Knowledge of the airborne nature of respiratory disease transmission owes much to the pioneering experiments of Wells and Riley over half a century ago. However, the mechanical, physiological, and immunopathological processes which drive the production of infectious aerosols by a diseased host remain poorly understood. Similarly, very little is known about the specific physiological, metabolic and morphological adaptations which enable pathogens such as Mycobacterium tuberculosis (Mtb) to exit the infected host, survive exposure to the external environment during airborne carriage, and adopt a form that is able to enter the respiratory tract of a new host, avoiding innate immune and physical defenses to establish a nascent infection. As a first step towards addressing these fundamental knowledge gaps which are central to any efforts to interrupt disease transmission, we developed and characterized a small personal clean room comprising an array of sampling devices which enable isolation and representative sampling of airborne particles and organic matter from tuberculosis (TB) patients. The complete unit, termed the Respiratory Aerosol Sampling Chamber (RASC), is instrumented to provide real-time information about the particulate output of a single patient, and to capture samples via a suite of particulate impingers, impactors and filters. Applying the RASC in a clinical setting, we demonstrate that a combination of molecular and microbiological assays, as well as imaging by fluorescence and scanning electron microscopy, can be applied to investigate the identity, viability, and morphology of isolated aerosolized particles. Importantly, from a preliminary panel of active TB patients, we observed the real-time production of large numbers of airborne particles including Mtb, as confirmed by microbiological culture and polymerase chain reaction (PCR) genotyping. Moreover, direct imaging of captured samples revealed the presence of multiple rod-like Mtb organisms whose physical dimensions suggested the capacity for travel deep into the alveolar spaces of the human lung.

In this paper we develop and demonstrate a flexible mathematical model that predicts the risk of airborne infectious diseases, such as tuberculosis under steady state and non-steady state conditions by monitoring exhaled air by infectors in a confined space. In the development of this model, we used the rebreathed air accumulation rate concept to directly determine the average volume fraction of exhaled air in a given space. From a biological point of view, exhaled air by infectors contains airborne infectious particles that cause airborne infectious diseases such as tuberculosis in confined spaces. Since not all infectious particles can reach the target infection site, we took into account that the infectious particles that commence the infection are determined by respiratory deposition fraction, which is the probability of each infectious particle reaching the target infection site of the respiratory tracts and causing infection. Furthermore, we compute the quantity of carbon dioxide as a marker of exhaled air, which can be inhaled in the room with high likelihood of causing airborne infectious disease given the presence of infectors. We demonstrated mathematically and schematically the correlation between TB transmission probability and airborne infectious particle generation rate, ventilation rate, average volume fraction of exhaled air, TB prevalence and duration of exposure to infectors in a confined space.

Tuberculosis (TB) transmission results from the interaction between infective sources and susceptible individuals within enabling socio-environmental conditions. As TB is an airborne pathogen, the transmission probability is determined by the volume of air inhaled from an infected source and the concentration of Mycobacterium tuberculosis containing respirable particles (doses) per volume of air. In this study, we model the contributions of infectious dose production, prevalence of infectious cases and daily rebreathed air volume (RAV) for defining the boundary conditions necessary to sustain endemic TB transmission at the population level. Results suggest that in areas with high RAV (range 300–1000 l d−1), such as prisons, TB transmission is contributed by both super-spreaders (exhaling ≥10 infectious doses hr−1) and lower infectivity individuals (exhaling less than 10 infectious doses hr−1). In settings with a low quantity of RAV (less than 100 l d−1), TB transmission occurs only from super-spreaders. Point-source epidemics occur in low rebreathed environments when super-spreaders infect a number of susceptibles but subsequent transmission is limited by the mean infectivity of secondary cases. By contrast, endemic TB occurs in poor socio-environmental conditions where mean infectivity cases are able to maintain a sufficiently high effective contact number.

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Tuberculosis (TB) disease burden is determined by both Background: infection and progression rate to disease. Progression rate varies by immune status, with prior infection in high burdened settings significantly reducing the progression to disease from subsequent reinfections and completion of successful treatment associated with increased risk of subsequent TB disease. Novel studies of TB vaccines are now underway targeting high risk individuals who have completed successful combination TB chemotherapy for active TB.In our study, we explored the impact of effective contact rate (β) and Methods: post-treatment immune status on population TB burden using a mathematical model incorporating five immunological states; susceptible, newly infected, reinfected, active TB and treated TB.We found that the number of newly infected individuals increased with Results: increasing values of β< 10yr , but declined when β> 10yr . Corresponding numbers of reinfected individuals increased with increasing values of β irrespective of post-treatment immune status. Furthermore, we noted that the number of active TB cases decreased by 7 -17% when treated individuals moved to either newly infected or reinfected immune states, respectively, rather than to the fully susceptible state at values of β< 10yr . The corresponding declines in TB burden were only 2 -7% at values of β> 10yr . Results show that TB prevalence in high burden settings is primarily driven by effective contact rates, which are significantly modified by pre-and post-treatment immune factors.The observation that impact of post-treatment immune status Conclusions: modification on population burden may be diminished in very high burdened settings will be important for vaccine design.