| Literature DB >> 35162224 |
Thi Tham Nguyen1, Graham R Johnson2, Scott C Bell3,4,5, Luke D Knibbs1,6.
Abstract
Interrupting the transmission of airborne (<≈5 µm) respiratory pathogens indoors is not a new challenge, but it has attracted unprecedented interest due to the COVID-19 pandemic during 2020-2021. However, bacterial respiratory pathogens with known or potential airborne transmission account for an appreciable proportion of the communicable disease burden globally. We aimed to systematically review quantitative, laboratory-based studies of air disinfection techniques for airborne respiratory bacteria. Three databases (PubMed, Web of Science, Scopus) were searched, following PRISMA guidelines. A total of 9596 articles were identified, of which 517 were assessed in detail and of which 26 met the inclusion and quality assessment criteria. Seven air disinfection techniques, including UV-C light, filtration, and face masks, among others, were applied to 13 different bacterial pathogens. More than 80% of studies suggested that air disinfection techniques were more effective at inactivating or killing bacteria than the comparator or baseline condition. However, it was not possible to compare these techniques because of methodological heterogeneity and the relatively small number of the studies. Laboratory studies are useful for demonstrating proof-of-concept and performance under controlled conditions. However, the generalisability of their findings to person-to-person transmission in real-world settings is unclear for most of the pathogens and techniques we assessed.Entities:
Keywords: air disinfection techniques; airborne transmission; bioaerosols; laboratory-based studies
Mesh:
Year: 2022 PMID: 35162224 PMCID: PMC8834760 DOI: 10.3390/ijerph19031197
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1PRISMA flowchart presenting the search results and selection process of articles.
Z-values of UV-C effects on respiratory bacteria at different relative humidity levels.
| Study | Microorganism | Relative Humidity (%) | Susceptibility |
|---|---|---|---|
| Riley et al., 1976 [ | 50 | 33 (23–42) | |
| 50 | 48 (44–55) | ||
| 50 | 37 (33–39) | ||
| 50 | 25 (23–28) | ||
| 65 | 31 | ||
| 65 | 24 | ||
|
| 65 | 214 (183–245) | |
| Ko et al., 2000 [ |
| 22–33 | 58 |
|
| 49–62 | 57 | |
|
| 85–91 | −4 | |
| 22–33 | 27 | ||
| 49–62 | 17 | ||
| 85–91 | 2 | ||
| Peccia et al., 2001 [ |
| 40–50 | 35–45 |
| Peccia et al., 2004 [ | 50 | 19.1 | |
| 95 | ~10 * | ||
| Yang et al., 2018 [ |
| 55 | 120 |
|
| 55 | 100 | |
| Zhang et al., 2019 [ |
| 50 | 85 |
|
| 70 | 61 | |
|
| 90 | 34 |
* No exact value provided; this value has been estimated from the published figure in [50].