Back

Workplace ventilation improvement to address coronavirus disease 2019 cluster occurrence in a manufacturing factory

Kitamura, H.; Ishigaki, Y.; Ohashi, H.; Yokogawa, S.

2022-04-05 occupational and environmental health
10.1101/2022.04.04.22271935 medRxiv
Show abstract

Aim and MethodsA coronavirus disease 2019 (COVID-19) cluster emerged in a manufacturing factory in early August 2021. In November 2021, a ventilation survey using tracer gas and data analysis was performed to reproduce the situation at the time of cluster emergence and verify that ventilation in the office increased the risk of aerosol transmission; verify the effectiveness of measures implemented immediately in August; and verify the effectiveness of additional measures when previously enforced measures proved inadequate. ResultsAt the time of cluster emergence, the average ventilation frequency was 0.73 times/h, less than the 2 times/h recommended by the Ministry of Health, Labour, and Welfare; as such, the factorys situation was deemed to have increased the risk of aerosol transmission. Due to the measures already taken at the time of the survey, the ventilation frequency increased to 3.41 times/h on average. It was confirmed that ventilation frequency increased to 8.33 times/h on average, when additional measures were taken. ConclusionTo prevent the re-emergence of COVID-19 clusters, it is necessary to continue the measures that have already been implemented. Additionally, introduction of real-time monitoring that visualizes CO2 concentrations is recommended. Furthermore, we believe it is helpful that external researchers in multiple fields and internal personnel in charge of health and safety department and occupational health work together to confirm the effectiveness of conducted measures, such as this case.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.