textgreater{} 5 years}
&\tabularnewline
\textbf{Comorbidities} & \textbf{Comorbidities} & \textbf{Comorbidities}
& \textbf{Comorbidities} & \textbf{Comorbidities} &
\textbf{Comorbidities}\tabularnewline
& 12/70 (17) & 7/70 (10) & 13/70 (19) & 38/70(54) &
70/101(69)\tabularnewline
\textbf{Intensive care unit} & \textbf{Intensive care unit} &
\textbf{Intensive care unit} & \textbf{Intensive care unit} &
\textbf{Intensive care unit} & \textbf{Intensive care
unit}\tabularnewline
& 6/17 (35) & 2/17 (12) & 2/17(12) & 7/17 (41) & 17/101
(17)\tabularnewline
\textbf{Hospital admission} & \textbf{Hospital admission} &
\textbf{Hospital admission} & \textbf{Hospital admission} &
\textbf{Hospital admission} & \textbf{Hospital admission}\tabularnewline
Influenza like illness & 13/36 (36) & 3/36 (8) & 2/36(6) & 18/36 (50) &
36/101(36)\tabularnewline
Decompensation of the underlying disease & 6/33(18) & 4/33(12) &
8/33(24) & 15/33(46) & 33/101(33)\tabularnewline
Other causes & 7/32(22) & 3/32(9) & 9/32(28) & 13/32(41) &
32/101(32)\tabularnewline
\textbf{Hospitalized readmission} & \textbf{Hospitalized readmission} &
\textbf{Hospitalized readmission} & \textbf{Hospitalized readmission} &
&\tabularnewline
& 3/26 (11.5) & 6/26 (23.1) & 5/26(19.2) & 12/26(46.2) &
26/101(26)\tabularnewline
\textbf{Coinfection cases} & \textbf{Coinfection cases} &
\textbf{Coinfection cases} & \textbf{Coinfection cases} &
\textbf{Coinfection cases} & \textbf{Coinfection cases}\tabularnewline
& 7/11(64) & 1/11 (9) & 1/11(9) & 2/11(18) & 11/101 (11)\tabularnewline
\bottomrule
\end{longtable}

The hospitalization time ranged from 1 to 240 days (Me= 13.7; SD +/-
31.85; Md= 6; IQR (4-9) days). The length of stay in the ICU ranged from
1 to 40 days (Me= 9.14; SD +/- 10.84; IQR (3-10) days). Only 17\%
(17/101) of the patients required ICU (Me= 4.9; SD+/- 4.27; Md= 4; IQR
(3 -10). Among these cases, 24\% (4/17) of the patients were
hospitalized due to decompensation of the underlying disease, and the
highest hospitalization rate was due to flu syndrome, representing 47\%
(8/17) of ICU patients. However, there was no correlation between the
time of hospitalization and the ICU admission with age ILI syndrome.

Regarding the viral load (CV) of the patient, CT was used as a proxy,
which is inversely proportional to the CVs, that is, the lower the CT,
the higher the CV. The general CT of the patients presented Me=27.57
DP+/- 6.71; Md= 29; IQR (22 - 34).

Hospitalization for ILI had CT value of Me=25.17 SD +/- 6.42 Md=25; IQR
(20.5- 31), the decompensation of the underlying disease a CT value of
Me = 29.27 SD +/- 6.72 Md = 33 IQR (23-35) and for other factors value
of Me = 28 SD +/- 6.21; Md=30.5 IQR (24-33.5). There was only a
statistically significant association between ILI and CT value (p=
0.028; OR =1.072; CI 95\% (1.00 - 1.14)). That is, for each point lower
than CT, it is 1.07 times more likely to be hospitalized for ILI.

The last two data evaluated were deaths and hospital cases readmission.
Death was approximately 2\% (2/101) of the cases, both of which had
comorbidities. One case occurred in 2021, the patient had cystic
fibrosis; hospitalization was due to the EG and remained in the ICU
until death. The other case occurred in 2022; the patient with
congenital heart disease was admitted for decompensation of the
underlying disease.

Hospital readmission occurred in 26\% (26/101) of the cases, with higher
frequency in children over 5 years (46\%) of the cases (p=0.0047; OR
4.25; CI95\% (1.02-17.69).

The frequency of COVID-19 cases among the years analyzed 2020, 2021 and
2022 was 7.5\% (23/307), 3.5\% (27/762) and 9.3\% (51/545),
respectively.

In the analyses between years in relation to COVID-19 infection, it
shows that in 2020 and 2022 there was a significant association in
relation to 2021. (Table 1) That is, children hospitalized in 2020 and
2022 had 2.2 and 2.8 times more chances of this infection occurring than
those hospitalized in 2021.

The frequency of cases of viral coinfection during this period was 11\%
(11/101). Only three of these pathogens were detected. RSV received 64\%
(7/11), four cases (\textless{} 1 year), one case (2 -\textbar{} 5
years), and two cases (\textgreater{} five years). HRV was detected in
three cases, 27\% (3/11), when the children were seven months old, and
the detection of Flu-A was 9\% (1/11) the child was two years old.

The following graph (figure 1) shows positive cases of age groups and
their monthly distribution since the beginning of the pandemic. The
peaks of cases in children younger than five years correspond to the
emergence and spread of new variants in Brazil, while in children older
than five years, beyond these peaks, there is a continuous detection for
all these periods.

\textbf{Discussion}

In this cross-sectional study, the characteristics of the population of
children up to 12 years of age hospitalized and diagnosed with COVID-19
in HSP were evaluated. It is noteworthy that patients treated and
hospitalized in the HSP are very complex. In this analysis, it was found
that a portion of the population was eligible to be vaccinated, but none
had completed vaccination during hospitalization. vaccination for
children between 5 and 11 years of age had not been approved until the
beginning of 2022 and for children between 6 months and four years of
age until the end of last year. Since the onset of this pandemic,
children have not been as susceptible to the virus as adults or the last
pandemic in 2009, which was caused by the H1N1 influenza virus and
severely affected children at the time. (5).

However, this scenario has changed, possibly due to the high vaccination
coverage in the adult and elderly population, immunization of children
older than 12 years until the end of 2021, the end of quarantine and the
emergence of new variants.

In this new context, our study children up to 11 years of age became
more susceptible to the new circulating variant of omicron. A recent
study reported a change in the current pandemic scenario, showing a
significant increase in the proportion of pediatric cases after the
emergence of the Omicron variant, rising from \textgreater{} 2\% at the
beginning of the pandemic to 25\% by March 2022 (4).

As observed in our study, most patients were hospitalized for other
causes or underlying diseases with an influenza-like illness. Only a few
cases required more intensive treatment or had a more severe clinical
outcome.

Other studies, such as Zhu's, report that although most cases are
lighter, children with underlying conditions are at higher risk of
developing severe symptoms of the disease. (4) In Brazil, one study
reported that approximately 40\% of the pediatric population had at
least one chronic condition, 14.6\% (associated with neurological
conditions) and 14.2\% of children diagnosed with two or more chronic
conditions as a risk factor for COVID-19. (5)

Evaluating this population, our findings show that the most affected
individuals were children older than five years of age. As age
increases, so does the likelihood of infection. This is consistent with
other studies, such as Siegel et al., which have shown over time that
children aged 12 to 17 years are more susceptible to this infection,
followed by the age group of 5 to 11 years and those under four years of
age. (6) In the United States, the percentage of general
hospitalizations related to COVID-19 in children was 36\%, with the
highest rate in the \textgreater{} 2 age group (32.7\%), followed by 2
to 4 years (8.7\%), 5 to 11 years (16.8\%). The highest rate was in the
age group from 12 to 17 years (41.8\%). The rate of ICU admissions was
approximately 33\%, with only one death. (7)

Data released by the CDC in March of this year through the COVID-NET
network, which conducts surveillance of hospitalizations in the United
States, show an increase in hospitalizations in the 0-4 age group, with
85\% of these cases attributable to COVID -19. Among these cases, 37\%
had one or more underlying conditions. (8) This differs from our data,
which showed that detection was more common in the \textless{} 5 age
group, and the incidence of underlying disease or comorbidities was
approximately 69\%.

The cases of coinfection we presented were low (11\%) compared with
other studies. Wu et al. analyzed COVID -19 coinfections in 74 confirmed
children positive for this pathogen. As a result, 34 (45.95\%) patients
were positive for the cold virus, and 19 (51.35\%) had coinfection with
pathogens other than SARS-CoV-2. (9).

Our study showed that children older than five years are more likely to
test positive for COVID-19. The group with the lowest frequency of this
infection was between 1 -\textbar{} 2 years old. Kolla's study et.al.
2022, suggests that, in children between these ages, vaccines against
the tuna virus may confer a protective factor against other viruses,
such as SARS-CoV-2, so this probably influenced the lower frequency of
cases. The main aged virus vaccines used in this range are quadrivalent
viral and poliomyelitis 1 and 3. (10)

Results in the literature usually show a lighter form of the disease in
most cases. However, it is worth mentioning that additional research is
needed in this population, as the number of cases has changed
significantly from the beginning of this pandemic to the current
scenario. With the natural evolution of SARS-CoV-2, due to evolutionary
pressure, the emergence of new variants and subtypes and the increase in
cases among children, such as what happened after the Omicron variant.
Therefore, it is difficult to predict the impact of this disease on
children over time and its effect on the seasonality of other
respiratory viruses and epidemiological control in this population.''

In conclusion, after the evolution of SARS-CoV-2, children were finally
impacted, as expected compared to other respiratory viruses. We
demonstrated that most of the hospitalized cases presented with
comorbidities especially patients with sickle cell anemia, a group that
was frequently readmitted suggesting that those children should be
contemplated with strong program of immunization. Omicron variant caused
the highest rate of hospitalization which is implicated in the best
formulation should be used among children. In this sense, the new
monovalent vaccine with \selectlanguage{ngerman}Ômicron XBB, may be the best options for them
particularly for those with comorbidities.

\textbf{Institutional Review Board Statement:}

The study was conducted in accordance with the Declaration of Helsinki
and approved by the Research Ethics Committee from Universidade Federal
de São Paulo (UNIFESP)/HSP (process number CEP 29407720.4.0000.5505).

\textbf{Data Availability Statement}

The data that support the findings of this study are available on
request from the corresponding author. The data are not publicly
available due to privacy or ethical restrictions.

\textbf{Conflicts of Interest:}

The authors declare no conflicts of interest.

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\textbf{Hosted file}

\verb`Figure 1.docx`  available at \url{https://authorea.com/users/669938/articles/670169-impact-of-variants-epidemiological-trends-and-comorbidities-on-hospitalization-rates-of-unvaccinated-children-in-brazil-a-retrospective-study-2020-2022}

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