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\begin{document}

\title{Determinants of school absences due to respiratory tract infections
among children during COVID-19 pandemic: a cross-sectional study of the
Sentinel Schools Network}



\author[1]{Antoni Soriano-Arandes}%
\author[2]{Andreu Colom-Cadena}%
\author[2]{Anna Bordas}%
\author[2]{Fabiana Ganem}%
\author[3]{Lucia Alonso}%
\author[2]{Marcos Montoro}%
\author[4]{Mireia Gascon}%
\author[4]{Maria Subirana}%
\author[5]{Ariadna Mas}%
\author[4]{Jordi Sunyer}%
\author[1]{Pere Soler Palacín}%
\author[2]{Jordi Casabona}%
\affil[1]{Hospital Universitari Vall d'Hebron}%
\affil[2]{CEEISCAT}%
\affil[3]{IGTP}%
\affil[4]{ISGlobal}%
\affil[5]{Institut Català de la Salut}%


\vspace{-1em}



  
  \date{June 18, 2024}


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\selectlanguage{english}
\begin{abstract}
We aimed to assess the association of household and classroom
determinants with students' school absence due to respiratory tract
infections (RTI) among 253 students (4-11 years) of 20 classrooms. We
collected 71 absences; RTI incidence was very high during the study
period, 17.5-33.1 cases per 100 population. Having someone else at home
with respiratory symptoms was the most significant epidemiological
factor (OR=9.12, CI 95\%=2.54-33.39), suggesting that households are
crucial for the transmission of RTI to the children. A positive but not
statistically significant association was observed between higher median
levels of CO2 and respiratory-related absences (OR=1.2, CI
95\%=0.98-1.46).%
\end{abstract}%



\sloppy


\textbf{Title:} Determinants of school absences due to respiratory tract
infections among children during COVID-19 pandemic: a cross-sectional
study of the Sentinel Schools Network.

\textbf{Short running title:} School absences and respiratory infections

Antoni Soriano-Arandes\textsuperscript{1,*,*}, Andreu
Colom-Cadena\textsuperscript{2,3,*}, Anna Bordas\textsuperscript{2,3},
Fabiana Ganem\textsuperscript{2,3,4}, Lucia Alonso\textsuperscript{3,5},
Marcos Montoro\textsuperscript{2,3}, Mireia
Gascon\textsuperscript{6,7,8}, Maria Subirana\textsuperscript{6,7,8},
Ariadna Mas\textsuperscript{9}, Jordi Sunyer\textsuperscript{6,7,8},
Pere Soler-Palacin\textsuperscript{1}, Jordi
Casabona\textsuperscript{2,3,4,8} ; on behalf of Sentinel School Network
of Catalonia*

\begin{enumerate}
\tightlist
\item
  Paediatric Infectious Diseases and Immunodeficiencies Unit. Children's
  Hospital. Vall d'Hebron Barcelona Hospital Campus, Barcelona,
  Catalonia, Spain.
\item
  Centre d'Estudis Epidemiol\selectlanguage{ngerman}ògics sobre les ITS i Sida de Catalunya
  (CEEISCAT). Badalona, Spain.
\item
  Institut d'Investigació Germans Trias i Pujol (IGTP), Badalona, Spain.
\item
  Departament de Pediatria, d'Obstetrícia i Ginecologia i de Medicina
  Preventiva i de Salut Publica, Universitat Autònoma de Barcelona,
  Bellaterra, Spain.
\item
  Fundació Lluita contra les infeccions, Badalona, Spain.
\item
  ISGlobal, Barcelona. Spain.
\item
  Universitat Pompeu Fabra (UPF), Barcelona, Spain
\item
  Centro de Investigación Biomédica en Red de Epidemiología y Salud
  Pública (CIBERESP) Instituto de Salud Carlos III, Madrid, Spain.
\item
  Direcció Assistencial d'Atenció Primària i Comunitària, Institut
  Català de la Salut, Barcelona, Catalonia, Spain
\end{enumerate}

\selectlanguage{english}\textsuperscript{*} Contributed equally to this work with: Antoni
Soriano-Arandes, Andreu Colom-Cadena

\selectlanguage{english}* Corresponding author: Antoni Soriano-
Arandes,\emph{toni.soriano@vallhebron.cat}. ORCID: 0000-0001-9613-7228

\textbf{Statements and Declarations}

\emph{Funding}

This work was supported by the Health Department of the Government of
Catalonia with no grant number. The funders had no role in study design,
data collection and analysis, decision to publish, or preparation of the
manuscript. AS-A, FG, AB, LA and ACC received a salary from the
abovementioned funder.

\emph{Competing Interests}

The authors have no relevant financial or non-financial interests to
disclose.

\emph{Author Contributions}

AS-A, ACC, AB, FG, MG, MS and JC conceived and designed the study. AS-A,
ACC, and MS were responsible for the data collection; FG, LA, and MM
performed the statistical and epidemiological analysis. AS-A and ACC
wrote the first draft of the manuscript. All authors drafted the
manuscript for important intellectual content, contributed to revision
of the final version of the manuscript, approved the final version
submitted, and agree to be accountable for all aspects of the work in
ensuring that questions related to the accuracy or integrity of any part
of the work are appropriately investigated and resolved. The
corresponding author attests that all listed authors meet authorship
criteria and that no others meeting the criteria have been omitted.

\emph{Ethics approval}

This study was approved on 17 December 2020 by the Ethical Committee of
the Foundation University Institute for Research in Primary Health Care
Jordi Gol i Gurina (IDIAPJGol) (code 20/192-PCV). All procedures
performed in studies involving human participants were in accordance
with the ethical standards of the institutional and/or national research
committee and with the 1964 Helsinki Declaration and its later
amendments or comparable ethical standards.

\emph{Consent to participate}

Informed consent providing information about anonymity, confidentiality,
use of the collected data, risks, and general information about the
study, was signed for parents or guardians of the participants because
all they were children under 16 years old. Participants were free to
decline/withdraw consent at any time without providing a reason and
without being subject to any resulting detriment.

\emph{Data sharing}

All anonymized databases and their corresponding codebooks are
available. Requests for complementary data can be sent as a formal
proposal to the CEEISCAT via email\emph{ceeiscat@iconcologia.net or to
the corresponding author} .

\textbf{Acknowledgments}

The authors would like to thank the Health Department and Department of
Education of the Government of the Catalonia (Spain), the former
D\emph{ireccio General de Recerca i Innovacio en Salut} (DGRIS)
and\emph{Institut Catala de la Salut} (ICS) that made this project
possible, and all the health care professionals acting as a COVID-19
pandemic health taskforce in Catalonia. Also, we would like to specially
thank the effort and dedication all the sentinel schools' staff,
students and families who participated in the project.

\textbf{* Sentinel School Network of Catalonia}

Principal investigators: Jordi Casabona {[}Centre d'Estudis
Epidemiologics sobre les Infeccions de Transmissio Sexual i Sida de
Catalunya (CEEISCAT)-CIBERESP{]}, Josep Basora (Institut Universitari
d'Investigacio en Atencio Primaria (IDIAP Jordi Gol).

Project manager: Anna Bordas (CEEISCAT).

\textbf{Technical committee:} Jordi Casabona (CEEISCAT), Jordi Sunyer
(ISGlobal), Antoni Soriano (Hospital Universitari Vall d'Hebron), Rosina
Malagrida (Living lab for Health, IRSICaixa) \emph{as Work Package
coordinators.} Cinta Folch, Pol Romano, Esteve Muntada, Anna Bordas,
Fabiana Ganem, Andreu Colom i Jordi Casabona (CEEISCAT), Mireia Gascon,
Maria Subirana, Pau Majo, Jordi Sunyer (ISGlobal), Rosina Malagrida,
Laia Vives (Living lab for Health), Antoni Soriano, Pere Soler-Palacin
(Vall d'Hebron Barcelona Hospital Campus).

Microbiology laboratories: Tomas Pumarola, Andres Anton, Cristina
Andres, Juliana Esperalba, Albert Blanco (Hospital Universitari Vall
d'Hebron), Ignacio Blanco, Pere-Joan Cardona, Maria Victoria Gonzalez,
Gema Fernandez, Cristina Esteban (Hospital Universitari Germans Trias i
Pujol)

\emph{\textbf{Data Management and statistical analysis}:} Yesika Diaz,
Lucia Alonso, Jordi Aceiton, Marcos Montoro (CEEISCAT).

\emph{\textbf{Data Protection Officer and Technical Support}:} Esteve
Muntada (CEEISCAT).

Communication manager: Pol Romano, Cristina Sanchez (CEEISCAT).

Field team: Maria Subirana, Pau Majo (ISGlobal), Jessica Fernandez, Laia
Vives (Living Lab for Health, IRSICaixa), Andreu Colom, Isabel Martinez,
Marina Herrero, Alba Garcia, Juan Rus, Paula Ribas, Alba Blanco
(CEEISCAT).

Universitat Autonoma de Barcelona team: Juan Leyva, Mariela Patricia
Aguayo, David Gimenez i Carolina Watson.

Community Paediatricians: Esperanca Macia i Silvia Burgaya (CAP
Manlleu), Ma Teresa Riera-Bosch, Elisabet Sola (EAP Vic Nord), Lidia
Aulet, Maria Mendoza, Lidia Busquets (EAP Vic Sud), Xavier Perramon,
Julia Sebastia (EAP Eixample Dret), Ana Moreno (Cap Ripollet), Xavier
Duran, Belen Perez (EAP Can Gibert del Pla), Anna Gatell (Equip
Territorial de Pediatria Alt Penedes), Maria Coma (Hospital Universitari
Joan XXIII).

Ministry of Health: Carmen Cabezas (Secretaria de Salut Publica de
Catalunya, Departament de Salut), Ana Bocio (Subdireccio general de
Promocio de la Salut), Ariadna Mas (Direccio Assistencial Atencio
Primaria, Institut Catala de la Salut), Maria Antonia Llopis
(Coordinacio dels laboratoris de l'Institut Catala de la Salut), Josep
Vidal (Gerencia Territorial de la Catalunya Central, Institut Catala de
la Salut), Sandra Pequeno and Jacobo Mendioroz (Subdireccio general de
Vigilancia i Resposta a Emergencies de l'Agencia de Salut Publica de
Catalunya, Departament de Salut), Robert Fabregat (former Direccio Gral
Recerca i Innovacio, Departament de Salut).

Department of Education: Josep Gonzalez-Cambray (Conseller d'Educacio),
Nuria Mora (Secretaria de Transformacio Educativa), Maria Neus Fornells
(former Gabinet del Conseller), Rut Ribas (former Direccio General de
l'Alumnat), Anna Chillida (Direccio General de l'Alumnat).

\textbf{Abstract}

We aimed to assess the association of household and classroom
determinants with students' school absence due to respiratory tract
infections (RTI) among 253 students (4-11 years) of 20 classrooms. We
collected 71 absences; RTI incidence was very high during the study
period, 17.5-33.1 cases per 100 population. Having someone else at home
with respiratory symptoms was the most significant epidemiological
factor (OR=9.12, CI 95\%=2.54-33.39), suggesting that households are
crucial for the transmission of RTI to the children. A positive but not
statistically significant association was observed between higher median
levels of CO\textsubscript{2} and respiratory-related absences (OR=1.2,
CI 95\%=0.98-1.46).

\textbf{Keywords}

COVID-19, respiratory infections, ventilation, school,
CO\textsubscript{2,} Indoor air quality

\textbf{Main text}

\textbf{Introduction}

Different public health measures were implemented during the COVID-19
pandemic to maintain the schools open\textsuperscript{1,2}. Regarding
COVID-19 vaccination, at the beginning of this study, more than 92\% and
40\% of population older than 12 years and children aged 5-11 years in
Spain was fully vaccinated against COVID-19,
respectively\textsuperscript{3}.

Ventilation was proposed as one of the main strategies to reduce aerosol
transmission for SARS-CoV-2 during the pandemic. A study from Germany
assessed the efficiency of air purifiers in reducing aerosols in
high-school classrooms\textsuperscript{4}. However, no clinical
endpoints were investigated and, therefore, a very low certainty of
evidence was graded by a Cochrane review\textsuperscript{5}. In an
Italian study, the authors concluded that ventilation reduced the
likelihood of SARS-CoV-2 infection in classrooms by
80\%\textsuperscript{6}. Moreover, a survey study from the US reported
that elementary schools with face masks and ventilation strategies in
place had lower SARS-CoV-2 incidence rates\textsuperscript{7}. In a
Lancet Task Force Commission review\textsuperscript{8}, the authors
concluded that improving building ventilation systems may carry benefits
beyond protection from COVID-19. However, there is scarce evidence that
demonstrate the association of epidemiological and environmental risk
factors, including CO\textsubscript{2} concentrations, with the
incidence of respiratory tract infections (RTI) in children who are
attending schools.

The present study is part of COVID-19 Sentinel Schools Network of
Catalonia (CSSNC), a project including 23 schools and 5687 students,
teachers and other school staff with the aim to monitor SARS-CoV-2 and
other respiratory viruses, their determinants and preventive measures in
Catalonia\textsuperscript{9}. The objectives of this study are to assess
the potential association of demographic and epidemiological factors,
including the indoor environmental conditions
(CO\textsubscript{2}levels) in the classrooms, with students' school
absence due to RTI.

\textbf{Methods}

\emph{Study design and participants}

This is a cross-sectional study conducted in two different periods, the
first from April 19 to June 21, 2022, and the second from November 8 to
December 21, 2022. The main outcome of the study was the absence of the
child from attending the school in person due to RTI or other
non-respiratory medical causes.

The study population was composed of 253 students (4-11 years) belonging
to 20 classrooms, 11 in spring 2022 and 9 in autumn 2022, attending 4
and 16 classrooms of preschool (4 to 5 years-old) and primary school (6
to 11 years-old) stages, respectively. A written informed consent was
previously obtained from parents or guardians of children.

\emph{Procedures}

Absences from school attendance were notified by the tutor/teacher to
the study researchers. We proceed to collect epidemiological and
clinical/diagnostic data within the first 48 hours through a case report
form deposited on the digital platform REDCap(c). All the absences (cases)
were followed-up through telephone calls made by health professionals
until their return to the school. RTI was registered according to the
symptoms described during the telephonic interview and confirmed through
the computerised health record programme of the Health Ministry (eCAP).

Sensors to monitor the CO\textsubscript{2} concentrations (DIOXCARE
DX700 PDF, Smartcare Services, Spain) were installed in classrooms,
recording data every 10 minutes. For the analysis we only used the
measurements taken during the time in which the students were in the
classroom. We obtained a median {[}IQR{]} of CO\textsubscript{2} levels
which was used to conduct our analyses. All the participating schools
received an operational protocol to install the sensor correctly and
download data weekly.

\emph{Statistical analysis}

We calculated the RTI incidence per week and for the total study period.
We performed a descriptive analysis of all survey variables, stratifying
them by respiratory-related absence or absence due to other causes.
Additionally, we ran a univariate logistic model to study the
association between the type of absence and each described variable to
obtain the corresponding odds ratios, 95\% confidence intervals and
p-values.

Furthermore, we conducted a Latent Class Analysis (LCA) to explore
potential groups of students with similar symptomatology. We started
exploring the optimal number of latent classes, trying two to five
classes, and we selected the best model using the entropy criterion,
which indicates the accuracy of the latent classes, combined with other
goodness of fit criteria such as BIC, cAIC and likelihood ratio. All
these measures suggested that the optimal number of classes was two.
However, we also examined the rest of number of classes to see if their
classification had more clinical significance. All statistical analyses
were performed in R (version 4.2.2).

\textbf{Results}

We registered one-hundred and five school absences during the study, 43
in the first study period (spring 2022), and 62 in the last one (autumn
2022) (\textbf{Supplementary Figure 1} ). Among these, we could obtain
data related to the diagnosis in 98 (93\%) cases, the rest of them were
lost during the follow-up of the absence. Seventy-one absences were
respiratory-related and 27 were due to other causes, mainly with
gastrointestinal symptoms (66.7\%). Among the absences due to RTI, the
most were upper RTI (56/71, 78.9\%), and only six (8.5\%) were confirmed
infections, 2 caused by influenza virus and 4 due to SARS-CoV-2
infection. These results represent a RTI incidence of 15.9 and 33.1
cases per 100 population in the first and second study period,
respectively. The maximum weekly RTI incidence was of 10.2 cases per 100
population in December 12-18, 2022.

The clinical, epidemiological and environmental characteristics of study
sample are summarized in \textbf{table 1} , categorized by type of
absence (respiratory versus non-respiratory). We found a statistically
significant association with absences due to RTI when someone else at
home had respiratory symptoms (OR=9.12, CI 95\%=2.54-33.39). We found a
positive association between higher median levels of
CO\textsubscript{2}at class and respiratory-related absences (OR=1.2, CI
95\%=0.98-1.46). Moreover, there were more respiratory absences in
autumn (OR=2.4, CI 95\%=0.97-5.94). However, these last two associations
did not reach statistical significance at a level of 0.05; although
their p-values were lower than 0.1.

No other epidemiological risk factors were associated with RTI
incidence, such as household floor level, number of people living at
home, living with smokers, having any comorbidity or being vaccinated
against COVID-19.

Finally, in \textbf{Figure 1} , we present the symptomatology of
absences belonging to each of the two latent classes. We can see that in
the first cluster, the most frequent symptoms were cough, nasal
congestion and fever, whereas in the second one, fever, gastrointestinal
symptoms, and fatigue predominated.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1.} Latent class analysis with two latent classes to
compare school absences due to RTI from other causes. Latent class 1:
Cough+nasal congestion+fever; Latent class 2: Fever+Gastrointestinal
symptoms+fatigue.

\textbf{Discussion}

Our findings confirm that the RTI incidence during the study period was
very high in children attending in the CNSSC schools, and the main
medical cause of school absence. Although differences on school absence
due to RTI were observed between spring and autumn, they were not
statistically significant and in any case they may be due to the
respiratory viruses' seasonal pattern. In fact, the most important and
significantly associated risk factor for RTI was the presence of someone
else at home with respiratory symptoms, suggesting that households could
be the main setting for initiating of the transmission of RTI.

We observed a slightly association between RTI and median of
CO\textsubscript{2} levels in classrooms (p=0.07), which is an indicator
of the degree of ventilation. However, we cannot exclude other potential
factors such as rainfall, ambient temperature, or air pollutants (e.g.
PM\textsubscript{2.5}, NO\textsubscript{2}, etc.) influencing on this
outcome, as suggested by other authors\textsuperscript{10}. To our
knowledge, previous studies assessed the
CO\textsubscript{2}concentration as a proxy of ventilation to evaluate
the risk transmission of SARS-CoV-2 in schools\textsuperscript{11,12},
but they did not analyse the association between CO\textsubscript{2}
median values and RTI incidence.

Finally, we studied the symptomatology associated with the school
absences through a LCA. The best approach to differentiate RTI from
other causes was using two latent classes, and the most frequent
symptoms were cough, nasal congestion and fever.

The major strength of this study is our extensive data collection on
clinical, epidemiological and environmental factors related to the
school and also to the households of the participants. However, there
were limitations such as possible incomplete reporting of RTI or
insufficient sample size to determine small effect sizes.
CO\textsubscript{2} concentration was only measured in a selection of
classrooms per school, so it may not be representative for the entire
study period and school.

In conclusion, RTI incidence was very high during the study period being
the most important and significantly associated factor with RTI to have
anyone else at home with respiratory symptoms. This suggests that
households and not schools could be the key epidemiological factor for
initiating the transmission of RTI to the children. Improving household
preventive measures could reduce childhood RTI. In the LCA, the most
frequent symptoms associated with RTI were cough, nasal congestion and
fever. Although we found a slightly association between RTI and reduced
ventilation we cannot exclude other potential factors influencing on
this outcome. The study has been crucial to assess the feasibility and
potential utility of collecting both school absence and morbidity data
for further developing a systematic monitoring system.

\textbf{References}

\begin{enumerate}
\tightlist
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\end{enumerate}

\textbf{Table 1.} Descriptive analysis of clinical, epidemiological and
environmental variables comparing absences due to Respiratory tract
infections (RTI) from absences due to other causes.\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& \textbf{Total absences from attending school in person} &
\textbf{Absences due to RTI} & \textbf{Absences due to other causes} &
\textbf{OR (95\% CI)} & \textbf{P value}\tabularnewline
\midrule
\endhead
\textbf{Characteristic} & N = 98 & N = 71 & N = 27 & &\tabularnewline
\textbf{Age group} & & & & &\tabularnewline
4-6 years & 66 (67.3) & 45 (63.4) & 21 (77.8) & 1 & ref\tabularnewline
7-9 years & 12 (12.2) & 11 (15.5) & 1 (3.7) & 5.13 (0.62,42.38) &
0.129\tabularnewline
10-11 years & 20 (20.4) & 15 (21.1) & 5 (18.5) & 1.4 (0.45,4.36) &
0.562\tabularnewline
\textbf{Period} & & & & &\tabularnewline
First year (spring) & 36 (36.7) & 22 (31) & 14 (51.9) & 1 &
ref\tabularnewline
Second year (autumn) & 62 (63.3) & 49 (69) & 13 (48.1) & 2.4 (0.97,5.94)
& 0.059\tabularnewline
\textbf{Sex} & & & & &\tabularnewline
Male & 46 (46.9) & 34 (47.9) & 12 (44.4) & 1.15 (0.47,2.8) &
0.76\tabularnewline
Female & 52 (53.1) & 37 (52.1) & 15 (55.6) & 1 & ref\tabularnewline
\textbf{Sports} & & & & &\tabularnewline
Yes & 52 (53.1) & 40 (56.3) & 12 (44.4) & 1.67 (0.68,4.08) &
0.263\tabularnewline
No & 45 (45.9) & 30 (42.3) & 15 (55.6) & 1 & ref\tabularnewline
Missing & 1 (1) & 1 (1.4) & 0 (0) & &\tabularnewline
\textbf{Floor level} & & & & &\tabularnewline
First floor or lower & 54 (55.1) & 41 (57.7) & 13 (48.1) & 1 &
ref\tabularnewline
Upper floors & 43 (43.9) & 29 (40.8) & 14 (51.9) & 0.66 (0.27,1.6) &
0.356\tabularnewline
Missing & 1 (1) & 1 (1.4) & 0 (0) & &\tabularnewline
\textbf{Number of cohabitants, median (IQR)} & 4 (4-4) & 4 (4-4) & 4
(3-4.5) & 1.07 (0.8,1.44) & 0.653\tabularnewline
\textbf{Number of cohabitants} & & & & &\tabularnewline
\textless{}4 & 24 (24.5) & 16 (22.5) & 8 (29.6) & 1 & ref\tabularnewline
\textgreater{}=4 & 73 (74.5) & 54 (76.1) & 19 (70.4) & 1.42 (0.52,3.85)
& 0.49\tabularnewline
Missing & 1 (1) & 1 (1.4) & 0 (0) & &\tabularnewline
\textbf{Smokers at home} & & & & &\tabularnewline
Yes & 35 (35.7) & 25 (35.2) & 10 (37) & 0.92 (0.37,2.32) &
0.866\tabularnewline
No & 63 (64.3) & 46 (64.8) & 17 (63) & 1 & ref\tabularnewline
\textbf{Hospital admissions} & & & & &\tabularnewline
Yes & 0 (0) & 0 (0) & 0 (0) & &\tabularnewline
No & 98 (100) & 71 (100) & 27 (100) & &\tabularnewline
\textbf{Comorbidities} & & & & &\tabularnewline
Yes & 10 (10.2) & 8 (11.3) & 2 (7.4) & 1.59 (0.31,8) &
0.576\tabularnewline
No & 88 (89.8) & 63 (88.7) & 25 (92.6) & 1 & ref\tabularnewline
\textbf{Asthma} & & & & &\tabularnewline
Yes & 5 (50) & 5 (62.5) & 0 (0) & &\tabularnewline
No & 5 (50) & 3 (37.5) & 2 (100) & &\tabularnewline
\textbf{Complete COVID-19 vaccination} & & & & &\tabularnewline
Yes & 19 (19.4) & 12 (16.9) & 7 (25.9) & 0.58 (0.2,1.68) &
0.316\tabularnewline
No & 79 (80.6) & 59 (83.1) & 20 (74.1) & 1 & ref\tabularnewline
\textbf{Complete COVID-19 vaccination at home} & & & & &\tabularnewline
Yes & 84 (85.7) & 63 (88.7) & 21 (77.8) & 2.5 (0.69,9.04) &
0.162\tabularnewline
No & 11 (11.2) & 6 (8.5) & 5 (18.5) & 1 & ref\tabularnewline
Missing & 3 (3.1) & 2 (2.8) & 1 (3.7) & &\tabularnewline
\textbf{Anyone at home with respiratory symptoms} & & & &
&\tabularnewline
Yes & 41 (41.8) & 38 (53.5) & 3 (11.1) & 9.21 (2.54,33.39) &
0.001\tabularnewline
No & 57 (58.2) & 33 (46.5) & 24 (88.9) & 1 & ref\tabularnewline
\textbf{Level of CO2, median (IQR)} & 567.76 (485-637.78) & 606.51
(485-876) & 485 (479-637.78) & 1.2 (0.98,1.46) & 0.077\tabularnewline
\textbf{Level of CO2} & & & & &\tabularnewline
\textless{} 1000 & 79 (80.6) & 54 (76.1) & 25 (92.6) & 1 &
ref\tabularnewline
\textgreater{}= 1000 & 19 (19.4) & 17 (23.9) & 2 (7.4) & 3.94
(0.84,18.35) & 0.081\tabularnewline
\textbf{Symptoms} & & & & &\tabularnewline
Fever (yes) & 50 (51.0) & 40 (56.3) & 10 (37.0) & & 0.121\tabularnewline
Cough (yes) & 53 (54.0) & 49 (69.0) & 7 (25.9) & &
\textless{}0.001\tabularnewline
Odynophagia (yes) & 31 (31.6) & 30 (42.3) & 1 (3.7) & &
0.001\tabularnewline
Nasal congestion (yes) & 60 (61.2) & 54 (76.1) & 6 (22.2) & &
\textless{}0.001\tabularnewline
Gastrointestinal symptoms (yes) & 30 (30.6) & 12 (16.9) & 18 (66.7) & &
\textless{}0.001\tabularnewline
\bottomrule
\end{longtable}

\textbf{Fig. 1} Latent class analysis with two latent classes to compare
school absences due to RTI from other causes. Latent class 1:
Cough+nasal congestion+fever; Latent class 2: Fever+Gastrointestinal
symptoms+fatigue.

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