|Year : 2017 | Volume
| Issue : 1 | Page : 18-23
Air sampling procedures to evaluate microbial contamination: A comparison between active and passive methods at high-risk areas in a Tertiary Care Hospital of Delhi
Rumpa Saha1, Shrreya Agarawal1, Amir Maroof Khan2
1 Department of Microbiology, University College of Medical Sciences and GTB Hospital, New Delhi, India
2 Department of Community Medicine, University College of Medical Sciences and GTB Hospital, New Delhi, India
|Date of Web Publication||18-Aug-2017|
Department of Microbiology, University College of Medical Sciences and GTB Hospital, New Delhi - 110 095
Source of Support: None, Conflict of Interest: None
Context: The microbial quality of air in the operation theatres (OTs) is a parameter which appreciably controls the healthcare-associated infections. However, there is currently no international consensus on the most suitable method to be used for air sampling or any set policy on how to achieve the total viable count (TVC) values although the optimum goals have been set.
Aims: This study aims to evaluate the microbial air quality in different OTs of our tertiary care hospital at rest and inoperational by comparing active and passive air sampling.
Settings and Design: The Department of Microbiology and all the OT rooms of UCMS and GTB Hospital, Delhi. There are 18 OT rooms. This was a cross-sectional, comparative study.
Subjects and Methods: Five at rest samples (before the start of operation) and five inoperational samples (during operation) were collected from each of the 18 OTs by both active (using air sampler) and passive (gravity settle plate technique as per the 1/1/1 scheme) methods using five percent sheep blood agar in 9 cm petri plates. The number of personnel present inoperational was recorded, and the number of colony forming units on the petri dish was counted after incubation and compared.
Statistical Analysis Used: As the data followed a non-normal distribution, non-parametric tests were applied. Wilcoxon signed rank test, Spearman's correlation coefficient, Simple linear regression and Independent sample t-test.
Results: The total bioburden in the OTs exceeded the maximum acceptable limit value during both moments of sampling. There was a significant positive correlation in the TVC values obtained by active and passive sampling methods in the two moments.
Conclusions: The present study demonstrates a comparability of results obtained by the two different sampling techniques at two sampling moments. However, authentication of this result necessitates additional studies. In the interim, it is promising to conclude that both methods can be used for universal scrutinising of air biocontamination.
Keywords: Air sampler, air sampling, settle plate method
|How to cite this article:|
Saha R, Agarawal S, Khan AM. Air sampling procedures to evaluate microbial contamination: A comparison between active and passive methods at high-risk areas in a Tertiary Care Hospital of Delhi. J Patient Saf Infect Control 2017;5:18-23
|How to cite this URL:|
Saha R, Agarawal S, Khan AM. Air sampling procedures to evaluate microbial contamination: A comparison between active and passive methods at high-risk areas in a Tertiary Care Hospital of Delhi. J Patient Saf Infect Control [serial online] 2017 [cited 2022 Aug 18];5:18-23. Available from: https://www.jpsiconline.com/text.asp?2017/5/1/18/213282
| Introduction|| |
The post-operative infection rate (PIR) depends not only on the type of surgery, the cleanliness of equipment, medical procedures, air quality of the operation theatre (OT) but also to a large extent on the microorganism in the surrounding environment. Post-operative infections constitute one-third of the hospital-acquired infections, and a large number of them arise from contaminated air in the OTs., Many developing countries have reported high PIR in their hospitals-15% from Brazil, 11% from Mumbai, 21.66% from Karnataka  as compared to 5% PIR reported from the USA and Europe having a well maintained conditioned and controlled ventilation system (CCVS). It is in fact estimated that a 13-fold reduction in the air microbial load would reduce wound infection by almost 50%.,
Airborne cells and spores of bacteria and fungi may be present as bioaerosols (droplets of very small isolated particles which may remain suspended or as larger aggregates settle onto surfaces. Thus, the environmental components (air, water and surfaces) are noteworthy reservoirs of microorganism. This holds true, particularly in the hospital environment where there is an increased susceptibility to infections owing to the exposure of tissues to the environment.,, Thus, microbiological monitoring of air for the concentration and quality of microorganisms is useful to determine the potential risk the individuals are exposed to and also the effectiveness of both the CCVS and the surgical team's hygiene procedures. Microbiological quality of air can thus be considered as a mirror of hygienic conditions at any place, especially in OTs. Thus, assessment of the bioburden in air in places which can jeopardize safety in health-care settings is considered to be a fundamental step towards avoidance of such infections. However, the ideal method to carry out the assessment, monitor the procedure, interpretation of data and maximum limit of biocontamination is still subject to dispute; hence, procedures have not been definitely ascertained. In fact, a choice between different methods (active or passive) and diverse samplers has been left open by the global standards.,
Active sampling uses air samplers which have been designed to draw in a pre-set volume of air onto a culture plate or a membrane of nitrocellulose. After incubation at a specific temperature, colony forming units (CFU)/m 3 of air is calculated from the microorganisms on the culture plate. This method is often applicable when the air microbial concentration is low, as in health-care settings.,,,
Passive monitoring uses settle plates, which are 9 cm diameter petri dishes containing a non-selective culture medium. They are kept open for a fixed period to collect particles which sediment out and are then incubated. Results are expressed in CFU/place/time or CFU/m 2/h.
Currently, the lack of set guidelines for air sampling makes evaluation of results from different studies complicated. Moreover, the presence of many factors which alter the results of air sampling like the kind of air flow, the participation of the number people with different kinds of personal protective equipment, emphasise the importance of precise air sampling (precise volumes of sampled air, duration of sampling, etc.). In fact, the presence of many factors demonstrated that if a strict protocol is followed, the two methods could correlate in a similar manner.
Keeping in mind the above background, the present study was aimed to evaluate the microbial quality of air in operation theatres (OTs) at different moments – at rest (before the start of surgery) and inoperational (during surgical activity) by both active and passive air sampling. The main objectives were as follows:
- Correlation of results of active and passive air sampling obtained by active and passive sampling in OTs
- Comparison of the results of bio-contamination surveillance carried out at different moments in OTs (at rest and inoperational)
- Analysing the relation between the number of people in the OT and the microbial loads for each method
- To determine which of the above method would be most suitable for microbiological air sampling in high-risk areas of our hospital setting.
| Subjects and Methods|| |
This cross-sectional comparative study was carried out within a period of 2 months (June 20, 2016–August 20, 2016) after obtaining clearance from the Institutional Ethics Committee. The study was conducted in a large 1800 bedded tertiary care hospital where the average number of surgeries per day is more than hundred. The study enrolled 18 turbulent airflow OTs (none equipped with high-efficiency particulate air [HEPA] filters) operating under five surgical departments. The mean OT room volume was found to be 110/m 3. After sampling, all plates were incubated in the Department of Microbiology. No clinical or animal subjects were involved in the present study.
Five resting and five inoperational samples were taken from each from the 18 OT rooms by both active and passive methods.
Air was sampled from one OT per day by both active and passive methods at both moments – at rest and inoperational. The number of people present during operation was also recorded for the association between the number of personnel and the total viable count (TVC). In our study, 5% sheep blood agar plates were used after pre-sterility testing by overnight incubation at 37°C.
Passive sampling: Passive sampling was used to obtain the index of microbial air contamination (IMA). This index corresponds to the values of CFU calculated from the culture plates of 9 cm diameter. The sealed petri dishes were transported to the OT where sampling was to be done and positioned as per the 1/1/1 scheme (for 1 h, at a height of 1 m from the floor, at a distance of 1 m from walls or any other obstacle).
Active sampling: Active sampling used a single stage slit-type air sampler (HiAirFlow LA881, Hi-Media, India) whose flow rate was set at 100 L/min. Accordingly, 1000 L of air was sampled in a single draw of 10 min. The sampler was positioned adjacent to the settle plates. Since there is no controlled ventilation system in our OTs, sampling at rest mainly determined the cleanliness of the OT and its preparation for the subsequent operation while the presence of people during the inoperational sampling reflected the team's hygiene behavior in addition to the OT cleanliness. During inoperational sampling, when the number of people in the room increased, the results of the sampling clearly reflected the team's hygiene procedures and behavior, in addition to the OT cleanliness. Hence, active sampling was continued for the entire duration, the settle plates were left open, with five air draws of 10 min each covering all the four corners and centre both at rest and during operation.
This procedure was followed for all the 18 OTs.
After exposure, the plates were covered with their lids and taken to the Microbiology laboratory and incubated at 37°C for 24 h.
After incubation, the total number of CFU was counted, different types of colonies were noted and the numbers of haemolytic colonies, if any, were identified for Staphylococcus aureus methicillin-sensitive S. aureus/ methicillin-resistant S. aureus (MSSA/MRSA) by standard bacteriological methods.
The CFU values obtained by passive method were converted to their respective IMA values, and the maximum acceptable level of IMA in OTs with a turbulent air flow was taken to be <5 CFU/9 cm diameter plate/h at rest and <25 CFU/9 cm diameter plate/h inoperational.
The CFU values for active method were modified and expressed as CFU/m 3 based on the conversion table given by the manufacturer. Maximum acceptable level taken as standard during active sampling, as per (Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro (ISPESL) 2009 guidelines, for microbial contamination in OTs with turbulent air flow were <35 CFU/m 3 at rest and <180 CFU/m 3 in operational.
Statistical tools: The data obtained by the two methods were entered into a computer-based Spreadsheet and was analysed using SPSS version 20.0 software and R software version 3.2.3. As the data followed a non-normal distribution, non-parametric tests were applied. The median TVC values between active and passive methods and between at rest and inoperational moments were compared by Wilcoxon signed-rank test. To correlate the TVC values of active and passive methods, Spearman's correlation coefficient was used. Simple linear regression was employed to find out whether TVC values in inoperational period was affected by the number of people present in the operation theatre during the operation. Independent sample t-test was applied to find out any difference between the TVC values at centre and four corners by both methods. P < 0.05 was considered statistically significant for all the statistical tests.
| Results|| |
A total of 18 OTs were sampled for IMA at two different moments (at rest and during operation) and by two different methods (active and passive) over the period of 2 months. Each OT had 20 samples taken– ten at rest and ten during operation. The ten samples taken at rest included five by passive method and five by active method. The same was also true for the ten inoperational samples. Hence, in total 360 samples, i.e., 180 at rest (90 by passive and 90 by active) and 180 during operation (90 by passive and 90 by active) were taken from the 18 OTs.
The evaluation of the microbial air quality in different OTs of our tertiary care hospital revealed the presence of a number of organisms. MSSA>MRSA Pseudomonas aeruginosa was isolated as the only Gram-negative organism by inoperational sampling of the Emergency OT only. Fungi were isolated only from four inoperational samples [Table 1].
|Table 1: Organisms isolated after evaluation of microbial air quality in different operation theatres|
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At rest, 17 (94.4%) and 16 (88.9%) OTs exceeded the maximum limit value of the passive (<5 CFU/9 cm diameter plate/h) and of the active (<35CFU/m 3) method, respectively. With inoperational sampling, nine (50%) and four (22.2%) OTs exceeded the maximum limit value of the passive (<25 CFU/9 cm diameter plate/h) and of the active (<180 CFU/m 3) method, respectively. However, no significant difference was noted between the median TVC values of samples taken by passive method at rest and during operation (P = 0.43). The same was also true for sampling by active method done at rest and during operation (P = 0.08), Wilcoxon signed-rank test [Figure 1].
|Figure 1: Box plot of the TVC obtained from samples at rest and inoperational by both active and passive methods. 1 = Passive at rest. (mean = 25.39 CFU/m2/h, standard deviation = +16.13, Median = 22.00, IQR = 16.0–32.0). 2 = Passive inoperational (mean = 29.67 CFU/m2/h, standard deviation = +15.43, Median = 26.00, IQR = 19.25–39.5). 3 = Active at rest. (Mean = 86.39 CFU/m3, standard deviation = +50.05, Median = 76.00, IQR = 57.0–97.5). 4 = Active inoperational (mean = 115.1 CFU/m3, standard deviation = +57.92, Median = 98.00, IQR = 80.5–172.0)|
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There was, however, a significant difference between the TVC values obtained by active and passive methods when sampled at rest (P = 0.0002) as well as when sampled during operation (P = 0.0002), using Wilcoxon signed-rank test. The active method gives significantly higher values as compared to the passive method. A statistically significant positive correlation was also noted between the results of the two sampling techniques, i.e., active and passive methods in both sampling moments done at rest (P = 0.007, ρ = 0.609) and during operation (P = 0.0006, ρ = 0.726), using Spearman's rank correlation.
Considering the TVC values as dependent variable and number of people present in the OT room during operation as independent variable, the number of people were not found to be an independent predictor of the TVC values using either active (P = 0.28) or passive (P = 0.16) microbial air sampling methods.
There was a significant difference in the number of haemolytic colonies obtained by passive and active method of sampling taken at rest (P = 0.0003), but the same was not true when sampled during operation (P = 0.05). However, there was neither any significant difference between the hemolytic colonies when sampled by active method at rest and during operation (P=0.44) nor was there any difference when the same different moments were sampled using passive method (P=0.28). [Figure 2].
|Figure 2: Box plot of the number of haemolytic colonies obtained from samples at rest and during operation by both active and passive methods. 1 = Passive at rest. (Mean = 9.50 CFU/m2/h, standard deviation = +5.08, Median = 8.50, IQR = 5.0–14.8). 2 = Passive during operation (mean = 13.44 CFU/m2/h, standard deviation = +12.86, Median = 11.00, IQR = 7.3–15.0). 3 = Active at rest. (Mean = 15.17 CFU/m3, standard deviation = 5.16, median = 16.50, IQR = 12.3–17.0). 4 = Active during operation (Mean = 14.17 CFU/m3, standard deviation = +3.73, Median = 16.50, IQR = 12.0–17.0)|
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There was also no significant difference in the median TVC values between the centre (26.0) and four corners (27.0) by active sampling method (P=0.569). Nor was there any significant difference in the median TVC values between the centre (50.5) and four corners (49.5) by passive sampling method (P=0.485).
| Discussion|| |
Healthcare-associated infections (HAI) reflect the quality of patient care and infection control practices observed in a particular hospital. The overall contamination in the hospital air plays a crucial factor in determining the rate of surgical site infections (SSI), which is the second most common HAI , while other patient or doctor-related factors are also important determinants, bio-burden in the OT environment is undoubtedly one of the most significant in the outcome of SSI and PIR.
The different types of microbial bioburden isolated from the air of the operating rooms in the present study are comparable with the studies from not only India  but also abroad. However, as the total bioburden has exceeded the maximum acceptable limit value during both moments of sampling. This point towards the fact that the performance capabilities of the OTs with regard to its cleaning procedures have to be improved drastically along with regular monitoring to improve the environmental quality in the OTs and to control HAI. The bioburden in the OT environment can be further improved by having adequate controlled ventilation system by installing HEPA filters in the OTs.,
The difference in the TVC values obtained by methods active and passive methods of sampling in the two moments can be explained by the fact that passive sampling collects mainly those large particles which settle under gravity while the air sampler used in the active sampling draws a fixed volume of air containing particles of various sizes.,
The present study demonstrated a statistically significant positive correlation between the results obtained by the two sampling methods at the two sampling moments which indicate that when the protocol is stringently adhered to, the results of active and passive sampling correlate in a comparable way with the quality of air for at rest and inoperational sampling. Therefore, either technique can be used for the bioburden surveillance. A studies by Napoli et al. from Italy also document a similar finding  though many studies do not recommend settle plate method, i.e., passive sampling for quantitative evaluation of hospital airborne bacteria.
Contrary to the finding that the number of people in the OT during operation directly reflects on the bio-burden, as would be expected due to dispersion of microbes from people, the present study documented that the number of people were not found to be an independent predictor of the TVC values by either method of sampling. This indicates that, during operation, the team's hygienic procedures and behaviours are satisfactory or the sample size is not adequate enough for such a comparison.
There was a significant difference in the haemolytic colonies obtained by the two techniques at rest, however, no significant difference was obtained when sampled during operation. This can indicate that either both the techniques of sampling give comparable results or that the bioburden of S. aureus (indicated by haemolytic colonies) in the atmosphere was different at different moments of sampling resulting in difference in statistical analysis. Additional studies are required to authenticate this.
Although the present study did not show any significant difference in the median TVC values between the centre and four corners during operation by active (P = 0.569) or passive sampling (P = 0.485), Tshokey et al. from Srilanka, found a significantly higher CFU count in the corners than that near the operating table probably due to the uneven turbulent airflow in the OTs, which, by diluting the air-borne particles may lower the contamination near the wound area. Results of the present study may indicate that, probably during operation, the team's hygienic procedures and behaviours are satisfactory or the sample size is not adequate enough for such a comparison.
The microbiological air quality is a significant indicator of HAI and regular monitoring can help assess the quality of environment and identify critical situations which would require corrective interventions. However, there is currently no international consensus (neither in the Italian ISPESL guidelines nor in the ISO standards) on the most suitable method for air sampling or any precise guidelines on how to obtain the TVC values although the recommended target limits have been set.
Passive sampling by gravity settling culture plate is perhaps the most extensively used hospital microbiologic air sampling technique. Advantages are not only simple and economical but also do not disturb the usual movement of the microbial population in the air during sampling nor does it interrupt the laminar airflow in any way. Hence, it reproduces the circumstances of infection by dust particles settling into the wound probably better than a slit sampler. However, its drawback is that it collects chiefly those particles large enough to be pulled by gravity or impacted by air turbulence onto the collecting surface. Although the slit air sampler may have the advantage of collecting all the particles suspended in the air, apart from the cost of the instrument, the noise that it produces during sampling often may disturb the operating surgeons during inoperational sampling.
The possible limitation of the present study is its low sample size. A greater sample size would allow more accurate statistical analysis.
| Conclusions|| |
The present study demonstrates that the results of active and passive sampling correlate in an analogous manner with the microbial air quality for both moments of sampling. However, authentication of this result necessitates additional studies. In the interim, it is promising to conclude that both methods can be used for universal scrutinising of air biocontamination.
The authors would like to thank all surgical speciality Heads of the Departments and OT sisters of our hospital who have cooperated with us for this research.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
French GL, Cheng AF, Wong SL, Donnan S. Repeated prevalence surveys for monitoring effectiveness of hospital infection control. Lancet 1989;2:1021-3.
Hart D. Pathogenic bacteria in air of operating rooms. Arch Surg 1938;37:521-30.
Melhado MA, Hensen JL, Loomans M. Review of ventilation systems in operating rooms in view of infection control. In: Proceedings of the 6th Int. Postgraduate Research Conference in the Built and Human Environment. Technische Universiteit Delft, University of Salford; 2006. p. 478-87.
Akhter MS, Verma R, Madhukar KP, Vaishampayan AR, Unadkat PC. Incidence of surgical site infection in postoperative patients at a tertiary care centre in India. J Wound Care 2016;25:210-2, 214-7.
Setty NK, Nagaraja MS, Nagappa DH, Giriyaiah CS, Gowda NR, Naik RD. A study on Surgical Site Infections (SSI) and associated factors in a government tertiary care teaching hospital in Mysore, Karnataka. Int J Med Public Health 2014;4:171-5. [Full text]
Whyte W, Hambraeus A, Laurell G, Hoborn J. The relative importance of the routes and sources of wound contamination during general surgery. II. Airborne. J Hosp Infect 1992;22:41-54.
Mangram AJ, Horan TC, Pearson ML, Silver LC, Jarvis WR. Guideline for prevention of surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee. Infect Control Hosp Epidemiol 1999;20:250-78.
Sehulster L, Chinn RY; CDC; HICPAC. Guidelines for environmental infection control in health-care facilities. Recommendations of CDC and the Healthcare Infection Control Practices Advisory Committee (HICPAC). MMWR Recomm Rep 2003;52:1-42.
Weiss KD, Osborne SF, Callahan-Lyon P. Prevention of surgical-site infections. N Engl J Med 2010;362:1541-2.
Barrow C. A patient's journey through the operating department from an infection control perspective. J Perioper Pract 2009;19:94-8.
Buettcher M, Heininger U. Prospective surveillance of nosocomial viral infections during and after hospitalization at a university children's hospital. Pediatr Infect Dis J 2010;29:950-6.
Sabharwal R, Sharma R. Estimation of microbial air contamination by settle plate method: Are we within acceptable limit. Sch Acad J Biosci 2015;3:703-7.
Pasquarella C, Albertini R, Dall'aglio P, Saccani E, Sansebastiano GE, Signorelli C. Air microbial sampling: The state of the art. Ig Sanita Pubbl 2008;64:79-120.
ISO. Clean Rooms and Associated Controlled Environments – Biocontamination Control
. General Principles and Methods. Part 1. ISO 14698-1. Milano: UNI; 2003.
Blomquist G. Sampling of biological particles. Analyst 1994;119:53-6.
Center for Disease Control and Prevention. Guidelines for Environmental Infection Control in Health-Care Facilities. Atlanta: Center for Disease Control and Prevention; 2003.
Pasquarella C, Pitzurra O, Savino A. The index of microbial air contamination. J Hosp Infect 2000;46:241-56.
Morse SA, Meitzner TA. The staphylococci. In: Jawetz, Melnick and Adelberg's Medical Microbiology. 26th
ed. New York: McGraw-Hill Companies, Inc.; 2013. p. 199-208.
Pitzurra M, Savino A, Pasquarella C. Microbiological environment monitoring (MEM). Ann Ig 1997;9:439-54.
Napoli C, Marcotrigiano V, Montagna MT. Air sampling procedures to evaluate microbial contamination: A comparison between active and passive methods in operating theatres. BMC Public Health 2012;12:594.
Imai E, Ueda M, Kanao K, Kubota T, Hasegawa H, Omae K, et al
. Surgical site infection risk factors identified by multivariate analysis for patient undergoing laparoscopic, open colon, and gastric surgery. Am J Infect Control 2008;36:727-31.
World Health Organization Prevention of hospital acquired infections: In G. Ducel, J. Fabry, L. Nicolle. A Practical Guide WHO/CDS/CSR/EPH/2002/12. 2nd
ed. 2002. Geneva, Switzerland: World Health Organization.
Dharan S, Pittet D. Environmental controls in operating theatres. J Hosp Infect 2002;51:79-84.
Lorenz R. Air conditioning systems. Acta Neurochir (Wien) 1980;55:49-61.
Oren I, Haddad N, Finkelstein R, Rowe JM. Invasive pulmonary aspergillosis in neutropenic patients during hospital construction: Before and after chemoprophylaxis and institution of HEPA filters. Am J Hematol 2001;66:257-62.
Herman LG, Morelli FA. Air sampling techniques in the hospital environment. Bacteriol Proc 1961;61:114.
Wolf HW, Skaliy P, Hall LB. Sampling microbiological aerosol. US Department Health Education and Welfare, Public Health Service Monograph 60, 1964. p. 9,39.
Sayer WJ, MacKnight NM, Wilson HW. Hospital airborne bacteria as estimated by the Andersen sampler versus the gravity settling culture plate. Am J Clin Pathol 1972;58:558-66.
Tshokey T, Somaratne P, Agampodi S. Comparison of two air sampling methods to monitor operating room air quality and assessment of air quality in two operating rooms with different ventilation systems in the national hospital of Sri Lanka. Int J Infect Control 2016;12:1-8.
[Figure 1], [Figure 2]