<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    aim
   </journal-id>
   <journal-title-group>
    <journal-title>
     Advances in Microbiology
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    2165-3402
   </issn>
   <issn publication-format="print">
    2165-3410
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/aim.2025.159032
   </article-id>
   <article-id pub-id-type="publisher-id">
    aim-145429
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Biomedical 
     </subject>
     <subject>
       Life Sciences
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    Prevalence of Air Contamination in the Operating Theatre of Port Bouët, Abidjan
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Yao Gilles Privat
      </surname>
      <given-names>
       Kouamé
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Serge Joseph
      </surname>
      <given-names>
       Lathro
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Kouadio Célestin
      </surname>
      <given-names>
       Yao
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff3"> 
      <sup>3</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Mian N’dede Arsher
      </surname>
      <given-names>
       Cablan
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       France Alida
      </surname>
      <given-names>
       Ndja
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff4"> 
      <sup>4</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Denise Affoué Blassonny
      </surname>
      <given-names>
       Guina
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Arthur Dreyfus
      </surname>
      <given-names>
       Boka
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Touré Aissata Epse
      </surname>
      <given-names>
       Kourouma
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Aimé
      </surname>
      <given-names>
       N’djomon
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Yao Guillaume
      </surname>
      <given-names>
       Loukou
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Yesse Zinzendorf
      </surname>
      <given-names>
       Nanga
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
   </contrib-group> 
   <aff id="aff1">
    <addr-line>
     aNational Public Health Laboratory (NPHL), Abidjan, Côte d’Ivoire
    </addr-line> 
   </aff> 
   <aff id="aff2">
    <addr-line>
     aDepartment of Bacteriology-Virology, Teaching and Research Unit of Pharmaceutical and Biological Sciences, Abidjan, Côte d’Ivoire
    </addr-line> 
   </aff> 
   <aff id="aff3">
    <addr-line>
     aFood Science and Technology Department, Nangui Abrogoua University, Abidjan, Côte d’Ivoire
    </addr-line> 
   </aff> 
   <aff id="aff4">
    <addr-line>
     aLaboratory Department, Port-Bouët General Hospital, Abidjan, Côte d’Ivoire
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     04
    </day> 
    <month>
     09
    </month>
    <year>
     2025
    </year>
   </pub-date> 
   <volume>
    15
   </volume> 
   <issue>
    09
   </issue>
   <fpage>
    496
   </fpage>
   <lpage>
    508
   </lpage>
   <history>
    <date date-type="received">
     <day>
      24,
     </day>
     <month>
      July
     </month>
     <year>
      2025
     </year>
    </date>
    <date date-type="published">
     <day>
      5,
     </day>
     <month>
      July
     </month>
     <year>
      2025
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      5,
     </day>
     <month>
      September
     </month>
     <year>
      2025
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    <b>Introduction</b>: Today, the challenge of combating surgical site infections has led to the adoption of a range of measures, of which the prevention of aerobiocontamination remains a determining factor. This is what justifies the scope of the present study, either to determine the level of particulate concentration of the ambient air in the operating theatre compared with the admissible threshold of the ISO 14644-1 normative standards. 
    <b>Objective</b>: To assess the level of aerobiocontamination in operating theatres and identify the associated germs. 
    <b>Methods</b>: The prospective study consisted of particulate air sampling using a biocollector, followed by conventional culture and particle counting, giving rise to one colony per cubic metre (
    <b>C.F.U./m</b>
    <b><sup>3</sup></b>). The samples taken covered the pre-operative, intraoperative and post-operative phases in the presence of various classes of surgery (clean, contaminated and dirty). 
    <b>Results</b>: The results revealed a higher level of contamination during surgical activities of 
    <b>410 ± 145 C.F.U./m</b>
    <b><sup>3</sup></b> followed by post-operative sampling 
    <b>352 ± 131 C.F.U./m</b>
    <b><sup>3</sup></b> and finally pre-operative sampling 
    <b>290 ± 135 C.F.U./m</b>
    <b><sup>3</sup></b>. In general, aerobiocontamination was high compared with the permissible contamination threshold of 
    <b>293 C.F.U./m</b>
    <b><sup>3</sup></b>. 
    <b>Conclusion: </b>Our study provides evidence that the risk of aerobiocontamination is increased by activity. The expression of this risk is essentially a function of the time factor and the nature of the surgery. However, preoperative precautions and compliance with decontamination kinetics between procedures, which are necessary for particle sedimentation, remain sound safety principles to be observed.
   </abstract>
   <kwd-group> 
    <kwd>
     Aerobiocontamination
    </kwd> 
    <kwd>
      Operating Theatre
    </kwd> 
    <kwd>
      Airborne Germs
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <sec id="s1">
   <title>1. Introduction</title>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref>The fight against hospital-acquired infections (HAI) is a fundamental component of the policy to improve health and the quality of care in hospitals. Among these nosocomial infections, surgical site infections (SSI) are the most common post-surgical complication: their rate has been measured in certain studies to be between 2 and 5% <xref ref-type="bibr" rid="scirp.145429-1">
     [1]
    </xref>. The lethality of SSI0s is of the order of (5 to 20)%, but after certain surgeries it can be as high as 30% <xref ref-type="bibr" rid="scirp.145429-2">
     [2]
    </xref>. Some of these infections can have devastating functional consequences. They are accompanied by an average increase in length of stay of 7 to 10 days, which can reach 20 to 30 days for serious infections <xref ref-type="bibr" rid="scirp.145429-3">
     [3]
    </xref>. Given this picture, it is only logical to look at the risk factors for SSI. Among these, the role of air in the occurrence of SSIs is not negligible <xref ref-type="bibr" rid="scirp.145429-4">
     [4]
    </xref>. Indeed, given the combined effect of the susceptibility of surgical wounds to microbial contamination and the fragility of patients, air undeniably appears to be a major factor in the risk of post-operative infections <xref ref-type="bibr" rid="scirp.145429-5">
     [5]
    </xref>.</p>
   <p>As a result, prophylaxis against particulate and microbial contamination of the air in operating theatres is fundamental to improving the safety and quality of care in hospitals <xref ref-type="bibr" rid="scirp.145429-6">
     [6]
    </xref>. Health establishments are responsible for preventing the “avoidable” part of iatrogenic risks, which means instituting regular microbiological checks on the quality of ambient air in operating theatres <xref ref-type="bibr" rid="scirp.145429-7">
     [7]
    </xref>. In 2014, the US healthcare-associated infection surveillance programmes (SENIC project) showed that SSI was the number one preventable healthcare-associated infection <xref ref-type="bibr" rid="scirp.145429-8">
     [8]
    </xref>. A 19% to 41% reduction in the rate of SSI over 6 years was also observed after the implementation of a policy to combat nosocomial infection in hospitals participating in these programmes <xref ref-type="bibr" rid="scirp.145429-9">
     [9]
    </xref>.</p>
   <p>It is in this context that the present study focuses on the prevalence of aerobiocontamination in the operating theatre and the identification of germs isolated at Port Bouët General Hospital. It proposes a method for assessing and determining the bacteriological and epidemiological characteristics of bacteria, in order to put in place, the necessary means to protect patients from post-operative infections.</p>
  </sec><sec id="s2">
   <title>2. Materials and Methods</title>
   <p>Confidentiality and anonymity were respected during the study, thanks to the use of a single survey form in which patients’ identities were replaced by codes. In addition, samples were taken with the written and informed consent of the parents of eligible patients. This study also required the authorisation of the Director of Port Bouët General Hospital.</p>
   <p>The samples were taken in the HGPB operating theatre in the Abidjan Sud health district. The hospital had three (03) operating theatres grouped together in one building. These rooms were used for all types of surgery, regardless of whether the operation was scheduled or urgent. Architecturally, the walls were covered in resin (oil) paint. The floor covering was smooth and dust-free, with a well-expanded skirting board. All the blocks were equipped with two (02) double doors always leading to an airlock. The doors to the patient movement circuit were fitted with an aluminium plate to cushion the impact of stretchers. Each unit was equipped with split air conditioning. The temperature in the blocks varied between 20 and 22˚C, in accordance with the recent recommendations of the clinical excellence commission health New South Wales of Australia <xref ref-type="bibr" rid="scirp.145429-10">
     [10]
    </xref>.</p>
   <p>Samples taken in the various operating theatres at the HGPB were sent directly to the LNSP for analysis.</p>
   <p>Air samples were taken in three stages around the operating field: before, during and after surgery.</p>
   <p>The determination of the number of sampling points in a cleanroom was proportional to the area of the cleanroom as defined in the equation below in ISO 14644-1. In addition, these sampling points should be uniformly distributed throughout the room <xref ref-type="bibr" rid="scirp.145429-11">
     [11]
    </xref>. The cleanrooms selected for our study had an average area (A) of 80 m<sup>2</sup>. In application of the principle relating to the determination of the number of sampling points in cleanrooms, the following equation was applied:</p>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref>N<sub>L</sub> = 
    <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <mo> 
      </mo> 
      <msqrt> 
       <mi>
         A 
       </mi> 
      </msqrt> 
     </mrow> 
    </math> = 
    <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msqrt> 
       <mrow> 
        <mn>
          80 
        </mn> 
       </mrow> 
      </msqrt> 
      <mo> 
      </mo> 
     </mrow> 
    </math> = 8.94. The minimum number of sampling points per room was therefore 9. However, for the purposes of the study, the number of samples per room was of the order of 14.</p>
   <p>The particulate cleanliness of the air was designated by a classification number N in accordance with ISO 14644-1:1 <xref ref-type="bibr" rid="scirp.145429-11">
     [11]
    </xref>. The maximum permissible concentration Cn, for each particle of size D taken into account, was given by the equation:</p>
   <p>
    <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <mi>
        C 
      </mi> 
      <mi>
        n 
      </mi> 
      <mo>
        = 
      </mo> 
      <msup> 
       <mrow> 
        <mn>
          10 
        </mn> 
       </mrow> 
       <mstyle mathvariant="bold" mathsize="normal"> 
        <mi>
          N 
        </mi> 
       </mstyle> 
      </msup> 
      <mo>
        × 
      </mo> 
      <msup> 
       <mrow> 
        <mrow> 
         <mo>
           ( 
         </mo> 
         <mrow> 
          <mfrac> 
           <mrow> 
            <mn>
              0 
            </mn> 
            <mo>
              , 
            </mo> 
            <mn>
              1 
            </mn> 
           </mrow> 
           <mstyle mathvariant="bold" mathsize="normal"> 
            <mi>
              D 
            </mi> 
           </mstyle> 
          </mfrac> 
         </mrow> 
         <mo>
           ) 
         </mo> 
        </mrow> 
       </mrow> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          , 
        </mo> 
        <mn>
          08 
        </mn> 
       </mrow> 
      </msup> 
     </mrow> 
    </math></p>
   <p>In the case of operating theatres, the particle cleanliness class chosen was 6 <xref ref-type="bibr" rid="scirp.145429-11">
     [11]
    </xref>.</p>
   <p>In the present study, the diameter of the particles measured was 5 µm <xref ref-type="bibr" rid="scirp.145429-12">
     [12]
    </xref>.</p>
   <p>In practice, the permissible particulate concentration was:</p>
   <p>
    <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <mi>
        C 
      </mi> 
      <mi>
        n 
      </mi> 
      <mo>
        = 
      </mo> 
      <msup> 
       <mrow> 
        <mn>
          10 
        </mn> 
       </mrow> 
       <mn>
         6 
       </mn> 
      </msup> 
      <mo>
        × 
      </mo> 
      <msup> 
       <mrow> 
        <mrow> 
         <mo>
           ( 
         </mo> 
         <mrow> 
          <mfrac> 
           <mrow> 
            <mn>
              0 
            </mn> 
            <mo>
              , 
            </mo> 
            <mn>
              1 
            </mn> 
           </mrow> 
           <mn>
             5 
           </mn> 
          </mfrac> 
         </mrow> 
         <mo>
           ) 
         </mo> 
        </mrow> 
       </mrow> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          , 
        </mo> 
        <mn>
          08 
        </mn> 
       </mrow> 
      </msup> 
     </mrow> 
    </math></p>
   <p>Cn = 293 C.F.U./m<sup>3</sup> of air</p>
   <p>The elemental volume of the sample expressed the sufficient volume of air to be sampled at each point so that, at the limit of the specified ISO class (<xref ref-type="table" rid="table1">
     Table 1
    </xref>), at least 20 particles would be detected. The elementary volume (Vs) per sampling point is given by the following equation:</p>
   <p>
    <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <mstyle mathvariant="bold" mathsize="normal"> 
       <mi>
         V 
       </mi> 
       <mi>
         s 
       </mi> 
      </mstyle> 
      <mo>
        = 
      </mo> 
      <mfrac> 
       <mrow> 
        <mn>
          20 
        </mn> 
       </mrow> 
       <mrow> 
        <mi>
          C 
        </mi> 
        <mi>
          n 
        </mi> 
        <mo>
          . 
        </mo> 
        <mi>
          m 
        </mi> 
       </mrow> 
      </mfrac> 
      <mo> 
      </mo> 
      <mo>
        × 
      </mo> 
      <mn>
        1000 
      </mn> 
      <mo>
        = 
      </mo> 
      <mfrac> 
       <mrow> 
        <mn>
          20 
        </mn> 
       </mrow> 
       <mrow> 
        <mn>
          293 
        </mn> 
       </mrow> 
      </mfrac> 
      <mo> 
      </mo> 
      <mo>
        × 
      </mo> 
      <mn>
        1000 
      </mn> 
     </mrow> 
    </math></p>
   <p>Vs = 68 litres</p>
   <table-wrap id="table1">
    <label>
     <xref ref-type="table" rid="table1">
      Table 1
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.145429-"></xref>Table 1. Maximum permissible particle concentrations in (particles/m<sup>3</sup> of air) <xref ref-type="bibr" rid="scirp.145429-11">
       [11]
      </xref> <xref ref-type="bibr" rid="scirp.145429-13">
       [13]
      </xref>.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="18.71%"><p style="text-align:center">Number of</p><p style="text-align:center">classification</p></td> 
      <td class="custom-bottom-td acenter" width="81.29%" colspan="6"><p style="text-align:center">Maximum permissible concentrations (particles/m<sup>3</sup> of air) of particulate matter</p><p style="text-align:center">of a size equal to or greater than that shown below</p></td> 
     </tr> 
     <tr> 
      <td class="custom-bottom-td custom-top-td acenter" width="18.71%"><p style="text-align:center">ISO (N)</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="14.38%"><p style="text-align:center">0.1 μm</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="12.51%"><p style="text-align:center">0.2 μm</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="12.51%"><p style="text-align:center">0.3 μm</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="15.62%"><p style="text-align:center">0.5 μm</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="14.37%"><p style="text-align:center">1 μm</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="11.91%"><p style="text-align:center">5 μm</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="18.71%"><p style="text-align:center">ISO Class 1</p></td> 
      <td class="custom-top-td acenter" width="14.38%"><p style="text-align:center">10</p></td> 
      <td class="custom-top-td acenter" width="12.51%"><p style="text-align:center">2</p></td> 
      <td class="custom-top-td acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="custom-top-td acenter" width="15.62%"><p style="text-align:center"></p></td> 
      <td class="custom-top-td acenter" width="14.37%"><p style="text-align:center"></p></td> 
      <td class="custom-top-td acenter" width="11.91%"><p style="text-align:center"></p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 2</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center">100</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">24</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">10</p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">4</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center"></p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 3</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center">1.000</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">237</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">102</p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">35</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">8</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center"></p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 4</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center">10.000</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">2.370</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">1.020</p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">352</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">83</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center"></p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 5</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center">100.000</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">23.700</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">10.200</p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">3.520</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">832</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center">29</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 6</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center">1.000.000</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">237.000</p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center">102.000</p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">35.200</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">8.320</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center">293</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 7</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">352.000</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">83,200</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center">29,300</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 8</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">3.520.000</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">832.000</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center">29.300</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="18.71%"><p style="text-align:center">ISO Class 9</p></td> 
      <td class="acenter" width="14.38%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="12.51%"><p style="text-align:center"></p></td> 
      <td class="acenter" width="15.62%"><p style="text-align:center">35.200.000</p></td> 
      <td class="acenter" width="14.37%"><p style="text-align:center">8.320.000</p></td> 
      <td class="acenter" width="11.91%"><p style="text-align:center">293,000</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <p>NB: Because of the uncertainties involved in measurement, concentrations are given to no more than 3 significant figures.</p>
   <p>In this study, the sampling device had a suction capacity of around 60 litres per 20 seconds, either 180 litres per minute.</p>
   <p>The sampling results were expressed as Colony-Forming Units per cubic metre (C.F.U./m<sup>3</sup>). The number of C.F.U./m<sup>3</sup> was determined from the sampling time and the flow rate of the device, which was 180 litres of air per minute (corresponding to 0.18 m<sup>3</sup> of air/min).</p>
   <p>
    <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <mtext>
        Number of 
      </mtext> 
      <mrow> 
       <mrow> 
        <mi>
          C 
        </mi> 
        <mo>
          . 
        </mo> 
        <mi>
          F 
        </mi> 
        <mo>
          . 
        </mo> 
        <mi>
          U 
        </mi> 
        <mo>
          . 
        </mo> 
       </mrow> 
       <mo>
         / 
       </mo> 
       <mrow> 
        <msup> 
         <mtext>
           m 
         </mtext> 
         <mn>
           3 
         </mn> 
        </msup> 
       </mrow> 
      </mrow> 
      <mo>
        = 
      </mo> 
      <mfrac> 
       <mrow> 
        <mtext>
          Number of colonies 
        </mtext> 
       </mrow> 
       <mrow> 
        <mtext>
          Sampling time 
        </mtext> 
        <mo>
          × 
        </mo> 
        <mn>
          0 
        </mn> 
        <mo>
          , 
        </mo> 
        <mn>
          18 
        </mn> 
       </mrow> 
      </mfrac> 
     </mrow> 
    </math></p>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref>The statistical analysis was carried out using Epi/ Info 6.2 (CDC) software to compare the independence of the means of the qualitative variables using the chi-square test (χ<sup>2</sup>). Fisher’s exact probability test was also used with this software to test the independence of the quantitative variables studied.</p>
  </sec><sec id="s3">
   <title>3. Results</title>
   <p>The prospective study of particulate contamination of ambient air recorded 135 samples taken, with an average of 44 samples taken in each operating theatre and 03 in the recovery and intensive care units. At each sampling point, based on the elementary volume (0.18 m<sup>3</sup>) sampled, the result obtained was defined as the number of particles giving rise to a colony per cubic metre (C.F.U./m<sup>3</sup>). The results were reported as the mean and standard deviation per block.</p>
   <table-wrap id="table2">
    <label>
     <xref ref-type="table" rid="table2">
      Table 2
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.145429-"></xref>Table 2. Average concentration of particles in the different operating phases in the operating theatre.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="35.32%"><p style="text-align:center">Sampling point for 03 blocks</p></td> 
      <td class="custom-bottom-td acenter" width="25.52%"><p style="text-align:center">Pre-operative (C.F.U/m³)</p></td> 
      <td class="custom-bottom-td acenter" width="21.12%"><p style="text-align:center">Per-operative (C.F.U/m³)</p></td> 
      <td class="custom-bottom-td acenter" width="18.04%"><p style="text-align:center">Post-operative (C.F.U/m³)</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="35.32%"><p style="text-align:center">Average</p></td> 
      <td class="custom-top-td acenter" width="25.52%"><p style="text-align:center">290</p></td> 
      <td class="custom-top-td acenter" width="21.12%"><p style="text-align:center">410</p></td> 
      <td class="custom-top-td acenter" width="18.04%"><p style="text-align:center">352</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="35.32%"><p style="text-align:center">Standard deviation</p></td> 
      <td class="acenter" width="25.52%"><p style="text-align:center">135</p></td> 
      <td class="acenter" width="21.12%"><p style="text-align:center">145</p></td> 
      <td class="acenter" width="18.04%"><p style="text-align:center">132</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref>These results indicated a level of contamination in the ambient air well in excess of the permissible threshold of 293 (C.F.U./m³) of the ISO 14644-1 <xref ref-type="bibr" rid="scirp.145429-11">
     [11]
    </xref> (<xref ref-type="table" rid="table2">
     Table 2
    </xref>). In addition, most of the particulate concentrations obtained at each sampling point were above the tolerable microbial concentration of 32 C.F.U./m<sup>3</sup> (no activity) or 180 C.F.U./m<sup>3</sup> (human presence) <xref ref-type="bibr" rid="scirp.145429-15">
     [15]
    </xref>.</p>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref></p>
   <fig id="fig1" position="float">
    <label>Figure 1</label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.145429-"></xref>Figure 1. Correlation between preoperative and intraoperative aerobiocontamination.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2272204-rId38.jpeg?20250908113943" />
   </fig>
   <p>With a correlation coefficient r = 0.6 and p &lt; 0.05, the results indicated that the pre-operative residual flora had a direct influence on the generation of intra-operative aerobiocontamination (<xref ref-type="fig" rid="fig1">
     Figure 1
    </xref>).</p>
   <fig id="fig2" position="float">
    <label>Figure 2</label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.145429-"></xref>Figure 2. Study of the correlation between intra-operative and post-operative aerobio- contamination.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2272204-rId39.jpeg?20250908113943" />
   </fig>
   <p>The interest here in counting particulate matter at the end of each procedure was guided by the need to assess the real impact of the said procedure on the quality of the ambient air in the operating theatre. Thus, with a correlation coefficient r = 0.74 and p &lt; 0.05, we could conclude that the extent of aerobiocontamination at the end of each operation was a direct consequence of the surgical procedure (<xref ref-type="fig" rid="fig2">
     Figure 2
    </xref>).</p>
   <fig id="fig3" position="float">
    <label>Figure 3</label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.145429-"></xref>Figure 3. Evolution of decontamination kinetics.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2272204-rId40.jpeg?20250908113943" />
   </fig>
   <fig id="fig4" position="float">
    <label>Figure 4</label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.145429-"></xref>Figure 4. Nature and frequency of micro-organisms identified in the operating theatre.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2272204-rId41.jpeg?20250908113943" />
   </fig>
   <p>The study of the correlation of microbial flora between the post-operative and pre-operative phases was a response to the need to respect decontamination kinetics between different surgical procedures. In theory, decontamination kinetics is the time required to eliminate 90% of particles 0.5 µm in diameter or larger <xref ref-type="bibr" rid="scirp.145429-16">
     [16]
    </xref>. In other words, this time is referred to as the resting time of the rooms. In view of the results of the statistical analysis of the present study, r = 0.8 and p &lt; 0.05, the decontamination kinetics were not satisfactory between interventions. On the other hand, decontamination kinetics were interesting for translating the dynamics of a room’s behaviour (<xref ref-type="fig" rid="fig3">
     Figure 3
    </xref>).</p>
   <p>Microbiological analysis of air samples from the three operating theatres revealed six (06) saprophytic bacterial strains (85%), namely: Staphylococcus saprophyticus, Staphylococcus epidermidis, Staphylococcus haemolyticus, Entérococcus sp, Micrococcus sp and Bacillus sp and five (05) fungal strains (15%): Penicillium sp, Aspergillus sp, Fusarium sp, Candida non albicans and Alternaria sp. The most frequent species were Staphylococcus saprophyticcus, Micrococcus sp and Bacillus sp, accounting for 72% of the germs identified, with an estimated bacterial load of 283 C.F.U./m<sup>3</sup> and a fungal load of 56 C.F.U./m<sup>3</sup>. Unlike various previous studies (<xref ref-type="fig" rid="fig4">
     Figure 4
    </xref>).</p>
  </sec><sec id="s4">
   <title>4. Discussion</title>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref>Air control in the operating theatre is one of the essential measures for preventing the risk of infection in surgery <xref ref-type="bibr" rid="scirp.145429-17">
     [17]
    </xref>. Because of its mobility, air is a real vector in the occurrence of surgical site infections (SSI), hence the need for regular control and monitoring of ambient air quality in operating theatres <xref ref-type="bibr" rid="scirp.145429-18">
     [18]
    </xref>. The results obtained from monitoring the quality of ambient air in the HGPB operating theatre were very high. Generally speaking, the average particulate concentrations obtained pre-operatively, per-operatively and post-operatively were 290 ± 135 C.F.U/m³, 410 ± 145 C.F.U./m³ and 352 ± 132 C.F.U./m³ respectively. The particulate concentrations obtained at each sampling point were regularly well above the permissible microbial concentration of 32 C.F.U./m<sup>3</sup> (no activity) or 180 C.F.U./m<sup>3</sup> (human presence). As an indication, after several years of investigation into air quality in several conventionally ventilated operating theatres, Pasquarella et al. proposed an alert level of 180 C.F.U./m³ for operating theatres and 32 C.F.U./m³ for non-operating theatres (using an active method measurement) <xref ref-type="bibr" rid="scirp.145429-15">
     [15]
    </xref>. In addition, in relation to the ISO 14644-1 standard, the results of the present study indicated a level of contamination of the ambient air well above the admissible threshold of 293 (C.F.U./m³) in the operating theatre <xref ref-type="bibr" rid="scirp.145429-19">
     [19]
    </xref>. The importance of aerobiocontamination in the intra-operative phase compared with the other phases observed here was also confirmed by the statistical analysis carried out (r = 0.74 and p &lt; 0.05) establishing a correlation between the occurrence of aerobiocontamination and the particulate load in the intra-operative phase. Far from being an isolated study, several previous similar studies looking at the question of the correlation between particulate concentration and microbiological air quality had led to various results <xref ref-type="bibr" rid="scirp.145429-20">
     [20]
    </xref>. Among them, some studies by Landrin et al. in 2005, Scaltriti et al. in 2007 and Cristina et al. in 2012 concluded that there was no correlation between particle count and microbiological contamination <xref ref-type="bibr" rid="scirp.145429-21">
     [21]
    </xref>-<xref ref-type="bibr" rid="scirp.145429-23">
     [23]
    </xref>. However, other studies by Stocks et al. in 2010 and by Wan et al. in 2011 have confirmed the existence of a correlation <xref ref-type="bibr" rid="scirp.145429-24">
     [24]
    </xref> <xref ref-type="bibr" rid="scirp.145429-25">
     [25]
    </xref>. This increase in aerobiocontamination could be explained in part by the surgical activity mobilising the surgical team <xref ref-type="bibr" rid="scirp.145429-22">
     [22]
    </xref> <xref ref-type="bibr" rid="scirp.145429-23">
     [23]
    </xref>. Previous experimental studies have shown that humans emit a considerable number of particles into their immediate environment, either around one million per minute for an average activity. These were skin flakes, more or less carrying bacteria. They were suspended in the air despite their large size (10 to 15 μm) thanks to convection currents generated by the temperature gradient between the body and its environment, known as the “human heat island” <xref ref-type="bibr" rid="scirp.145429-26">
     [26]
    </xref>. Our results were also in line with those of Clarke et al. who, in the course of 40 hip replacement operations using PCR and conventional culture, showed that the percentage of positive samples was significantly higher at the end of the operation than at the beginning <xref ref-type="bibr" rid="scirp.145429-27">
     [27]
    </xref>. Looking at the consequences of aerobiocontamination, talon et al. in 2006 established that the patient’s skin was the source of only 2% of contamination, while particles in the air accounted for the remaining 98% through direct contamination of the site <xref ref-type="bibr" rid="scirp.145429-28">
     [28]
    </xref>. Similarly, Pasquarella et al. in 2003 maintained that the risk of contamination of the surgical site by airborne particles was attributable in 30% of cases to the direct deposition of particles on the wound and in 70% of cases to their deposition on the surgeon’s instruments and hands, followed by transfer to the wound <xref ref-type="bibr" rid="scirp.145429-14">
     [14]
    </xref>. This argument confirms that of Knobben et al. in 2006 and other studies which also explained that particle sedimentation would lead to contamination of instruments (up to more than 30% of positive samples), hence the need to respect the postoperative decontamination kinetics as recommended by the experts of the French Hospital Hygiene Society <xref ref-type="bibr" rid="scirp.145429-29">
     [29]
    </xref>. However, in the present study, the statistical analysis (r = 0.8 and p &lt; 0.05) of the data relating to the decontamination kinetics indicated that the rest time of the rooms was satisfactory. In fact, rest periods between different surgical procedures were rarely observed during the survey. In view of the negative impact of non-compliance with decontamination kinetics on the increase in particulate contamination during the operating phase, both cleaning staff and surgeons need to be made aware of the need to comply with environmental and hygiene requirements in operating theatres.</p>
   <p>Therefore, far from concluding that there are no infectious risks preoperatively (inappropriate antibiotic prophylaxis, lack of hygiene, significant residual flora) and postoperatively (irregularity of postoperative care), according to the results of several studies Munckhof et al. in 2005 or Crader et al. in 2022, the risk remains at all levels to varying degrees <xref ref-type="bibr" rid="scirp.145429-30">
     [30]
    </xref> <xref ref-type="bibr" rid="scirp.145429-31">
     [31]
    </xref>. In addition to the obvious risk of aerobiocontamination for SSI, other risk factors coexist, such as the duration of the operation, the ASA score, the nature of the operation and the Altemeir classification of operations, which should not be underestimated <xref ref-type="bibr" rid="scirp.145429-32">
     [32]
    </xref>.</p>
   <p>Finally, the microbiological identification of the samples taken at the end of the operations revealed the existence of eleven micro-organisms, including six (06) saprophytic bacterial strains (85%), namely: Staphylococcus saprophyticus, Staphylococcus epidermidis, Staphylococcus haemolyticus, Entérococcus sp, Micrococcus sp and Bacillus sp and five (05) fungal strains (15%): Penicillium sp, Aspergillus sp Fusarium sp, Candida non albicans and Alternaria sp. The most frequent species were Staphylococcus saprophyticcus, Micrococcus sp and Bacillus sp, accounting for 72% of the germs identified, with an estimated bacterial load of 283 C.F.U./m<sup>3</sup> and a fungal load of 56 C.F.U./m<sup>3</sup>. Following the example of several previous studies , most of the airborne microbes identified are saprophytic germs which may prove potentially pathogenic for patients weakened by the surgical wound. At the end of this study, a significant correlation emerged between airborne particles (5 µm) and the microbes found in operating theatres. In addition, our results are supported by those of Wang et al. who also concluded that there was a correlation between particles (5 µm) and aerobiocontamination in the operating theatre due to the fragility of the patients operated on <xref ref-type="bibr" rid="scirp.145429-33">
     [33]
    </xref>. However, in contrast to our results, several studies similar to ours have directly demonstrated pathogenic S. aureus species which are even multi-resistant to meticillin and ampicillin <xref ref-type="bibr" rid="scirp.145429-17">
     [17]
    </xref> <xref ref-type="bibr" rid="scirp.145429-34">
     [34]
    </xref>.</p>
  </sec><sec id="s5">
   <title>5. Limits</title>
   <p>Although this experimental study has the advantage of reflecting the natural microbial flora of the operating theatre, it has a number of limitations. Due to limited resources (human and financial), we were unable to follow patients with surgical site infections during the study period to determine the susceptibility or responsibility of airborne germs. Nor did the small sample size allow for a more optimal interpretation of the prevalence of airborne contamination. Thus, with the current implementation of sampling procedures and techniques, we encourage the use of larger sample sizes and improved SSI data.</p>
  </sec><sec id="s6">
   <title>6. Conclusion</title>
   <p>
    <xref ref-type="bibr" rid="scirp.145429-"></xref>Today, the aggressive nature of surgical site infections means that health establishments need to adopt more preventive measures in addition to traditional biocleaning and maintenance methods. Among these measures, control of the microbiological quality of the air is strongly recommended. In addition, the high levels of aerobiocontamination in the blocks: 290 ± 135 C.F.U./m³, 410 ± 145 C.F.U./m³ and 352 ± 132 C.F.U./m³ compared with the admissible threshold of 293 C.F.U./m³ in our work demonstrate the need for regular monitoring, including the associated risk factors. Finally, these results call on the health authorities to fulfil their duty to prevent the avoidable proportion of surgical site infections and improve management of the unavoidable proportion.</p>
  </sec><sec id="s7">
   <title>What Is Known about This Subject?</title>
   <p>Given the combined effect of the sensitivity of surgical wounds to microbial contamination and the fragility of patients, air undeniably appears to be a major factor in the risk of post-operative infections.</p>
   <p>Prophylaxis against particulate and microbial contamination of the air in operating theatres is therefore fundamental to improving the safety and quality of care in hospitals <xref ref-type="bibr" rid="scirp.145429-6">
     [6]
    </xref>. Health establishments are responsible for preventing the “avoidable” part of iatrogenic risks, which means instituting regular microbiological checks on the quality of ambient air in operating theatres.</p>
  </sec><sec id="s8">
   <title>What’s New in This Study</title>
   <p>Unlike previous similar studies using passive sampling approaches, this study adopted an active sampling mode using a portable S.A.S. air bio-collector. The study also established sampling protocols for future studies and defined the characteristics to be measured in operating theatre air contamination studies.</p>
  </sec><sec id="s9">
   <title>Acknowledgements</title>
   <p>The authors would like to thank the medical staff of the operating theatres of the Port Bouet General Hospital during the study period for their help, as well as the technical staff of the National Public Health Laboratory. A special mention to my master Professor LOUKOU Yao Guillaume now retired.</p>
  </sec>
 </body><back>
  <ref-list>
   <title>References</title>
   <ref id="scirp.145429-ref1">
    <label>1</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ngaroua,, Ngah, J.E., Bénet, T. and Djibrilla, Y. (2016) Incidence des infections du site opératoire en Afrique sub-saharienne: Revue systématique et méta-analyse. Pan African Medical Journal, 24, Article 171. &gt;https://doi.org/10.11604/pamj.2016.24.171.9754
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref2">
    <label>2</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Andersen, B.M. (2019) Prevention of Postoperative Wound Infections. In: Andersen, B.M., Ed., Prevention and Control of Infections in Hospitals, Springer, 377-437. &gt;https://doi.org/10.1007/978-3-319-99921-0_33
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref3">
    <label>3</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Mehtar, S., Wanyoro, A., Ogunsola, F., Ameh, E.A., Nthumba, P., Kilpatrick, C., et al. (2020) Implementation of Surgical Site Infection Surveillance in Low-and Middle-Income Countries: A Position Statement for the International Society for Infectious Diseases. International Journal of Infectious Diseases, 100, 123-131. &gt;https://doi.org/10.1016/j.ijid.2020.07.021
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref4">
    <label>4</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Persson, M. (2019) Airborne Contamination and Surgical Site Infection: Could a Thirty-Year-Old Idea Help Solve the Problem? Medical Hypotheses, 132, Article ID: 109351. &gt;https://doi.org/10.1016/j.mehy.2019.109351
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref5">
    <label>5</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Popp, W., Alefelder, C., Bauer, S., Daeschlein, G., Geistberger, P., Gleich, S., et al. (2019) Air Quality in the Operating Room: Surgical Site Infections, HVAC Systems and Discipline—Position Paper of the German Society of Hospital Hygiene (DGKH). GMS Hygiene and Infection Control, 14, 6. &gt;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997799/ 
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref6">
    <label>6</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Spagnolo, A.M., Ottria, G., Amicizia, D., Perdelli, F. and Cristina, M.L. (2013) Operating Theatre Quality and Prevention of Surgical Site Infections. Journal of Preventive Medicine and Hygiene, 54, 131-137.
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref7">
    <label>7</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Saintoyant, V., Duhamel, G. and Minvielle, É. (2012) Gestion des risques associés aux soins: État des lieux et perspectives. Pratiques et Organisation des Soins, 43, 35-45. &gt;https://doi.org/10.3917/pos.431.0035
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref8">
    <label>8</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Merzougui, L., Marwen, N., Hannachi, H., Asma, M., Ben Elhaj, O., Waddah, M., et al. (2018) Incidence et facteurs de risque de l’infection du site opératoire après césarienne dans une maternité de Tunisie. Santé Publique, 30, 339-347. &gt;https://doi.org/10.3917/spub.183.0339
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref9">
    <label>9</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Geubbels, E.L.P.E., Nagelkerke, N.J.D., Mintjes-De Groot, A.J., Vandenbroucke-Grauls, C.M.J.E., Grobbee, D.E. and De Boer, A.S. (2006) Reduced Risk of Surgical Site Infections through Surveillance in a Network. International Journal for Quality in Health Care, 18, 127-133. &gt;https://doi.org/10.1093/intqhc/mzi103
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref10">
    <label>10</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     CEC Health NSW (2024) Risk Assessment and Escalation of Temperature or Humidity Variation in Perioperative and Sterile STOCK environments.&gt;https://www.cec.health.nsw.gov.au/__data/assets/pdf_file/0007/941560/Risk-assessment-and-escalation-of-temperature-or-humidity-variation-in-perioperative-and-sterile-stock-environments.pdf 
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref11">
    <label>11</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     CEC Health NSW. Risk assessment and escalation of temperature or humidity variation in perioperative and sterile stock environments. Version 1.0. April 2024. 3-4 &gt;https://www.cec.health.nsw.gov.au/__data/assets/pdf_file/0007/941560/Risk-assessment-and-escalation-of-temperature-or-humidity-variation-in-perioperative-and-sterile-stock-environments.pdf 
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref12">
    <label>12</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     International Organization for Standardization (2015) Cleanrooms and Associated Controlled Environments Part 1: Classification of Air Cleanliness by Particle Concentration. ISO.
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref13">
    <label>13</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     (2022) ISO 14644-2:2000(fr), Salles propres et environnements maîtrisés apparentés—Partie 2: Spécifications pour les essais et la surveillance en vue de démontrer le maintien de la conformité avec l’ISO 14644-1. &gt;https://www.iso.org/obp/ui/fr/#iso:std:iso:14644:-2:ed-1:v1:fr 
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref14">
    <label>14</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Pasquarella, C., Pitzurra, O., Herren, T., Poletti, L. and Savino, A. (2003) Lack of Influence of Body Exhaust Gowns on Aerobic Bacterial Surface Counts in a Mixed-Ventilation Operating Theatre. a Study of 62 Hip Arthroplasties. Journal of Hospital Infection, 54, 2-9. &gt;https://doi.org/10.1016/s0195-6701(03)00077-x
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref15">
    <label>15</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Pasquarella, C., Vitali, P., Saccani, E., Manotti, P., Boccuni, C., Ugolotti, M., et al. (2012) Microbial Air Monitoring in Operating Theatres: Experience at the University Hospital of Parma. Journal of Hospital Infection, 81, 50-57. &gt;https://doi.org/10.1016/j.jhin.2012.01.007
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref16">
    <label>16</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Gola, M., Settimo, G. and Capolongo, S. (2019) Indoor Air Quality in Inpatient Environments: A Systematic Review on Factors That Influence Chemical Pollution in Inpatient Wards. Journal of Healthcare Engineering, 2019, 1-20. &gt;https://doi.org/10.1155/2019/8358306
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref17">
    <label>17</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Fu Shaw, L., Chen, I.H., Chen, C.S., Wu, H.H., Lai, L.S., Chen, Y.Y., et al. (2018) Factors Influencing Microbial Colonies in the Air of Operating Rooms. BMC Infectious Diseases, 18, Article No. 4. &gt;https://doi.org/10.1186/s12879-017-2928-1
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref18">
    <label>18</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Montagna, M.T., Rutigliano, S., Trerotoli, P., Napoli, C., Apollonio, F., D’Amico, A., et al. (2019) Evaluation of Air Contamination in Orthopaedic Operating Theatres in Hospitals in Southern Italy: The IMPACT Project. International Journal of Environmental Research and Public Health, 16, Article 3581. &gt;https://doi.org/10.3390/ijerph16193581
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref19">
    <label>19</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Afnor EDITIONS (2003) NF S90-351. &gt;https://www.boutique.afnor.org/fr-fr/norme/nf-s90351/etablissement-de-sante-salles-propres-et-environnements-maitrises-apparente/fa122255/21563 
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref20">
    <label>20</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Dharan, S. and Pittet, D. (2002) Environmental Controls in Operating Theatres. Journal of Hospital Infection, 51, 79-84. &gt;https://doi.org/10.1053/jhin.2002.1217
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref21">
    <label>21</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Landrin, A., Bissery, A. and Kac, G. (2005) Monitoring Air Sampling in Operating Theatres: Can Particle Counting Replace Microbiological Sampling? Journal of Hospital Infection, 61, 27-29. &gt;https://doi.org/10.1016/j.jhin.2005.03.002
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref22">
    <label>22</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Scaltriti, S., Cencetti, S., Rovesti, S., Marchesi, I., Bargellini, A. and Borella, P. (2007) Risk Factors for Particulate and Microbial Contamination of Air in Operating Theatres. Journal of Hospital Infection, 66, 320-326. &gt;https://doi.org/10.1016/j.jhin.2007.05.019
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref23">
    <label>23</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Cristina, M.L., Spagnolo, A.M., Sartini, M., Panatto, D., Gasparini, R., Orlando, P., et al. (2012) Can Particulate Air Sampling Predict Microbial Load in Operating Theatres for Arthroplasty? PLOS ONE, 7, e52809. &gt;https://doi.org/10.1371/journal.pone.0052809
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref24">
    <label>24</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wang, J. and Chow, T. (2014) Influence of Human Movement on the Transport of Airborne Infectious Particles in Hospital. Journal of Building Performance Simulation, 8, 205-215. &gt;https://doi.org/10.1080/19401493.2014.905636
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref25">
    <label>25</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Stocks, G.W., Self, S.D., Thompson, B., Adame, X.A. and O’Connor, D.P. (2010) Predicting Bacterial Populations Based on Airborne Particulates: A Study Performed in Nonlaminar Flow Operating Rooms during Joint Arthroplasty Surgery. American Journal of Infection Control, 38, 199-204. &gt;https://doi.org/10.1016/j.ajic.2009.07.006
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref26">
    <label>26</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Rundstadler, Y. and Di majo, P. (2002) Lutter contre la contamination au bloc opératoire. ITBM-RBM, 23, 180-185. &gt;https://doi.org/10.1016/s1297-9562(02)80016-x
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref27">
    <label>27</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Clarke, M., Lee, P., Roberts, C., Gray, J., Keene, G. and Rushton, N. (2004) Contamination of Primary Total Hip Replacements in Standard and Ultra-Clean Operating Theaters Detected by the Polymerase Chain Reaction. Acta Orthopaedica Scandinavica, 75, 544-548. &gt;https://doi.org/10.1080/00016470410001394
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref28">
    <label>28</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Talon, D., Schoenleber, T., Bertrand, X. and Vichard, P. (2006) Performances en activité de différents types d’installation de traitement de l’air au bloc opératoire. Annales de Chirurgie, 131, 316-321. &gt;https://doi.org/10.1016/j.anchir.2006.02.002
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref29">
    <label>29</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Société Française d’Hygiène Hospitalière (2004) Recommandations sur l’environnement au bloc opératoire, Hygiènes, 12, 81-94.
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref30">
    <label>30</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Munckhof, W. (2005) Antibiotics for Surgical Prophylaxis. Australian Prescriber, 28, 38-40. &gt;https://doi.org/10.18773/austprescr.2005.030
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref31">
    <label>31</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Crader, M.F. and Varacallo, M. (2022) Preoperative Antibiotic Prophylaxis. StatPearls. &gt;http://www.ncbi.nlm.nih.gov/books/NBK442032/ 
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref32">
    <label>32</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Altemeier, W.A. and Vistnes, L.M. (1977) Manual on Control of Infection in Surgery Patients by the Committe on Control of Surgical Infections, American College of Surgeons. Plastic and Reconstructive Surgery, 59, 740. &gt;https://doi.org/10.1097/00006534-197705000-00025
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref33">
    <label>33</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wang, F.H., Chen, M.L., Lin, H.L., Huang, L.C., Hwang, K.C. and Chen, Y.H. (2011) Particle Burden and Bioaerosol Levels in Operating Rooms: A Case Study in a Medical Center. Aerosol and Air Quality Research, 11, 30-39.
    </mixed-citation>
   </ref>
   <ref id="scirp.145429-ref34">
    <label>34</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ramdani-Bouguessa, N., Bes, M., Meugnier, H., Forey, F., Reverdy, M., Lina, G., et al. (2006) Detection of Methicillin-Resistant staphylococcus Aureus Strains Resistant to Multiple Antibiotics and Carrying the Panton-Valentine Leukocidin Genes in an Algiers Hospital. Antimicrobial Agents and Chemotherapy, 50, 1083-1085. &gt;https://doi.org/10.1128/aac.50.3.1083-1085.2006
    </mixed-citation>
   </ref>
  </ref-list>
 </back>
</article>