ABSTRACT
The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused an unparalleled disruption to daily life. Given that COVID-19 primarily spreads in densely populated indoor areas, urban public transport (UPT) systems pose significant risks. This study presents an analysis of the air change rate in buses, subways, and high speed trains based on measured CO2 concentrations and passenger behaviors. The resulting values were used as inputs for an infection risk assessment model, which was used to quantitatively evaluate the effects of various factors, including ventilation rates, respiratory activities, and viral variants, on the infection risk. The findings demonstrate that ventilation has a negligible impact on reducing average risks (less than 10.0%) for short-range scales, but can result in a reduction of average risks by 32.1%-57.4% for room scales. When all passengers wear masks, the average risk reduction ranges from 4.5-folds to 7.5-folds. Based on our analysis, the average total reproduction numbers (R) of subways are 1.4-folds higher than buses, and 2-folds higher than high speed trains. Additionally, it is important to note that the Omicron variant may result in a much higher R value, estimated to be approximately 4.9-folds higher than the Delta variant. To reduce disease transmission, it is important to keep the R value below 1. Thus, two indices have been proposed: time-scale based exposure thresholds and spatial-scale based upper limit warnings. Mask wearing provides the greatest protection against infection in the face of long exposure duration to the omicron epidemic.
ABSTRACT
OBJECTIVES: Sanitation workers are at high-risk of suffering from heat-related illnesses in high temperature weather. However, some well-known heat stress indexes have limitations in practical application. This paper aims to establish a new index-comprehensive physiological index (CPI) for evaluating physiological safety. METHODS: Firstly, the real-time weights of physiological parameters are obtained by entropy method. Secondly, the new index- CPI is established based on the distance between the measured values and the ideal solutions by the technique for order of preference by similarity to ideal solution (TOPSIS). Then the reasonability of CPI is verified. Finally, the safety range of the CPI is determined. RESULTS: The mean skin temperature (MST), systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the sanitation workers are greatly affected by the high temperature. The weight range of the MST, tympanic temperature, SBP, DBP and heart rate is 0.155-0.274, 0.146-0.200, 0.173-0.399, 0.150-0.298 and 0.146-0.200, respectively. And the weights of MST, SBP and DBP account for a relatively large proportion, ranging from 60.1% to 70.9%. The danger range of the CPI is (0, 0.6] while the safety range of the CPI is (0.6, 1.0]. CONCLUSIONS: The CPI can provide simple and easily-measured real-time monitoring of the physiological status. It has the potential to be a practical index for guaranteeing occupational health for sanitation workers in summer.
Subject(s)
Heat Stress Disorders , Sanitation , Blood Pressure , Entropy , Hot Temperature , Humans , TemperatureABSTRACT
Face-to-face meetings on a conference table are a frequent form of communication. The short-range exposure risk of aerosol disease transmission is high in the scenario of susceptible facing the infectious person over the table. We propose a mitigation methodology using the air curtain to reduce direct exposure to virus-laden aerosols. A numerical model was validated with experimental data to simulate the dispersion of aerosols. A dynamic mesh was adopted to consider the head movement of a 3D thermal manikin model. Results show that nodding head increase the potential risk by 74 % compared to motionless. Subsequently, for a single air curtain, placing it in the middle of the table is more effective in preventing risks than on the sides. For double air curtains, increasing the distance between them has a greater risk reduction effect than a shorter distance. Increasing the air velocity or width is more effective than increasing the number of air curtains. A moderate velocity (1 m s-1) works well to reduce the risk of nasal breathing. A higher velocity (2 m s-1) is needed for the coughing scenario. For similar indoor environments, the air curtains on the table can offer active precautions without changing the current ventilation system.
Subject(s)
Manikins , Humans , Respiratory Aerosols and Droplets , COVID-19/prevention & control , COVID-19/transmission , Aerosols , SARS-CoV-2 , Inhalation Exposure/prevention & controlABSTRACT
Conventional buses, as an indispensable part of the urban public transport system, impose cross-infection risks on passengers. To assess differential risks due to dynamic staying durations and locations, this study considered four spatial distributions (i = 1-4) and six temporal scenarios (j = 1-6) of buses. Based on field measurements and a risk assessment approach combining both short-range and room-scale effects, risks are evaluated properly. The results showed that temporal asynchrony between infected and susceptible individuals significantly affects disease transmission rates. The Control Case assumes that infected and susceptible individuals enter and leave synchronously. However, ignoring temporal asynchrony scenarios, i.e., the Control Case, resulted in overestimation (+30.7 % to +99.6 %) or underestimation (-15.2 % to -69.9 %) of the actual risk. Moreover, the relative difference ratios of room-scale risks between the Control Case and five temporal scenarios are impacted by ventilation. Short-range risk exists only if infected and susceptible individuals have temporal overlap on the bus. Considering temporal and spatial asynchrony, a more realistic total reproduction number (R) can be obtained. Subsequently, the total R was assessed under five temporal scenarios. On average, for the Control Case, the total R was estimated to be +27.3 % higher than j = 1, -9.3 % lower than j = 2, +12.8 % higher than j = 3, +33.0 % lower than j = 4, and + 77.6 % higher than j = 5. This implies the need for a combination of active prevention and real-time risk monitoring to enable rigid travel demand and control the spread of the epidemic.