The occurrence of close proximity infection for many respiratory diseases is often cited as evidence of large droplet and/or close contact transmission. We explored interpersonal exposure of exhaled droplets and droplet nuclei of two standing thermal manikins as affected by distance, humidity, ventilation, and breathing mode. Under the specific set of conditions studied, we found a substantial increase in airborne exposure to droplet nuclei exhaled by the source manikin when a susceptible manikin is within about 1.5 m of the source manikin, referred to as the proximity effect. The threshold distance of about 1.5 m distinguishes the two basic transmission processes of droplets and droplet nuclei, that is, short-range modes and the long-range airborne route. The short-range modes include both the conventional large droplet route and the newly defined short-range airborne transmission. We thus reveal that transmission occurring in close proximity to the source patient includes both droplet-borne (large droplet) and short-range airborne routes, in addition to the direct deposition of large droplets on other body surfaces. The mechanisms of the droplet-borne and short-range airborne routes are different; their effective control methods also differ. Neither the current droplet precautions nor dilution ventilation prevents short-range airborne transmission, so new control methods are needed.© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

为得出呼吸道病原体在飞机客舱内的传播特征,降低乘客的感染概率。首先,建立Boeing 737客舱仿真模型,利用Boeing 737试验舱和粒子图像测速法(PIV)验证客舱仿真模型的合理性;然后,基于客舱仿真模型与离散相模型(DPM)模拟患病乘客通过咳嗽和呼吸2种方式释放含有呼吸道病原体过程,得出呼吸道病原体的传播轨迹与速度;最后,基于Wells-Riley模型评估乘客的感染风险。结果表明:当传播时间达到200 s时,大部分呼吸道病原体的传播距离均在1 m以内;改变患病乘客的座位与飞机客舱的通风量,当患病乘客位于3号位置且客舱通风量为900 m³/h时,其余乘客感染风险概率下降至7.7%。

In order to study transmission law of respiratory pathogens in aircraft cabin and to reduce infection risk of passengers, firstly, a simulation model of Boeing 737 cabin was established and validated by using Boeing 737 experimental cabin and PIV. Then, release process of respiratory pathogens through coughing and breathing of sick passengers was simulated based on the model and DPM (discrete phase model), from which pathogens' trajectory and velocity were obtained. Finally, infection risk of passengers was assessed with Wells-Riley model. The results show that when transmission time reaches 200 s, transmission distance between most respiratory pathogens is within 1 m. By changing seats of sick passengers and ventilation in aircraft cabin, infection risk of remaining passengers can be reduced, which is 7.7% when sick passenger is at position 3 and ventilation of aircraft cabin is 900 m³/h.

A CFD-based numerical model was integrated with the Wells Riley equation to numerically assess the risk of airborne influenza infection in a popular means of public transportation, e.g. the bus microenvironment. Three mixing ventilation methods, which are widely used in current bus configurations, and an alternative displacement ventilation method were numerically assessed in terms of their ability to limit the risk of airborne influenza infection. Furthermore, both the non air-recirculation and air-recirculation with filtration ventilation modes were investigated in terms of the influenza infection probability. According to the simulation results, air-recirculation mode with high efficiency filtration was found to cause almost the same infection risk as non air-recirculation mode (100% outdoor air supply), which indicated a potential benefit of filtration in reducing the infection risk. Additionally, for the commonly used mixing ventilation methods, air distribution method, location of return/exhaust opening and seat arrangement affected the airborne transmission of influenza between passengers. The displacement ventilation method was found to be more effective in limiting the risk of airborne infection. Overall, the developed numerical model can provide insights into how the micro-environmental conditions affect airborne infection transmission in buses. This numerical model can assist in developing effective control strategies related to airborne transmitted diseases for other frequently used public transportation systems, such as trains and airplanes. (C) 2011 Elsevier Ltd.

Dispersion characteristics of expiratory aerosols were investigated in an enclosure with two different idealized airflow patterns: the ceiling-return and the unidirectional downward. A multiphase numerical model, which was able to capture the polydispersity and evaporation features of the aerosols, was adopted. Experiments employing optical techniques were conducted in a chamber with downward airflow pattern to measure the dispersion of aerosols. Some of the numerical results were compared with the chamber measurement results. Reasonable agreement was found. Small aerosols (initial size <or=45 microm) had settling times of below 20 s in downward flow but increased to 32-80 s in ceiling-return flow. Lateral dispersion was limited to around 0.3 m in downward flow, in which only turbulent dispersion was significant. It increased to over 2 m in ceiling-return flow, which had a combination of both turbulant dispersion and bulk flow transport mechanisms. The significance of aerosol transport by bulk flow was about an order of magnitude stronger than that by turbulent dispersion. However, results also show that aerosols could be dispersed for considerable distances solely by turbulence if they were suspended longer. Large aerosols settled within very short time due to heavy gravitational effects. The results provided new insights in designing proper bed spacing in hospital ward environments. This study shows that transport by bulk airflow stream was the major dispersion mechanism of expiratory aerosols in ventilated indoor environments. Dispersion by turbulence was about an order of magnitude less than that by bulk flow transport but considerable distance could be achieved by turbulent dispersion with long enough settling time. It was demonstrated that the dispersion of expiratory aerosol could be controlled by manipulating the ventilation airflow patterns in indoor environments.

A measles epidemic in a modern suburban elementary school in upstate New York in spring, 1974, is analyzed in terms of a model which provides a basis for apportioning the chance of infection from classmates sharing the same home room, from airborne organisms recirculated by the ventilating system, and from exposure in school buses. The epidemic was notable because of its explosive nature and its occurrence in a school where 97% of the children had been vaccinated. Many had been vaccinated at less than one year of age. The index case was a girl in second grade who produced 28 secondary cases in 14 different classrooms. Organisms recirculated by the ventilating system were strongly implicated. After two subsequent generations, 60 children had been infected, and the epidemic subsided. From estimates of major physical and biologic factors, it was possible to calculate that the index case produced approximately 93 units of airborne infection (quanta) per minute. The epidemic pattern suggested that the secondaries were less infectious by an order of magnitude. The exceptional infectiousness of the index case, inadequate immunization of many of the children, and the high percentage of air recirculated throughout the school, are believed to account for the extent and sharpness of the outbreak.

Infection risk assessment is very useful in understanding the transmission dynamics of infectious diseases and in predicting the risk of these diseases to the public. Quantitative infection risk assessment can provide quantitative analysis of disease transmission and the effectiveness of infection control measures. The Wells-Riley model has been extensively used for quantitative infection risk assessment of respiratory infectious diseases in indoor premises. Some newer studies have also proposed the use of dose-response models for such purpose. This study reviews and compares these two approaches to infection risk assessment of respiratory infectious diseases. The Wells-Riley model allows quick assessment and does not require interspecies extrapolation of infectivity. Dose-response models can consider other disease transmission routes in addition to airborne route and can calculate the infectious source strength of an outbreak in terms of the quantity of the pathogen rather than a hypothetical unit. Spatial distribution of airborne pathogens is one of the most important factors in infection risk assessment of respiratory disease. Respiratory deposition of aerosol induces heterogeneous infectivity of intake pathogens and randomness on the intake dose, which are not being well accounted for in current risk models. Some suggestions for further development of the risk assessment models are proposed.This review article summarizes the strengths and limitations of the Wells-Riley and the dose-response models for risk assessment of respiratory diseases. Even with many efforts by various investigators to develop and modify the risk assessment models, some limitations still persist. This review serves as a reference for further development of infection risk assessment models of respiratory diseases. The Wells-Riley model and dose-response model offer specific advantages. Risk assessors can select the approach that is suitable to their particular conditions to perform risk assessment.

Understanding how respiratory droplets become droplet nuclei and their dispersion is essential for understanding the mechanisms and control of disease transmission via droplet-borne and airborne routes. A theoretical model was developed to estimate the size of droplet nuclei and their dispersion as a function of the ambient humidity and droplet composition. The model-predicted dried droplet nuclei size was 32% of the original diameter, which agrees with the maximum residue size in the classic study by Duguid, 1946, Edinburg Med. J., 52, 335 and the validation experiment in this study, but is smaller than the 50% size predicted by Nicas et al., 2005, J. Occup. Environ. Hyg., 2, 143. The droplet nuclei size at a relative humidity of 90% (25°C) could be 30% larger than the size of the same droplet at a relative humidity of less than 67.3% (25°C). The trajectories of respiratory droplets in a cough jet are significantly affected by turbulence, which promotes the wide dispersion of droplets. We found that medium-sized droplets (e.g., 60 μm) are more influenced by humidity than are smaller and larger droplets, while large droplets (≥100 μm), whose travel is less influenced by humidity, quickly settle out of the jet.© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.