Abstract: Background and Objective: Reduced indoor air quality is a burden in schools because of the large number of pupils per classroom, especially in government-owned schools. This work investigated microbial indoor air quality in 25 randomly selected classrooms of five public primary schools and their general toilets. Materials and Methods: Institutional based cross-sectional study was conducted between April and June, 2021 to evaluate the bacterial and fungal load of these rooms using the settle plate method. An Independent sample Mann-Whitney U test was implemented on the data. Results: In the morning, school 1 primary 2 and primary 1 had the lowest and highest hemolytic bacterial count of 1.3×104 and 3.1×104 CFU m–3, respectively. School 1primary 4 and toilet had the lowest and highest staphylococcal count of 8.1×103 and 8.0×104 CFU m–3. School 1 primary 4 and toilet had the highest fungal count of 1.3×103 and 1.8×104 SFU m–3. Bacteria presumptively identified were Streptococcus pneumoniae, Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pyogenes, Staphylococcus epidermidis and Enterococcus faecalis. Fungi presumptively identified were Aspergillus fumigatus, Aspergillus niger, Cladosporium sphaerospermum and Aspergillus flavus. Mann-Whitney U test revealed that the distribution of bacteria count using blood agar is significantly different from mannitol salt agar. Conclusion: High microbial load was found in government public primary schools in the Akure City of Nigeria in comparison to indoor air biological standards of WHO. This indicates a high risk of air-borne infections to government school pupils and a call for attention by stakeholders in authority.
INTRODUCTION
Indoor air quality is the air quality within and around buildings and structures. Indoor air quality is known to affect the health, comfort and well-being of building occupants. Indoor air quality is part of indoor environmental quality, which includes indoor air quality as well as other physical and psychological aspects of life indoors (e.g., lighting, visual quality, acoustics and thermal comfort)1. Poor indoor air quality has been linked to sick building syndrome, reduced productivity and impaired learning in schools. Indoor air quality can be affected by gases (including carbon monoxide, radon, volatile organic compounds), particulates, microbial contaminants (mould, bacteria) or any mass or energy stressor that can induce adverse health conditions2. Source control, filtration and the use of ventilation to dilute contaminants are the primary methods for improving indoor air quality in most buildings3. Residential units can further improve indoor air quality by routine cleaning of carpets and area rugs. Determination of indoor air quality involves the collection of air samples, monitoring human exposure to pollutants, collection of samples on building surfaces and computer modelling of airflow inside buildings4. Indoor air quality has been the object of several studies due to an increasing concern within the scientific community on the effects of indoor air quality upon health, especially when people tend to spend more time indoors than outdoors5.
Frequently, pollutants from indoor sources may build up to appreciable levels due to the slowness of air exchange. It is estimated that a quarter of the world population is exposed to unhealthy concentrations of air pollutants and children are the ones most at risk of these indoor air pollutants due to their respiratory organ systems immaturity6. Moreover, children are susceptible to air pollutants because they breathe in relatively greater air volume than adults. The indoor air quality of schools is gaining much attention in recent years. Children spend almost 25-30% of their time, inside classrooms and worldwide, the length of the education expectancy of children over the age of five increased from 10.1 years in 1999-11.0 years in 20077. School environments differ from adult work environments because children have special habits such as unprotected coughs and sneezes, less likely to wash their hands and more likely to share the “tools of the trade” such as pencils, that encourage the spread of infectious disease. Moreover, children are more sensitive to air pollutants, since their organs are in the developing stage they breathe more air relative to their body size than adults8. Poor indoor air quality can increase the chance of long-term and short-term health problems for students and staff, reduce the productivity of teachers and degrade the student learning environment and comfort levels9.
This study is therefore, designed to isolate and enumerate bacterial and fungal isolates from indoor air samples of selected government primary schools, presumptively identify bacteria and fungi enumerated from government primary schools as well as determine the frequency of occurrence of bacterial and fungal isolates from indoor air in government primary school.
MATERIALS AND METHODS
Study design and study area: An Institutional based cross-sectional study was carried out to investigate indoor bacterial and fungal loads of government public primary schools in Akure city, Nigeria. Akure is the capital of Ondo State in Southwestern Nigeria. It is located between latitude 7°12'N-7°58'N and between longitude 5°15'E-5°17'E. The climate of Akure is subtropical with two main distinct seasons: Rainy and dry seasons. The humidity of the air masses over the city varies from 60% in January, to 80% in July (NIMET, 2016). This study was carried out at the Microbiology Department, Federal University of Technology Akure, Nigeria from June-August, 2021.
Experimentation: The exposed air culture technique was adopted for estimating the air microflora of the sampling areas. Blood agar and mannitol salt agar plates, were rendered in the air at 1.5 m above the ground for 10-15 min. Exposed plates were incubated at 37°C for 18-24 hrs as described by Udochukwu et al.10:
Where:
| a | = | Number of colonies on the petri dishes |
| p | = | Surface of the petri dishes |
| t | = | Time of petri dish exposure |
After which the frequency of occurrence of this bacteria and fungi count was placed on a frequency table and interpreted. Individual bacterial isolates were identified using standard methods (including colonial morphology, microscopy and biochemical tests).
Statistical analysis: Analysis was performed using a Statistical Package for Social Sciences (SPSS) version 20.0. Data obtained were subjected to analysis of variance and expressed as Mean±Standard error. Statistical significance was determined at values (p<0.05) and the means were separated using Duncan’s Multiple Range Test. An Independent sample Mann-Whitney U test was implemented on the data.
RESULTS
Table 1 shows the bacterial and fungal counts of indoor air samples from government primary school 1 in the morning, it revealed a total haemolytic, staphylococcal and fungal counts of 1.1×105, 6.4×104 CFU m–3 and 5.3×104 SFU m–3, respectively. The bacterial and fungal counts of indoor air samples from government primary school 2 in the morning were represented in Table 2 and revealed a total haemolytic, staphylococcal and fungal counts of 6.8×104 CFU m–3, 5.9×104 CFU m–3 and 1.9×104 SFU m–3, respectively. The result of Table 3, 4 and 5 equally showed the bacterial and fungal counts of indoor air samples from government primary schools 3, 4 and 5 in the morning while Table 6-10 revealed the bacterial and fungal counts of indoor air samples from government primary schools 1 to 5 observed in the afternoon.
Generally, school 1 primary 1 had the highest haemolytic bacteria count of 3.1×104 CFU m–3 while primary 2 and primary 4 had the least haemolytic bacterial count of 1.3×104 CFU m–3 blood agar. School 1 toilet had the highest count of 8.0×104 CFU m–3 while primary 4 has the least lactose fermenter count of 8.1×103 CFU m–3 on mannitol salt agar.
School 1, primary 5 had the highest haemolytic bacteria count of 2.7×104 CFU m–3 while primary 2 had the least haemolytic bacterial count of 7.5×103 CFU m–3 on blood Agar in the afternoon exposure. School 1 the toilet had the highest lactose fermenter count of 2.7×104 CFU m–3 while primary 5 had the least lactose fermenter count of 5.6×103 CFU m–3 on mannitol salt agar. School 1 primary 2 had the highest fungal count of 1.2×104 SFU m–3 while primary 1 and primary 2 had the least with 3.8×103 SFU m–3 each on potato dextrose agar.
Figure 1 illustrated the occurrence of Staphylococcus aureus in each school for morning and afternoon exposure, so also, Fig. 2-11 revealed the occurrence of S. epidermis, Klebsiella pneumonia, Streptococcus pyogenes, Escherichia coli, Streptococcus pneumonia, Enterococcus faecalis, Aspergillus flavus, A. fumigatus, A. niger and Cladosporium sphaerospermum in each school for morning and afternoon exposure, respectively.
In general, Staphylococcus aureus had the highest occurrence of 2.0×101 CFU in school 1 primary 5 and the least of 0 CFU in school 3 toilets. While it had the highest occurrence of 2.3×101 CFU in school 1 primary 1 in the morning. Staphylococcus aureus had the highest occurrence of 2.3×101 CFU in school 1 primary 1 and the least of 1 CFU in school 3 primary 5 in the afternoon. Staphylococcus epidermis had the highest occurrence of 33 CFU school 2 primary 5 in the morning. Aspergillus flavus had the highest occurrence of 9 CFU in school 4 primary 2 and the last occurrence of 1 CFU in school 3 primary 5 while Aspergillus flavus had the highest occurrence of 15 CFU in school 3 primaries 4 and the last occurrence of 1 CFU in the afternoon.
Table 11 presents descriptive statistics of bacteria count using blood agar and Mannitol salt agar. It is found that there is a small difference in the mean bacteria count for the two agar types. Figure 12a-b presents a boxplot of bacteria count using blood agar and mannitol salt agar. The range of bacteria count using blood agar is higher than when mannitol salt agar is used, except for a few outlying counts. Also, high variability of bacteria count using Mannitol salt agar was observed compared with blood agar. A test of the hypothesis was conducted to test if the distribution of bacteria count is the same for different agar types (blood agar and mannitol salt agar). An Independent sample Mann-Whitney U test was performed. The test rejects the null hypothesis that the distribution of bacteria count is the same using blood agar and mannitol salt agar (p = 0.001) at a 5% level of significance and concludes that the distribution of bacteria count using blood agar is significantly different from mannitol salt agar. This difference is shown in Fig. 12.
| Table 1: | Bacterial and fungal counts of indoor air samples from government primary school 1 in the morning |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 3.1×104 | 8.1×103 | 3.1×103 |
| Primary 2 | 1.3×104 | 8.0×104 | 1.3×103 |
| Primary 3 | 1.8×104 | 1.3×104 | 1.1×104 |
| Primary 4 | 1.3×104 | 1.0×104 | 1.1×104 |
| Primary 5 | 1.8×104 | 1.9×104 | 1.8×104 |
| Toilet | 1.9×104 | 9.4×103 | 7.5×103 |
| Total | 1.1×105 | 6.4×104 | 5.3×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 2: | Bacterial and fungal counts of indoor air samples from government primary school 2 in the morning |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 8.8×103 | 3.1×103 | 6.3×104 |
| Primary 2 | 1.0×104 | 8.8×103 | 3.1×103 |
| Primary 3 | 1.1×104 | 6.3×104 | NG |
| Primary 4 | 1.3×104 | 8.1×103 | 3.1×103 |
| Primary 5 | 1.3×104 | 2.1×104 | 8.0×104 |
| Toilet | 1.3×104 | 1.3×104 | 1.3×103 |
| Total | 6.8×104 | 5.9×104 | 1.9×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 3: | Bacterial and fungal counts of indoor air samples from government primary school 3 in the morning |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 8.1×103 | 8.8×103 | 3.1×103 |
| Primary 2 | 6.9×103 | 6.9×103 | 3.8×103 |
| Primary 3 | 9.4×103 | 7.5×103 | 8.0×104 |
| Primary 4 | 2.0×104 | 6.9×103 | 1.0×104 |
| Primary 5 | 6.3×103 | 8.1×103 | 3.1×103 |
| Toilet | 1.0×104 | 1.3×103 | 6.3×102 |
| Total | 6.1×104 | 3.9×104 | 2.6×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 4: | Bacterial and fungal counts of indoor air samples from government primary school 4 in the morning |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 2.8×104 | 7.5×103 | 6.9×103 |
| Primary 2 | 2.1×104 | 2.5×103 | 1.1×104 |
| Primary 3 | 7.5×103 | 4.4×103 | 5.6×103 |
| Primary 4 | 1.4×104 | 8.0×104 | 8.1×103 |
| Primary 5 | 1.0×104 | 4.4×103 | 8.1×103 |
| Toilet | 8.1×103 | 1.1×104 | 2.3×104 |
| Total | 7.9×104 | 3.6×104 | 6.3×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 5: | Bacterial and fungal counts of indoor air samples from government primary school 5 in the morning |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 7.5×103 | 5.6×103 | 1.9×103 |
| Primary 2 | 9.4×103 | 1.9×103 | 1.9×103 |
| Primary 3 | 8.8×103 | 0 | 2.5×103 |
| Primary 4 | 7.5×103 | 3.1×103 | 3.8×103 |
| Primary 5 | 7.5×103 | 1.3×103 | 9.4×103 |
| Toilet | 5.3×104 | 2.3×104 | 2.5×103 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 6: | Bacterial and fungal counts of indoor air samples from government primary school 1 in the afternoon |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 9.4×103 | 2.4×104 | 1.0×104 |
| Primary 2 | 7.5×103 | 1.0×104 | 1.2×104 |
| Primary 3 | 2.0×104 | 7.5×103 | 9.4×103 |
| Primary 4 | 1.4×104 | 1.1×104 | 7.5×103 |
| Primary 5 | 2.7×104 | 5.6×103 | 3.8×103 |
| Toilet | 1.0×104 | 2.7×104 | 4.4×103 |
| Total | 8.8×104 | 8.5×104 | 4.7×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 7: | Bacterial and fungal counts of indoor air samples from government primary school 2 in the afternoon |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 1.1×104 | 1.2×103 | 5.6×103 |
| Primary 2 | 1.4×104 | 9.4×103 | 1.1×104 |
| Primary 3 | 1.9×104 | 6.3×104 | 8.8×103 |
| Primary 4 | 1.8×104 | 1.1×104 | 6.3×104 |
| Primary 5 | 1.3×104 | 1.0×104 | 7.5×103 |
| Toilet | 1.3×104 | 1.2×104 | 1.9×103 |
| Total | 8.8×104 | 6.7×104 | 4.1×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 8: | Bacterial and fungal counts of indoor air samples from government primary school 3 in the afternoon |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 8.8×103 | 2.6×104 | 3.8×103 |
| Primary 2 | 1.2×104 | 1.3×104 | 3.8×103 |
| Primary 3 | 1.1×104 | 8.8×103 | 4.4×104 |
| Primary 4 | 2.5×104 | 8.1×103 | 9.4×103 |
| Primary 5 | 1.4×104 | 6.3×104 | 6.3×104 |
| Toilet | 8.8×103 | 6.3×102 | 0 |
| Total | 7.1×104 | 5.3×104 | 2.9×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 9: | Bacterial and fungal counts of indoor air samples from government primary school 4 in the afternoon |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 2.8×103 | 8.1×103 | 8.8×103 |
| Primary 2 | 2.1×104 | 6.3×103 | 1.1×104 |
| Primary 3 | 8.8×103 | 8.1×103 | 1.2×104 |
| Primary 4 | 2.4×104 | 6.3×103 | 1.0×104 |
| Primary 5 | 1.3×104 | 7.5×103 | 1.0×104 |
| Toilet | 1.4×104 | 1.3×104 | 3.1×103 |
| Total | 1.1×105 | 4.9×104 | 5.4×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 10: | Bacterial and fungal counts of indoor air samples from government primary school 5 in the afternoon |
| Classes | Haemolytic (CFU m–3) | Staphylococcal (CFU m–3) | Fungal (SFU m–3) |
| Primary 1 | 1.0×104 | 8.1×103 | 4.4×103 |
| Primary 2 | 1.3×104 | 2.1×104 | 6.3×102 |
| Primary 3 | 1.4×104 | 1.9×103 | 9.0×103 |
| Primary 4 | 9.4×103 | 8.1×103 | 6.3×102 |
| Primary 5 | 9.4×103 | 9.4×103 | 3.8×103 |
| Toilet | 1.0×104 | 1.8×104 | 4.4×103 |
| Total | 6.6×104 | 6.6×104 | 1.9×104 |
| CFU m–3: Colony-forming unit per cubic meter and SFU m–3: Spore-forming unit per cubic meter | |||
| Table 11: | Descriptive statistics of bacteria count using blood agar and mannitol salt agar |
| Agar types | Minimum | Maximum | Mean | Std. deviation |
| Blood agar | 2800 | 53000 | 13811.67 | 7762.231 |
| Mannitol salt agar | 0 | 80000 | 13611.67 | 16885.24 |
| Fig. 1: | Occurrence of Staphylococcus aureus in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 2: | Occurrence of Staphylococcus epidermis in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 3: | Occurrence of Klebsiella pneumoniae in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 4: | Occurrence of Streptococcus pyogenes in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 5: | Occurrence of Escherichia coli in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 6: | Occurrence of Streptococcus pneumoniae in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 7: | Occurrence of Enterococcus faecalis in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 8: | Occurrence of Aspergillus flavus in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 9: | Occurrence of Aspergillus fumigatus in all schools for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 10: | Occurrence of Aspergillus niger in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 11: | Occurrence of Cladosporium sphaerospermum in each school for morning and afternoon exposure 1A: School 1 primary 1, 1B: School 1 primary 2, 1C: School 1 primary 3, 1D: School 1 primary 4, 1E: School 1 primary 5, 1F: School 1 toilet, 2A: School 2 primary 1, 2B: School 2 primary 2, 2C: School 2 primary 3, 2D: School 2 primary 4, 2E: School 2 primary 5, 2F: School 2 toilet, 3A: School 3 primary 1, 3B: School 3 primary 2, 3C: School 3 primary 3, 3D: School 3 primary 4, 3E: School 3 primary 5, 3F: School 3 toilet, 4A: School 4 primary 1, 4B: School 4 primary 2, 4C: School 4 primary 3, 4D: School 4 primary 4, 4E: School 4 primary 5, 4F: School 4 toilet, 5A: School 5 primary 1, 5B: School 5 primary 2, 5C: School 5 primary 3, 5D: School 5 primary 4, 5E: School 5 primary 5, 5F: School 5 toilet, AM: Morning and PM: Afternoon |
| Fig. 12(a-b): | Boxplot of bacteria count using (a) Blood agar and (b) Mannitol salt agar |
DISCUSSION
A study on the indoor microbial air quality in government primary schools in Akure Metropolis, Nigeria was evaluated in this study. The concentrations of bacteria and fungi aerosols in the indoor air environment as sampled in this research work estimated with the use of the plate method is in parallel with the observation of Amengialue et al.5. There was variation in concentration of bacteria and fungi across the various sample sites as primary 5 and toilet generally recorded the highest count while primary 1 recorded the least count. This could be attributed to the variation in density of human population activities taking place before and during sampling time as well as the variation of ventilation conditions. These findings do agree with earlier reports by Graudenz et al.6 and Wemedo et al.7. However, there was a slightly significant difference between the morning and the evening counts, with an observable increase in the afternoon counts over the morning counts. This difference could be attributed to the fact that there were many activities in the afternoon due to the human activities of the day. This finding is in agreement with the work done by Hayleeyesus and Manaye8, where the microbial load was more in the afternoon compared to the morning. Another determinant factor in the characteristics of microbial load in the air that was taken into consideration in this study is atmospheric conditions. This played an important role in the determination of internal air quality. The variation of bacterial load in indoor environments might be due to environmental factors such as the ventilation system of the classroom, temperature, humidity and particulate matter concentration. In addition, the activities of students such as playing and running could also have contributed to bacterial counts. Traced the sources of classroom airborne contamination to several factors such as students’ own normal floral, uniforms, bags, foot-wears as well as activities such as sneezing, coughing, talking and talking and yawning.
Faustman et al.3 also reveal that materials in the classrooms and offices such as cupboards, books and files have been implicated as viable sources and these were present in the school understudy. The students and staff undertake a lot of housekeeping activities such as sweeping or applying dry mops can also create aerosols carrying particles that may contain microorganisms.
The bacteria associated with indoor air in this study compared with the identified bacterial general are Staphylococcus aureus, Staphylococcus epidermis, Klebsiella pneumoniae, Streptococcus pyogenes, Escherichia coli, Streptococcus pneumoniae and Enterococcus faecalis. The identified isolates are in partial agreement with Mohan et al.9, who reported also Bacillus sp., Enterococcus sp., Micrococcus sp. and Staphylococcus sp. Similarly, it agrees with the report of Udochukwu et al.10 on Escherichia coli, Pseudomonas and Staphylococcus species. The fungal organism associated with indoor air in this study compared with the identified bacterial general is Aspergillus fumigatus, Aspergillus niger, Cladosporium sphaerospermum and Aspergillus flavus. These outcomes are in full agreement with Kumari et al.11. Also, it agrees with the reports of Enitan et al.12 on Alternaria sp., Aspergillus niger, Penicillium sp. and Rhizopus sp. The study, therefore, opines that the occupants within the sampled enclosures are frequently exposed to health hazards associated with this bioaerosol.
CONCLUSION
The findings of this study have described the overview of the air microflora of selected densely populated government primary schools in the Akure Metropolis. This study shows the diversity of different bacterial and fungi associated with indoor air in this study. Based on the result of this study, it is recommended that the possible health consequences of air microflora causing harmful respiratory diseases thereby affecting human health necessitates proper sanitary practices across different government primary schools adopted for this study to reduce the potential incidence of bacterial and mycotic infections.
SIGNIFICANCE STATEMENT
This study discovered that the indoor air of selected government primary schools in Akure harboured bacteria and fungi including haemolytic bacteria. The unacceptable microbial air quality of the air samples will help researchers to uncover the dangers the pupils and school workers are exposed to and design studies related to respiratory infectious diseases.