<?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="research-article" 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.164787.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Implementation and Efficacy of COVID-19 Infection Prevention and Controls Measures Among Indonesia&#x2019;s Health Care Workers</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Modjo</surname>
                        <given-names>Robiana</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</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/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-4435-1473</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>Lestari</surname>
                        <given-names>Fatma</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>.</surname>
                        <given-names>Hendra</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/">Supervision</role>
                    <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>Rahmadani</surname>
                        <given-names>Meilisa</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Chaeruman</surname>
                        <given-names>Ali Syahrul</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</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/">Supervision</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Lestari</surname>
                        <given-names>Fetrina</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <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>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Kadir</surname>
                        <given-names>Abdul</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sulistiyorini</surname>
                        <given-names>Desy</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9129-0653</uri>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sutanto</surname>
                        <given-names>Juliana</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</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/">Visualization</role>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Occupational Health and Safety, Faculty of Public Health, University of Indonesia, Depok, 16425, Indonesia</aff>
                <aff id="a2">
                    <label>2</label>Indonesia Occupational Health Experts Association, Depok, 16424, Indonesia</aff>
                <aff id="a3">
                    <label>3</label>Disaster Risk Reduction Center, University of Indonesia, Depok, 16424, Indonesia</aff>
                <aff id="a4">
                    <label>4</label>University of Indonesia Hospital, Depok, 16424, Indonesia</aff>
                <aff id="a5">
                    <label>5</label>Department of Public Health, Faculty of Health Science, Universitas Indonesia Maju, Jakarta, 12610, Indonesia</aff>
                <aff id="a6">
                    <label>6</label>Department of Human Centered Computing, Monash University, Clayton, Victoria, Australia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:bian@ui.ac.id">bian@ui.ac.id</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>7</day>
                <month>7</month>
                <year>2025</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2025</year>
            </pub-date>
            <volume>14</volume>
            <elocation-id>662</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>27</day>
                    <month>5</month>
                    <year>2025</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Modjo R 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/14-662/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted primary healthcare (PHC) workers, placing them at heightened risk of infection. Ensuring the implementation of infection prevention and control (IPC) measures in PHC settings is critical to safeguarding health workers and maintaining essential health services. This study aimed to assess the compliance of PHC facilities with the Indonesian Ministry of Health&#x2019;s COVID-19 regulations.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>A cross-sectional study was conducted across 17 Primary Health Care (Puskesmas) facilities located in six provinces of Indonesia. Data were collected over a six-month period and analyzed based on 11 key variables: leadership and incident management systems; coordination and communication; surveillance and information management; risk management and public involvement; administrative, financial, and business continuity; human resources; essential support services; patient management; occupational health; mental health and psychosocial support; rapid identification and diagnosis; and infection prevention and control. Compliance was evaluated using a scoring system aligned with Ministry of Health standards.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>Of the 17 PHC facilities evaluated, 12 (71%) were classified as having &#x201c;very good&#x201d; compliance with COVID-19 IPC measures, while 5 (29%) were categorized as &#x201c;good.&#x201d; However, specific areas showed lower compliance rates, including occupational health, mental health, and psychosocial support (41%), human resources (50%), risk communication and community engagement (57%), and administrative, financial, and business continuity (58%).</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>While overall compliance with Ministry of Health regulations among PHC facilities was high, critical areas such as worker mental health, human resource management, and risk communication require targeted improvement. Policymakers, government agencies, and health institutions must enhance protection measures for PHC workers by strengthening human resource systems, updating risk communication strategies, and integrating business continuity planning tailored to pandemic conditions.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>COVID-19 infection prevention &amp; control</kwd>
                <kwd>primary health care facilities</kwd>
                <kwd>occupational health</kwd>
                <kwd>healthcare workers protection.&#x202f;</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1" xlink:href="https://doi.org/10.13039/501100021726">
                    <funding-source>Direktorat Riset and Pengembangan, Universitas Indonesia</funding-source>
                    <award-id>Q2InternationalIndexedPublication(PUTI)fundingscheme(grantno.NKB-467/UN2.RST/HKP.05.00/2022)</award-id>
                </award-group>
                <funding-statement>This research was funded by Directorate of Research and Development (Risbang) Universitas Indonesia through the Q2 International Indexed Publication (PUTI) funding scheme (grant no. NKB-467/UN2.RST/HKP.05.00/2022)</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>The global coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on the occupational health of health care professionals. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been identified as the causative agent of this pandemic. The virus initially triggered an outbreak in Wuhan, Hubei, China on December 31, 2019.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>,
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Primary healthcare workers face immense pressure throughout the ongoing COVID-19 crisis, a situation expected to persist until a significant reduction in cases is achieved.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> Notably, the risk of nosocomial infection and transmission poses a considerable threat to the control of COVID-19, particularly among primary healthcare workers.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> According to the World Health Organization (WHO), the prevalence of infections among health workers has exhibited significantly, ranging from 2%-35%.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> Healthcare workers are susceptible to infection through prolonged exposure to COVID-19 patients, with certain healthcare activities, such as endotracheal intubation, noninvasive ventilation, tracheotomy, and manual ventilation before intubation, potentially leading to the virus becoming airborne. These procedures increase the risk to healthcare workers.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
            </p>
            <p>In Indonesia, the Ministry of Health established two pivotal regulations aimed at guiding and safeguarding healthcare workers in the face of the COVID-19 pandemic. These regulations are Ministry of Health Regulation No. 413 of the year 2020, outlining guidelines for COVID-19 prevention and control, and Ministry of Health Regulation No. 327 designating COVID-19 as a work-related disease for specific occupations. The latter regulation serves the purpose of protecting healthcare workers from the risk of contracting COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>,
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> According to WHO data on May 14, 2021, there have been 160,813,869 confirmed COVID-19 cases worldwide, with 3,339,002 reported deaths.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> Additionally, WHO reported that as of May 11, 2021, 1,264,164,553 vaccine doses have been administered globally.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> The initial cases of COVID-19 in Indonesia were documented on March 2, 2020, with two confirmed positive cases.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> Recognizing the severity of the situation, Presidential Decree No. 12 of 2020, issued on April 13, 2020, declared the spread of COVID-19 as a non-natural disaster, designating it an Indonesian national disaster.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
            </p>
            <p>As of May 14, 2021, Indonesia had reported 1,734,285 confirmed COVID-19 cases, with 1,592,886 individuals having successfully recovered and 47,823 reported deaths. These cases are distributed across 34 provinces in the country.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
            </p>
            <p>Puskesmas, or primary healthcare (PHC) in Indonesia, play a vital role in executing preventive and promotive programs within local communities. This encompasses activities such as providing early warning for endemic or pandemic diseases; executing public health infectious or disease prevention measures; conducting education and promoting a healthy lifestyle; and actively participating in COVID-19 contact tracing, testing, and early treatment of COVID-19 patients. The expansive network comprises 10,134 primary healthcare centers across Indonesia.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> To ensure the effective execution of COVID-19 prevention and control measures within these Primary Health Care settings, the Ministry of Health, Republic of Indonesia, under the coordination of the Occupational Health and Sports Directorate, collaborated with the Indonesian Occupational Health Association and Universitas Indonesia to conduct this research. The primary objective of this research was to analyze the implementation of COVID-19 prevention and control measures among primary health care workers in Indonesia.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Research design and primary health care selection</title>
                <p>The research design employed in this study adopted a cross-sectional approach, with data collection spanning a period of six months from July to December 2020. The analysis focused on evaluating the protection measures in place for primary healthcare workers, specifically assessing their compliance with Ministry of Health regulations No. 413 of the year 2020 regarding Guidelines on COVID-19 Prevention and Control, and Ministry of Health Regulation No. 327 designating COVID-19 as a work-related disease on specific workers.
                    <sup>
                        <xref ref-type="bibr" rid="ref7">7</xref>,
                        <xref ref-type="bibr" rid="ref8">8</xref>
                    </sup> 17 (seventeen) primary healthcare (PHC) facilities were strategically selected from 6 (six) provinces in Indonesia: West Java, Central Java, South Kalimantan, East Java, West Kalimantan, and West Sumatera. The Primary Health Care centers in each province are West Java (two PHC), East Java (two PHC), Central Java (two PHC), South Kalimantan (two PHC), West Kalimantan (three PHC), and West Sumatera (six PHC). The selection process utilized a non-probabilistic purposive sampling method with the chosen PHC members within the network of the Indonesia Occupational Health Association (IOHA).</p>
            </sec>
            <sec id="sec8">
                <title>Evaluation elements and scoring system</title>
                <p>The assessment of primary healthcare (PHC) facilities involved the administration of a self-assessment evaluation form. This form was distributed through the network of the Indonesia Occupational Health Association (IOHA) network and completed by designated key informants. The gathered information was validated and verified through the local network of the IOHA. The evaluation form encompassed 11 crucial elements: Leadership and Incident Management System, Coordination and Communication, Surveillance, Information Management, Administration, Finance, and Business Continuity, Human resources, sustainability of essential services, Patient Management, Occupational Health, Mental health and psychosocial support, rapid identification and diagnosis, and Infection Prevention and Control. To evaluate adherence to the Ministry of Health regulations, compliance levels were categorized as &#x201c;Very Good&#x201d; for exceeding compliance, &#x201c;Good&#x201d; for 61%&#x2013;80%, &#x201c;Sufficient&#x201d; for 41%&#x2013;60%, and &#x201c;Poor&#x201d; for below 40%.</p>
            </sec>
            <sec id="sec9">
                <title>Data analysis, weighting, and score calculation</title>
                <p>The collected data were analyzed using Microsoft Excel. Univariate analysis was conducted, presenting essential information related to the variables and evaluating compliance with Indonesia&#x2019;s Ministry of Health regulations. The analysis involved the creation of visual representations, including bar charts, spider webs, and compliance-level charts, to effectively communicate the findings. These graphical representations provided a comprehensive overview of the data, highlighting patterns and variations in compliance across the evaluated elements.</p>
            </sec>
            <sec id="sec10">
                <title>Ethical consideration</title>
                <p>The study underwent thorough evaluation and was approved by the ethics committee of the Research and Community Engagement of the Faculty of Public Health, Universitas Indonesia. The Ethics Approval Letter No. Ket-435/UN2.F10.D11/PPM.00.02/2020 was issued on August 15, 2020. Detailed information regarding the informed consent process was provided during the Ethics Approval and Consent stages before the commencement of the study.</p>
                <p>Informed consent for participation in the study was obtained orally from all individuals prior to the commencement of data collection. Participants were provided with comprehensive information regarding the study&#x2019;s objectives, procedures, and the measures taken to ensure confidentiality, as part of the informed consent process. All research procedures were conducted in full accordance with the ethical guidelines and regulations approved by the relevant ethics committee. It should be noted that the study did not involve the use of animals or human biological materials, thereby reinforcing adherence to ethical principles and standards throughout the research process.</p>
            </sec>
        </sec>
        <sec id="sec11" sec-type="results">
            <title>Results</title>
            <sec id="sec12">
                <title>Primary healthcare (PHC) information</title>
                <p>
                    <xref ref-type="table" rid="T1">
Table 1</xref> provides a comprehensive profile of Primary Health Care (PHC), encompassing essential details such as PHC classification, status, codes, provinces, capacity of beds available for COVID-19 patients, number of beds designated for routine care, and workforce size. The selected PHC sample for the analysis of COVID-19 prevention and control included both inpatient and outpatient services. The study incorporated PHCs classified based on their inpatient and outpatient services, further categorizing them based on their status. PHC status includes those affiliated with the Local General Services Body (LGSB), referred to as &#x201c;
                    <italic toggle="yes">Badan Layanan Umum Daerah</italic>&#x201d; (BLUD), and those not affiliated with LGSB or Non-BLUD. The BLUD status signifies a system implemented by local government work units to deliver public services with financial management flexibility, which is distinct from other general local government services. Generally, inpatient PHCs tend to have more beds than outpatient PHCs. This detailed profile serves as a foundation for understanding the diverse characteristics of the selected PHC samples under investigation (
                    <xref ref-type="table" rid="T1">
Table 1</xref>).</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>
Table 1. </label>
                    <caption>
                        <title>COVID-19 confirmed cases in hospital workers.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">No.</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Primary health care classification &amp; status</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
PHC code</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Provinces</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Number of beds for COVID-19 patients</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Number of beds for routine care</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Number of workers</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">G</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Kalimantan</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">103</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">P</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Java</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">86</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">B</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">East Java</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">77</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD, Primary)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">K</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Sumatera</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD, Primary)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">D</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Central Java</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (BLUD, Primary)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">E</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Kalimantan</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (Full-BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">F</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Kalimantan</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">68</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD, Primary)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">J</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Sumatera</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">62</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD, Intermediate)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">O</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Sumatera</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">38</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient (BLUD, Intermediate)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">N</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Sumatera</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">26</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Inpatient t (Non-BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">M</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Sumatera</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">159</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (Non-BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">L</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Sumatera</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">68</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">I</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">South Kalimantan</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">14</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (BLUD, Intermediate)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">H</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">South Kalimantan</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">53</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (BLUD, Primary)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">C</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Central Java</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">38</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">East Java</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">35</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">17</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Outpatient (Non- BLUD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Q</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">West Java</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec13">
                <title>Regulation compliance of COVID-19 prevention and control implementation in primary health care (PHC)</title>
                <p>
                    <xref ref-type="fig" rid="f1">
Figure 1</xref> illustrates the compliance of OHC facilities in six provinces with the regulations for COVID-prevention and control, as stipulated by the Indonesian Ministry of Health.
                    <sup>
                        <xref ref-type="bibr" rid="ref7">7</xref>,
                        <xref ref-type="bibr" rid="ref8">8</xref>
                    </sup> The observed compliance and the specified requirements outlined by the Ministry were compared. 
                    <xref ref-type="fig" rid="f3">
Figure 3</xref> further represents the compliance levels in three distinct ranges: greater than 80%, between 60% and 80%, and less than 60.</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>
Figure 1. </label>
                    <caption>
                        <title>Regulation compliance of COVID-19 prevention and control in PHC.</title>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/181359/ae59cc02-8832-4294-8e3b-00099e3c00ca_figure1.gif"/>
                </fig>
                <p>The evaluation of each element of COVID-19 prevention and control in PHC, as presented in 
                    <xref ref-type="table" rid="T2">
Table 2</xref>, indicates notable strengths in certain areas. The strongest element across all regions was infection prevention and control, consistently achieving a compliance rate of above 80%. Additionally, elements focusing on leadership and incident management systems show strength in several areas, including East Java, West Kalimantan, and West Java. The ranking of achievements for the implementation of COVID-19 prevention and control in PHC, listed from the highest to the lowest, was as follows: East Java, West Java, West Sumatera, West Kalimantan, South Kalimantan, and Central Java.</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>
Table 2. </label>
                    <caption>
                        <title>Evaluation on each element of COVID-19 prevention and control in PHC.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">No.</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Evaluation elements</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
East Java</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Central Java</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
West Kalimantan</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
South Kalimantan</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
West Sumatera</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
West Java</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Average score</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Leadership and incident management system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">71%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">93%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">81%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Coordination and communication</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">83%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">83%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">79%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">76%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Surveillance and information management</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">71%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">74%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Risk communication and community engagement</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">63%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">57%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Administration, finance and business continuity</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">38%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">61%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Human resources</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">39%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">56%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">57%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Continuity of essential support services</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">79%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">93%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Patient management</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">92%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">61%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">81%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">81%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Occupational health, mental health and psychosocial support</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">40%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">35%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">45%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">41%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Rapid identification and diagnosis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">85%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">70%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">70%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">80%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">95%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">Infection prevention and control</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">93%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">97%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">96%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">96%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">93%</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="bottom">
                                    <bold>Mean</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>78%</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>63%</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>66%</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>64%</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>69%</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>74%</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>The average score results clearly show that the strongest elements are infection prevention and control (93%), leadership and incident management systems (81%), and patient management (81%). The weakest elements were occupational health, mental health, psychosocial support, and human resources.</p>
                <p>
                    <xref ref-type="fig" rid="f2">
Figure 2</xref> presenting a radar plot analysis of the evaluation scores for COVID-19 prevention and control in Primary Health Care (PHC), illustrates several notable patterns. There are several elements are the strongest which include infection prevention and control, leadership and incident management system, and patient management. However, there are several elements which are the weakest including occupational health, mental health and psychosocial support and human resources. Result from radar plot analysis align with mean score evaluation results.</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>
Figure 2. </label>
                    <caption>
                        <title>Radar plot on evaluation score of COVID 19 prevention and control in PHC.</title>
                    </caption>
                    <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/181359/ae59cc02-8832-4294-8e3b-00099e3c00ca_figure2.gif"/>
                </fig>
                <p>
                    <xref ref-type="fig" rid="f3">
Figure 3</xref> shows the Box-Whisker plot analysis used to analyze the tendencies and distributions of compliance among all locations. The highest and smallest tendencies and distributions show that the element of infection prevention and control is best implemented in most locations. The locations of the boxes show how well the element is implemented, and it is clear that occupational health, mental health, and psychosocial support are the lowest for most of the locations.</p>
                <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                    <label>
Figure 3. </label>
                    <caption>
                        <title>Box-whisker plot analysis for compliance tendencies and distributions.</title>
                    </caption>
                    <graphic id="gr3" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/181359/ae59cc02-8832-4294-8e3b-00099e3c00ca_figure3.gif"/>
                </fig>
            </sec>
        </sec>
        <sec id="sec14" sec-type="discussion">
            <title>Discussion</title>
            <p>The comprehensive findings of this study suggest that the most robust elements in the realm of COVID-19 prevention and control within primary healthcare (PHC) are COVID-19 infection prevention and control, leadership and incident management, and patient management (
                <xref ref-type="fig" rid="f3">
Figure 3</xref>). The majority of the selected PHC locations have demonstrated exemplary implementation of COVID-19 prevention and control measures, with an impressive compliance rate of 93%. Several critical factors contribute to the success of COVID-19 prevention and control in these PHC. This includes the effective reinforcement of the role of health and safety officers, ensuring the meticulous implementation of COVID-19 infection prevention and control measures among healthcare workers. There is also a strong emphasis on ensuring the availability of appropriate personal protective equipment (masks, respirators, gloves, gowns, and goggles). Moreover, careful attention is given to ensuring that the Personal Protective Equipment (PPE) is both adequate and acceptable based on the specific requirements within facility zones and the tasks performed by workers. Other noteworthy aspects contributing to success include the availability of standard operating procedures for working with COVID-19 patients, a systematic approach to conducting investigations in the event of confirmed cases among workers, and a well-established mechanism for reporting and recording COVID-19 cases. The commendable implementation of COVID-19 infection prevention and control measures across the majority of the 17 PHC locations is attributed to proactive measures taken by the Indonesian government, particularly through the Ministry of Health. The release of regulations on COVID-19 infection prevention and control since July 13, 2020, has played a pivotal role in guiding and facilitating successful implementation in these locations.</p>
            <p>The second aspect demonstrating commendable implementation is leadership and incident management, which is notably well-executed in the majority of the 17 PHC locations (
                <xref ref-type="fig" rid="f2">
Figures 2</xref> and 
                <xref ref-type="fig" rid="f3">3</xref>). The leadership and incident management elements encompass various critical components, including the establishment of an emergency response plan; formation of a COVID-19 task force; issuance of a formal decree delineating assigned responsibilities for coordinators and task force teams; ensuring the execution of incident management for COVID-19; utilizing evidence-based data for decision-making; conducting simulations; implementing COVID-19 incident management; defining mechanisms for coordinated responses with local and national governments; addressing community prevention, preparedness, response, and recovery from COVID-19; and ensuring that all related documents for COVID-19 risk management are established and readily available to all PHC staff and workers. The importance of leadership and incident management during a pandemic is well known.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> This is a well-known incident management approach and response framework that has been used in many organizations in disasters or complex event management and has proven to be effective.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>,
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> These findings align with the WHO report from the field assessment of Pandemic Preparedness and response capacity in Indonesia that most health facilities have had command and control structures for pandemic management.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
            </p>
            <p>The third aspect demonstrating exemplary implementation is patient management, with an achievement rate of 81% in compliance with the requirements set by the local Indonesian government, as presented in 
                <xref ref-type="table" rid="T2">
Table 2</xref>, 
                <xref ref-type="fig" rid="f2">
Figure 2</xref>, and 
                <xref ref-type="fig" rid="f3">
Figure 3</xref>.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Several aspects covered under this patient management element include updating standard operating procedures (SOP) according to the Indonesian Ministry of Health 413,
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> and the SOP that has been made readily available to workers and relevant stakeholders, patient administration, patient referral, patient therapy, diagnostics, COVID-19 infection prevention and control, network with other PHC, and safe patient transport before and after referral including from homecare. The Indonesian Ministry of Health guidelines on COVID-19 prevention and control have provided clear guidance for health services, and the majority of PHC have implemented this in their routine patient management before the pandemic. PHC only need to update and adjust the requirement and compliance to the guidance, and most PHC have fully functioning patient management according to the guidelines.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>On the contrary, the elements exhibiting the weakest implementation in COVID-19 prevention and control are occupational health, mental health and psychosocial support (41% compliance), human resources (50% compliance), risk communication and community engagement (57% compliance), and administration, finance, and business continuity (58% compliance). Both the World Health Organization (WHO) and the International Labour Organization (ILO) issued guidance for occupational health, with a revised version of the initial guidance released in March 2020.
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> The guidance provides information for the primary prevention of COVID-19 among health workers, which was based on risk assessment and introduction of appropriate measures; several risks to healthcare workers, including worker protection from workplace violence, harassment, negative stigma, discrimination, heavy workload, and prolonged use of personal protective equipment (PPE), which should be managed. Indeed, WHO and ILO stated that all healthcare workers should acquire occupational health services, mental health and psychosocial support, adequate hygiene, sanitation, and rest services, and healthcare services should have an occupational health program in conjunction with programs for infection prevention and control. Moreover, Universitas Indonesia has taken proactive steps by launching educational materials on COVID-19 through a massive open online course (MOOC) for health workers. This initiative is facilitated through the &#x201c;EDURISK&#x201d; platform, covering essential topics such as mental health management and mindfulness techniques.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref29">23</xref>
                </sup> Recognizing the critical role of healthcare workers, prioritizing their protection is imperative to ensure continuous and effective functioning of the health sector.
                <sup>
                    <xref ref-type="bibr" rid="ref23">24</xref>,
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup>
            </p>
            <p>The lack of human resources during the pandemic COVID-19 is also an area of concern and improvement.
                <sup>
                    <xref ref-type="bibr" rid="ref24">26</xref>,
                    <xref ref-type="bibr" rid="ref26">27</xref>
                </sup> Other studies and reports have indicated a lack of human resources during the pandemic COVID-19, including the availability of competent human resources, adequate number of human resources, and distribution of appropriate human resources.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>,
                    <xref ref-type="bibr" rid="ref27">28</xref>
                </sup> The majority of the 17 locations had inadequate human resources, ranging from 39% to 58% compliance with the Indonesian Ministry of Health guidance, as presented in 
                <xref ref-type="table" rid="T2">
Table 2</xref> and 
                <xref ref-type="fig" rid="f2">
Figures 2</xref> and 
                <xref ref-type="fig" rid="f3">3</xref>. These results suggest that several measures can be taken to increase human resources during the COVID-19 pandemic. These measures include conducting workplace risk assessments, making changes to work procedures, recruiting volunteers, understanding health workers&#x2019; challenges and needs, and providing capacity-building initiatives.
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>,
                    <xref ref-type="bibr" rid="ref26">27</xref>,
                    <xref ref-type="bibr" rid="ref28">29</xref>
                </sup>
            </p>
            <p>With regard to risk communication and community engagement, the results suggest that it is also an area that needs improvement. The results from this study suggested that the average compliance with regard to risk communication and community engagement was 57%, as presented in 
                <xref ref-type="table" rid="T2">
Table 2</xref> and 
                <xref ref-type="fig" rid="f2">
Figures 2</xref> and 
                <xref ref-type="fig" rid="f3">3</xref>. Aspects evaluated under risk communication and community engagement, including SOPs for risk communication, and all workers, patients, visitors, relevant stakeholders, and the community have been informed and educated. The majority of PHC achieved compliance between 44-69%, which means that it needs to be improved further. The WHO, in conjunction with UNICEF, IFRC, and GOARN, has released guidance related to the Global Risk Communication and Community Engagement (RCCE) strategy to guide how to better communicate COVID-19 and empower community involvement.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup>
            </p>
            <p>In assessing the elements of administration, finance, and business continuity, the study revealed an average compliance percentage of 58%, as detailed in 
                <xref ref-type="table" rid="T2">
Table 2</xref>, 
                <xref ref-type="fig" rid="f2">
Figure 2</xref>, and 
                <xref ref-type="fig" rid="f3">
Figure 3</xref>. The evaluation encompasses several critical aspects, including the availability of necessary SOPs related to administration and finance for effective COVID-19 control, and encompassing areas such as purchasing, supply chain, and essential services. Additionally, the study examined the provision of guidance and policies pertaining to COVID-19 pandemic control for all staff and health workers. It further explored the implementation of systems to manage COVID-19-related measures, encompassing testing and case management. The study also assessed the presence and execution of systems governing working hours and procedures to mitigate fatigue and work overload, ensuring the sustained business continuity of Primary Health Care (PHC). Furthermore, the evaluation considers the implementation of individual care strategies, including independent non-critical care, such as home care, and innovative approaches, such as telemedicine. Despite these measures, this study highlights a notable gap in the establishment of business continuity plans (BCP) within the health sector. The research papers provided offer insights into the strategies and technologies that can enhance the resilience of healthcare systems, emphasizing the importance of robust BCP in maintaining service continuity to ensure the uninterrupted delivery of services even in the face of disasters.</p>
        </sec>
    </body>
    <back>
        <sec id="sec17" sec-type="data-availability">
            <title>Data availability statement</title>
            <p>The data supporting the findings of this study cannot be shared publicly due to ethical restrictions related to participant confidentiality and institutional requirements. The data contain sensitive information collected from key informants at primary health care facilities and are subject to confidentiality agreements approved by the Ethics Committee of the Faculty of Public Health, Universitas Indonesia (Ethics Approval No. Ket-435/UN2.F10.D11/PPM.00.02/2020). The Institutional Review Board did not approve public sharing of the dataset to protect the privacy of participating individuals and facilities. However, data may be made available to qualified researchers upon reasonable request and with permission from the corresponding author, subject to ethical review and approval. Requests for access should be directed to the corresponding author (Robiana Modjo, 
                <email xlink:href="mailto:bian@ui.ac.id">bian@ui.ac.id</email>), and applicants will be required to submit a written request outlining the purpose of data use and provide evidence of ethical approval from their institution.</p>
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    <sub-article article-type="reviewer-report" id="report409775">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.181359.r409775</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Ahmad</surname>
                        <given-names>Junaid</given-names>
                    </name>
                    <xref ref-type="aff" rid="r409775a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-8580-7529</uri>
                </contrib>
                <aff id="r409775a1">
                    <label>1</label>Zhejiang University, Hangzhou, China</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>17</day>
                <month>9</month>
                <year>2025</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Ahmad J</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="relatedArticleReport409775" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.164787.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Peer-Review of the Manuscript</p>
            <p> Title:&#x00a0;
                <italic>Implementation and Efficacy of COVID-19 Infection Prevention and Control Measures Among Indonesia's Health Care Workers</italic>
            </p>
            <p> </p>
            <p> The manuscript under review presents an analysis of COVID-19 infection prevention and control (IPC) measures implemented across selected primary healthcare (PHC) facilities in Indonesia. The study focuses on assessing the level of compliance with the Indonesian Ministry of Health's regulations during the early phases of the COVID-19 pandemic. While the topic is timely and essential, several methodological and analytical shortcomings need to be addressed to improve the manuscript's rigor and policy relevance.</p>
            <p> </p>
            <p> Abstract</p>
            <p> The abstract introduces the core of the study, which aims to evaluate compliance with COVID-19 IPC measures in Indonesia's PHC facilities. The findings suggest that while overall compliance was high, specific areas such as occupational health and mental health support were notably deficient. The study's contribution is timely; however, the abstract could benefit from greater clarity regarding its limitations, such as the small sample size and temporal mismatch with the current situation. Additionally, the lack of clear linkage between IPC compliance and health outcomes (e.g., healthcare worker infection rates) leaves essential questions unanswered.</p>
            <p> </p>
            <p> Introduction</p>
            <p> The introduction effectively sets the stage by outlining the global impact of the COVID-19 pandemic, with a focus on Indonesia. The significance of safeguarding healthcare workers through robust IPC measures is well-argued, and the relevant Ministry of Health regulations (No. 413/2020 and No. 327/2020) are cited. However, a crucial element missing from this section is a discussion of how these regulations evolved. Given the rapidly changing nature of COVID-19, referencing updated regulations (such as MoH Circular No. HK.02.02/C/3806/2022) would strengthen the context. Additionally, there is a lack of a clear statement on the study&#x2019;s contribution to the current phase of the pandemic or endemic strategies, which would have added more relevance to the findings.</p>
            <p> </p>
            <p> Methods</p>
            <p> The study design is described as a cross-sectional assessment of 17 PHC facilities in six provinces of Indonesia, with data collection spanning from July to December 2020. While the choice of a cross-sectional design is appropriate for a snapshot evaluation, several critical issues arise regarding sampling and data collection methods: 
                <list list-type="bullet">
                    <list-item>
                        <p>Sampling Frame: The facilities were selected through a non-probabilistic purposive sampling method via the Indonesia Occupational Health Association (IOHA) network. This introduces significant bias, as the sample is likely to over-represent well-resourced, well-connected facilities. The manuscript does not justify the selection process or explain why these particular 17 sites were chosen. Without randomization or a probability sampling approach, the findings cannot be generalized to the entire population of over 10,000 PHC facilities in Indonesia.</p>
                    </list-item>
                    <list-item>
                        <p>Sample Size Power: The sample size of 17 facilities is exceedingly small and represents less than 0.2% of the total PHC facilities in Indonesia. The manuscript does not provide a power calculation, and given the sample size, the findings are underpowered, limiting their ability to detect meaningful differences. A more robust sample size is necessary for generalization and to ensure that the results reflect the diversity of PHC settings across Indonesia.</p>
                    </list-item>
                    <list-item>
                        <p>Temporal Mismatch: The study collected data in 2020, yet the manuscript was submitted for peer review in 2025. The five-year lag between data collection and submission without an explanation regarding the current relevance of the data is a significant issue. The manuscript should justify why data collected five years ago remain applicable to current IPC strategies and how they inform ongoing pandemic preparedness.</p>
                    </list-item>
                    <list-item>
                        <p>Ethical Considerations: The study reports obtaining oral consent from participants; however, it does not explain how this consent was recorded or verified, which raises concerns regarding participant protection and data integrity. Furthermore, the manuscript states that public data sharing is prohibited due to "sensitive information," but individual-level data are not presented. This contradicts F1000Research's policy on open data and transparency, and the authors should reconsider this embargo and share anonymized datasets.</p>
                    </list-item>
                </list> Results:</p>
            <p> The results section provides an overview of the compliance levels with COVID-19 IPC measures, using a scoring system based on the Indonesian Ministry of Health's regulations. Key findings suggest that overall compliance was relatively high, with infection prevention and control being the strongest domain (93% compliance). However, several areas showed lower compliance, particularly in occupational health (41% compliance), mental health (41%), and psychosocial support (41%), as well as human resources (50%) and risk communication (57%).</p>
            <p> While these findings are important, the results section contains several significant issues: 
                <list list-type="bullet">
                    <list-item>
                        <p>Internal Contradictions: The manuscript reports an overall "very good" compliance rate of 71%, yet it highlights critical deficiencies in areas like occupational health and mental health support, which scored only 41%. This paradox raises questions about the appropriateness of the aggregated compliance score, suggesting that the summary measure may obscure substantial deficits in specific areas.</p>
                    </list-item>
                    <list-item>
                        <p>Lack of Linkage to Health Outcomes: The study does not report any data linking compliance levels with actual healthcare worker (HCW) infection rates or seroprevalence. Without these health outcomes, it is impossible to assess the real-world efficacy of the IPC measures. The manuscript would benefit from linking compliance scores with infection data to provide a more holistic evaluation of the implemented measures.</p>
                    </list-item>
                    <list-item>
                        <p>Missing Denominators: The manuscript does not specify how many healthcare workers were interviewed per facility, which is critical for assessing response bias and ensuring that the sample adequately represents the workforce at each facility. This missing information hampers the ability to interpret the data meaningfully.</p>
                    </list-item>
                    <list-item>
                        <p>Data Presentation Issues: Figures 2 and 3 (radar and box-whisker plots) lack essential annotations, including error bars and sample size information. This omission undermines the clarity of the visualizations and makes it difficult to assess the precision of the data presented.</p>
                    </list-item>
                </list> Discussion:</p>
            <p> The discussion emphasizes the importance of strong IPC measures in the majority of the 17 PHC facilities, particularly in areas such as infection prevention and control, leadership, and patient management. However, the manuscript does not adequately address the significance of the weaker compliance areas, particularly occupational health, mental health, and psychosocial support, which are crucial in safeguarding the overall well-being of healthcare workers during a pandemic.</p>
            <p> Additionally, while the manuscript presents valuable insights into IPC measures during the early pandemic, it misses the opportunity to discuss the evolving nature of these strategies. Given that the data were collected in 2020, it is essential to update the discussion to reflect the current regulatory landscape and the ongoing challenges faced by healthcare workers in 2025.</p>
            <p> The authors should also broaden the discussion to include how their findings can inform current IPC strategies in Indonesia and globally, particularly as countries shift from pandemic management to endemic preparedness. This would enhance the manuscript&#x2019;s policy relevance and provide actionable recommendations for future health crises.</p>
            <p> </p>
            <p> Conclusion and Recommendations:</p>
            <p> The manuscript provides valuable insights into the implementation of COVID-19 IPC measures in Indonesian PHC facilities. Still, several key issues need to be addressed to improve its scientific rigor and policy relevance. 
                <list list-type="order">
                    <list-item>
                        <p>Sampling and Generalizability: The use of purposive sampling and the small sample size limit the generalizability of the findings. Future studies should incorporate a larger, more representative sample to ensure the results apply to the broader population of PHC facilities in Indonesia.</p>
                    </list-item>
                    <list-item>
                        <p>Statistical Analysis: The study would benefit from inferential statistical tests and the inclusion of confidence intervals for compliance percentages to assess the precision of the findings. Additionally, multivariable adjustment should be applied to account for confounding factors.</p>
                    </list-item>
                    <list-item>
                        <p>Health Outcome Linkage: The authors should provide data linking IPC compliance with HCW infection rates or seroprevalence to demonstrate the efficacy of the measures better.</p>
                    </list-item>
                    <list-item>
                        <p>Data Transparency: The authors should reconsider the data embargo and share anonymized datasets in line with open data policies.</p>
                    </list-item>
                    <list-item>
                        <p>Policy Relevance: The discussion should be updated to reflect the evolving nature of COVID-19 strategies and provide actionable recommendations for improving IPC measures in future pandemics.</p>
                    </list-item>
                </list> The manuscript addresses an important issue; however, it requires significant revisions to ensure that its findings are comprehensive, relevant, and applicable to current health policy.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</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>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Public Health Emergency Management</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>
</article>
