2 research outputs found

    Indoor environmental conditions of selected shopping malls in Nigeria: A comparative study of microclimatic conditions, noise levels, and microbial burdens

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    oai:repository.uel.ac.uk:8x3x4The activities of people and equipment used within shopping malls are major factors that contribute to air pollution and increased sound levels, thereby affecting indoor environmental quality and the well-being of mall operators. This study assessed indoor environmental quality through microbial characterization and measurement of environmental conditions present in selected shopping malls. Investigations were conducted at three shopping malls in Ibadan selected through convenience sampling technique. Environmental parameters such as noise level, relative humidity, temperature, PM₂.₅ levels, total volatile organic compound (TVOC) levels, microbial characterization, and quantity were determined. Microclimatic parameters (temperature and relative humidity) were measured using a 4-in-1 Precision Gold N09AQ multi-tester. Culturable airborne microbes were collected using the settle plate technique. PM₂.₅ and TVOC levels were measured using a Thermo Scientific MIE pDR-1500 PM monitor and sf200-TVOC meter respectively. Two bacteria species and five fungi species were isolated across the malls. The noise levels ranged from 61.27 to 81.20 dB. The mean temperatures (highest mean of 33.44 ± 1.42 °C), PM₂.₅ (highest mean of 114.06 ± 25.64 ÎŒg/mÂł), and TVOC (highest mean of 55.21 ± 8.28 ppm) concentrations were higher than the permissible limits stipulated by the WHO guidelines and NESREA standard limits across all the selected malls. A positive correlation was found to exist between particulate matter and TVOC (r = 0.174, p = 0.004). The total bacteria count was generally high with the highest mean of 1965.33 ± 368.56 CFU/mÂł, while the total fungi count was generally low with the highest mean of 579.82 ± 51.55 CFU/mÂł. Bacillus spp. and Candida spp. were found to the consistent from all sample points across the three malls. The bacteria isolated are Gram-positive bacteria associated with human skin which suggests a high rate of indoor pollution from humans. In conclusion, this research has demonstrated the necessity to monitor noise levels and indoor air quality in malls. Also, there is need for government policies to improve indoor air quality which must be enforced and regulated, especially within shopping malls

    SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

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    Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population
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