<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="brief-report" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.164631.2</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Brief Report</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Emerging pathogens associated with acute respiratory infections in children in Hanoi, Vietnam: an analysis of microbiology assay data from 2019 to 2023</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 2; peer review: 1 approved, 1 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Thi Ho</surname>
                        <given-names>Nhan</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-7898-0956</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Nguyen</surname>
                        <given-names>Hang Thi Thuy</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0009-0009-2643-0790</uri>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Hoang</surname>
                        <given-names>Ha Thi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Pham</surname>
                        <given-names>Dung Van</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Nguyen</surname>
                        <given-names>Quang Ngoc</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Le</surname>
                        <given-names>Huong Thi Minh</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Pham</surname>
                        <given-names>An Nhat</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Doan</surname>
                        <given-names>Phuong Mai</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="corresp" rid="c2">b</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Research Management Department, Vinmec Healthcare System, Hanoi, Vietnam</aff>
                <aff id="a2">
                    <label>2</label>Vinmec Times City International Hospital, Hanoi, Vietnam</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:nhanhocumc@gmail.com">nhanhocumc@gmail.com</email>
                </corresp>
                <corresp id="c2">
                    <label>b</label>
                    <email xlink:href="mailto:v.phuongdm@vinmec.com">v.phuongdm@vinmec.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>26</day>
                <month>12</month>
                <year>2025</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2025</year>
            </pub-date>
            <volume>14</volume>
            <elocation-id>505</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>19</day>
                    <month>12</month>
                    <year>2025</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Thi Ho N et al.</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/14-505/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>The COVID-19 pandemic has caused changes in respiratory infectious diseases. Examining the patterns of pathogens associated with acute respiratory infection (ARI) in children before, during, and after the COVID-19 pandemic would help to understand the impact of the pandemic on pathogen emergence or re-emergence.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>We analyzed de-identified data from microbiology assays of nasopharyngeal and blood samples of children &#x2264;15 years old with ARI who visited Vinmec Times City International Hospital in Hanoi, Vietnam from 01/01/2019 to 31/12/2023. The data were aggregated by month, and time-series analysis and visualization were performed.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>A Bacterial Polymerase Chain Reaction (PCR) panel was performed on 4,125 samples (67% positive), 
                        <italic toggle="yes">Mycoplasma pneumonia</italic> (MP) IgM was performed on 5,049 samples (39% positive), bacterial culture was performed on 10,280 samples (43% positive), and viral PCR or rapid test was performed on 42,300 samples (23% positive). After the COVID-19 pandemic from mid-2022, 
                        <italic toggle="yes">Haemophilus influenzae</italic> (HI) and 
                        <italic toggle="yes">Streptococcus pneumoniae</italic> (SP) have re-emerged as epidemic pathogens associated with lower respiratory tract infection (LRI). 
                        <italic toggle="yes">Influenza type A</italic> and 
                        <italic toggle="yes">type B</italic> have re-established regular cycles of peaks in winter-spring months after an early rebound together with an unprecedented new emergence of 
                        <italic toggle="yes">Human Adenovirus</italic> (HAdV) soon after the relief of COVID-19 restriction in mid-2022. Late after the COVID-19 pandemic, from mid-2023, atypical pneumonia pathogen 
                        <italic toggle="yes">Mycoplasma pneumonia</italic> (MP) has emerged remarkably and has become epidemic; there was also a small, brief emergence of 
                        <italic toggle="yes">Chlamydophila pneumoniae</italic> (CP) infection.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>Our data characterize the influence of the COVID-19 pandemic on the patterns of respiratory infection pathogens in children and is useful for disease surveillance and public health interventions.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>emerging; pathogen; acute respiratory infection; children; Vietnam</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Vinmec Healthcare System</funding-source>
                </award-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 1</title>
                <p>This version 2 includes some minor edits following the reviewer&#x2019;s comments: 1) Additional information clarifying microbiological assays in the Methods section; 2) Shortened Figure 1 legend; 3) Additional text in the Discussions showing that the outbreaks after the COVID-19 pandemic shown by our data corresponded with actual outbreaks observed by authorities in Vietnam during the same time period and additional citations; 4) Additional text in the Discussions regarding public health measures for governments to implement to contain future respiratory outbreaks and the usefulness of our data; 5) Additional text in the Discussions regarding future research that may be expanded from our current data.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>1. Introduction</title>
            <p>The COVID-19 pandemic and related policies have changed the patterns of respiratory infectious diseases.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> The incidence of most respiratory infections, apart from COVID-19, has decreased during the COVID-19 pandemic due to restricted measures.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> After easing COVID-19 related restricted measures, the sudden increase of exposure in the community, whose immunity might be waned during the prolonged no-contact quarantine period, might lead to irregular respiratory infection patterns.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> There have been some reports regarding the rebound of viral pathogens, such as influenza,
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>,
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> and bacterial pathogens, such as Mycoplasma,
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> after the COVID-19 pandemic. We previously reported the molecular data of a case series of 
                <italic toggle="yes">Human Adenovirus</italic> (HAdV) outbreak in 2022
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> and 
                <italic toggle="yes">Mycoplasma pneumonia</italic> (MP) outbreak in 2023
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> in Hanoi, Vietnam.</p>
            <p>Knowing how the COVID-19 pandemic and related restrictions influenced the pattern of viral and bacterial pathogens associated with acute respiratory infections (ARIs) in children would be helpful for public health interventions during the post-COVID-19 era. This could also provide useful information for health authorities to cope with future pandemics. Some studies have described the impact of COVID-19 on the pattern of pathogens associated with ARIs in children, including those in Italy
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> and China.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> However, published data regarding this matter in Vietnam are still scarce. As Vietnam may be different from other countries in terms of the COVID-19 outbreak situation and related restricted measures as well as population characteristics, such studies specifically in Vietnam are necessary.</p>
            <p>In this report, we describe the overall pattern of emerging viral and bacterial pathogens associated with ARIs in children before, during, and after the COVID-19 pandemic in Hanoi, Vietnam, to understand the influence of the COVID-19 pandemic and related restrictions on the emergence or re-emergence of other respiratory infection pathogens in children.</p>
        </sec>
        <sec id="sec6">
            <title>2. Materials and methods</title>
            <p>This study was conducted after obtaining ethical approval (approval No 110/2024/CN/HDDD VMEC, date October 10, 2024) from the Ethical Committee of Vinmec Healthcare System and VinUniversity (Ethical Committee establishment decision No 24/2016/QD-VINMEC). Informed consent was waived by the Ethical Committee for retrospective analysis and report of de-identified
 data.</p>
            <p>We analyzed the deidentified data of microbiology assays of nasopharyngeal and blood samples of children with ARIs who visited Vinmec Times City International Hospital in Hanoi, Vietnam, from January 1, 2019, to December 31, 2023. These microbiological assays were done in Vinmec hospital for patients with corresponding indications (e.g. assays for Mycoplasma pneumoniae (MP) were indicated and done if the patient had signs or symptoms suggesting MP infection and assays for MP were not routinely done for all patients with any acute respiratory infections). This study data period included the time before, during, and after the COVID-19 pandemic, and thus facilitated the evaluation of the impact of the COVID-19 pandemic on the patterns of pathogens associated with ARIs in children. Data were obtained from the recorded microbiology assay result database of the Vinmec Microbiology Department. The original data contained information regarding patient identification, sex, date of birth, date of microbiological assays, diagnosis of microbiological assay indication, and assay results. The data were de-identified before being transferred to the research team, which had no access to information that could identify individual participants during data access and analysis. All patients included in the analysis were &#x2264;15 years old with one or more diagnoses of respiratory infection and with one or more microbiological assays of nasopharyngeal or blood samples. All included patients were from Hanoi and surrounding provinces.</p>
            <p>During the study period in Hanoi, Vietnam, due to the COVID-19 pandemic, intermittent social distancing was applied from mid-2020 to the first half of 2021, when there were only sporadic COVID-19 cases or clusters, and there was no remarkable COVID-19 outbreak. The lockdown was then applied in the second half of 2021 due to the severe COVID-19 outbreak in Vietnam during this time.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> After the lockdown period, milder social distancing was applied in early 2022, when most of the population had been vaccinated with COVID-19 vaccines, and most of the cases were mild and Omicron was the dominant reported variant. Then COVID-19 related restriction was relieved starting from the second quarter of 2022, when COVID-19 was no longer a public health concern in Vietnam.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> The timeline associated with COVID-19 activity and COVID-19 related restricted measures is shown in 
                <xref ref-type="fig" rid="f1">
Figure 1</xref>. Our study data included the periods before, during and after the COVID-19 related restriction and thus enabling us to examine the impact of the COVID-19 pandemic on the pattern of pathogens associated with ARIs in children.</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>
Figure 1. </label>
                <caption>
                    <title>Time series plots of pathogens associated with ARIs in children from 2019 to 2023.</title>
                    <p>(A) Allplex Respiratory Panel 4 (
                        <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_4">https://www.seegene.com/assays/allplex_respiratory_panel_4</ext-link>) using multiplex one-step real-time Polymerase Chain Reaction (PCR) of nasopharyngeal samples for the detection of 7 bacteria causing respiratory tract infections including 
                        <italic toggle="yes">Bordetella parapertussis (BPP)</italic>, 
                        <italic toggle="yes">Bordetella pertussis (BP)</italic>, 
                        <italic toggle="yes">Chlamydophila pneumoniae (CP)</italic>, 
                        <italic toggle="yes">Haemophilus influenzae (HI)</italic>, 
                        <italic toggle="yes">Legionella pneumophila (LP)</italic>, 
                        <italic toggle="yes">Mycoplasma pneumoniae (MP)</italic>, 
                        <italic toggle="yes">Streptococcus pneumoniae (SP)</italic>.</p>
                    <p>(B) Blood IgM serology test for 
                        <italic toggle="yes">Mycoplasma pneumoniae</italic> (LIAISON Mycoplasma pneumoniae IgM of Diasorin, Ireland).</p>
                    <p>(C) Bacterial culture of nasopharyngeal samples (following the procedures guided in &#x201c;Clinical Microbiology Procedures Handbook&#x201d; of American Society for Microbiology
                        <sup>
                            <xref ref-type="bibr" rid="ref17">17</xref>
                        </sup>) including 
                        <italic toggle="yes">Haemophilus influenzae</italic> (HI), 
                        <italic toggle="yes">Streptococcus pneumoniae</italic> (SP), 
                        <italic toggle="yes">Moraxella catarrhalis</italic> (MC) and other pathogens.</p>
                    <p>(D) Viral assays including Allplex Respiratory PCR Panel 1 (
                        <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_1">https://www.seegene.com/assays/allplex_respiratory_panel_1</ext-link>) using multiplex one-step real-time RT-PCR for the detection of 
                        <italic toggle="yes">Influenza type A (Flu A), Influenza type B (Flu B) and Respiratory Syncytial Virus (RSV)</italic>, or rapid test for the detection of Flu A and Flu B (SD Bioline Influenza A/B Ag of Standard Diagnostic, South Korea), and RSV (BD Veritor System RSV Devices of Becton, Dickinson and Company, USA) or Allplex Respiratory PCR Panel 2 (
                        <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_2">https://www.seegene.com/assays/allplex_respiratory_panel_2</ext-link>) using multiplex one-step real-time RT-PCR of nasopharyngeal samples for the detection of 7 viruses causing respiratory tract infections including 
                        <italic toggle="yes">Human Adenovirus (HAdV), Enterovirus (HEV), Metapneumovirus (MPV), Parainfluenza virus 1,2,3 4 (PIV1,2,3,4)</italic>.</p>
                    <p>The plot shows the number of patients tested (n.tested) and the number of patients positive for each pathogen.</p>
                    <p>The x-axis shows the year and month of the year (e.g. 19.01 means January 2019, 23.10 means October 2023).</p>
                    <p>Co-detection: &#x2265;2 pathogens were detected.</p>
                    <p>ARIs: acute respiratory infections.</p>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/194032/0a501276-dd43-42b4-b222-39f750a30250_figure1.gif"/>
            </fig>
            <p>The microbiology assays included in the analysis were:
                <list list-type="alpha-upper">
                    <list-item>
                        <label>(A)</label>
                        <p>Allplex Respiratory Panel 4 (
                            <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_4">https://www.seegene.com/assays/allplex_respiratory_panel_4
</ext-link>) using real-time Polymerase Chain Reaction (PCR) of nasopharyngeal samples to detect seven bacteria causing respiratory tract infections, including 
                            <italic toggle="yes">Bordetella parapertussis</italic> (BPP), 
                            <italic toggle="yes">Bordetella pertussis</italic> (BP), 
                            <italic toggle="yes">Chlamydophila pneumoniae</italic> (CP), 
                            <italic toggle="yes">Haemophilus influenzae</italic> (HI), 
                            <italic toggle="yes">Legionella pneumophila</italic> (LP), 
                            <italic toggle="yes">Mycoplasma pneumoniae</italic> (MP), 
                            <italic toggle="yes">Streptococcus pneumoniae</italic> (SP).</p>
                    </list-item>
                    <list-item>
                        <label>(B)</label>
                        <p>Blood IgM serology test for 
                            <italic toggle="yes">Mycoplasma pneumonia</italic> (LIAISON Mycoplasma pneumoniae IgM; Diasorin, Ireland).</p>
                    </list-item>
                    <list-item>
                        <label>(C)</label>
                        <p>Bacterial culture of nasopharyngeal samples (following the procedures guided in the &#x201c;Clinical Microbiology Procedures Handbook&#x201d; of the American Society for Microbiology
                            <sup>
                                <xref ref-type="bibr" rid="ref17">17</xref>
                            </sup>).</p>
                    </list-item>
                    <list-item>
                        <label>(D)</label>
                        <p>Viral assays including Allplex Respiratory PCR Panel 1 (
                            <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_1">https://www.seegene.com/assays/allplex_respiratory_panel_1
</ext-link>) using multiplex one-step real-time RT-PCR for the detection of 
                            <italic toggle="yes">Influenza type A</italic> (Flu A), 
                            <italic toggle="yes">Influenza type B</italic> (Flu B), and 
                            <italic toggle="yes">Respiratory Syncytial Virus</italic> (RSV), or rapid test for the detection of Flu A and Flu B (SD Bioline Influenza A/B Ag of Standard Diagnostic, South Korea), and RSV (BD Veritor System RSV Devices of Becton, Dickinson and Company, USA) or Allplex Respiratory PCR Panel 2 (
                            <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_2">https://www.seegene.com/assays/allplex_respiratory_panel_2
</ext-link>) using multiplex one-step real-time RT-PCR of nasopharyngeal samples for the detection of seven viruses causing respiratory tract infections, including 
                            <italic toggle="yes">Human Adenovirus</italic> (HAdV), 
                            <italic toggle="yes">Enterovirus</italic> (HEV), 
                            <italic toggle="yes">Metapneumovirus</italic> (MPV), 
                            <italic toggle="yes">Parainfluenza virus</italic> 1,2,3 4 (PIV1,2,3,4).</p>
                    </list-item>
                </list>
            </p>
            <p>Clinical data accompanying the microbiological assay data available for our analysis were patient diagnosis, age, and sex. Patients were classified into two groups: upper respiratory infections (URI) and lower respiratory infections (LRI) based on the diagnoses for indication of microbiology assays. LRI included those with the following diagnoses: pneumonia, bronchitis, bronchiolitis, bronchopneumonia, and asthma. Those with a diagnosis of upper respiratory tract infection and without any diagnosis involving the lower respiratory tract were classified as having URI. All participants included in the analysis must have data regarding the results of at least one microbiological assay using nasopharyngeal or blood samples, the date when the assays were performed, diagnosis of ARIs, age, and sex. Those with missing data for one or more variables were excluded from the analysis.</p>
            <p>The data were aggregated by month, and time-series plots were used to visualize the data by month from January 2019 to December 2023. The number of samples tested and the number of samples positive for each pathogen were plotted by month. For patient characteristics, the mean age with standard error, percentage of males, and percentage of diagnosis category LRI were plotted. Co-detection (&#x2265; 2 pathogens detected in a patient) was also described. Patient characteristics were compared between the groups using the Kruskal&#x2013;Wallis test for continuous variables and the chi-square test for categorical variables.</p>
        </sec>
        <sec id="sec7" sec-type="results">
            <title>3. Results</title>
            <p>In overall, in the beginning of the pandemic time from early 2020 to the first half of 2021, when intermittent social distancing was applied and when there were sporadic COVID-19 cases or clusters in Hanoi, Vietnam, the number of ARI cases positive for bacterial or other viral pathogens decreased as compared to that before the COVID-19 pandemic. However, there were still peaks of both bacterial and other viral pathogens from winter 2020 to spring 2021, although the peak of other viral pathogens was smaller than that before COVID-19. An exception was the relatively high number of bacterial cultures positive for SP, HI, and MI at the end of 2020 and early 2021. During the lockdown period in the second half of 2021 due to the severe COVID-19 outbreak in Vietnam, the reduction was much more remarkable in that the number of ARI cases positive for bacterial or other viral pathogens was almost close to zero. Both bacterial and other viral pathogens started to increase after the relief of COVID-19 related restriction starting from the second quarter of 2022. However, the rise of viral pathogens was sooner and faster, resulting in a high peak just a few months after the relief of COVID-19 related restriction (
                <xref ref-type="fig" rid="f1">
Figure 1</xref>).</p>
            <p>Bacterial PCR Panel 4 was performed on 4125 samples from 3708 patients, of which 2762 (67%) samples were positive for &#x2265;1 pathogen tested in the panel. LRI accounted for 73%, males accounted for 58%, and the average age was 3.2 years. A total of 1606 (39%) samples were positive for HI, 1237 (30%) for SP, 675 (16%) for MP, and 777 (18.8%) for &#x2265;2 pathogens (co-detection). Co-detection was observed in 44% of those positive for MP, 49% of those positive for SP, and 41% of those positive for HI. Nearly all (90%) of those positive for MP had LRI, and approximately three-fourths of those positive for SP or HI had LRI. The average age of patients positive for SP or HI was less than 3 years, while the average age of those positive for MP was nearly 5 years (p &lt; 0.001) (
                <xref ref-type="table" rid="T1">
Table 1</xref>, 
                <xref ref-type="fig" rid="f2">
Figure 2A</xref>). There was one peak of HI and SP infections at the end of 2019 before the COVID-19 pandemic and a smaller peak at the end of 2020 before a close-to-zero flat period during the severe COVID-19 outbreak in the second half of 2021 in Vietnam. After the relief of COVID-19 related restriction starting from the second quarter of 2022, a much higher peak of HI and SP infection re-emerged in the middle of 2023 in parallel with a newly emerged large peak of MP infection. A new small peak of CP infection also briefly emerged a few months later, in the middle of 2023 (
                <xref ref-type="fig" rid="f1">
Figure 1A</xref>).</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>
Table 1. </label>
                <caption>
                    <title>Summary of patient characteristics.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="14" rowspan="1" valign="top">Bacterial pathogens</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                            <th align="left" colspan="6" rowspan="1" valign="top">PCR Panel 4
                                <xref ref-type="table-fn" rid="tfn1">
                                    <sup>a</sup>
                                </xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">MP IgM
                                <xref ref-type="table-fn" rid="tfn2">
                                    <sup>b</sup>
                                </xref>
                            </th>
                            <th align="left" colspan="5" rowspan="1" valign="top">Culture
                                <xref ref-type="table-fn" rid="tfn3">
                                    <sup>c</sup>
                                </xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Patient characteristics</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
MP Positive (N = 675; 16%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
SP Positive (N = 1237; 30%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
HI positive (N = 1606; 39%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Co-detection (N = 777; 19%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Total panel 4 (N = 4125)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
p value
                                <xref ref-type="table-fn" rid="tfn5">*</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
MP IgM Positive (N = 1976; 39%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
HI positive (N = 1878; 18%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
SP positive (N = 1230; 12%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
MC positive (N = 1367; 13%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Co-detection (N = 177; 1.7%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Total culture (N = 10280)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
P value
                                <xref ref-type="table-fn" rid="tfn5">*</xref>
                            </th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age Mean (95%CI)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.6 (4.4, 4.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.8 (2.7, 2.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.9 (2.8, 3.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.296 (3.130, 3.462)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.2 (3.2, 3.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.6 (3.5, 3.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.4 (2.3, 2.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.3 (2.2, 2.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.3 (2.2, 2.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.1 (1.9, 2.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.6 (2.6, 2.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.228</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Sex male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">378 (56.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">722 (58.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">954 (59.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">456 (58.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2416 (58.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.169</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1027 (52.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1124 (59.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">700 (56.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">803 (58.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">104 (58.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6134 (59.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.453</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">ARI category: LRI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">612 (90.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">909 (73.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1191 (74.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">607 (78.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3035 (73.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1545 (78.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1201 (64.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">773 (62.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">792 (57.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">133 (75.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5890 (57.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.607</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Co-detection
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">298 (44.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">606 (49.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">660 (41.1%)</td>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">777 (18.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">118 (6.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">107 (8.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">129 (9.4%)</td>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">177 (1.7%)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="12" rowspan="1" valign="top">Viral pathogens</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                            <th align="left" colspan="5" rowspan="1" valign="top">PCR or rapid test
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>d</sup>
                                </xref>
                            </th>
                            <th align="left" colspan="5" rowspan="1" valign="top">PCR Panel 2
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>d</sup>
                                </xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Patient characteristics</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Flu A positive (N = 6614/40112; 17%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Flu B positive (N = 1677/40112; 4%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">RSV positive (N = 810/2772; 29%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total PCR or rapid test for Flu A, Flu B, RSV (N = 41236)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">p-value
                                <xref ref-type="table-fn" rid="tfn5">*</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HAdV positive (N = 413; 39%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HEV positive (N = 161; 15%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">MPV positive (N = 121; 11%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total PCR panel 2 (N = 1064)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">p-value
                                <xref ref-type="table-fn" rid="tfn5">*</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total all viral assays (N = 42300)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age Mean (95%CI)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.9 (4.8, 5.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.6 (5.4, 5.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.0 (0.96, 1.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.64 (3.61, 3.68)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.0 (2.8, 3.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.8 (2.5, 3.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.8 (2.5, 3.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.1 (2.9, 3.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.084</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.6 (3.5, 3.6)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Sex male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3736 (56.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">979 (58.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">465 (57.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23628 (57.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.189</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">256 (62.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">92 (57.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">79 (65.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">650 (61.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.620</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24127 (57.4%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">ARI category: LRI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">604 (9.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">123 (7.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">685 (84.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7463 (18.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">93 (22.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45 (28.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">60 (49.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">357 (33.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8169 (19.4%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Co-detection
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10 (0.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14 (1.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">98 (23.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">70 (43.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53 (43.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">130 (12.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt; 0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">149 (0.4%)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>ARI: Acute respiratory infection; LRI: Lower respiratory infection. </p>
                    <p>Co-detection: &#x2265;2 pathogens were detected. </p>
                    <p>95% CI: 95% confidence interval.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>
                                <sup>a</sup>
                            </label>
                            <p>Allplex Respiratory Panel 4 (
                                <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_4">https://www.seegene.com/assays/allplex_respiratory_panel_4
</ext-link>) using multiplex one-step real-time Polymerase Chain Reaction (PCR) of nasopharyngeal samples for the detection of seven bacteria causing respiratory tract infections, including 
                                <italic toggle="yes">Bordetella parapertussis (BPP), Bordetella pertussis (BP), Chlamydophila pneumoniae (CP), Haemophilus influenzae (HI), Legionella pneumophila (LP), Mycoplasma pneumoniae (MP), Streptococcus pneumoniae (SP).</italic> The table shows the patient characteristics for the total number of patients tested and the number of patients positive for each pathogen.</p>
                        </fn>
                        <fn id="tfn2">
                            <label>
                                <sup>b</sup>
                            </label>
                            <p>Blood IgM serology test for 
                                <italic toggle="yes">Mycoplasma pneumoniae</italic> (LIAISON Mycoplasma pneumoniae IgM, Diasorin, Ireland). The table shows the patient characteristics for the number of patients with IgM seropositivity for 
                                <italic toggle="yes">Mycoplasma pneumoniae.</italic>
                            </p>
                        </fn>
                        <fn id="tfn3">
                            <label>
                                <sup>c</sup>
                            </label>
                            <p>Bacterial culture of nasopharyngeal samples (following the procedures guided in the &#x201c;Clinical Microbiology Procedures Handbook&#x201d; of the American Society for Microbiology (17)). The table shows patient characteristics for the total number of patients tested and the number of patients with positive cultures for each pathogen: 
                                <italic toggle="yes">Haemophilus influenzae</italic> (HI), 
                                <italic toggle="yes">Streptococcus pneumoniae</italic> (SP), 
                                <italic toggle="yes">Moraxella catarrhalis</italic> (MC).</p>
                        </fn>
                        <fn id="tfn4">
                            <label>
                                <sup>d</sup>
                            </label>
                            <p>Viral assays including Allplex Respiratory PCR Panel 1 (
                                <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_1">https://www.seegene.com/assays/allplex_respiratory_panel_1
</ext-link>) using multiplex one-step real-time RT-PCR for the detection of 
                                <italic toggle="yes">Influenza type A (Flu A), Influenza type B (Flu B) and Respiratory Syncytial Virus (RSV)</italic>, or rapid test for the detection of Flu A and Flu B (SD Bioline Influenza A/B Ag of Standard Diagnostic, South Korea), and RSV (BD Veritor System RSV Devices of Becton, Dickinson and Company, USA) or Allplex Respiratory PCR Panel 2 (
                                <ext-link ext-link-type="uri" xlink:href="https://www.seegene.com/assays/allplex_respiratory_panel_2">https://www.seegene.com/assays/allplex_respiratory_panel_2
</ext-link>) using multiplex one-step real-time RT-PCR of nasopharyngeal samples for the detection of seven viruses causing respiratory tract infections, including 
                                <italic toggle="yes">Human Adenovirus (HAdV), Enterovirus (HEV), Metapneumovirus (MPV), Parainfluenza virus 1,2,3 4 (PIV1,2,3,4).</italic> The table shows the patient characteristics for the total number of patients tested and the number of patients positive for each pathogen.</p>
                        </fn>
                        <fn id="tfn5">
                            <label>*</label>
                            <p>p-values for comparison between groups are from the Kruskal-Wallis test for continuous variables or Chi-square test for categorical variables.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                <label>
Figure 2. </label>
                <caption>
                    <title>Time series plot of patient characteristics from 2019 to 2023.</title>
                    <p>PCR, Polymerase Chain Reaction; LRI, Lower respiratory infection. Co-detection: &#x2265;2 pathogens were detected. The x-axis shows the year and month of the year (e.g. 19.01 means January 2019, 23.10 means October 2023). The characteristics of all patients tested are displayed. Mean age with standard error, percentage of males, percentage of LRI, and percentage of co-detection were aggregated and plotted by month.</p>
                </caption>
                <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/194032/0a501276-dd43-42b4-b222-39f750a30250_figure2.gif"/>
            </fig>
            <p>There were 5049 samples from 4361 patients tested for MP IgM, of which 1976 samples (39%) were serologically positive. The average age of those with seropositive MP IgM was 3.6 years old and 78% had LRI, and 52% were males (
                <xref ref-type="table" rid="T1">
Table 1</xref>, 
                <xref ref-type="fig" rid="f2">
Figure 2B</xref>). There was no clear peak in MP IgM seropositivity before and during the COVID-19 pandemic from January 2019 to early 2022. In middle of 2022 when COVID-19 related restriction in Vietnam were relieved, even though there was an increase in the number of patients tested, the number of MP IgM seropositive cases remained low. By March 2023, a new peak of MP IgM seropositivity began to emerge in parallel with the peak of MP PCR positivity in 2023 (
                <xref ref-type="fig" rid="f1">
Figure 1B</xref>).</p>
            <p>Bacterial culture was performed on 10280 samples from 8073 patients, of which 4369 samples (43%) were positive for &#x2265;1 bacterial pathogen. LRI accounted for 57%, males accounted for 60%, and the average age was 2.6 years old. The most common culture-positive pathogens were HI (N = 1878 (18%)), SP (N = 1230, 12%), and 
                <italic toggle="yes">Moraxella catarrhalis</italic> (MC) (N = 1367, 13%). Co-detection of &#x2265;2 pathogens was observed in 177 patients (1.7%). Co-detection was observed in approximately 6% of those positive for HI and 9% of those positive for SP or MC (
                <xref ref-type="table" rid="T1">
Table 1</xref>, 
                <xref ref-type="fig" rid="f2">
Figure 2C</xref>). There was one peak of HI, SP, and MC infections from the end of 2020 to early 2021 when intermittent social distancing was applied, and there were only sporadic COVID-19 cases or clusters in Vietnam. After the relief of COVID-19 related restriction starting from the second quarter of 2022 in Vietnam, there was a large, long-lasting increase in positive bacterial cultures from the middle of 2022 until the end of the data period in December 2023 (
                <xref ref-type="fig" rid="f1">
Figure 1C</xref>).</p>
            <p>Regarding viral pathogens, Allplex PCR Panel 1 or rapid test for Flu A, Flu B, RSV, or Allplex PCR Panel 2 was done on 42300 samples from 28178 patients, of which 9777 (23%) samples were positive for &#x2265;1 viral pathogens tested. A total of 6614/40112 (17%) samples were positive for Flu A, 1677/40112 (4%) samples were positive for Flu B, and 810/2772 (29%) samples were positive for RSV. In Allplex PCR Panel 2, 413/1064 (39%) samples were positive for HAdV, 161/1064 (15%) samples were positive for HEV, and 121/1064 (11%) samples were positive for MPV. LRI accounted for &lt;10% of those positive for Flu A or Flu B, 85% of those positive for RSV, 23% of those positive for HAdV, 28% of those positive for HEV, and 50% of those positive for MPV. Co-detection was common in those positive for HAdV, HEV, or MPV (24&#x2013;44%). Males accounted for approximately 60% of those positive for viral pathogens. The average age of those positive for HAdV, HEV, or MPV was approximately 3 years, the average age of those positive for RSV was 1 year, and the average age of those positive for Flu A or Flu B was approximately 5 years (p &lt; 0.001) (
                <xref ref-type="table" rid="T1">
Table 1</xref>, 
                <xref ref-type="fig" rid="f2">
Figure 2D</xref>). Flu A showed a regular cycle with peaks in the winter-spring months of 2019-2020, 2020-2021, 2022-2023 and the end of 2023 (except for a close-to-zero flat period during the lockdown due to the severe COVID-19 outbreak in the second half of 2021 to early 2022). Flu A peaks were often followed by smaller Flu B peaks a few months later. Soon after the relief of COVID-19 restriction starting from the second quarter of 2022, there was an exceptionally early peak of Flu A in the summer months of 2022, followed by a smaller peak of Flu B three months later. Another exception was the newly emerged peak of HAdV in the second half of 2022 (
                <xref ref-type="fig" rid="f1">
Figure 1D</xref>).</p>
            <p>The overall patient characteristics are summarized in 
                <xref ref-type="table" rid="T1">
Table 1</xref> and plotted as a time series in 
                <xref ref-type="fig" rid="f2">
Figure 2</xref>. Males accounted for ~60% of patients with ARI for all pathogens. Most bacteria-associated ARI patients had lower respiratory infections (LRI), whereas most virus-associated ARI patients (except RSV) had upper respiratory infections (URI). Most ARI patients were young (average age ~3 years old or younger), except those infected with MP, Flu A, and Flu B, who were slightly older (average age ~5 years old).</p>
        </sec>
        <sec id="sec8" sec-type="discussion">
            <title>4. Discussion</title>
            <p>Our analysis of microbiology assay data of nasopharyngeal and blood samples of children with ARI from January 2019 to December 2023 provides an overall picture of the pattern of respiratory infections other than COVID-19 and the emerging pathogens before, during, and after the COVID-19 pandemic in Hanoi, Vietnam.</p>
            <p>The reduction pattern of bacterial and other viral pathogens at the beginning of the pandemic from 2020 to early 2021 was somewhat similar to the pattern of bacterial and other viral pathogens in other countries such as Israel
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup> and China
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> during this time. The close-to-zero flat period of bacterial and other viral pathogens during the lockdown period due to the severe COVID-19 outbreak in Vietnam in the second half of 2021 was explicable.</p>
            <p>After the relief of COVID-19 related restriction starting from the second quarter of 2022 in Vietnam, the rebound of HI and SP was not only large in number of positive cases but also long-lasting. An increase in the number of HI-positive cases was observed from the middle of 2022 until the end of our data period in December 2023. Approximately three-fourths of these positive cases had LRI. This indicates that after the COVID-19 pandemic, HI and SP have largely re-emerged and become persistent epidemic pathogens associated with LRI in children. This pattern is similar to that observed in other countries, as summarized by Nygaard et al.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup>
            </p>
            <p>After the relief of COVID-19 related restriction starting from the second quarter of 2022 in Vietnam, although the number of patients tested for MP IgM increased from early 2022, the number of patients with seropositive MP IgM did not increase until the middle of 2023. The increase in the number of patients with seropositive MP IgM was consistent with the increase in the number of patients with positive MP PCR results during the same period. This indicates that the increase was due to the real increase in the number of MP infection cases and not just due to the increase in the number of patients tested. Most of the patients positive for MP had LRI and were older than other patients positive for other bacterial pathogens. There was also a small newly emerged peak of CP-positive cases two months after the peak of MP-positive cases. These peaks were consistent with the outbreak of bacteria, especially atypical bacteria-associated pneumonia, in 2023, late after the COVID-19 pandemic, as reported in Vietnam,
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> China,
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> and some other countries.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup>
            </p>
            <p>The outbreaks after the COVID-19 pandemic shown by our data corresponded with actual outbreaks observed by authorities in Vietnam during the same time period. For example, the HAdV and MP outbreaks corresponded to the outbreak of HAdV and MP reported by Vietnam authorities (Ministry of Health, National Children Hospital) in Vietnam at the same time period.
                <sup>
                    <xref ref-type="bibr" rid="ref24">22</xref>,
                    <xref ref-type="bibr" rid="ref25">23</xref>
                </sup> The Flu A and Flu B outbreaks observed in our data also corresponded with the Flu outbreak reported by Vietnam authorities at the same time period.
                <sup>
                    <xref ref-type="bibr" rid="ref26">24</xref>
                </sup> We also previously published molecular data of HAdV outbreak early after the relief of COVID-19 related restriction in 2022
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> and MP outbreak late after the relief of COVID-19 related restriction in 2023.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>Overall, the pattern of viral pathogens during and after the COVID-19 pandemic in our data was quite similar to that in other countries, such as Italy
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> and China.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> After the relief of COVID-19 related restriction starting from the second quarter of 2022 in Vietnam, the early rebound of Flu A and Flu B in the summer months of 2022 was consistent with the irregular rebound of viral ARI after the relief of COVID-19 restriction, as reported in many places.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>,
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> The exceptional newly emerged peak of HAdV in the second half of 2022 was consistent with the unprecedented outbreak of HAdV-associated ARI in children in Vietnam, as previously reported.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> A similar post-COVID-19 outbreak of HAdV-associated ARI in children was also reported a year later in Japan.
                <sup>
                    <xref ref-type="bibr" rid="ref22">25</xref>
                </sup>
            </p>
            <p>Regarding the methodology, instead of plotting the positive rate, we plotted the number of samples tested and the number of samples positive for each pathogen by month. This would help contextualize the emergence or outbreak of pathogens better because it not only provides information on the number of samples tested and the number of positive samples (which are higher in case of outbreak) but also helps to infer the pathogen positive rate over time. Plotting the positive rates alone may be misleading. For example, one positive sample out of one tested sporadically would give a positive rate of 100%, but there would probably be no outbreak. Whereas 3000 positive samples out of 10000 samples tested in a short time would give a positive rate of 30%, and there would likely be an outbreak.</p>
            <p>There may be some implication regarding public health measures for governments to implement to contain future respiratory outbreaks. The appropriate measures to contain future respiratory outbreaks may include maintaining availability and coverage of vaccines for outbreak-prone respiratory pathogens (e.g. maintaining Flu, HI, SP,&#x2026; vaccination for community) alongside with maintaining public health interventions to reduce or prevent exposure and transmission (e.g. mask, handwash,&#x2026;) as well as improving host health (e.g. proper nutrition for children) before, during and after the pandemic. Putting all together, we believe that our data helps anticipate the impact of emerging respiratory outbreaks and guide preparedness efforts.</p>
            <p>The strength of our study is the relatively large number of cases tested for various viral and bacterial pathogens over five years. This enabled us to examine the pattern and emergence of pathogens associated with ARI in children before, during, and after the COVID-19 pandemic. The main limitation of our study is that the data were from a single private hospital and might not accurately represent the overall population of children in Hanoi, Vietnam.</p>
            <p>Regarding future direction, we keep archiving and observing our microbiological assay data over time as a surveillance approach for potential future outbreaks of infections. We also store some samples for further molecular analysis in case of observed emerging outbreaks.</p>
            <p>In brief, our data show that after the COVID-19 pandemic, HI and SP re-emerged as epidemic pathogens associated with LRI. Flu A and Flu B have re-established regular cycles of peaks in the winter-spring months after an early rebound, together with an unprecedented new HAdV emergence soon after the relief of COVID-19 restriction in 2022. Late after the COVID-19 pandemic, from the middle of 2023, the atypical pneumonia pathogen MP has emerged remarkably and has become epidemic, and there has also been a small, brief emergence of CP infection. Our data will be useful for infectious disease surveillance and public health intervention strategies in the post-COVID-19 era in Vietnam. Our data also provide additional and consistent useful information for health authorities to anticipate the impact of respiratory disease pandemics on the pattern of other pathogens associated with ARIs in children to prepare and manage if there is a similar pandemic in the future.</p>
        </sec>
        <sec id="sec10">
            <title>Ethics and consent</title>
            <p>This study was approved (approval No 110/2024/CN/HDDD VMEC, date October 10, 2024) by the Ethical Committee of Vinmec Healthcare System and VinUniversity (Ethical Committee establishment decision No 24/2016/QD-VINMEC).</p>
            <p>Informed consent was waived by the Ethical Committee for retrospective analysis and report of de-identified
 data.</p>
        </sec>
    </body>
    <back>
        <sec id="sec13" sec-type="data-availability">
            <title>Data availability</title>
            <p>The data generated and analyzed during the current study are not publicly deposited for security reason because they are protected property of the Vinmec Healthcare System. On reasonable data request for research or scientific validation purpose (not for commercial purpose and not for public data deposition), the data may be shared after data access application is approved by the Vinmec Ethical Committee and Vinmec Data Committee. Readers or reviewers may apply for access to the data by contacting the corresponding author via email: 
                <email xlink:href="mailto:v.nhanht6@vinmec.com">v.nhanht6@vinmec.com</email>.</p>
            <sec id="sec9">
                <title>Reporting guidelines</title>
                <p>Repository: &#x2018;STROBE checklist for Emerging pathogens associated with acute respiratory infections in children in Hanoi, Vietnam: An analysis of microbiology assay data from 2019 to 2023&#x2019; DOI: 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.15293879">10.5281/zenodo.15293879</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref23">26</xref>
                    </sup>
                </p>
                <p>

                    <ext-link ext-link-type="uri" xlink:href="https://zenodo.org/records/15293879">https://zenodo.org/records/15293879</ext-link>.</p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/publicdomain/zero/1.0/">Creative Commons Zero &#x2018;No rights reserved&#x2019; data waiver</ext-link> (CC0 1.0 Public domain dedication).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgments</title>
            <p>We would like to thank the Vinmec Healthcare System for their support in this study.</p>
        </ack>
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    </back>
    <sub-article article-type="reviewer-report" id="report444741">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.194032.r444741</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>de Campos</surname>
                        <given-names>Gabriel Montenegro</given-names>
                    </name>
                    <xref ref-type="aff" rid="r444741a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r444741a1">
                    <label>1</label>University of S&#x00e3;o Paulo, Ribeir&#x00e3;o Preto, Brazil</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>20</day>
                <month>1</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 de Campos GM</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport444741" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.164631.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>I have no concerns about the revised version.&#x00a0;I would like to accept this study.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>NA</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report448053">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.194032.r448053</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Zewotir</surname>
                        <given-names>Temesgen</given-names>
                    </name>
                    <xref ref-type="aff" rid="r448053a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r448053a1">
                    <label>1</label>University of KwaZulu Natal, KwaZulu-Natal, South Africa</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>16</day>
                <month>1</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Zewotir T</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport448053" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.164631.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>1.&#x00a0; The analysis is currently limited to the visual inspection of plots. While descriptive, this approach lacks the statistical power to quantify changes in level, trend, or seasonality associated with specific intervention periods.&#x00a0; Incorporating formal time-series modeling, including confidence intervals and hypothesis testing, is necessary to support causal interpretations.</p>
            <p> 2.&#x00a0;The study focuses on absolute counts of positive tests rather than standardized metrics, such as positivity rates adjusted for testing volume. Given that testing intensity fluctuated significantly during the study period, the current metrics risk misinterpretation. Supplementing the data with positivity rates or modeled expected counts would provide a more robust basis for inference.</p>
            <p> </p>
            <p> 3.&#x00a0;Though some factors such as shifting admission policies, vaccination coverage, and viral variants are mentioned narratively, they are not controlled for analytically. Without adjusting for these time-varying confounders, it is difficult to definitively attribute pathogen &#x201c;re-emergence&#x201d; to COVID-19 interventions rather than external variables</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>No</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>No</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Statistics</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report399417">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.181171.r399417</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>de Campos</surname>
                        <given-names>Gabriel Montenegro</given-names>
                    </name>
                    <xref ref-type="aff" rid="r399417a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r399417a1">
                    <label>1</label>University of S&#x00e3;o Paulo, Ribeir&#x00e3;o Preto, Brazil</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>25</day>
                <month>8</month>
                <year>2025</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 de Campos GM</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport399417" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.164631.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>This article examines the evolution of respiratory diseases&#x2014;both bacterial and viral&#x2014;during a period marked by profound societal disruption: the emergence of a novel pathogen that triggered a pandemic lasting approximately two and a half years.</p>
            <p> </p>
            <p> As the pandemic unfolded, successive public health measures were implemented to reduce transmission and mortality. Given the respiratory nature of the virus, these mitigation strategies also impacted the circulation of other respiratory pathogens, as demonstrated in the article. By analyzing data from the pre-pandemic, pandemic, and post-pandemic periods, the study highlights how these interventions influenced the incidence of various respiratory diseases.</p>
            <p> </p>
            <p> Replicating this study would likely require either the occurrence of another pandemic or access to extensively archived clinical data, as was available from Vinmec Times City International Hospital in Hanoi. Given the challenges of acquiring such comprehensive datasets, it is understandable why this topic was only partially explored. Nonetheless, the statistical analyses are clearly and rigorously described. The PCR and bacterial culture protocols are also well-detailed; however, they might be better placed in the Methods section rather than in the caption of Figure 1, which would be more appropriately included in the Results. It would be useful to know whether these diagnostic tests are routinely performed at the hospital.</p>
            <p> </p>
            <p> I acknowledge and understand the justification for not making the data publicly available, given their highly sensitive nature. For this reason, I marked &#x201c;no&#x201d; in the data availability section. Nevertheless, I fully understand the rationale behind this.</p>
            <p> I do have one question regarding the conclusion. Based on the findings, the measures implemented to mitigate the spread of SARS-CoV-2 also contributed to a reduction in the circulation of other respiratory pathogens. In light of this, what would be the most appropriate public health measure(s) for governments to implement to contain future respiratory outbreaks?</p>
            <p> </p>
            <p> Regarding the reported outbreaks (HI, SP, Flu A and B, HAdV), is there a specific government agency responsible for declaring or monitoring these outbreaks? I believe your study is particularly valuable in demonstrating that your dataset detected an increase in cases that coincided with the early stages of the epidemic. Comparing your findings with official surveillance data could further strengthen the conclusion that your approach may help anticipate the impact of emerging respiratory outbreaks and guide preparedness efforts.</p>
            <p> </p>
            <p> Below, I am sharing two articles that came to mind while reviewing your manuscript.</p>
            <p> Just out of curiosity, do the authors intend to use this dataset in future studies or expand upon this research in any specific direction?</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Metagenomics, Next-Generation Sequencing, Virology, Bioinformatics</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <back>
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        <sub-article article-type="response" id="comment14651-399417">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Ho</surname>
                            <given-names>Nhan Thi</given-names>
                        </name>
                        <aff>Research Management, Vinmec Health Care System, Hanoi, Hanoi, Vietnam</aff>
                    </contrib>
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                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>The authors declare no competing interest.</p>
                    </fn>
                </author-notes>
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                    <month>9</month>
                    <year>2025</year>
                </pub-date>
            </front-stub>
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                <p>The authors would like to thank the reviewer for his contributive comments which have helped improve our paper.</p>
                <p> We would like to response to the comments below.</p>
                <p> </p>
                <p> 1. Thank you for pointing out redundancy error in the caption of Figure 1. There is repeated information that makes the caption of Figure 1 much longer than it is supposed to be. We will fix this. The description/ protocol for microbiological assays is already included in the Methods section (started with &#x201c;The microbiology assays included in the analysis were:&#x201d; &#x2026;. .</p>
                <p> These microbiological assays are done in Vinmec hospital for patients with corresponding indications (e.g. assays for Mycoplasma pneumoniae (MP) are indicated and done if the patient has signs/ symptoms suggesting MP infection and assays for MP are not routinely done for all patients with any acute respiratory infections).</p>
                <p> </p>
                <p> 2.&#x00a0;Regarding the most appropriate public health measure(s) for governments to implement to contain future respiratory outbreaks: We believe that the measures to contain future respiratory outbreaks include maintaining availability and coverage of vaccines for outbreak-prone respiratory pathogens (e.g. maintaining Flu, HI, SP,&#x2026; vaccination for community) alongside with maintaining public health interventions to reduce/ prevent exposure and transmission (e.g. mask, handwash,&#x2026;) as well as improving host health (e.g. proper nutrition for children) before, during and after the pandemic.</p>
                <p> </p>
                <p> 3.&#x00a0;The outbreaks shown by our data corresponds with actual outbreaks observed by authorities in Vietnam during the same time period. For example, the HAdV and Mycoplasma pneumoniae (MP) outbreaks correspond to the outbreak of HAdV and MP reported by authorities in Vietnam at the same time period (
                    <ext-link ext-link-type="uri" xlink:href="https://moh.gov.vn/hoat-dong-cua-dia-phuong/-/asset_publisher/gHbla8vOQDuS/content/cap-nhat-moi-nhat-ve-benh-virus-adeno-so-tre-mac-a-tang-len-1-406-co-7-ca-tu-vong">https://moh.gov.vn/hoat-dong-cua-dia-phuong/-/asset_publisher/gHbla8vOQDuS/content/cap-nhat-moi-nhat-ve-benh-virus-adeno-so-tre-mac-a-tang-len-1-406-co-7-ca-tu-vong</ext-link> ; 
                    <ext-link ext-link-type="uri" xlink:href="https://baochinhphu.vn/bo-y-te-yeu-cau-phan-tich-dich-te-hoc-cac-ca-mac-va-tu-vong-do-virus-adeno-102220921182250996.htm">https://baochinhphu.vn/bo-y-te-yeu-cau-phan-tich-dich-te-hoc-cac-ca-mac-va-tu-vong-do-virus-adeno-102220921182250996.htm</ext-link> ; 
                    <ext-link ext-link-type="uri" xlink:href="https://benhviennhitrunguong.gov.vn/tre-mac-viem-phoi-do-mycoplasma-gia-tang-huong-dan-phong-benh.html">https://benhviennhitrunguong.gov.vn/tre-mac-viem-phoi-do-mycoplasma-gia-tang-huong-dan-phong-benh.html</ext-link> ). We also previously published molecular data of HAdV and MP outbreaks (doi: 10.1371/journal.pntd.0011311 ;&#x00a0; doi: 10.3201/eid3005.231632). The Flu A and Flu B outbreaks observed in our data also correspond with the Flu outbreak reported by Vietnam authorities at the same time period (
                    <ext-link ext-link-type="uri" xlink:href="https://baochinhphu.vn/su-tro-lai-cua-dich-cum-sau-dai-dich-covid-19-102220831115300348.htm">https://baochinhphu.vn/su-tro-lai-cua-dich-cum-sau-dai-dich-covid-19-102220831115300348.htm</ext-link> ; 
                    <ext-link ext-link-type="uri" xlink:href="https://thainguyen.gov.vn/y-te-giao-duc/-/asset_publisher/L0n17VJXU23O/content/dich-cum-mua-co-dien-bien-bat-thuong-sau-covid-19?inheritRedirect=true">https://thainguyen.gov.vn/y-te-giao-duc/-/asset_publisher/L0n17VJXU23O/content/dich-cum-mua-co-dien-bien-bat-thuong-sau-covid-19?inheritRedirect=true</ext-link> ).&#x00a0;</p>
                <p> </p>
                <p> 4.&#x00a0;Many thanks for sharing the two articles and thanks for your question. We keep archiving, observing our microbiological assay data over time as surveillance for potential future outbreaks of infections. We also store some samples for further molecular analysis in case of observed emerging outbreaks.</p>
                <p> </p>
                <p> Putting all these together, we believe that our data helps anticipate the impact of emerging respiratory outbreaks and guide preparedness efforts.</p>
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