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\begin{document}

\title{Influence of non-pharmacological interventions on inhaled allergen
sensitization in children during the COVID-19 pandemic}



\author[1]{Xueshan Huang}%
\author[2]{Min Yang}%
\author[2]{Ma Ye}%
\author[2]{Jun Qiu}%
\author[2]{Yanping Chen}%
\affil[1]{University of South China Medical College}%
\affil[2]{Hunan Children's Hospital}%


\vspace{-1em}



  
  \date{May 19, 2024}


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\selectlanguage{english}
\begin{abstract}
\textbf{Objective:} To explore the impact of non-pharmacological
interventions on inhaled allergen sensitization in children during the
COVID-19 pandemic. \textbf{Methods:} The positive rate of inhaled
allergens, allergens sIgE grade, and multiple sensitization rates before
and during the pandemic were analyzed retrospectively in this study.
Logistic regression analysis was used to compare the positive rate of
allergens before and after the pandemic, using OR and OR 95\%CI to
investigate the impact of the pandemic on allergen sensitization.
\textbf{Results}:Positive rates of d1(49.5\% vs 38.5\%), d2 (50.2\% vs
32.2\%), e2(10.1\% vs 6.1\%), e1(6.2\% vs 1.7\%), mx2(10.1\% vs 2.7\%),
sycamore (7.2\% vs 2.1\%), w1(4.0\% vs 1.7\%),elm(3.1\% vs 0.6\%),
w6(3.0\% vs 1.7\%), and u80(1.3\% vs 0.5\%) increased significantly
during the COVID-19 pandemic. After adjusting gender, age, season and
other potential influencing factors, the COVID-19 pandemic was found to
be a risk factor for the positive rate of d1(
\emph{OR=1.174,95\%CI=1.015\textasciitilde{}1.358}), d2(
\emph{OR=1.301,95\%CI=1.093\textasciitilde{}1.549}), e2(
\emph{OR=1.499,95\%CI=1.280\textasciitilde{}1.756}), mx2(
\emph{OR=3.959,95\%CI=3.358\textasciitilde{}4.446}), w1( \emph{OR=1.828,
95\%CI=1.353\textasciitilde{}2.470}, w6( \emph{OR=1.538,
95\%CI=1.123\textasciitilde{}2.106})), u80( \emph{OR=2.521,
95\%CI=1.413\textasciitilde{}4.497}) ( \emph{P\textless{}0.05}). What's
more, d1 and d2 allergen sIgE grades increased during the COVID-19
pandemic(d1 \emph{:X\textsuperscript{2}=9.576,P\textless{}0.05;}d2
\emph{:X\textsuperscript{2}=39.063,P\textless{}0.05)}. The proportion
of multiple allergies was significantly higher than that before the
pandemic, with a statistical significance (
\emph{X\textsuperscript{2}=1621.815, P\textless{}0.05}).
\textbf{Conclusion:} During the COVID-19 pandemic, non-pharmacological
interventions increased the positive rate of both indoor and outdoor
allergens in children. The sIgE grade of dust mite allergen and multiple
sensitization rate were significantly higher than those before COVID-19.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Allergies are chronic immune-mediated diseases that have become a
worldwide public health problem\textsuperscript{{[}1{]}}. An
epidemiological survey conducted by WAO revealed that 22\% of total
population in more than 30 countries suffer from allergic
diseases\textsuperscript{{[}2{]}}. In high-income countries, 20\% of
children have atopic dermatitis\textsuperscript{{[}3{]}}. In addition,
the incidence of allergic diseases has been and will continue to rise
over the next two decades\textsuperscript{{[}4{]}}. For individuals,
allergic diseases can reduce the quality of life and productivity. A
study in Canada found that 48.7\% of asthmatic patients recruited
experienced the drop in productivity due to
asthma\textsuperscript{{[}5{]}}. Allergic diseases have caused a
tremendous socioeconomic burden as well. For example, researches have
shown the United States has spent over \$960 billion annually on asthma
management\textsuperscript{{[}6{]}}.

COVID-19 outbreak was declared a global pandemic after the first case of
Coronavirus Disease 2019 (COVID-19) was identified in Wuhan, Hubei
Province, China, in 2019. During the pandemic, strict prevention and
control measures have been adopted worldwide, particularly in China,
among which non-pharmacological interventions (NPI), including closing
public spaces, restricting gatherings, reducing unnecessary outings and
maintaining social distancing wearing masks, and keeping hand hygiene.
These NPIs have influenced people's living environments and lifestyles,
leading to higher indoor allergen concentrations and more time spent
indoors\textsuperscript{{[}7{]}}.The exposure to outdoor allergens also
rises as people travel more after the lifting of certain travel
restrictions. These are bound to bring changes in allergen
sensitization. Yet, few researches have studied the impact of COVID-19
on allergen sensitization. Understanding allergen sensitization during
the pandemic can help patients identify allergens, as well as~take steps
to reduce allergen sensitization and allergic disease progression in a
period of regular epidemic prevention and control. In this study, we
analyzed the positive rates of inhaled allergen sIgE (specific antibody
immunoglobulin IgE, sIgE) before and during COVID-19 to investigate its
impact on allergy sensitization.

\textbf{Materials and Methods}

\textbf{Study subjects}

In this study, 29,926 inhaled allergen sIgE test results were
retrospectively analyzed in Hunan Children's Hospital from 2014 to 2021.
Inclusion criteria: (1) receiving serum inhaled allergen sIgE test; (2)
under 18 years old. Exclusion criteria: (1) lacking complete basic
personal information; (2) infected with COVID-19. The collected
information includes the patient's name, gender, age, medical record
number, testing time, serum sIgE test items~and results. According to
the time of COVID-19 outbreak, the subjects are divided into two groups:
Before COVID-19(January 1\textsuperscript{st}, 2014.-January
31\textsuperscript{st}, 2020), and During COVID-19 (after January
1\textsuperscript{st}, 2020). They are divided into four age groups by
the developmental stage: infancy (\textless{}3 years old), preschool
(3-5 years old), school age (6-9 years old), and adolescence (10-18
years old), as well as spring (March-May), summer (June-August), autumn
(September-November), and winter (December-February) groups based on the
time of testing.

The examined allergens include: D. pteronyssinus (d1), D. farinae (d2),
dog hair (e2), cat hair (e1), cockroaches (i6), mulberry (T70), sycamore
pollen (sycamore), elm pollen (elm), grass pollen (u80), mugwort pollen
(w6), common ragweed pollen (w1), amaranth (w14), green oysters (f37),
mold (mx2). the testing of E1, elm, and sycamore began in November 2019.

\textbf{AllergyScreen Test}

Collect 2-3ml venous blood from the child, centrifuge for 10 at
3000r/min minutes, and take the serum supernatant. Inhaled allergen sIgE
levels were measured using the AllergyScreen test (Mediwiss Analytic
GmbH, Moers, Germany), an immunoblot assay that uses a uniform and
standardized procedure.

Results were interpreted into the following groups: grade 0
(\textless{}0.35KU/L), grade 1 (0.35\textasciitilde{}0.7 KU/L), grade 2
(0.7\textasciitilde{}3.5 KU/L), grade 3 (3.5\textasciitilde{}17.5 KU/L),
grade 4 (17.5\textasciitilde{}50.0 KU/L), grade 5
(50.0\textasciitilde{}100.0 KU/L), grade 6 ([?] 100.0 KU/L). The positive
is [?] 0.35 KU/L.

\textbf{Statistical method}

SPSS 25.0 software was applied for statistical analysis. The positive
rate of allergens during and before COVID-19 was tested by the
Chi-square test. It could analyze the difference of allergens positive
rate in different subgroups by gender, season and age. Univariate
regression analyses were adopted to calculate the odds ratio (OR) and
95\%CI for the associations between theCOVID-19 pandemic and allergen
sensitization. Multivariate regression analyses were used to calculate
the adjusted ORfor each allergen during the pandemic compared to that
before the pandemic, after adjusting confounding factors such as sex,
age, and season. \emph{P\textless{}0.05} was considered to have
statistical significance.

\textbf{Result}

\textbf{Characteristics of study population}

A total of 29926 inhaled allergen sIgE test results were included from
2014 to 2021, including 12484 cases before COVID-19 and 17442 cases
during COVID-19. There were 19125 males and 10801 females, with an
average age of 4.59\selectlanguage{ngerman}±3.103 years (age range: 0-18 years). The number of
people in each age and season group is shown in \textbf{Table 1.} The
number of examined cases and positive cases of each allergen are shown
in \textbf{Table 1.}

\textbf{Comparison of the number of allergen examined cases and positive
rate before and during COVID-19}

The most common allergens in Changsha, Hunan province were
d1(44.39\%,2711/6107), d2(38.5\%, 2053/4801s), followed by e2(9.19\%,
1976/21510), mx2(7.4\%, 21510). 1947/26334), sycamore (6.71\%,
916/13747), e1(5.77\%, 834/14460). Except for t70 and w14, the number of
positive allergens was higher than that before COVID-19. The positive
rates of d1, d2, e2, mx2, sycamore, e1, w1, elm and w6 during COVID-19
were significantly higher than those before COVID-19, with a statistical
significance (\emph{P \textless{}0.05)} . There was no significant
difference in the positive rates of i6, w14, t70 and f37 before and
during COVID-19. (\textbf{Table S1} )

The number of examined cases and positive numbers of allergens during
and before COVID-19 in each month are shown in \textbf{Figure S1.} The
number of d1,d2,e2,mx2,i6,w1,w6,u80 examined cases and positive cases in
the majority of months during COVID-19 was higher than
before.\textbf{Figure 1} shows the positive rates of allergens during
and before COVID-19 in each month. Except for i6 and w6, the positive
rates of other allergens during COVID-19 were significantly higher than
those before COVID in each month. From June to September during
COVID-19, the positive rate of w6 was higher than before.

\textbf{logistics regression analysis}

The positive rate of allergens was different in gender, age, and season
(\textbf{Table S2-S4} ). \textbf{Table S5} -\textbf{S7} respectively
described the impact of the COVID-19 pandemic on allergen sensitization
in subgroups by gender groups\selectlanguage{english},age groups and season groups.

The positive rate of allergens was used as the dependent variable, and
the time before and during COVID-19 was used as the independent
variable. Multivariate regression analysis was conducted after adjusting
gender, age and season. The results showed that the risk of d1, d2, mx2,
e1, e2, w1, elm and w6 positive rates during COVID-19 was significantly
higher than that before, with a statistical difference
(d1(\emph{OR=1.174,95\%CI=1.015\textasciitilde{}1.358}
),d2(\emph{OR=1.301,95\%CI=1.093\textasciitilde{}1.549} ),
e2(\emph{OR=1.499,95\%CI=1.280\textasciitilde{}1.756} ),
mx2(\emph{OR=3.959,95\%CI=3.358\textasciitilde{}4.446} ),
sycamore(\emph{OR=2.510,95\%CI=1.522\textasciitilde{}4.139} ),
e1(\emph{OR=249,95\%CI=2.338\textasciitilde{}7.722} ),
w1(\emph{OR=1.828, 95\%CI=1.353\textasciitilde{}2.470} ,
elm(\emph{OR=3.576, 95\%CI=1.425\textasciitilde{}8.974} ),
w6(\emph{OR=1.538, 95\%CI=1.123\textasciitilde{}2.106}
)\selectlanguage{english},u80(\emph{OR=2.521, 95\%CI=1.413\textasciitilde{}4.497} )) (all
\emph{P\textless{}0.05} ).

\textbf{(Table 2)}

\textbf{The difference in inhaled allergen sIgE grade~before and during
COVID-19}

The inhaled allergen sIgE grade distribution before and during COVID-19
was as follows: The sIgE grades of d1 and d2 were mainly at the grade
4-6 (high-grade group), while the sIgE grades of other inhaled allergens
were mainly at the grade 1-3 (low-grade group). During COVID-19, the
proportion of d1 and d2 high-grade groups increased compared with that
before COVID-19, the difference was statistically significant
(P\textless{}0.05), while the proportion of mx2 and e2 high-grade groups
decreased compared with that before COVID-19, with a statistical
difference (d1:\selectlanguage{english}\emph{X\textsuperscript{2}=9.576, P\textless{}0.05;d2}
:\emph{X\textsuperscript{2}=39.063, P\textless{}0.05} )(\textbf{Table 3}
).

\textbf{Multiple allergy differences before and after COVID-19}

The proportion of people sensitized by allergens during COVID-19
increased noticeably compared with that before COVID-19, and the
proportion of people with multiple sensitivities also increased
considerably, with a statistical significance
(\emph{X\textsuperscript{2}=1621.815, P\textless{}0.05} , \textbf{Table
4} ). Before COVID-19, 8.5\% of patients were sensitized to one
allergen, 5.7\% to two allergens and 0.5\% to three or more allergens.
While 18\% of patients were sensitized to one allergen, 12.8\% to two
allergens, 3.0\% to three allergens, and 1.3\% to four or more allergens
during COVID-19. Additionally, explore the cross-allergy of five common
allergens (\textbf{Figure S2} ). Only 26.8\% (16/596) and 12.0\% (7/584)
of the patients were sensitized to single d1 and d2, respectively. In
other words, patients with d1 and d2 allergies were often sensitized to
other allergens. A total of 610 patients with d1 and/or d2 sensitization
were identified as dust mite sensitization. The most common
co-sensitization was e2, with a rate of 15.9\% (97/600), and dust mite
as the most common allergen.

\textbf{Discussion}

During the COVID-19 pandemic, the NPI have profoundly impacted allergen
sensitization. This study reached the following conclusions by analyzing
the results of inhaled~allergen sIgE testing in 29,926 cases before and
during the COVID-19 pandemic: (1) During the pandemic, the positive rate
of indoor and outdoor allergens increased significantly, and the outcome
remained the same after adjusting potential influencing factors~such as
gender, season, and age. (2) Dust mite allergen sIgE grade and multiple
sensitization rate have increased during the COVID-19~pandemic. (3) The
allergens sensitization differed by gender, age, and season.

The risk of indoor allergen sensitization during the COVID-19 is 1.2 to
4 times higher than that before the COVID-19 (\emph{OR
range:1.194\textasciitilde{}4.014, P\textless{}0.05)} . Li
Y\textsuperscript{{[}8{]}} discovered that the positive rate of indoor
allergens in South China increased dramatically during COVID-19
pandemic. The study of Qing Ye\textsuperscript{{[}9{]}} also~observed
that the positive rate of allergens during COVID-19 was 51.50\%, higher
than~42.23\% before COVID-19. Additionally, another study of~Qing
Ye\textsuperscript{{[}10{]}} discovered that the positive rate of indoor
allergens increased during COVID-19, while the number of positive
allergens decreased. But in our study, the number of allergens also
increased remarkably during COVID-19. The following factors may be
studied to determine the reason for increased positive rate of indoor
allergens: (1) NPI during the COVID-19 pandemic increased population
density, indoor temperature and humidity\textsuperscript{{[}11{]}}, as
well as the time that pets spent indoors\textsuperscript{{[}12{]}},
causing the growth of indoor allergen
concentrations\textsuperscript{{[}9{]}}.
Wahn\textsuperscript{{[}13{]}}found a dose-response relationship between
inhaled allergen exposure and allergen sensitization. Another
study\textsuperscript{{[}14{]}}indicated that 2ug/g of dust mites in the
air was a risk factor for sensitization, whereas 10ug/g was a risk
factor for asthma among dust mite-sensitized persons. (2) The increasing
concentration of other allergens in the air, such as mold and animal
fur, will also increase the risk of dust mite allergens sensitization,
because of the cross-reaction\textsuperscript{{[}15{]}}. (3) During the
COVID-19 pandemic, children spend more time indoors, which increases
their chances of being exposed to indoor
allergens\textsuperscript{{[}16{]}}. Repeated exposure is easy to cause
allergens sensitization. It is recommended that individuals use
dehumidifiers, vacuuming, air purification, acaricides, and open windows
frequently for ventilation to reduce indoor temperature and humidity.
Additionally, allergen-reducing measures, including removing carpets and
fabric curtains, washing and replacing mattresses and pillows, cleaning
air conditioner should be adopted to reduce the accumulation of indoor
allergens\textsuperscript{{[}17{]}}.

Though wearing disposable medical masks for a longer period during the
pandemic can prevent the inhalation of allergens theoretically, this
study revealed that the positive rate of outdoor allergens actually
increased during the pandemic (P \textless{}0.05). The result
contradicts the study of Qing Ye \textsuperscript{{[}10{]}}. There are
five factors contributing to the increase in outdoor allergen
sensitization rate during the pandemic. Firstly, the masks currently
used on children are merely scaled-down copies of masks created for
adults which have not been specifically tested or
approved\textsuperscript{{[}18{]}.} A research on FFP masks proved that
wearing a mask could not completely prevent allergen inhalation due to
facial leakage penetration and increased total inward leakage caused by
higher breathing frequencies\textsuperscript{{[}19{]}}. Second, several
studies have demonstrated that long-term mask use without change
increases the chance of severe skin reactions\textsuperscript{{[}20{]}},
and the impaired skin barrier provides a pathway for allergen
sensitization\textsuperscript{{[}21{]}}. ~Moreover, outdoor activity and
allergen exposure increased with the gradual resumption of work and
school in the second half of 2020, which is proved by a significant rise
in the positive rate of w6 from June to September during COVID-19 in
this study, Furthermore, as children usually feel hot and have breathing
difficulties while wearing masks, some of them may remove the masks
during physical activities\textsuperscript{{[}22{]},} raising the
prevalence of outdoor allergens during the pandemic. To decrease
allergen stimulation and allergy symptoms, it is recommended that
children reduce outside activities and use adequate masks with timely
replacement during the pollen season.

During the COVID-19 pandemic, the proportion of medium and high-level
sIgE to dust mite allergens increased, whereas the proportion of middle
and high-level sIgE to mold and cockroach allergens dropped
(P\textless{}0.05). In the same study, Qing
Ye\textsuperscript{{[}9{]}}discovered that, except for dust mite
allergens, the majority of allergen-specific IgE levels were lower than
those before the pandemic. This may also contribute to increased
exposure to dust mite allergens by longer time indoors during the
pandemic\textsuperscript{{[}16{]}}.

Moreover, the proportion of multiple sensitivities grew greatly during
COVID-19 compared to that before the same period
(\emph{P\textless{}0.05)} . Studies have pointed out that~ dust mite
sensitization is often associated with other allergens due to
antigen-cross and co-sensitivity across
allergens\textsuperscript{{[}23{]}}. Therefore,~when advising patients
to avoid allergens, doctors should not only focusing on the target
allergen while ignoring other frequent allergens. Studies have shown
that avoiding a single allergen cannot prevent allergy sensitization,
whereas reducing the levels of numerous inhaled allergens together can
achieve this purpose\textsuperscript{{[}24{]}}.

There were gender differences in the positive rate of allergens, which
has been reported in other pieces of
literature\textsuperscript{{[}25{]}}, yet the reason and mechanism
remain unknown. It could be the different living habits between men and
women, which may result in varied allergen
exposure\textsuperscript{{[}25{]}}, or the difference in hormone
secretion between the two genders\textsuperscript{{[}26{]}}.

The positive rate of~inhaled~allergens~changes with age. The positive
rates of dust mites and cockroaches increased with age, as found in the
studies of Ying\textsuperscript{{[}25{]}}, and
D'Souza\textsuperscript{{[}27{]}}. The differences in allergen
sensitization at different ages, due to the different range of activity
at different ages, might result in differences in allergen exposure.
Clinicians should give recommendations to patients properly in avoiding
allergen sensitization based on the distribution characteristics of
allergens in different age groups and the trend of allergen
sensitization with age.

This study also discovered that the positive rate of inhaled allergens
was higher in summer and autumn than in winter and spring, and similar
conclusions were found in an analysis of allergen sensitization in
children in Shanghai, China\textsuperscript{{[}25{]}}. This is due to
seasonal differences in allergen concentrations in the air caused by the
characteristics of various allergens. Dust mite reproduction peaked in
July and August and began to decline in
October\textsuperscript{{[}28{]}}. Animal hair sheds primarily in the
summer and autumn. Trees bloom in the spring, grasses in the late spring
to early summer, and weeds in the autumn \textsuperscript{{[}29{]}}. As
a result, patients who are sensitive to inhalation allergens should wear
masks based on the seasonal distribution characteristics of local
allergens to avoid contact with allergens and reduce allergen
stimulation and allergic reactions.

There are currently few studies investigating the impact of the COVID-19
pandemic on allergen distributions. This study offers nearly 30,000 test
results from large sample size and includes an analysis of indoor and
outdoor allergens, which can be used as a reference for the prevention
and control of allergens sensitization under normal pandemic conditions.
Nevertheless, this study has some limitations. It lacks data on allergy
diseases in the study population for the privacy of the study
population, making it impossible to assess the association between the
COVID-19 pandemic and allergic diseases. Future studies can therefore
investigate whether the COVID-19 pandemic influences the prevalence of
allergy diseases.

\textbf{Conclusion}

NPI during the COVID-19 pandemic is a risk factor for indoor and outdoor
allergen sensitization. It was also found that allergen grade~of dust
mite and rates of multiple sensitizations were significantly higher than
those before the COVID-19. To reduce indoor allergen concentrations, we
recommend: (1) Use a dehumidifier, vacuum, air purification, mite
removal instrument, and open windows frequently for ventilation. (2) No
use of carpets and fabric curtains, and regularly wash and replace
mattresses and pillows. (3) Avoid keeping pets. (4) Avoid going out
during pollen season. Wear a mask when going out, and change masks on
time. (5) Avoid allergens based on their age and seasonal
characteristics.

\textbf{Acknowledgements}

We would express our heartfelt thanks to all the schoolchildren who
participated in the study and their parents. We also appreciate the
staff of Hunan Children's Hospital for their support.

Consent for publication

{\label{consent-for-publication}}

Not applicable

\textbf{Author Contributions:} XSH, JQ and YPC contributed to the
conception and design of the work. JQ, MY and YM provisioned the study
materials or patients. XSH collected and assembled the data. XSH
performed the statistical analyses and interpretated. XSH drafted the
manuscript. XSH and JQ revised the manuscript for important intellectual
content. All authors contributed to the manuscript writing, and all
authors read and approved the final version of manuscript.

\textbf{Funding Sources}

There are currently no Funding Sources in the list.

\textbf{Competing interest}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\textbf{Data availability statement}

All data pertaining to this study are within the manuscript\selectlanguage{english},further
inquiries can be directed to the corresponding author.

\textbf{Ethical Approval} : The studies involving human participants
were reviewed and approved by the Ethics Committee of the Hunan Children
Hospital. This study is retrospective, and the clinical test data of
previous inpatients are analyzed and collated. The results of this study
are not intended for clinical diagnosis and do not require the name of
the patient to be known. And the clinical study does not have any risks
to the subjects, does not require the subject to know.

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Table 1. General information about the study population\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Characteristic & Total(n) & Before the COVID-19 & During the
COVID-19\tabularnewline
\midrule
\endhead
Total(n) & 29926 & 12484 & 17442\tabularnewline
Sex(male/female) & 19125/10801 & 8050/4434 & 11075/6367\tabularnewline
Age(mean\selectlanguage{ngerman}±SD) & 4.59\selectlanguage{ngerman}±3.103 & 4.21\selectlanguage{ngerman}±3.145 & 4.86\selectlanguage{ngerman}±3.043\tabularnewline
Age group & & &\tabularnewline
Infant(n) & 8535 & 4444 & 3909\tabularnewline
Preschool(n) & 12388 & 4593 & 12388\tabularnewline
School(n) & 6566 & 2435 & 6566\tabularnewline
Adolescence(n) & 2619 & 1015 & 2619\tabularnewline
Season & & &\tabularnewline
Spring (3-5) (n) & 7660 & 3064 & 4596\tabularnewline
Summer (6-8) (n) & 8122 & 3306 & 4816\tabularnewline
Autumn (9-11) (n) & 8154 & 3109 & 5045\tabularnewline
Winter (12-2) (n) & 5990 & 3005 & 2985\tabularnewline
allergen(n) & & &\tabularnewline
d1 & 6107 & 2854 & 3253\tabularnewline
d2 & 4801 & 1990 & 2811\tabularnewline
e2 & 21510 & 5063 & 16447\tabularnewline
mx2 & 26334 & 9699 & 16635\tabularnewline
sycamore & 13645 & 1318 & 12327\tabularnewline
e1 & 14460 & 1318 & 13142\tabularnewline
w1 & 19904 & 3932 & 15972\tabularnewline
elm & 13647 & 1318 & 12329\tabularnewline
w6 & 19656 & 4156 & 15500\tabularnewline
i6 & 21593 & 5142 & 16451\tabularnewline
w14 & 1592 & 1131 & 461\tabularnewline
t70 & 1592 & 1131 & 461\tabularnewline
u80 & 19898 & 3932 & 15966\tabularnewline
f37 & 1592 & 1131 & 461\tabularnewline
\bottomrule
\end{longtable}

Abbreviations: Dermatophagoides pteronyssinus (d1), Dermatophagoides
farinae (d2), dog hair (e2), cat hair (e1), cockroaches (i6), mulberry
(t70), sycamore pollen (sycamore), elm pollen (elm), grass pollen (u80),
mugwort pollen (w6), common ragweed pollen (w1), amaranth (w14), green
oysters (f37), mold (mx2)

Table 2. Logistics regression analysis of positive rate of inhaled
allergens before and during the COVID-19\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
Allergen & Univariate regression analysis & Univariate regression
analysis & Univariate regression analysis & Univariate regression
analysis & Multivariate regression analysis & Multivariate regression
analysis & Multivariate regression analysis & Multivariate regression
analysis\tabularnewline
\midrule
\endhead
& \emph{Wald X\textsuperscript{2}} & \emph{P} & \emph{OR}
\textsuperscript{a} & \emph{OR 95\% CI} & \emph{Wald
X\textsuperscript{2}} & \emph{P} & \emph{OR} \textsuperscript{b} &
\emph{OR 95\% CI}\tabularnewline
d1 & 73.933 & \textless{}0.001 & 1.564 & 1.413\textasciitilde{}1.732 &
4.641 & 0.031 & 1.174 & 1.015\textasciitilde{}1.358\tabularnewline
d2 & 152.380 & \textless{}0.001 & 2.124 & 1.885\textasciitilde{}2.394 &
8.760 & 0.003 & 1.301 & 1.093\textasciitilde{}1.549\tabularnewline
e2 & 73.835 & \textless{}0.001 & 1.735 & 1.530\textasciitilde{}1.968 &
25.261 & \textless{}0.001 & 1.499 &
1.280\textasciitilde{}1.756\tabularnewline
mx2 & 425.378 & \textless{}0.001 & 4.023 & 3.524\textasciitilde{}4.592 &
268.628 & \textless{}0.001 & 3.959 &
3.358\textasciitilde{}4.667\tabularnewline
sycamore & 43.075 & \textless{}0.001 & 3.576 &
2.444\textasciitilde{}5.233 & 13.013 & \textless{}0.001 & 2.510 &
1.522\textasciitilde{}4.139\tabularnewline
e1 & 38.662 & \textless{}0.001 & 3.879 & 2.530\textasciitilde{}5.948 &
22.527 & \textless{}0.001 & 4.249 &
2.338\textasciitilde{}7.722\tabularnewline
w1 & 47.907 & \textless{}0.001 & 2.483 & 1.919\textasciitilde{}3.213 &
15.457 & \textless{}0.001 & 1.828 &
1.353\textasciitilde{}2.470\tabularnewline
elm & 21.405 & \textless{}0.001 & 5.250 & 2.601\textasciitilde{}10.598 &
7.372 & 0.007 & 3.576 & 1.425\textasciitilde{}8.974\tabularnewline
w6 & 21.038 & \textless{}0.001 & 1.803 & 1.402\textasciitilde{}2.320 &
7.202 & 0.007 & 1.538 & 1.123\textasciitilde{}2.106\tabularnewline
i6 & 1.480 & 0.224 & 0.885 & 0.727\textasciitilde{}1.077 & 1.396 & 0.237
& 0.862 & 0.675\textasciitilde{}1.102\tabularnewline
w14 & 0.494 & 0.482 & 0.751 & 0.337\textasciitilde{}1.670 & 0.833 &
0.361 & 0.686 & 0.305\textasciitilde{}1.541\tabularnewline
t70 & 0.062 & 0.804 & 1.106 & 0.500\textasciitilde{}2.448 & 0.029 &
0.866 & 1.072 & 0.479\textasciitilde{}2.397\tabularnewline
U80 & 16.146 & \textless{}0.001 & 2.569 & 1.621\textasciitilde{}4.071 &
9.799 & 0.002 & 2.521 & 1.413\textasciitilde{}4.497\tabularnewline
F37 & 0.808 & 0.369 & 2.460 & 0.345\textasciitilde{}17.514 & 1.028 &
0.327 & 2.741 & 0.365\textasciitilde{}20.566\tabularnewline
\bottomrule
\end{longtable}

\textbf{Note:} a. Univariate regression analysis was performed in groups
before and during COVID-19. b. Adjusted for gender, age and season.

\textbf{Abbreviations} : Dermatophagoides pteronyssinus (d1),
Dermatophagoides farinae (d2), dog hair (e2), cat hair (e1), cockroaches
(i6), mulberry (t70), sycamore pollen (sycamore), elm pollen (elm),
grass pollen (u80), mugwort pollen (w6), common ragweed pollen (w1),
amaranth (w14), green oysters (f37), mold (mx2).

Table 3. Difference in inhaled allergen sIgE grade~before and during the
COVID-19{[}\%(n){]}\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
Allergens & Before & Before & During & During &
\emph{X\textsuperscript{2}} & \emph{P}\tabularnewline
\midrule
\endhead
& Lower group & High group & Lower group & High group & &\tabularnewline
d1 & 509(46.3) & 591(53.7) & 649(40.3) & 962(59.7) & 9.576 &
0.002\tabularnewline
d2 & 331(51.6) & 310(48.4) & 522(37.0) & 890(63.0) & 39.063 &
\textless{}0.001\tabularnewline
e2 & 303(98.1) & 6(1.9) & 1601(96.2) & 63(3.8) & 2.612 &
0.106\tabularnewline
mx2 & 258(97.7) & 6(2.3) & 1670(99.2) & 13(0.8) & 5.316 &
0.021\tabularnewline
sycamore & 28(100.0) & 0(0.0) & 886(99.6) & 4(0.4) & 0.126 &
0.722\tabularnewline
e1 & 20(90.0) & 2(9.1) & 796(98.0) & 16(2.0) & 5.143 &
0.023\tabularnewline
w1 & 65(100.0) & 0(0.0) & 640(100.0) & 0(0.0) & / & /\tabularnewline
elm & 8(100.0) & 0(0.0) & 382(99.7) & 1(0.3) & 0.021 &
0.885\tabularnewline
w6 & 68(95.8) & 3(4.2) & 464(98.5) & 7(1.5) & 2.556 &
0.110\tabularnewline
i6 & 135(97.8) & 3(2.2) & 385(98.2) & 7(1.8) & 0.083 &
0.773\tabularnewline
w14 & 25(96.2) & 1(3.8) & 8(100.0) & 0(0.0) & 0.317 &
0.573\tabularnewline
t70 & 20(100.0) & 0(0.0) & 9(100.0) & 0(0.0) & / & /\tabularnewline
u80 & 19(95.0) & 1(5.0) & 206(99.5) & 1(0.5) & 4.261 &
0.039\tabularnewline
f37 & 2(100.0) & 0(0.0) & 2(100.0) & 0(0.0) & / & /\tabularnewline
\bottomrule
\end{longtable}

\textbf{Note:} / indicates that there is no data for this item.
Abbreviations: Dermatophagoides pteronyssinus (d1), Dermatophagoides
farinae (d2), dog hair (e2), cat hair (e1), cockroaches (i6), mulberry
(t70), sycamore pollen (sycamore), elm pollen (elm), grass pollen (u80),
mugwort pollen (w6), common ragweed pollen (w1), amaranth (w14), green
oysters (f37), mold (mx2).

Table 4. Differences in the number of allergens sensitized before and
during the COVID-19\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Number of allergens\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Before the COVID-19 (n=12484) n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
After the COVID-19 (n=17422) n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\emph{X\textsuperscript{2}}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\emph{P}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
10648(85.3)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
11331(65.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1621.815\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1060(8.5)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
3137(18.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
707(5.7)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2227(12.8)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
3\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
49(0.4)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
526(3.0)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
4\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
12(0.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
139(0.8)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textgreater{}4\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
8(0.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
82(0.5)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1. The number of allergen positive rates and positive cases in
each month during and before COVID-19. Abbreviations: Dermatophagoides
pteronyssinus (d1), Dermatophagoides farinae (d2), dog hair (e2),
cockroaches (i6), grass pollen (u80), mugwort pollen (w6), common
ragweed pollen (w1), mold (mx2).

\selectlanguage{english}
\FloatBarrier
\end{document}

