Bacteria and Their Antibiotic Resistance Profiles in Ambient Air in Accra, Ghana, February 2020: A Cross-Sectional Study Article Swipe
Godfred Saviour Kudjo Azaglo
,
Mohammed Khogali
,
Katrina Hann
,
John Pwamang
,
Emmanuel Appoh
,
Ebenezer Kwabena Appah-Sampong
,
Meldon Agyarkwa
,
Carl Fiati
,
Jewel Kudjawu
,
George Kwesi Hedidor
,
Amos Akumwena
,
Collins Timire
,
Hannock Tweya
,
Japheth A. Opintan
,
Anthony Harries
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/tropicalmed6030110
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/tropicalmed6030110
Inappropriate use of antibiotics has led to the presence of antibiotic-resistant bacteria in ambient air. There is no published information about the presence and resistance profiles of bacteria in ambient air in Ghana. We evaluated the presence and antibiotic resistance profiles of selected bacterial, environmental and meteorological characteristics and airborne bacterial counts in 12 active air quality monitoring sites (seven roadside, two industrial and three residential) in Accra in February 2020. Roadside sites had the highest median temperature, relative humidity, wind speed and PM10 concentrations, and median airborne bacterial counts in roadside sites (115,000 CFU/m3) were higher compared with industrial (35,150 CFU/m3) and residential sites (1210 CFU/m3). Bacillus species were isolated in all samples and none were antibiotic resistant. There were, however, Pseudomonas aeruginosa, Escherichia coli, Pseudomonas species, non-hemolytic Streptococci, Coliforms and Staphylococci species, of which six (50%) showed mono-resistance or multidrug resistance to four antibiotics (penicillin, ampicillin, ciprofloxacin and ceftriaxone). There was a positive correlation between PM10 concentrations and airborne bacterial counts (rs = 0.72), but no correlations were found between PM10 concentrations and the pathogenic bacteria nor their antibiotic resistance. We call for the expansion of surveillance of ambient air to other cities of Ghana to obtain nationally representative information.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/tropicalmed6030110
- https://www.mdpi.com/2414-6366/6/3/110/pdf?version=1624584860
- OA Status
- gold
- Cited By
- 3
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3175019052
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3175019052Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/tropicalmed6030110Digital Object Identifier
- Title
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Bacteria and Their Antibiotic Resistance Profiles in Ambient Air in Accra, Ghana, February 2020: A Cross-Sectional StudyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-06-25Full publication date if available
- Authors
-
Godfred Saviour Kudjo Azaglo, Mohammed Khogali, Katrina Hann, John Pwamang, Emmanuel Appoh, Ebenezer Kwabena Appah-Sampong, Meldon Agyarkwa, Carl Fiati, Jewel Kudjawu, George Kwesi Hedidor, Amos Akumwena, Collins Timire, Hannock Tweya, Japheth A. Opintan, Anthony HarriesList of authors in order
- Landing page
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https://doi.org/10.3390/tropicalmed6030110Publisher landing page
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https://www.mdpi.com/2414-6366/6/3/110/pdf?version=1624584860Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2414-6366/6/3/110/pdf?version=1624584860Direct OA link when available
- Concepts
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Antibiotic resistance, Ciprofloxacin, Ampicillin, Antibiotics, Bacteria, Penicillin, Amp resistance, Microbiology, Pathogenic bacteria, Ofloxacin, Veterinary medicine, Biology, Pseudomonas aeruginosa, Medicine, GeneticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2025: 2, 2022: 1Per-year citation counts (last 5 years)
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.compared | 97 |
| abstract_inverted_index.however, | 121 |
| abstract_inverted_index.isolated | 110 |
| abstract_inverted_index.positive | 154 |
| abstract_inverted_index.presence | 8, 22, 36 |
| abstract_inverted_index.profiles | 25, 40 |
| abstract_inverted_index.relative | 78 |
| abstract_inverted_index.roadside | 91 |
| abstract_inverted_index.selected | 42 |
| abstract_inverted_index.species, | 127, 133 |
| abstract_inverted_index.Coliforms | 130 |
| abstract_inverted_index.bacterial | 50, 88, 161 |
| abstract_inverted_index.evaluated | 34 |
| abstract_inverted_index.expansion | 186 |
| abstract_inverted_index.humidity, | 79 |
| abstract_inverted_index.multidrug | 141 |
| abstract_inverted_index.published | 18 |
| abstract_inverted_index.roadside, | 60 |
| abstract_inverted_index.antibiotic | 38, 117, 180 |
| abstract_inverted_index.bacterial, | 43 |
| abstract_inverted_index.industrial | 62, 99 |
| abstract_inverted_index.monitoring | 57 |
| abstract_inverted_index.nationally | 199 |
| abstract_inverted_index.pathogenic | 176 |
| abstract_inverted_index.resistance | 24, 39, 142 |
| abstract_inverted_index.resistant. | 118 |
| abstract_inverted_index.Escherichia | 124 |
| abstract_inverted_index.Pseudomonas | 122, 126 |
| abstract_inverted_index.aeruginosa, | 123 |
| abstract_inverted_index.ampicillin, | 147 |
| abstract_inverted_index.antibiotics | 3, 145 |
| abstract_inverted_index.correlation | 155 |
| abstract_inverted_index.information | 19 |
| abstract_inverted_index.residential | 103 |
| abstract_inverted_index.resistance. | 181 |
| abstract_inverted_index.(penicillin, | 146 |
| abstract_inverted_index.correlations | 168 |
| abstract_inverted_index.information. | 201 |
| abstract_inverted_index.residential) | 65 |
| abstract_inverted_index.surveillance | 188 |
| abstract_inverted_index.temperature, | 77 |
| abstract_inverted_index.Inappropriate | 0 |
| abstract_inverted_index.Staphylococci | 132 |
| abstract_inverted_index.Streptococci, | 129 |
| abstract_inverted_index.ceftriaxone). | 150 |
| abstract_inverted_index.ciprofloxacin | 148 |
| abstract_inverted_index.environmental | 44 |
| abstract_inverted_index.non-hemolytic | 128 |
| abstract_inverted_index.concentrations | 158, 173 |
| abstract_inverted_index.meteorological | 46 |
| abstract_inverted_index.representative | 200 |
| abstract_inverted_index.characteristics | 47 |
| abstract_inverted_index.concentrations, | 84 |
| abstract_inverted_index.mono-resistance | 139 |
| abstract_inverted_index.antibiotic-resistant | 10 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5090794201 |
| countries_distinct_count | 6 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I182185646 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.5799999833106995 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.45041517 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |